From 4ec03af16ef64f7c50cc5d08080439fac3e08ee9 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Thu, 13 Feb 2025 11:03:34 -0800 Subject: [PATCH 01/37] use archfc hosted on aws (#409) --- model_server/src/commons/globals.py | 2 +- model_server/src/main.py | 4 +++- tests/rest/api_model_server.rest | 5 ++--- tests/rest/insurance_agent.rest | 6 +++--- tests/rest/network_agent.rest | 2 +- 5 files changed, 10 insertions(+), 9 deletions(-) diff --git a/model_server/src/commons/globals.py b/model_server/src/commons/globals.py index 68c2e53a..2f533024 100644 --- a/model_server/src/commons/globals.py +++ b/model_server/src/commons/globals.py @@ -15,7 +15,7 @@ logger = get_model_server_logger() # Define the client -ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "https://api.fc.archgw.com/v1") +ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "https://archfc.katanemo.dev/v1") ARCH_API_KEY = "EMPTY" ARCH_CLIENT = OpenAI(base_url=ARCH_ENDPOINT, api_key=ARCH_API_KEY) diff --git a/model_server/src/main.py b/model_server/src/main.py index 74f60011..683d6227 100644 --- a/model_server/src/main.py +++ b/model_server/src/main.py @@ -4,7 +4,7 @@ import time import logging import src.commons.utils as utils -from src.commons.globals import handler_map +from src.commons.globals import ARCH_ENDPOINT, handler_map from src.core.utils.model_utils import ( ChatMessage, ChatCompletionResponse, @@ -51,6 +51,8 @@ logging.getLogger("opentelemetry.exporter.otlp.proto.grpc.exporter").setLevel( app = FastAPI() FastAPIInstrumentor().instrument_app(app) +logger.info(f"using archfc endpoint: {ARCH_ENDPOINT}") + @app.get("/healthz") async def healthz(): diff --git a/tests/rest/api_model_server.rest b/tests/rest/api_model_server.rest index ed86fac3..3e5d2f47 100644 --- a/tests/rest/api_model_server.rest +++ b/tests/rest/api_model_server.rest @@ -1,6 +1,5 @@ @model_server_endpoint = http://localhost:51000 -@archfc_endpoint = https://api.fc.archgw.com - +@archfc_endpoint = https://archfc.katanemo.dev ### talk to function calling endpoint POST {{model_server_endpoint}}/function_calling HTTP/1.1 @@ -119,7 +118,7 @@ Content-Type: application/json } ### talk to Arch-Intent directly for completion -POST {{archfc_endpoint}}/v1/chat/completions HTTP/1.1 +POST {{{{archfc_endpoint}}}}/v1/chat/completions HTTP/1.1 Content-Type: application/json { diff --git a/tests/rest/insurance_agent.rest b/tests/rest/insurance_agent.rest index 225c7d8a..c45ebb85 100644 --- a/tests/rest/insurance_agent.rest +++ b/tests/rest/insurance_agent.rest @@ -1,5 +1,5 @@ @model_server_endpoint = http://localhost:51000 -@archfc_endpoint = https://api.fc.archgw.com +@archfc_endpoint = https://archfc.katanemo.dev ### multi turn conversation with intent, except parameter gathering @@ -55,7 +55,7 @@ Content-Type: application/json ] } ### talk to Arch-Intent directly for completion -POST https://api.fc.archgw.com/v1/chat/completions HTTP/1.1 +POST https://archfc.katanemo.dev/v1/chat/completions HTTP/1.1 Content-Type: application/json { @@ -126,7 +126,7 @@ Content-Type: application/json ] } ### talk to Arch-Intent directly for completion, expect No -POST https://api.fc.archgw.com/v1/chat/completions HTTP/1.1 +POST https://archfc.katanemo.dev/v1/chat/completions HTTP/1.1 Content-Type: application/json { diff --git a/tests/rest/network_agent.rest b/tests/rest/network_agent.rest index 319b5106..dc03fa6c 100644 --- a/tests/rest/network_agent.rest +++ b/tests/rest/network_agent.rest @@ -1,5 +1,5 @@ @model_server_endpoint = http://localhost:51000 -@archfc_endpoint = https://api.fc.archgw.com +@archfc_endpoint = https://archfc.katanemo.dev ### single turn function calling all parameters insurance agent summary From e7b370cd2f9626cdfc978770ade8ee9364178e67 Mon Sep 17 00:00:00 2001 From: CTran Date: Fri, 14 Feb 2025 09:57:39 -0800 Subject: [PATCH 02/37] fix error in function name + new thresholds (#406) * fix error in function name + new thresholds * fix * fix * remove example * remove example --- .../src/core/utils/hallucination_utils.py | 44 +++++++++++-------- .../tests/core/test_function_calling.py | 15 ------- .../modelserver/test_hallucination_data.yaml | 4 +- 3 files changed, 28 insertions(+), 35 deletions(-) diff --git a/model_server/src/core/utils/hallucination_utils.py b/model_server/src/core/utils/hallucination_utils.py index 50006224..91effc92 100644 --- a/model_server/src/core/utils/hallucination_utils.py +++ b/model_server/src/core/utils/hallucination_utils.py @@ -44,7 +44,7 @@ HALLUCINATION_THRESHOLD_DICT = { }, MaskToken.PARAMETER_VALUE.value: { "entropy": 0.28, - "varentropy": 1.2, + "varentropy": 1.4, "probability": 0.8, }, } @@ -60,7 +60,7 @@ def check_threshold(entropy: float, varentropy: float, thd: Dict) -> bool: thd (dict): A dictionary containing the threshold values with keys 'entropy' and 'varentropy'. Returns: - bool: True if either the entropy or varentropy exceeds their respective thresholds, False otherwise. + bool: True if both the entropy and varentropy exceeds their respective thresholds, False otherwise. """ return entropy > thd["entropy"] and varentropy > thd["varentropy"] @@ -82,7 +82,7 @@ def calculate_uncertainty(log_probs: List[float]) -> Tuple[float, float]: token_probs = torch.exp(log_probs) entropy = -torch.sum(log_probs * token_probs, dim=-1) / math.log(2, math.e) varentropy = torch.sum( - token_probs * (log_probs / math.log(2, math.e)) + entropy.unsqueeze(-1) ** 2, + token_probs * (log_probs / math.log(2, math.e) + entropy.unsqueeze(-1)) ** 2, dim=-1, ) return entropy.item(), varentropy.item(), token_probs[0].item() @@ -303,22 +303,30 @@ class HallucinationState: self.mask.append(MaskToken.PARAMETER_VALUE) # checking if the parameter doesn't have enum and the token is the first parameter value token - if ( - len(self.mask) > 1 - and self.mask[-2] != MaskToken.PARAMETER_VALUE - and is_parameter_required( - self.function_properties[self.function_name], - self.parameter_name[-1], + # check if function name is in function properties + if self.function_name in self.function_properties: + if ( + len(self.mask) > 1 + and self.mask[-2] != MaskToken.PARAMETER_VALUE + and is_parameter_required( + self.function_properties[self.function_name], + self.parameter_name[-1], + ) + and not is_parameter_property( + self.function_properties[self.function_name], + self.parameter_name[-1], + "enum", + ) + ): + if self.parameter_name[-1] not in self.check_parameter_name: + self._check_logprob() + self.check_parameter_name[self.parameter_name[-1]] = True + else: + self._check_logprob() + self.error_message = f"Function name {self.function_name} not found in function properties" + logger.warning( + f"Function name {self.function_name} not found in function properties" ) - and not is_parameter_property( - self.function_properties[self.function_name], - self.parameter_name[-1], - "enum", - ) - ): - if self.parameter_name[-1] not in self.check_parameter_name: - self._check_logprob() - self.check_parameter_name[self.parameter_name[-1]] = True else: self.mask.append(MaskToken.NOT_USED) # if the state is parameter value and the token is an end token, change the state diff --git a/model_server/tests/core/test_function_calling.py b/model_server/tests/core/test_function_calling.py index 3f7971d8..0f2c9995 100644 --- a/model_server/tests/core/test_function_calling.py +++ b/model_server/tests/core/test_function_calling.py @@ -54,20 +54,6 @@ def get_hallucination_data_complex(): return req, True, True, True -def get_hallucination_data_easy(): - # Create instances of the Message class - message1 = Message(role="user", content="How is the weather in Seattle?") - - # Create a list of tools - tools = [get_weather_api] - - # Create an instance of the ChatMessage class - req = ChatMessage(messages=[message1], tools=tools) - - # model will hallucinate - return req, True, True, True - - def get_hallucination_data_medium(): # Create instances of the Message class message1 = Message(role="user", content="How is the weather in?") @@ -142,7 +128,6 @@ def get_greeting_data(): "get_data_func", [ get_hallucination_data_complex, - get_hallucination_data_easy, get_complete_data, get_irrelevant_data, get_complete_data_2, diff --git a/tests/modelserver/test_hallucination_data.yaml b/tests/modelserver/test_hallucination_data.yaml index 8e6e6b26..935a8f5f 100644 --- a/tests/modelserver/test_hallucination_data.yaml +++ b/tests/modelserver/test_hallucination_data.yaml @@ -63,7 +63,7 @@ test_cases: - role: "assistant" content: "Can you please provide me the days for the weather forecast?" - role: "user" - content: "los angeles in 5 days" + content: "5 days" tools: - type: "function" function: @@ -82,7 +82,7 @@ test_cases: required: ["location", "days"] expected: - type: "metadata" - hallucination: true + hallucination: false - id: "[WEATHER AGENT] - multi turn, single tool, clarification" input: From 2f6c4348fd60ecce8ec4d87a0fe7e67e7fe0d7a6 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 14 Feb 2025 14:55:41 -0800 Subject: [PATCH 03/37] update jaeger (#411) --- demos/shared/jaeger/Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/demos/shared/jaeger/Dockerfile b/demos/shared/jaeger/Dockerfile index 64fd1404..ee50d82e 100644 --- a/demos/shared/jaeger/Dockerfile +++ b/demos/shared/jaeger/Dockerfile @@ -1,4 +1,4 @@ -FROM jaegertracing/all-in-one:1.62.0 +FROM jaegertracing/jaeger:2.3.0 HEALTHCHECK \ --interval=1s \ --timeout=1s \ From d0a783cca819aa9efe96e5c061b9018fc1e4b2ef Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 14 Feb 2025 17:46:58 -0800 Subject: [PATCH 04/37] use docker cli to communicate to docker sub system (#412) --- arch/Dockerfile | 2 +- arch/tools/cli/core.py | 152 +-- arch/tools/cli/docker_cli.py | 118 ++ arch/tools/cli/main.py | 25 +- arch/tools/cli/targets.py | 1 - arch/tools/cli/utils.py | 84 +- arch/tools/poetry.lock | 2023 +++++++++++++++++++++++++++++++++- arch/tools/pyproject.toml | 2 - 8 files changed, 2159 insertions(+), 248 deletions(-) create mode 100644 arch/tools/cli/docker_cli.py diff --git a/arch/Dockerfile b/arch/Dockerfile index e1c49f1d..2c3c8744 100644 --- a/arch/Dockerfile +++ b/arch/Dockerfile @@ -8,7 +8,7 @@ RUN cd prompt_gateway && cargo build --release --target wasm32-wasip1 RUN cd llm_gateway && cargo build --release --target wasm32-wasip1 # copy built filter into envoy image -FROM envoyproxy/envoy:v1.32-latest as envoy +FROM docker.io/envoyproxy/envoy:v1.32-latest as envoy #Build config generator, so that we have a single build image for both Rust and Python FROM python:3.12-slim as arch diff --git a/arch/tools/cli/core.py b/arch/tools/cli/core.py index c91120df..78d9499c 100644 --- a/arch/tools/cli/core.py +++ b/arch/tools/cli/core.py @@ -2,104 +2,26 @@ import subprocess import os import time import sys -import glob -import docker -from docker.errors import DockerException -from cli.utils import getLogger, update_docker_host_env +from cli.utils import getLogger from cli.consts import ( - ARCHGW_DOCKER_IMAGE, ARCHGW_DOCKER_NAME, KATANEMO_LOCAL_MODEL_LIST, - MODEL_SERVER_LOG_FILE, - ACCESS_LOG_FILES, ) from huggingface_hub import snapshot_download -from dotenv import dotenv_values +import subprocess +from cli.docker_cli import ( + docker_container_status, + docker_remove_container, + docker_start_archgw_detached, + docker_stop_container, + health_check_endpoint, + stream_gateway_logs, +) log = getLogger(__name__) -def start_archgw_docker(client, arch_config_file, env): - logs_path = "~/archgw_logs" - logs_path_abs = os.path.expanduser(logs_path) - - return client.containers.run( - name=ARCHGW_DOCKER_NAME, - image=ARCHGW_DOCKER_IMAGE, - detach=True, # Run in detached mode - ports={ - "10000/tcp": 10000, - "10001/tcp": 10001, - "11000/tcp": 11000, - "12000/tcp": 12000, - "9901/tcp": 19901, - }, - volumes={ - f"{arch_config_file}": { - "bind": "/app/arch_config.yaml", - "mode": "ro", - }, - "/etc/ssl/cert.pem": {"bind": "/etc/ssl/cert.pem", "mode": "ro"}, - logs_path_abs: {"bind": "/var/log"}, - }, - environment={ - "OTEL_TRACING_HTTP_ENDPOINT": "http://host.docker.internal:4318/v1/traces", - "MODEL_SERVER_PORT": os.getenv("MODEL_SERVER_PORT", "51000"), - **env, - }, - extra_hosts={"host.docker.internal": "host-gateway"}, - healthcheck={ - "test": ["CMD", "curl", "-f", "http://localhost:10000/healthz"], - "interval": 5000000000, # 5 seconds - "timeout": 1000000000, # 1 seconds - "retries": 3, - }, - ) - - -def stream_gateway_logs(follow): - """ - Stream logs from the arch gateway service. - """ - log.info("Logs from arch gateway service.") - - options = ["docker", "logs", "archgw"] - if follow: - options.append("-f") - try: - # Run `docker-compose logs` to stream logs from the gateway service - subprocess.run( - options, - check=True, - stdout=sys.stdout, - stderr=sys.stderr, - ) - - except subprocess.CalledProcessError as e: - log.info(f"Failed to stream logs: {str(e)}") - - -def stream_access_logs(follow): - """ - Get the archgw access logs - """ - log_file_pattern_expanded = os.path.expanduser(ACCESS_LOG_FILES) - log_files = glob.glob(log_file_pattern_expanded) - - stream_command = ["tail"] - if follow: - stream_command.append("-f") - - stream_command.extend(log_files) - subprocess.run( - stream_command, - check=True, - stdout=sys.stdout, - stderr=sys.stderr, - ) - - def start_arch(arch_config_file, env, log_timeout=120, foreground=False): """ Start Docker Compose in detached mode and stream logs until services are healthy. @@ -111,55 +33,47 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False): log.info("Starting arch gateway") try: - try: - client = docker.from_env() - except DockerException as e: - # try setting up the docker host environment variable and retry - update_docker_host_env() - client = docker.from_env() + archgw_container_status = docker_container_status(ARCHGW_DOCKER_NAME) + if archgw_container_status != "not found": + log.info("archgw found in docker, stopping and removing it") + docker_stop_container(ARCHGW_DOCKER_NAME) + docker_remove_container(ARCHGW_DOCKER_NAME) - try: - container = client.containers.get("archgw") - log.info("archgw container found in docker, stopping and removing it") - # ensure that previous docker container is stopped and removed - container.stop() - container.remove() - log.info("Stopped and removed archgw container") - except docker.errors.NotFound as e: - pass - - container = start_archgw_docker(client, arch_config_file, env) + return_code, _, archgw_stderr = docker_start_archgw_detached( + arch_config_file, os.path.expanduser("~/archgw_logs"), env + ) + if return_code != 0: + log.info("Failed to start arch gateway: " + str(return_code)) + log.info("stderr: " + archgw_stderr) + sys.exit(1) start_time = time.time() - while True: - container = client.containers.get(container.id) + health_check_status = health_check_endpoint( + "http://localhost:10000/healthz" + ) + archgw_status = docker_container_status(ARCHGW_DOCKER_NAME) current_time = time.time() elapsed_time = current_time - start_time # Check if timeout is reached if elapsed_time > log_timeout: - log.info(f"Stopping log monitoring after {log_timeout} seconds.") + log.info(f"stopping log monitoring after {log_timeout} seconds.") break - container_status = container.attrs["State"]["Health"]["Status"] - - if container_status == "healthy": - log.info("Container is healthy!") + if health_check_status: + log.info("archgw is running and is healthy!") break else: - log.info(f"Container health status: {container_status}") + log.info(f"archgw status: {archgw_status}, health status: starting") time.sleep(1) if foreground: - for line in container.logs(stream=True): - print(line.decode("utf-8").strip("\n")) + stream_gateway_logs(follow=True) except KeyboardInterrupt: log.info("Keyboard interrupt received, stopping arch gateway service.") stop_arch() - except docker.errors.APIError as e: - log.info(f"Failed to start Arch: {str(e)}") def stop_arch(): @@ -173,10 +87,10 @@ def stop_arch(): try: subprocess.run( - ["docker", "stop", "archgw"], + ["docker", "stop", ARCHGW_DOCKER_NAME], ) subprocess.run( - ["docker", "remove", "archgw"], + ["docker", "remove", ARCHGW_DOCKER_NAME], ) log.info("Successfully shut down arch gateway service.") diff --git a/arch/tools/cli/docker_cli.py b/arch/tools/cli/docker_cli.py new file mode 100644 index 00000000..2ef9eb5f --- /dev/null +++ b/arch/tools/cli/docker_cli.py @@ -0,0 +1,118 @@ +import subprocess +import json +import sys +import requests # Add this import + +from cli.consts import ARCHGW_DOCKER_IMAGE, ARCHGW_DOCKER_NAME +from cli.utils import getLogger + +log = getLogger(__name__) + + +def docker_container_status(container: str) -> str: + result = subprocess.run( + ["docker", "inspect", container], capture_output=True, text=True, check=False + ) + if result.returncode != 0: + return "not found" + return json.loads(result.stdout)[0]["State"]["Status"] + + +def docker_stop_container(container: str) -> str: + result = subprocess.run( + ["docker", "stop", container], capture_output=True, text=True, check=False + ) + return result.returncode + + +def docker_remove_container(container: str) -> str: + result = subprocess.run( + ["docker", "remove", container], capture_output=True, text=True, check=False + ) + return result.returncode + + +def docker_start_archgw_detached( + arch_config_file: str, logs_path_abs: str, env: dict +) -> str: + env_args = [item for key, value in env.items() for item in ["-e", f"{key}={value}"]] + + port_mappings = ["10000:10000", "12000:12000", "9901:19901"] + port_mappings_args = [item for port in port_mappings for item in ("-p", port)] + + volume_mappings = [ + f"{logs_path_abs}:/var/log:rw", + f"{arch_config_file}:/app/arch_config.yaml:ro", + ] + volume_mappings_args = [ + item for volume in volume_mappings for item in ("-v", volume) + ] + + options = [ + "docker", + "run", + "-d", + "--name", + ARCHGW_DOCKER_NAME, + *port_mappings_args, + *volume_mappings_args, + *env_args, + "--add-host", + "host.docker.internal:host-gateway", + ARCHGW_DOCKER_IMAGE, + ] + + result = subprocess.run(options, capture_output=True, text=True, check=False) + return result.returncode, result.stdout, result.stderr + + +def health_check_endpoint(endpoint: str) -> bool: + try: + response = requests.get(endpoint) + if response.status_code == 200: + return True + except requests.RequestException as e: + pass + return False + + +def stream_gateway_logs(follow): + """ + Stream logs from the arch gateway service. + """ + log.info("Logs from arch gateway service.") + + options = ["docker", "logs", ARCHGW_DOCKER_NAME] + if follow: + options.append("-f") + try: + # Run `docker-compose logs` to stream logs from the gateway service + subprocess.run( + options, + check=True, + stdout=sys.stdout, + stderr=sys.stderr, + ) + + except subprocess.CalledProcessError as e: + log.info(f"Failed to stream logs: {str(e)}") + + +def docker_validate_archgw_schema(arch_config_file): + result = subprocess.run( + [ + "docker", + "run", + "--rm", + "-v", + f"{arch_config_file}:/app/arch_config.yaml:ro", + "--entrypoint", + "python", + ARCHGW_DOCKER_IMAGE, + "config_generator.py", + ], + capture_output=True, + text=True, + check=False, + ) + return result.returncode, result.stdout, result.stderr diff --git a/arch/tools/cli/main.py b/arch/tools/cli/main.py index 22ed7123..240a1b8c 100644 --- a/arch/tools/cli/main.py +++ b/arch/tools/cli/main.py @@ -5,11 +5,12 @@ import subprocess import multiprocessing import importlib.metadata from cli import targets +from cli.docker_cli import docker_validate_archgw_schema, stream_gateway_logs from cli.utils import ( getLogger, get_llm_provider_access_keys, load_env_file_to_dict, - validate_schema, + stream_access_logs, ) from cli.core import ( start_arch_modelserver, @@ -17,12 +18,9 @@ from cli.core import ( start_arch, stop_arch, download_models_from_hf, - stream_access_logs, - stream_gateway_logs, ) from cli.consts import ( KATANEMO_DOCKERHUB_REPO, - KATANEMO_LOCAL_MODEL_LIST, SERVICE_NAME_ARCHGW, SERVICE_NAME_MODEL_SERVER, SERVICE_ALL, @@ -174,17 +172,24 @@ def up(file, path, service, foreground): log.info(f"Validating {arch_config_file}") - try: - validate_schema(arch_config_file) - except Exception as e: - log.info(f"Exiting archgw up: validation failed") - log.info(f"Error: {str(e)}") + ( + validation_return_code, + validation_stdout, + validation_stderr, + ) = docker_validate_archgw_schema(arch_config_file) + if validation_return_code != 0: + log.info(f"Error: Validation failed. Exiting") + log.info(f"Validation stdout: {validation_stdout}") + log.info(f"Validation stderr: {validation_stderr}") sys.exit(1) log.info("Starting arch model server and arch gateway") # Set the ARCH_CONFIG_FILE environment variable - env_stage = {} + env_stage = { + "OTEL_TRACING_HTTP_ENDPOINT": "http://host.docker.internal:4318/v1/traces", + "MODEL_SERVER_PORT": os.getenv("MODEL_SERVER_PORT", "51000"), + } env = os.environ.copy() # check if access_keys are preesnt in the config file access_keys = get_llm_provider_access_keys(arch_config_file=arch_config_file) diff --git a/arch/tools/cli/targets.py b/arch/tools/cli/targets.py index a25c1aad..73b14b36 100644 --- a/arch/tools/cli/targets.py +++ b/arch/tools/cli/targets.py @@ -2,7 +2,6 @@ import ast import sys import yaml from typing import Any -from pydantic import BaseModel FLASK_ROUTE_DECORATORS = ["route", "get", "post", "put", "delete", "patch"] FASTAPI_ROUTE_DECORATORS = ["get", "post", "put", "delete", "patch"] diff --git a/arch/tools/cli/utils.py b/arch/tools/cli/utils.py index cc6ac20b..eeb4516e 100644 --- a/arch/tools/cli/utils.py +++ b/arch/tools/cli/utils.py @@ -1,10 +1,11 @@ +import glob import os +import subprocess +import sys import yaml import logging -import docker -from docker.errors import DockerException -from cli.consts import ARCHGW_DOCKER_IMAGE, ARCHGW_DOCKER_NAME +from cli.consts import ACCESS_LOG_FILES logging.basicConfig( level=logging.INFO, @@ -21,63 +22,6 @@ def getLogger(name="cli"): log = getLogger(__name__) -def update_docker_host_env(): - """ - Update DOCKER_HOST environment variable to use the local Docker socket - """ - if os.getenv("DOCKER_HOST"): - return - - default_docker_socket = os.getenv("DEFAULT_DOCKER_SOCKET", "/var/run/docker.sock") - if not os.path.exists(default_docker_socket): - home_dir = os.getenv("HOME") - docker_host = f"unix://{home_dir}/.docker/run/docker.sock" - log.info( - f"Default docker socket {default_docker_socket} not found, using {docker_host}" - ) - os.environ["DOCKER_HOST"] = docker_host - - -def validate_schema(arch_config_file: str) -> None: - try: - try: - client = docker.from_env() - except DockerException as e: - # try setting up the docker host environment variable and retry - update_docker_host_env() - client = docker.from_env() - - container = client.containers.run( - image=ARCHGW_DOCKER_IMAGE, - volumes={ - f"{arch_config_file}": { - "bind": "/app/arch_config.yaml", - "mode": "ro", - }, - }, - entrypoint=["python", "config_generator.py"], - detach=True, - ) - - # Wait for the container to finish and get the exit code - exit_code = container.wait() - - # Check exit code for validation success - if exit_code["StatusCode"] != 0: - # Validation failed (non-zero exit code) - logs = container.logs().decode() # Get container logs for debugging - raise ValueError( - f"Validation failed. Container exited with code {exit_code}.\nLogs:\n{logs}" - ) - - # Successful validation (exit code 0) - log.info("Schema validation successful!") - - except docker.errors.APIError as e: - # Handle container creation error - raise ValueError(f"Failed to create container: {e}") - - def get_llm_provider_access_keys(arch_config_file): with open(arch_config_file, "r") as file: arch_config = file.read() @@ -127,3 +71,23 @@ def load_env_file_to_dict(file_path): env_dict[key] = value return env_dict + + +def stream_access_logs(follow): + """ + Get the archgw access logs + """ + log_file_pattern_expanded = os.path.expanduser(ACCESS_LOG_FILES) + log_files = glob.glob(log_file_pattern_expanded) + + stream_command = ["tail"] + if follow: + stream_command.append("-f") + + stream_command.extend(log_files) + subprocess.run( + stream_command, + check=True, + stdout=sys.stdout, + stderr=sys.stderr, + ) diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index d5a45050..e04c6db3 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -1,17 +1,116 @@ # This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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a/arch/tools/pyproject.toml b/arch/tools/pyproject.toml index 7ed79a36..c32ea929 100644 --- a/arch/tools/pyproject.toml +++ b/arch/tools/pyproject.toml @@ -15,8 +15,6 @@ click = "^8.1.7" jinja2 = "^3.1.4" jsonschema = "^4.23.0" setuptools = "75.5.0" -docker = "^7.1.0" -python-dotenv = "^1.0.1" [tool.poetry.scripts] archgw = "cli.main:main" From e40b13be05280fb93777c34eefe4021edf430a3f Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 14 Feb 2025 19:28:10 -0800 Subject: [PATCH 05/37] Update arch_config and add tests for arch config file (#407) --- .github/workflows/validate_arch_config.yml | 31 +++++++++ arch/arch_config_schema.yaml | 54 ++++++++++----- arch/envoy.template.yaml | 60 +++++++++-------- arch/tools/cli/config_generator.py | 20 ++++++ arch/tools/cli/core.py | 35 +++++++++- arch/tools/cli/docker_cli.py | 14 +++- arch/tools/poetry.lock | 65 ++++++++++++++++++- arch/tools/pyproject.toml | 3 + arch/validate_arch_config.sh | 20 ++++++ crates/common/src/configuration.rs | 37 ----------- crates/common/src/consts.rs | 5 +- crates/common/src/tracing.rs | 2 +- crates/llm_gateway/src/stream_context.rs | 2 +- crates/prompt_gateway/src/http_context.rs | 11 +++- crates/prompt_gateway/src/stream_context.rs | 13 ++-- crates/prompt_gateway/tests/integration.rs | 6 +- .../arch_config.yaml | 10 +-- .../currency_exchange/arch_config.yaml | 11 ++-- .../human_resources_agent/arch_config.yaml | 10 +-- .../multi_turn_rag_agent/arch_config.yaml | 11 ++-- .../arch_config.yaml | 10 +-- .../stock_quote/arch_config.yaml | 11 ++-- .../weather_forecast/arch_config.yaml | 11 ++-- demos/use_cases/llm_routing/arch_config.yaml | 11 ++-- demos/use_cases/ollama/arch_config.yaml | 11 ++-- .../spotify_bearer_auth/arch_config.yaml | 10 +-- .../source/concepts/includes/arch_config.yaml | 17 ++--- docs/source/get_started/quickstart.rst | 26 ++++---- docs/source/guides/includes/arch_config.yaml | 17 ++--- .../includes/arch_config_full_reference.yaml | 36 ++++------ tests/archgw/arch_config.yaml | 11 ++-- 31 files changed, 379 insertions(+), 212 deletions(-) create mode 100644 .github/workflows/validate_arch_config.yml create mode 100644 arch/validate_arch_config.sh diff --git a/.github/workflows/validate_arch_config.yml b/.github/workflows/validate_arch_config.yml new file mode 100644 index 00000000..9503dad2 --- /dev/null +++ b/.github/workflows/validate_arch_config.yml @@ -0,0 +1,31 @@ +name: arch config tests + +on: + push: + branches: + - main + pull_request: + +jobs: + validate_arch_config: + runs-on: ubuntu-latest + defaults: + run: + working-directory: . + + steps: + - name: Checkout code + uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: "3.12" + + - name: build arch docker image + run: | + docker build -f arch/Dockerfile . -t katanemo/archgw + + - name: validate arch config + run: | + bash arch/validate_arch_config.sh diff --git a/arch/arch_config_schema.yaml b/arch/arch_config_schema.yaml index 1b32b730..1432c0b9 100644 --- a/arch/arch_config_schema.yaml +++ b/arch/arch_config_schema.yaml @@ -3,21 +3,38 @@ type: object properties: version: type: string - listener: + listeners: type: object - properties: - address: - type: string - port: - type: integer - message_format: - type: string - connect_timeout: - type: string additionalProperties: false - required: - - address - - port + properties: + ingress_traffic: + type: object + properties: + address: + type: string + port: + type: integer + message_format: + type: string + enum: + - openai + timeout: + type: string + additionalProperties: false + egress_traffic: + type: object + properties: + address: + type: string + port: + type: integer + message_format: + type: string + enum: + - openai + timeout: + type: string + additionalProperties: false endpoints: type: object patternProperties: @@ -107,7 +124,10 @@ properties: required: type: boolean default: - type: string + anyOf: + - type: string + - type: integer + - type: boolean description: type: string type: @@ -115,7 +135,10 @@ properties: enum: type: array items: - type: string + anyOf: + - type: string + - type: integer + - type: boolean in_path: type: boolean format: @@ -224,5 +247,4 @@ properties: additionalProperties: false required: - version - - listener - llm_providers diff --git a/arch/envoy.template.yaml b/arch/envoy.template.yaml index 0040b57b..ca722b7c 100644 --- a/arch/envoy.template.yaml +++ b/arch/envoy.template.yaml @@ -29,11 +29,11 @@ stats_config: - 180000 static_resources: listeners: - - name: arch_listener_http + - name: ingress_traffic address: socket_address: - address: 0.0.0.0 - port_value: 10000 + address: {{ prompt_gateway_listener.address }} + port_value: {{ prompt_gateway_listener.port }} traffic_direction: INBOUND filter_chains: - filters: @@ -55,7 +55,7 @@ static_resources: random_sampling: value: {{ arch_tracing.random_sampling }} {% endif %} - stat_prefix: arch_listener_http + stat_prefix: ingress_traffic codec_type: AUTO scheme_header_transformation: scheme_to_overwrite: https @@ -76,13 +76,13 @@ static_resources: route: auto_host_rewrite: true cluster: arch_prompt_gateway_listener - timeout: 60s + timeout: {{ prompt_gateway_listener.timeout }} http_filters: - name: envoy.filters.http.router typed_config: "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router - - name: arch_prompt_gateway_listener + - name: ingress_traffic_prompt address: socket_address: address: 0.0.0.0 @@ -104,11 +104,11 @@ static_resources: envoy_grpc: cluster_name: opentelemetry_collector timeout: 0.250s - service_name: prompt_processor + service_name: ingress_traffic random_sampling: value: {{ arch_tracing.random_sampling }} {% endif %} - stat_prefix: arch_prompt_gateway_listener + stat_prefix: ingress_traffic codec_type: AUTO scheme_header_transformation: scheme_to_overwrite: https @@ -201,7 +201,7 @@ static_resources: typed_config: "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router - - name: arch_internal + - name: egress_api_traffic address: socket_address: address: 0.0.0.0 @@ -223,11 +223,11 @@ static_resources: envoy_grpc: cluster_name: opentelemetry_collector timeout: 0.250s - service_name: prompt_processor + service_name: egress_api_traffic random_sampling: value: {{ arch_tracing.random_sampling }} {% endif %} - stat_prefix: arch_internal + stat_prefix: egress_api_traffic codec_type: AUTO scheme_header_transformation: scheme_to_overwrite: https @@ -273,13 +273,12 @@ static_resources: typed_config: "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router - - - name: arch_listener_http_llm + - name: egress_traffic address: socket_address: - address: 0.0.0.0 - port_value: 12000 - traffic_direction: INBOUND + address: {{ llm_gateway_listener.address }} + port_value: {{ llm_gateway_listener.port }} + traffic_direction: OUTBOUND filter_chains: - filters: - name: envoy.filters.network.http_connection_manager @@ -300,7 +299,7 @@ static_resources: random_sampling: value: {{ arch_tracing.random_sampling }} {% endif %} - stat_prefix: arch_listener_http + stat_prefix: egress_traffic codec_type: AUTO scheme_header_transformation: scheme_to_overwrite: https @@ -321,14 +320,13 @@ static_resources: route: auto_host_rewrite: true cluster: arch_listener_llm - timeout: 60s + timeout: {{ llm_gateway_listener.timeout }} http_filters: - name: envoy.filters.http.router typed_config: "@type": type.googleapis.com/envoy.extensions.filters.http.router.v3.Router - - - name: arch_listener_llm + - name: egress_traffic_llm address: socket_address: address: 0.0.0.0 @@ -349,11 +347,11 @@ static_resources: envoy_grpc: cluster_name: opentelemetry_collector timeout: 0.250s - service_name: llm_gateway + service_name: egress_traffic_llm random_sampling: value: {{ arch_tracing.random_sampling }} {% endif %} - stat_prefix: arch_listener_http + stat_prefix: egress_traffic codec_type: AUTO scheme_header_transformation: scheme_to_overwrite: https @@ -443,7 +441,7 @@ static_resources: clusters: - name: openai - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -467,7 +465,7 @@ static_resources: tls_minimum_protocol_version: TLSv1_2 tls_maximum_protocol_version: TLSv1_3 - name: mistral - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -488,7 +486,7 @@ static_resources: sni: api.mistral.ai {% for internal_cluster in ["arch_fc", "model_server"] %} - name: {{ internal_cluster }} - connect_timeout: 5s + connect_timeout: 0.5s type: STRICT_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -504,7 +502,7 @@ static_resources: hostname: {{ internal_cluster }} {% endfor %} - name: mistral_7b_instruct - connect_timeout: 5s + connect_timeout: 0.5s type: STRICT_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -523,7 +521,7 @@ static_resources: {% if cluster.connect_timeout -%} connect_timeout: {{ cluster.connect_timeout }} {% else -%} - connect_timeout: 5s + connect_timeout: 0.5s {% endif -%} type: LOGICAL_DNS dns_lookup_family: V4_ONLY @@ -557,7 +555,7 @@ static_resources: {% for local_llm_provider in local_llms %} - name: {{ local_llm_provider.name }} - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -589,7 +587,7 @@ static_resources: {% endfor %} - name: arch_internal - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -605,7 +603,7 @@ static_resources: hostname: arch_internal - name: arch_prompt_gateway_listener - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN @@ -621,7 +619,7 @@ static_resources: hostname: arch_prompt_gateway_listener - name: arch_listener_llm - connect_timeout: 5s + connect_timeout: 0.5s type: LOGICAL_DNS dns_lookup_family: V4_ONLY lb_policy: ROUND_ROBIN diff --git a/arch/tools/cli/config_generator.py b/arch/tools/cli/config_generator.py index 447585fb..7392849e 100644 --- a/arch/tools/cli/config_generator.py +++ b/arch/tools/cli/config_generator.py @@ -104,7 +104,27 @@ def validate_and_render_schema(): arch_config_string = yaml.dump(config_yaml) arch_llm_config_string = yaml.dump(config_yaml) + prompt_gateway_listener = config_yaml.get("listeners", {}).get( + "ingress_traffic", {} + ) + if prompt_gateway_listener.get("port") == None: + prompt_gateway_listener["port"] = 10000 # default port for prompt gateway + if prompt_gateway_listener.get("address") == None: + prompt_gateway_listener["address"] = "127.0.0.1" + if prompt_gateway_listener.get("timeout") == None: + prompt_gateway_listener["timeout"] = "10s" + + llm_gateway_listener = config_yaml.get("listeners", {}).get("egress_traffic", {}) + if llm_gateway_listener.get("port") == None: + llm_gateway_listener["port"] = 12000 # default port for llm gateway + if llm_gateway_listener.get("address") == None: + llm_gateway_listener["address"] = "127.0.0.1" + if llm_gateway_listener.get("timeout") == None: + llm_gateway_listener["timeout"] = "10s" + data = { + "prompt_gateway_listener": prompt_gateway_listener, + "llm_gateway_listener": llm_gateway_listener, "arch_config": arch_config_string, "arch_llm_config": arch_llm_config_string, "arch_clusters": inferred_clusters, diff --git a/arch/tools/cli/core.py b/arch/tools/cli/core.py index 78d9499c..291ca808 100644 --- a/arch/tools/cli/core.py +++ b/arch/tools/cli/core.py @@ -2,6 +2,8 @@ import subprocess import os import time import sys + +import yaml from cli.utils import getLogger from cli.consts import ( ARCHGW_DOCKER_NAME, @@ -22,6 +24,29 @@ from cli.docker_cli import ( log = getLogger(__name__) +def _get_gateway_ports(arch_config_file: str) -> tuple: + PROMPT_GATEWAY_DEFAULT_PORT = 10000 + LLM_GATEWAY_DEFAULT_PORT = 12000 + + # parse arch_config_file yaml file and get prompt_gateway_port + arch_config_dict = {} + with open(arch_config_file) as f: + arch_config_dict = yaml.safe_load(f) + + prompt_gateway_port = ( + arch_config_dict.get("listeners", {}) + .get("ingress_traffic", {}) + .get("port", PROMPT_GATEWAY_DEFAULT_PORT) + ) + llm_gateway_port = ( + arch_config_dict.get("listeners", {}) + .get("egress_traffic", {}) + .get("port", LLM_GATEWAY_DEFAULT_PORT) + ) + + return prompt_gateway_port, llm_gateway_port + + def start_arch(arch_config_file, env, log_timeout=120, foreground=False): """ Start Docker Compose in detached mode and stream logs until services are healthy. @@ -39,8 +64,14 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False): docker_stop_container(ARCHGW_DOCKER_NAME) docker_remove_container(ARCHGW_DOCKER_NAME) + prompt_gateway_port, llm_gateway_port = _get_gateway_ports(arch_config_file) + return_code, _, archgw_stderr = docker_start_archgw_detached( - arch_config_file, os.path.expanduser("~/archgw_logs"), env + arch_config_file, + os.path.expanduser("~/archgw_logs"), + env, + prompt_gateway_port, + llm_gateway_port, ) if return_code != 0: log.info("Failed to start arch gateway: " + str(return_code)) @@ -50,7 +81,7 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False): start_time = time.time() while True: health_check_status = health_check_endpoint( - "http://localhost:10000/healthz" + f"http://localhost:{prompt_gateway_port}/healthz" ) archgw_status = docker_container_status(ARCHGW_DOCKER_NAME) current_time = time.time() diff --git a/arch/tools/cli/docker_cli.py b/arch/tools/cli/docker_cli.py index 2ef9eb5f..edb8f764 100644 --- a/arch/tools/cli/docker_cli.py +++ b/arch/tools/cli/docker_cli.py @@ -1,7 +1,7 @@ import subprocess import json import sys -import requests # Add this import +import requests from cli.consts import ARCHGW_DOCKER_IMAGE, ARCHGW_DOCKER_NAME from cli.utils import getLogger @@ -33,11 +33,19 @@ def docker_remove_container(container: str) -> str: def docker_start_archgw_detached( - arch_config_file: str, logs_path_abs: str, env: dict + arch_config_file: str, + logs_path_abs: str, + env: dict, + prompt_gateway_port, + llm_gateway_port, ) -> str: env_args = [item for key, value in env.items() for item in ["-e", f"{key}={value}"]] - port_mappings = ["10000:10000", "12000:12000", "9901:19901"] + port_mappings = [ + f"{prompt_gateway_port}:{prompt_gateway_port}", + f"{llm_gateway_port}:{llm_gateway_port}", + "9901:19901", + ] port_mappings_args = [item for port in port_mappings for item in ("-p", port)] volume_mappings = [ diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index e04c6db3..0ccc45d3 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -318,6 +318,28 @@ files = [ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, ] +[[package]] +name = "docker" +version = "7.1.0" +description = "A Python library for the Docker Engine API." +optional = false +python-versions = ">=3.8" +files = [ + {file = "docker-7.1.0-py3-none-any.whl", hash = "sha256:c96b93b7f0a746f9e77d325bcfb87422a3d8bd4f03136ae8a85b37f1898d5fc0"}, + {file = "docker-7.1.0.tar.gz", hash = "sha256:ad8c70e6e3f8926cb8a92619b832b4ea5299e2831c14284663184e200546fa6c"}, +] + +[package.dependencies] +pywin32 = {version = ">=304", markers = "sys_platform == \"win32\""} +requests = ">=2.26.0" +urllib3 = ">=1.26.0" + +[package.extras] +dev = ["coverage (==7.2.7)", "pytest (==7.4.2)", "pytest-cov (==4.1.0)", "pytest-timeout (==2.1.0)", "ruff (==0.1.8)"] +docs = ["myst-parser (==0.18.0)", "sphinx (==5.1.1)"] +ssh = ["paramiko (>=2.4.3)"] +websockets = ["websocket-client (>=1.3.0)"] + [[package]] name = "exceptiongroup" version = "1.2.2" @@ -1602,6 +1624,20 @@ files = [ [package.dependencies] six = ">=1.5" +[[package]] +name = "python-dotenv" +version = "1.0.1" +description = "Read key-value pairs from a .env file and set them as environment variables" +optional = false +python-versions = ">=3.8" +files = [ + {file = "python-dotenv-1.0.1.tar.gz", hash = "sha256:e324ee90a023d808f1959c46bcbc04446a10ced277783dc6ee09987c37ec10ca"}, + {file = "python_dotenv-1.0.1-py3-none-any.whl", hash = "sha256:f7b63ef50f1b690dddf550d03497b66d609393b40b564ed0d674909a68ebf16a"}, +] + +[package.extras] +cli = ["click (>=5.0)"] + [[package]] name = "pytz" version = "2025.1" @@ -1613,6 +1649,33 @@ files = [ {file = "pytz-2025.1.tar.gz", hash = "sha256:c2db42be2a2518b28e65f9207c4d05e6ff547d1efa4086469ef855e4ab70178e"}, ] +[[package]] +name = "pywin32" +version = "308" +description = "Python for Window Extensions" +optional = false +python-versions = "*" +files = [ + {file = "pywin32-308-cp310-cp310-win32.whl", hash = "sha256:796ff4426437896550d2981b9c2ac0ffd75238ad9ea2d3bfa67a1abd546d262e"}, + {file = "pywin32-308-cp310-cp310-win_amd64.whl", hash = "sha256:4fc888c59b3c0bef905ce7eb7e2106a07712015ea1c8234b703a088d46110e8e"}, + 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+1,20 @@ +#!/bin/bash + +failed_files=() + +for file in $(find . -name arch_config.yaml -o -name arch_config_full_reference.yaml); do + echo "Validating $file..." + if ! docker run --rm -v "$(pwd)/$file:/app/arch_config.yaml:ro" --entrypoint /bin/sh katanemo/archgw:latest -c "python config_generator.py" 2>&1 > /dev/null ; then + echo "Validation failed for $file" + failed_files+=("$file") + fi +done + +# Print summary of failed files +if [ ${#failed_files[@]} -ne 0 ]; then + echo -e "\nValidation failed for the following files:" + printf '%s\n' "${failed_files[@]}" + exit 1 +else + echo -e "\nAll files validated successfully!" +fi diff --git a/crates/common/src/configuration.rs b/crates/common/src/configuration.rs index 069695ba..1b954c3d 100644 --- a/crates/common/src/configuration.rs +++ b/crates/common/src/configuration.rs @@ -9,7 +9,6 @@ use crate::api::open_ai::{ #[derive(Debug, Clone, Serialize, Deserialize)] pub struct Configuration { pub version: String, - pub listener: Listener, pub endpoints: Option>, pub llm_providers: Vec, pub overrides: Option, @@ -48,32 +47,6 @@ pub struct ErrorTargetDetail { pub endpoint: Option, } -#[derive(Debug, Clone, Serialize, Deserialize)] -pub struct Listener { - pub address: String, - pub port: u16, - pub message_format: MessageFormat, - // pub connect_timeout: Option, -} - -impl Default for Listener { - fn default() -> Self { - Listener { - address: "".to_string(), - port: 0, - message_format: MessageFormat::default(), - // connect_timeout: None, - } - } -} - -#[derive(Debug, Clone, Serialize, Deserialize, Default)] -pub enum MessageFormat { - #[serde(rename = "huggingface")] - #[default] - Huggingface, -} - #[derive(Debug, Clone, Serialize, Deserialize, Default)] pub struct PromptGuards { pub input_guards: HashMap, @@ -353,16 +326,6 @@ mod test { Some("/agent/summary".to_string()) ); - let error_target = config.error_target.as_ref().unwrap(); - assert_eq!( - error_target.endpoint.as_ref().unwrap().name, - "error_target_1".to_string() - ); - assert_eq!( - error_target.endpoint.as_ref().unwrap().path, - Some("/error".to_string()) - ); - let tracing = config.tracing.as_ref().unwrap(); assert_eq!(tracing.sampling_rate.unwrap(), 0.1); diff --git a/crates/common/src/consts.rs b/crates/common/src/consts.rs index 561dbae3..cd52220e 100644 --- a/crates/common/src/consts.rs +++ b/crates/common/src/consts.rs @@ -3,7 +3,10 @@ pub const SYSTEM_ROLE: &str = "system"; pub const USER_ROLE: &str = "user"; pub const TOOL_ROLE: &str = "tool"; pub const ASSISTANT_ROLE: &str = "assistant"; -pub const ARCH_FC_REQUEST_TIMEOUT_MS: u64 = 120000; // 2 minutes +pub const ARCH_FC_REQUEST_TIMEOUT_MS: u64 = 30000; // 30 seconds +pub const DEFAULT_TARGET_REQUEST_TIMEOUT_MS: u64 = 30000; // 30 seconds +pub const API_REQUEST_TIMEOUT_MS: u64 = 30000; // 30 seconds +pub const MODEL_SERVER_REQUEST_TIMEOUT_MS: u64 = 30000; // 30 seconds pub const MODEL_SERVER_NAME: &str = "model_server"; pub const ARCH_ROUTING_HEADER: &str = "x-arch-llm-provider"; pub const MESSAGES_KEY: &str = "messages"; diff --git a/crates/common/src/tracing.rs b/crates/common/src/tracing.rs index 85a95b0f..363a0870 100644 --- a/crates/common/src/tracing.rs +++ b/crates/common/src/tracing.rs @@ -166,7 +166,7 @@ impl TraceData { attributes: vec![Attribute { key: "service.name".to_string(), value: AttributeValue { - string_value: Some("upstream-llm".to_string()), + string_value: Some("egress_llm_traffic".to_string()), }, }], }; diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 528358a3..69496a61 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -381,7 +381,7 @@ impl HttpContext for StreamContext { Ok(traceparent) => { let mut trace_data = common::tracing::TraceData::new(); let mut llm_span = Span::new( - "upstream_llm_time".to_string(), + "egress_traffic".to_string(), Some(traceparent.trace_id), Some(traceparent.parent_id), self.request_body_sent_time.unwrap(), diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index 1ff7f91d..53a2d25b 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -6,7 +6,8 @@ use common::{ consts::{ ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_STATE_HEADER, ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, CHAT_COMPLETIONS_PATH, HEALTHZ_PATH, - MODEL_SERVER_NAME, REQUEST_ID_HEADER, TOOL_ROLE, TRACE_PARENT_HEADER, USER_ROLE, + MODEL_SERVER_NAME, MODEL_SERVER_REQUEST_TIMEOUT_MS, REQUEST_ID_HEADER, TOOL_ROLE, + TRACE_PARENT_HEADER, USER_ROLE, }, errors::ServerError, http::{CallArgs, Client}, @@ -144,7 +145,10 @@ impl HttpContext for StreamContext { if metadata.is_none() { metadata = Some(HashMap::new()); } - metadata.as_mut().unwrap().insert("optimize_context_window".to_string(), "true".to_string()); + metadata + .as_mut() + .unwrap() + .insert("optimize_context_window".to_string(), "true".to_string()); } } @@ -170,12 +174,15 @@ impl HttpContext for StreamContext { debug!("sending request to model server"); trace!("request body: {}", json_data); + let timeout_str = MODEL_SERVER_REQUEST_TIMEOUT_MS.to_string(); + let mut headers = vec![ (ARCH_UPSTREAM_HOST_HEADER, MODEL_SERVER_NAME), (":method", "POST"), (":path", "/function_calling"), ("content-type", "application/json"), (":authority", MODEL_SERVER_NAME), + ("x-envoy-upstream-rq-timeout-ms", timeout_str.as_str()), ]; if self.request_id.is_some() { diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index e6db7f59..d197b3e0 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -6,9 +6,9 @@ use common::api::open_ai::{ }; use common::configuration::{Overrides, PromptTarget, Tracing}; use common::consts::{ - ARCH_FC_MODEL_NAME, ARCH_FC_REQUEST_TIMEOUT_MS, ARCH_INTERNAL_CLUSTER_NAME, - ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, MESSAGES_KEY, REQUEST_ID_HEADER, SYSTEM_ROLE, - TOOL_ROLE, TRACE_PARENT_HEADER, USER_ROLE, + API_REQUEST_TIMEOUT_MS, ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, + ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, DEFAULT_TARGET_REQUEST_TIMEOUT_MS, MESSAGES_KEY, + REQUEST_ID_HEADER, SYSTEM_ROLE, TOOL_ROLE, TRACE_PARENT_HEADER, USER_ROLE, }; use common::errors::ServerError; use common::http::{CallArgs, Client}; @@ -89,7 +89,7 @@ impl StreamContext { streaming_response: false, user_prompt: None, is_chat_completions_request: false, - overrides: overrides, + overrides, request_id: None, traceparent: None, _tracing: tracing, @@ -160,7 +160,7 @@ impl StreamContext { callout_context.request_body.messages.clone(), ); let arch_messages_json = serde_json::to_string(¶ms).unwrap(); - let timeout_str = ARCH_FC_REQUEST_TIMEOUT_MS.to_string(); + let timeout_str = DEFAULT_TARGET_REQUEST_TIMEOUT_MS.to_string(); let mut headers = vec![ (":method", "POST"), @@ -302,6 +302,8 @@ impl StreamContext { } }; + let timeout_str = API_REQUEST_TIMEOUT_MS.to_string(); + let http_method_str = http_method.to_string(); let mut headers: HashMap<_, _> = [ (ARCH_UPSTREAM_HOST_HEADER, endpoint_details.name.as_str()), @@ -310,6 +312,7 @@ impl StreamContext { (":authority", endpoint_details.name.as_str()), ("content-type", "application/json"), ("x-envoy-max-retries", "3"), + ("x-envoy-upstream-rq-timeout-ms", timeout_str.as_str()), ] .into_iter() .collect(); diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index 4af98166..0792a319 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -81,10 +81,11 @@ fn normal_flow(module: &mut Tester, filter_context: i32, http_context: i32) { (":path", "/function_calling"), ("content-type", "application/json"), (":authority", "model_server"), + ("x-envoy-upstream-rq-timeout-ms", "30000"), ]), None, None, - None, + Some(5000), ) .returning(Some(1)) .expect_log(Some(LogLevel::Trace), None) @@ -387,10 +388,11 @@ fn prompt_gateway_request_to_llm_gateway() { (":authority", "api_server"), ("x-envoy-max-retries", "3"), (":path", "/weather"), + ("x-envoy-upstream-rq-timeout-ms", "30000"), ]), Some(expected_body), None, - None, + Some(5000), ) .returning(Some(2)) .expect_metric_increment("active_http_calls", 1) diff --git a/demos/samples_java/weather_forcecast_service/arch_config.yaml b/demos/samples_java/weather_forcecast_service/arch_config.yaml index 10c22819..0e3007e2 100644 --- a/demos/samples_java/weather_forcecast_service/arch_config.yaml +++ b/demos/samples_java/weather_forcecast_service/arch_config.yaml @@ -1,8 +1,10 @@ version: v0.1 -listener: - address: 127.0.0.1 - port: 10000 #If you configure port 443, you'll need to update the listener with tls_certificates - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: diff --git a/demos/samples_python/currency_exchange/arch_config.yaml b/demos/samples_python/currency_exchange/arch_config.yaml index 89a9e65b..1475abca 100644 --- a/demos/samples_python/currency_exchange/arch_config.yaml +++ b/demos/samples_python/currency_exchange/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s llm_providers: - name: gpt-4o diff --git a/demos/samples_python/human_resources_agent/arch_config.yaml b/demos/samples_python/human_resources_agent/arch_config.yaml index 09264821..5b1a9aa2 100644 --- a/demos/samples_python/human_resources_agent/arch_config.yaml +++ b/demos/samples_python/human_resources_agent/arch_config.yaml @@ -1,8 +1,10 @@ version: v0.1 -listener: - address: 127.0.0.1 - port: 8080 #If you configure port 443, you'll need to update the listener with tls_certificates - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: diff --git a/demos/samples_python/multi_turn_rag_agent/arch_config.yaml b/demos/samples_python/multi_turn_rag_agent/arch_config.yaml index 1399965f..8e8feb4f 100644 --- a/demos/samples_python/multi_turn_rag_agent/arch_config.yaml +++ b/demos/samples_python/multi_turn_rag_agent/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 127.0.0.1 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s endpoints: rag_energy_source_agent: diff --git a/demos/samples_python/network_switch_operator_agent/arch_config.yaml b/demos/samples_python/network_switch_operator_agent/arch_config.yaml index ad3bfae5..40d529a2 100644 --- a/demos/samples_python/network_switch_operator_agent/arch_config.yaml +++ b/demos/samples_python/network_switch_operator_agent/arch_config.yaml @@ -1,8 +1,10 @@ version: v0.1 -listener: - address: 127.0.0.1 - port: 8080 #If you configure port 443, you'll need to update the listener with tls_certificates - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: diff --git a/demos/samples_python/stock_quote/arch_config.yaml b/demos/samples_python/stock_quote/arch_config.yaml index c763d4ca..96901620 100644 --- a/demos/samples_python/stock_quote/arch_config.yaml +++ b/demos/samples_python/stock_quote/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s llm_providers: - name: gpt-4o diff --git a/demos/samples_python/weather_forecast/arch_config.yaml b/demos/samples_python/weather_forecast/arch_config.yaml index 94a6bdfb..8b0f4ca0 100644 --- a/demos/samples_python/weather_forecast/arch_config.yaml +++ b/demos/samples_python/weather_forecast/arch_config.yaml @@ -1,10 +1,11 @@ version: "0.1-beta" -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s endpoints: weather_forecast_service: diff --git a/demos/use_cases/llm_routing/arch_config.yaml b/demos/use_cases/llm_routing/arch_config.yaml index f7ce78cd..e3238484 100644 --- a/demos/use_cases/llm_routing/arch_config.yaml +++ b/demos/use_cases/llm_routing/arch_config.yaml @@ -1,10 +1,11 @@ version: "0.1-beta" -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + egress_traffic: + address: 0.0.0.0 + port: 12000 + message_format: openai + timeout: 30s llm_providers: - name: gpt-4o-mini diff --git a/demos/use_cases/ollama/arch_config.yaml b/demos/use_cases/ollama/arch_config.yaml index 5cb77750..394d3d6c 100644 --- a/demos/use_cases/ollama/arch_config.yaml +++ b/demos/use_cases/ollama/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s llm_providers: diff --git a/demos/use_cases/spotify_bearer_auth/arch_config.yaml b/demos/use_cases/spotify_bearer_auth/arch_config.yaml index a259a539..1d82a426 100644 --- a/demos/use_cases/spotify_bearer_auth/arch_config.yaml +++ b/demos/use_cases/spotify_bearer_auth/arch_config.yaml @@ -1,8 +1,10 @@ version: v0.1 -listener: - address: 127.0.0.1 - port: 8080 #If you configure port 443, you'll need to update the listener with tls_certificates - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s overrides: optimize_context_window: true diff --git a/docs/source/concepts/includes/arch_config.yaml b/docs/source/concepts/includes/arch_config.yaml index c78f35f7..a7d0a289 100644 --- a/docs/source/concepts/includes/arch_config.yaml +++ b/docs/source/concepts/includes/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 0.0.0.0 # or 127.0.0.1 - port: 10000 - # Defines how Arch should parse the content from application/json or text/pain Content-type in the http request - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: @@ -13,7 +14,6 @@ llm_providers: access_key: $OPENAI_API_KEY model: gpt-4o default: true - stream: true # default system prompt used by all prompt targets system_prompt: You are a network assistant that just offers facts; not advice on manufacturers or purchasing decisions. @@ -52,11 +52,6 @@ prompt_targets: default: false enum: [true, false] -error_target: - endpoint: - name: error_target_1 - path: /error - # Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem. endpoints: app_server: diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index 268bf45d..d73ef7ca 100644 --- a/docs/source/get_started/quickstart.rst +++ b/docs/source/get_started/quickstart.rst @@ -42,11 +42,12 @@ Create ``arch_config.yaml`` file with the following content: version: v0.1 - listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s + listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s llm_providers: - name: gpt-4o @@ -144,22 +145,23 @@ Create ``arch_config.yaml`` file with the following content: version: v0.1 - listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s + listeners: + egress_traffic: + address: 0.0.0.0 + port: 12000 + message_format: openai + timeout: 30s llm_providers: - name: gpt-4o access_key: $OPENAI_API_KEY - provider: openai + provider_interface: openai model: gpt-4o default: true - name: ministral-3b access_key: $MISTRAL_API_KEY - provider: mistral + provider_interface: openai model: ministral-3b-latest Step 2. Start arch gateway diff --git a/docs/source/guides/includes/arch_config.yaml b/docs/source/guides/includes/arch_config.yaml index 415c74aa..e86c6072 100644 --- a/docs/source/guides/includes/arch_config.yaml +++ b/docs/source/guides/includes/arch_config.yaml @@ -1,10 +1,11 @@ version: v0.1 -listener: - address: 0.0.0.0 # or 127.0.0.1 - port: 10000 - # Defines how Arch should parse the content from application/json or text/pain Content-type in the http request - message_format: huggingface +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: @@ -13,7 +14,6 @@ llm_providers: access_key: $OPENAI_API_KEY model: gpt-4o default: true - stream: true # default system prompt used by all prompt targets system_prompt: You are a network assistant that just offers facts; not advice on manufacturers or purchasing decisions. @@ -54,11 +54,6 @@ prompt_targets: default: false enum: [true, false] -error_target: - endpoint: - name: error_target_1 - path: /error - # Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem. endpoints: app_server: diff --git a/docs/source/resources/includes/arch_config_full_reference.yaml b/docs/source/resources/includes/arch_config_full_reference.yaml index f21fc1f5..90bbef56 100644 --- a/docs/source/resources/includes/arch_config_full_reference.yaml +++ b/docs/source/resources/includes/arch_config_full_reference.yaml @@ -1,16 +1,16 @@ version: v0.1 -listener: - address: 0.0.0.0 # or 127.0.0.1 - port: 10000 - # Defines how Arch should parse the content from application/json or text/pain Content-type in the http request - message_format: huggingface - common_tls_context: # If you configure port 443, you'll need to update the listener with your TLS certificates - tls_certificates: - - certificate_chain: - filename: /etc/certs/cert.pem - private_key: - filename: /etc/certs/key.pem +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 5s + egress_traffic: + address: 0.0.0.0 + port: 12000 + message_format: openai + timeout: 5s # Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem. endpoints: @@ -35,15 +35,6 @@ llm_providers: access_key: $OPENAI_API_KEY model: gpt-4o default: true - stream: true - rate_limits: - selector: #optional headers, to add rate limiting based on http headers like JWT tokens or API keys - http_header: - name: Authorization - value: "" # Empty value means each separate value has a separate limit - limit: - tokens: 100000 # Tokens per unit - unit: minute - name: Mistral8x7b provider_interface: openai @@ -99,11 +90,6 @@ prompt_targets: default: false enum: [true, false] -error_target: - endpoint: - name: error_target_1 - path: /error - tracing: # sampling rate. Note by default Arch works on OpenTelemetry compatible tracing. sampling_rate: 0.1 diff --git a/tests/archgw/arch_config.yaml b/tests/archgw/arch_config.yaml index 2c3d85d5..d1990330 100644 --- a/tests/archgw/arch_config.yaml +++ b/tests/archgw/arch_config.yaml @@ -1,10 +1,11 @@ version: "0.1-beta" -listener: - address: 0.0.0.0 - port: 10000 - message_format: huggingface - connect_timeout: 0.005s +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s endpoints: weather_forecast_service: From 1bbc5d22330edb70cfeced5c2ef0abcdb560d77e Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 14 Feb 2025 20:02:59 -0800 Subject: [PATCH 06/37] release 0.2.2 (#413) --- README.md | 2 +- arch/tools/README.md | 2 +- arch/tools/poetry.lock | 2159 +----------------------- arch/tools/pyproject.toml | 6 +- docs/source/conf.py | 2 +- docs/source/get_started/quickstart.rst | 2 +- model_server/poetry.lock | 573 +++---- model_server/pyproject.toml | 2 +- 8 files changed, 306 insertions(+), 2442 deletions(-) diff --git a/README.md b/README.md index e3a6a8ba..e3eca933 100644 --- a/README.md +++ b/README.md @@ -73,7 +73,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. ```console $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate -$ pip install archgw==0.2.1 +$ pip install archgw==0.2.2 ``` ### Build AI Agent with Arch Gateway diff --git a/arch/tools/README.md b/arch/tools/README.md index a4722c4a..240e3ba3 100644 --- a/arch/tools/README.md +++ b/arch/tools/README.md @@ -19,7 +19,7 @@ source venv/bin/activate ### Step 3: Run the build script ```bash -pip install archgw==0.2.1 +pip install archgw==0.2.2 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index 0ccc45d3..5ff3eaa4 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -1,116 +1,17 @@ # This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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-- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index d73ef7ca..5598eb33 100644 --- a/docs/source/get_started/quickstart.rst +++ b/docs/source/get_started/quickstart.rst @@ -25,7 +25,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate - $ pip install archgw==0.2.1 + $ pip install archgw==0.2.2 Build AI Agent with Arch Gateway diff --git a/model_server/poetry.lock b/model_server/poetry.lock index c08f77ca..a02b4b2c 100644 --- a/model_server/poetry.lock +++ b/model_server/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "accelerate" -version = "1.2.1" +version = "1.3.0" description = "Accelerate" optional = false python-versions = ">=3.9.0" files = [ - {file = 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"] license = "Apache 2.0" From ae6b2bef59cfee31ed2d86f771372d3bc2b2b986 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Thu, 20 Feb 2025 16:19:48 -0800 Subject: [PATCH 07/37] Fix compatibility issues with podman system (#415) - "dokcer inspect" doesn't return State/Status if container is not running - "docker remove" is not a command supported by podman - "docker logs" expect -f to be passed before container name --- arch/tools/cli/core.py | 2 +- arch/tools/cli/docker_cli.py | 9 ++++++--- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/arch/tools/cli/core.py b/arch/tools/cli/core.py index 291ca808..b263aed2 100644 --- a/arch/tools/cli/core.py +++ b/arch/tools/cli/core.py @@ -121,7 +121,7 @@ def stop_arch(): ["docker", "stop", ARCHGW_DOCKER_NAME], ) subprocess.run( - ["docker", "remove", ARCHGW_DOCKER_NAME], + ["docker", "rm", ARCHGW_DOCKER_NAME], ) log.info("Successfully shut down arch gateway service.") diff --git a/arch/tools/cli/docker_cli.py b/arch/tools/cli/docker_cli.py index edb8f764..6b8e3b59 100644 --- a/arch/tools/cli/docker_cli.py +++ b/arch/tools/cli/docker_cli.py @@ -15,7 +15,9 @@ def docker_container_status(container: str) -> str: ) if result.returncode != 0: return "not found" - return json.loads(result.stdout)[0]["State"]["Status"] + + container_status = json.loads(result.stdout)[0] + return container_status.get("State", {}).get("Status", "") def docker_stop_container(container: str) -> str: @@ -27,7 +29,7 @@ def docker_stop_container(container: str) -> str: def docker_remove_container(container: str) -> str: result = subprocess.run( - ["docker", "remove", container], capture_output=True, text=True, check=False + ["docker", "rm", container], capture_output=True, text=True, check=False ) return result.returncode @@ -90,9 +92,10 @@ def stream_gateway_logs(follow): """ log.info("Logs from arch gateway service.") - options = ["docker", "logs", ARCHGW_DOCKER_NAME] + options = ["docker", "logs"] if follow: options.append("-f") + options.append(ARCHGW_DOCKER_NAME) try: # Run `docker-compose logs` to stream logs from the gateway service subprocess.run( From a402fee13b16076903dca30127eaa4333ecfdb07 Mon Sep 17 00:00:00 2001 From: Sid Golestane Date: Fri, 28 Feb 2025 17:03:21 -0800 Subject: [PATCH 08/37] fix: add --type=container to docker inspect to prevent Podman conflicts (#418) * fix: add --type=container to docker inspect to prevent Podman conflicts Adding `--type=container` ensures `docker inspect` targets containers specifically, preventing conflicts with images in Podman. * Format Python code using pre-commit hook --------- Co-authored-by: Sid Golestaneh --- arch/tools/cli/docker_cli.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/arch/tools/cli/docker_cli.py b/arch/tools/cli/docker_cli.py index 6b8e3b59..59a0553c 100644 --- a/arch/tools/cli/docker_cli.py +++ b/arch/tools/cli/docker_cli.py @@ -11,7 +11,10 @@ log = getLogger(__name__) def docker_container_status(container: str) -> str: result = subprocess.run( - ["docker", "inspect", container], capture_output=True, text=True, check=False + ["docker", "inspect", "--type=container", container], + capture_output=True, + text=True, + check=False, ) if result.returncode != 0: return "not found" From 10cad4d0b7bbb98e31d4dd0e6b641ebbd5fc19c2 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Mon, 3 Mar 2025 13:11:57 -0800 Subject: [PATCH 09/37] add health check endpoint for llm gateway (#420) * add health check endpoint for llm gateway * fix rust tests --- arch/tools/cli/core.py | 9 +++++++-- crates/common/src/api/open_ai.rs | 5 ++++- crates/llm_gateway/src/stream_context.rs | 8 +++++++- crates/llm_gateway/tests/integration.rs | 2 ++ 4 files changed, 20 insertions(+), 4 deletions(-) diff --git a/arch/tools/cli/core.py b/arch/tools/cli/core.py index b263aed2..b0a6e58c 100644 --- a/arch/tools/cli/core.py +++ b/arch/tools/cli/core.py @@ -80,9 +80,14 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False): start_time = time.time() while True: - health_check_status = health_check_endpoint( + prompt_gateway_health_check_status = health_check_endpoint( f"http://localhost:{prompt_gateway_port}/healthz" ) + + llm_gateway_health_check_status = health_check_endpoint( + f"http://localhost:{llm_gateway_port}/healthz" + ) + archgw_status = docker_container_status(ARCHGW_DOCKER_NAME) current_time = time.time() elapsed_time = current_time - start_time @@ -92,7 +97,7 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False): log.info(f"stopping log monitoring after {log_timeout} seconds.") break - if health_check_status: + if prompt_gateway_health_check_status or llm_gateway_health_check_status: log.info("archgw is running and is healthy!") break else: diff --git a/crates/common/src/api/open_ai.rs b/crates/common/src/api/open_ai.rs index 8c72a7cd..2a07ce3f 100644 --- a/crates/common/src/api/open_ai.rs +++ b/crates/common/src/api/open_ai.rs @@ -135,7 +135,10 @@ impl From for ParameterType { "array" => ParameterType::List, "dict" => ParameterType::Dict, "dictionary" => ParameterType::Dict, - _ => ParameterType::String, + _ => { + log::warn!("Unknown parameter type: {}, assuming type str", s); + ParameterType::String + }, } } } diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 69496a61..a3f67dfc 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -5,7 +5,7 @@ use common::api::open_ai::{ }; use common::configuration::LlmProvider; use common::consts::{ - ARCH_PROVIDER_HINT_HEADER, ARCH_ROUTING_HEADER, CHAT_COMPLETIONS_PATH, + ARCH_PROVIDER_HINT_HEADER, ARCH_ROUTING_HEADER, CHAT_COMPLETIONS_PATH, HEALTHZ_PATH, RATELIMIT_SELECTOR_HEADER_KEY, REQUEST_ID_HEADER, TRACE_PARENT_HEADER, }; use common::errors::ServerError; @@ -176,6 +176,12 @@ impl HttpContext for StreamContext { // Envoy's HTTP model is event driven. The WASM ABI has given implementors events to hook onto // the lifecycle of the http request and response. fn on_http_request_headers(&mut self, _num_headers: usize, _end_of_stream: bool) -> Action { + let request_path = self.get_http_request_header(":path").unwrap_or_default(); + if request_path == HEALTHZ_PATH { + self.send_http_response(200, vec![], None); + return Action::Continue; + } + self.select_llm_provider(); // if endpoint is not set then use provider name as routing header so envoy can resolve the cluster name diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index 0b28a175..777d3790 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -18,6 +18,8 @@ fn wasm_module() -> String { fn request_headers_expectations(module: &mut Tester, http_context: i32) { module .call_proxy_on_request_headers(http_context, 0, false) + .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some(":path")) + .returning(Some("/v1/chat/completions")) .expect_get_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider-hint"), From e77fc47225b2489552c631accc79eabb668b00f8 Mon Sep 17 00:00:00 2001 From: Shuguang Chen <54548843+nehcgs@users.noreply.github.com> Date: Tue, 4 Mar 2025 12:49:13 -0800 Subject: [PATCH 10/37] Handle intent matching better in arch gateway (#391) --- crates/common/src/api/open_ai.rs | 9 +- crates/prompt_gateway/src/stream_context.rs | 174 ++++--- crates/prompt_gateway/tests/integration.rs | 267 +++++++++- .../currency_exchange/arch_config.yaml | 2 +- model_server/src/core/function_calling.py | 33 +- model_server/src/core/utils/model_utils.py | 2 +- model_server/src/main.py | 1 + tests/e2e/poetry.lock | 471 ++++++++++-------- tests/e2e/pyproject.toml | 2 +- tests/e2e/test_prompt_gateway.py | 1 - 10 files changed, 653 insertions(+), 309 deletions(-) diff --git a/crates/common/src/api/open_ai.rs b/crates/common/src/api/open_ai.rs index 2a07ce3f..f318ebc4 100644 --- a/crates/common/src/api/open_ai.rs +++ b/crates/common/src/api/open_ai.rs @@ -138,7 +138,7 @@ impl From for ParameterType { _ => { log::warn!("Unknown parameter type: {}, assuming type str", s); ParameterType::String - }, + } } } } @@ -205,13 +205,6 @@ pub struct ToolCallState { pub enum ArchState { ToolCall(Vec), } -#[derive(Deserialize, Serialize)] -#[serde(untagged)] -pub enum ModelServerResponse { - ChatCompletionsResponse(ChatCompletionsResponse), - ModelServerErrorResponse(ModelServerErrorResponse), -} - #[derive(Debug, Clone, Serialize, Deserialize)] pub struct ModelServerErrorResponse { pub result: String, diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index d197b3e0..87cf3ee9 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -2,7 +2,7 @@ use crate::metrics::Metrics; use crate::tools::compute_request_path_body; use common::api::open_ai::{ to_server_events, ArchState, ChatCompletionStreamResponse, ChatCompletionsRequest, - ChatCompletionsResponse, Message, ModelServerResponse, ToolCall, + ChatCompletionsResponse, Message, ToolCall, }; use common::configuration::{Overrides, PromptTarget, Tracing}; use common::consts::{ @@ -128,7 +128,7 @@ impl StreamContext { debug!("model server response received"); trace!("response body: {}", body_str); - let model_server_response: ModelServerResponse = match serde_json::from_str(&body_str) { + let model_server_response: ChatCompletionsResponse = match serde_json::from_str(&body_str) { Ok(arch_fc_response) => arch_fc_response, Err(e) => { warn!( @@ -139,77 +139,121 @@ impl StreamContext { } }; - let arch_fc_response = match model_server_response { - ModelServerResponse::ChatCompletionsResponse(response) => response, - ModelServerResponse::ModelServerErrorResponse(response) => { - debug!("archgw <= modelserver error response: {}", response.result); - if response.result == "No intent matched" { - if let Some(default_prompt_target) = self - .prompt_targets - .values() - .find(|pt| pt.default.unwrap_or(false)) - { - debug!("default prompt target found, forwarding request to default prompt target"); - let endpoint = default_prompt_target.endpoint.clone().unwrap(); - let upstream_path: String = endpoint.path.unwrap_or(String::from("/")); + // intent was matched if we see function_latency in metadata + let intent_matched = model_server_response + .metadata + .as_ref() + .and_then(|metadata| metadata.get("function_latency")) + .is_some(); - let upstream_endpoint = endpoint.name; - let mut params = HashMap::new(); - params.insert( - MESSAGES_KEY.to_string(), - callout_context.request_body.messages.clone(), - ); - let arch_messages_json = serde_json::to_string(¶ms).unwrap(); - let timeout_str = DEFAULT_TARGET_REQUEST_TIMEOUT_MS.to_string(); + if !intent_matched { + debug!("intent not matched"); + // check if we have a default prompt target + if let Some(default_prompt_target) = self + .prompt_targets + .values() + .find(|pt| pt.default.unwrap_or(false)) + { + debug!("default prompt target found, forwarding request to default prompt target"); + let endpoint = default_prompt_target.endpoint.clone().unwrap(); + let upstream_path: String = endpoint.path.unwrap_or(String::from("/")); - let mut headers = vec![ - (":method", "POST"), - (ARCH_UPSTREAM_HOST_HEADER, &upstream_endpoint), - (":path", &upstream_path), - (":authority", &upstream_endpoint), - ("content-type", "application/json"), - ("x-envoy-max-retries", "3"), - ("x-envoy-upstream-rq-timeout-ms", timeout_str.as_str()), - ]; + let upstream_endpoint = endpoint.name; + let mut params = HashMap::new(); + params.insert( + MESSAGES_KEY.to_string(), + callout_context.request_body.messages.clone(), + ); + let arch_messages_json = serde_json::to_string(¶ms).unwrap(); + let timeout_str = DEFAULT_TARGET_REQUEST_TIMEOUT_MS.to_string(); - if self.request_id.is_some() { - headers.push((REQUEST_ID_HEADER, self.request_id.as_ref().unwrap())); - } + let mut headers = vec![ + (":method", "POST"), + (ARCH_UPSTREAM_HOST_HEADER, &upstream_endpoint), + (":path", &upstream_path), + (":authority", &upstream_endpoint), + ("content-type", "application/json"), + ("x-envoy-max-retries", "3"), + ("x-envoy-upstream-rq-timeout-ms", timeout_str.as_str()), + ]; - // if self.trace_arch_internal() && self.traceparent.is_some() { - // headers.push((TRACE_PARENT_HEADER, self.traceparent.as_ref().unwrap())); - // } + if self.request_id.is_some() { + headers.push((REQUEST_ID_HEADER, self.request_id.as_ref().unwrap())); + } - let call_args = CallArgs::new( - ARCH_INTERNAL_CLUSTER_NAME, - &upstream_path, - headers, - Some(arch_messages_json.as_bytes()), - vec![], - Duration::from_secs(5), - ); - callout_context.response_handler_type = ResponseHandlerType::DefaultTarget; - callout_context.prompt_target_name = - Some(default_prompt_target.name.clone()); + let call_args = CallArgs::new( + ARCH_INTERNAL_CLUSTER_NAME, + &upstream_path, + headers, + Some(arch_messages_json.as_bytes()), + vec![], + Duration::from_secs(5), + ); + callout_context.response_handler_type = ResponseHandlerType::DefaultTarget; + callout_context.prompt_target_name = Some(default_prompt_target.name.clone()); - if let Err(e) = self.http_call(call_args, callout_context) { - warn!("error dispatching default prompt target request: {}", e); - return self.send_server_error( - ServerError::HttpDispatch(e), - Some(StatusCode::BAD_REQUEST), - ); - } - return; + if let Err(e) = self.http_call(call_args, callout_context) { + warn!("error dispatching default prompt target request: {}", e); + return self.send_server_error( + ServerError::HttpDispatch(e), + Some(StatusCode::BAD_REQUEST), + ); + } + return; + } else { + debug!("no default prompt target found, forwarding request to upstream llm"); + let mut messages = Vec::new(); + // add system prompt + match self.system_prompt.as_ref() { + None => {} + Some(system_prompt) => { + let system_prompt_message = Message { + role: SYSTEM_ROLE.to_string(), + content: Some(system_prompt.clone()), + model: None, + tool_calls: None, + tool_call_id: None, + }; + messages.push(system_prompt_message); } } - return self.send_server_error( - ServerError::LogicError(response.result), - Some(StatusCode::BAD_REQUEST), - ); - } - }; - arch_fc_response.choices[0] + messages.append( + &mut self + .filter_out_arch_messages(callout_context.request_body.messages.as_ref()), + ); + + let chat_completion_request = ChatCompletionsRequest { + model: self + .chat_completions_request + .as_ref() + .unwrap() + .model + .clone(), + messages, + tools: None, + stream: callout_context.request_body.stream, + stream_options: callout_context.request_body.stream_options, + metadata: None, + }; + + let chat_completion_request_json = + serde_json::to_string(&chat_completion_request).unwrap(); + debug!( + "archgw => upstream llm request: {}", + chat_completion_request_json + ); + self.set_http_request_body( + 0, + self.request_body_size, + chat_completion_request_json.as_bytes(), + ); + self.resume_http_request(); + return; + } + } + + model_server_response.choices[0] .message .tool_calls .clone_into(&mut self.tool_calls); @@ -238,7 +282,7 @@ impl StreamContext { ), ChatCompletionStreamResponse::new( Some( - arch_fc_response.choices[0] + model_server_response.choices[0] .message .content .as_ref() diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index 0792a319..c5d23297 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -363,7 +363,11 @@ fn prompt_gateway_request_to_llm_gateway() { }, }], model: String::from("test"), - metadata: None, + metadata: { + let mut map: HashMap = HashMap::new(); + map.insert("function_latency".to_string(), "0.0".to_string()); + Some(map) + }, }; let expected_body = "{\"city\":\"seattle\"}"; @@ -378,17 +382,17 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) .expect_http_call( Some("arch_internal"), Some(vec![ - (":method", "POST"), - ("content-type", "application/json"), - ("x-arch-upstream", "api_server"), - (":authority", "api_server"), ("x-envoy-max-retries", "3"), - (":path", "/weather"), + ("x-arch-upstream", "api_server"), + ("content-type", "application/json"), ("x-envoy-upstream-rq-timeout-ms", "30000"), + (":path", "/weather"), + (":method", "POST"), + (":authority", "api_server"), ]), Some(expected_body), None, @@ -452,3 +456,252 @@ fn prompt_gateway_request_to_llm_gateway() { .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); } + +#[test] +#[serial] +fn prompt_gateway_request_no_intent_match() { + let args = tester::MockSettings { + wasm_path: wasm_module(), + quiet: false, + allow_unexpected: false, + }; + let mut module = tester::mock(args).unwrap(); + + module + .call_start() + .execute_and_expect(ReturnType::None) + .unwrap(); + + // Setup Filter + let mut config: Configuration = serde_yaml::from_str(default_config()).unwrap(); + config.ratelimits.as_mut().unwrap()[0].limit.tokens += 1000; + let config_str = serde_json::to_string(&config).unwrap(); + + let filter_context = setup_filter(&mut module, &config_str); + + // Setup HTTP Stream + let http_context = 2; + + normal_flow(&mut module, filter_context, http_context); + + let arch_fc_resp = ChatCompletionsResponse { + usage: Some(Usage { + completion_tokens: 0, + }), + choices: vec![Choice { + finish_reason: Some("test".to_string()), + index: Some(0), + message: Message { + role: "system".to_string(), + content: None, + tool_calls: Some(vec![ToolCall { + id: String::from("test"), + tool_type: ToolType::Function, + function: FunctionCallDetail { + name: String::from("weather_forecast"), + arguments: HashMap::from([( + String::from("city"), + Value::String(String::from("seattle")), + )]), + }, + }]), + model: None, + tool_call_id: None, + }, + }], + model: String::from("test"), + metadata: None, + }; + + let arch_fc_resp_str = serde_json::to_string(&arch_fc_resp).unwrap(); + module + .call_proxy_on_http_call_response(http_context, 1, 0, arch_fc_resp_str.len() as i32, 0) + .expect_metric_increment("active_http_calls", -1) + .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) + .returning(Some(&arch_fc_resp_str)) + .expect_log(Some(LogLevel::Warn), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), Some("intent not matched")) + .expect_log( + Some(LogLevel::Debug), + Some("no default prompt target found, forwarding request to upstream llm"), + ) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) + .execute_and_expect(ReturnType::None) + .unwrap(); +} + +fn arch_config_default_target() -> &'static str { + r#" +version: "0.1-beta" + +listener: + address: 0.0.0.0 + port: 10000 + message_format: huggingface + connect_timeout: 0.005s + +endpoints: + api_server: + endpoint: api_server:80 + connect_timeout: 0.005s + +llm_providers: + - name: open-ai-gpt-4 + provider_interface: openai + access_key: secret_key + model: gpt-4 + default: true + +overrides: + # confidence threshold for prompt target intent matching + prompt_target_intent_matching_threshold: 0.0 + +system_prompt: | + You are a helpful assistant. + +prompt_guards: + input_guards: + jailbreak: + on_exception: + message: "Looks like you're curious about my abilities, but I can only provide assistance within my programmed parameters." + +prompt_targets: + - name: weather_forecast + description: This function provides realtime weather forecast information for a given city. + parameters: + - name: city + required: true + description: The city for which the weather forecast is requested. + - name: days + description: The number of days for which the weather forecast is requested. + - name: units + description: The units in which the weather forecast is requested. + endpoint: + name: api_server + path: /weather + http_method: POST + system_prompt: | + You are a helpful weather forecaster. Use weater data that is provided to you. Please following following guidelines when responding to user queries: + - Use farenheight for temperature + - Use miles per hour for wind speed + + - name: default_target + default: true + description: This is the default target for all unmatched prompts. + endpoint: + name: weather_forecast_service + path: /default_target + http_method: POST + system_prompt: | + You are a helpful assistant! Summarize the user's request and provide a helpful response. + # if it is set to false arch will send response that it received from this prompt target to the user + # if true arch will forward the response to the default LLM + auto_llm_dispatch_on_response: false + +ratelimits: + - model: gpt-4 + selector: + key: selector-key + value: selector-value + limit: + tokens: 1 + unit: minute +"# +} + +#[test] +#[serial] +fn prompt_gateway_request_no_intent_match_default_target() { + let args = tester::MockSettings { + wasm_path: wasm_module(), + quiet: false, + allow_unexpected: false, + }; + let mut module = tester::mock(args).unwrap(); + + module + .call_start() + .execute_and_expect(ReturnType::None) + .unwrap(); + + // Setup Filter + let mut config: Configuration = serde_yaml::from_str(arch_config_default_target()).unwrap(); + config.ratelimits.as_mut().unwrap()[0].limit.tokens += 1000; + let config_str = serde_json::to_string(&config).unwrap(); + + let filter_context = setup_filter(&mut module, &config_str); + + // Setup HTTP Stream + let http_context = 2; + + normal_flow(&mut module, filter_context, http_context); + + let arch_fc_resp = ChatCompletionsResponse { + usage: Some(Usage { + completion_tokens: 0, + }), + choices: vec![Choice { + finish_reason: Some("test".to_string()), + index: Some(0), + message: Message { + role: "system".to_string(), + content: None, + tool_calls: Some(vec![ToolCall { + id: String::from("test"), + tool_type: ToolType::Function, + function: FunctionCallDetail { + name: String::from("weather_forecast"), + arguments: HashMap::from([( + String::from("city"), + Value::String(String::from("seattle")), + )]), + }, + }]), + model: None, + tool_call_id: None, + }, + }], + model: String::from("test"), + metadata: None, + }; + + let arch_fc_resp_str = serde_json::to_string(&arch_fc_resp).unwrap(); + module + .call_proxy_on_http_call_response(http_context, 1, 0, arch_fc_resp_str.len() as i32, 0) + .expect_metric_increment("active_http_calls", -1) + .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) + .returning(Some(&arch_fc_resp_str)) + .expect_log(Some(LogLevel::Warn), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), Some("intent not matched")) + .expect_log( + Some(LogLevel::Debug), + Some("default prompt target found, forwarding request to default prompt target"), + ) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_http_call( + Some("arch_internal"), + Some(vec![ + (":method", "POST"), + ("x-arch-upstream", "weather_forecast_service"), + (":path", "/default_target"), + (":authority", "weather_forecast_service"), + ("content-type", "application/json"), + ("x-envoy-max-retries", "3"), + ("x-envoy-upstream-rq-timeout-ms", "30000"), + ]), + None, + None, + Some(5000), + ) + .returning(Some(2)) + .expect_metric_increment("active_http_calls", 1) + .execute_and_expect(ReturnType::None) + .unwrap(); +} diff --git a/demos/samples_python/currency_exchange/arch_config.yaml b/demos/samples_python/currency_exchange/arch_config.yaml index 1475abca..03e5a01d 100644 --- a/demos/samples_python/currency_exchange/arch_config.yaml +++ b/demos/samples_python/currency_exchange/arch_config.yaml @@ -19,7 +19,7 @@ endpoints: protocol: https system_prompt: | - You are a helpful assistant. + You are a helpful assistant. Only respond to queries related to currency exchange. If there are any other questions, I can't help you. prompt_guards: input_guards: diff --git a/model_server/src/core/function_calling.py b/model_server/src/core/function_calling.py index 99dd29ba..e1cc1b94 100644 --- a/model_server/src/core/function_calling.py +++ b/model_server/src/core/function_calling.py @@ -355,7 +355,7 @@ class ArchFunctionHandler(ArchBaseHandler): try: tool_content = json.loads(fixed_content) except Exception: - tool_calls, is_valid, error_message = [], False, e + is_valid, error_message = False, e break tool_calls.append( @@ -573,23 +573,26 @@ class ArchFunctionHandler(ArchBaseHandler): # Extract tool calls from model response extracted = self._extract_tool_calls(model_response) - if len(extracted["result"]) and extracted["status"]: - verified = self._verify_tool_calls( - tools=req.tools, tool_calls=extracted["result"] - ) - - if verified["status"]: - logger.info( - f"[Tool calls]: {json.dumps([tool_call['function'] for tool_call in extracted['result']])}" + if extracted["status"]: + # Response with tool calls + if len(extracted["result"]): + verified = self._verify_tool_calls( + tools=req.tools, tool_calls=extracted["result"] ) - model_response = Message(content="", tool_calls=extracted["result"]) + + if verified["status"]: + logger.info( + f"[Tool calls]: {json.dumps([tool_call['function'] for tool_call in extracted['result']])}" + ) + model_response = Message(content="", tool_calls=extracted["result"]) + else: + logger.error(f"Invalid tool call - {verified['message']}") + # Response without tool calls else: - logger.error(f"Invalid tool call - {verified['message']}") - # raise ValueError( - # f"[Arch-Function]: Invalid tool call - {verified['message']}" - # ) + model_response = Message(content=model_response, tool_calls=[]) + # Response with tool calls but contain errors else: - model_response = Message(content=model_response, tool_calls=[]) + logger.error(f"Tool call extraction error - {extracted['message']}") chat_completion_response = ChatCompletionResponse( choices=[Choice(message=model_response)], model=self.model_name diff --git a/model_server/src/core/utils/model_utils.py b/model_server/src/core/utils/model_utils.py index 7dc71acf..73dc6fef 100644 --- a/model_server/src/core/utils/model_utils.py +++ b/model_server/src/core/utils/model_utils.py @@ -171,7 +171,7 @@ class ArchBaseHandler: assert processed_messages[-1]["role"] == "user" if extra_instruction: - processed_messages[-1]["content"] += extra_instruction + processed_messages[-1]["content"] += "\n" + extra_instruction # keep the first system message and shift conversation if the total token length exceeds the limit def truncate_messages(messages: List[Dict[str, Any]]): diff --git a/model_server/src/main.py b/model_server/src/main.py index 683d6227..081ee241 100644 --- a/model_server/src/main.py +++ b/model_server/src/main.py @@ -104,6 +104,7 @@ async def function_calling(req: ChatMessage, res: Response): res.status_code = 500 error_messages = f"[Arch-Function] - Error in ChatCompletion: {e}" else: + # no intent matched intent_response.metadata = { "intent_latency": str(round(intent_latency * 1000, 3)), } diff --git a/tests/e2e/poetry.lock b/tests/e2e/poetry.lock index de08f7ee..7e296f88 100644 --- a/tests/e2e/poetry.lock +++ b/tests/e2e/poetry.lock @@ -1,14 +1,14 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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--git a/tests/e2e/pyproject.toml b/tests/e2e/pyproject.toml index bf557ef2..f9a0defd 100644 --- a/tests/e2e/pyproject.toml +++ b/tests/e2e/pyproject.toml @@ -8,7 +8,7 @@ readme = "README.md" package-mode = false [tool.poetry.dependencies] -python = "^3.12" +python = "^3.10" pytest = "^8.3.3" requests = "^2.29.0" selenium = "^4.11.2" diff --git a/tests/e2e/test_prompt_gateway.py b/tests/e2e/test_prompt_gateway.py index e4f64d89..f122ad30 100644 --- a/tests/e2e/test_prompt_gateway.py +++ b/tests/e2e/test_prompt_gateway.py @@ -257,7 +257,6 @@ def test_prompt_gateway_param_tool_call(stream): @pytest.mark.parametrize("stream", [True, False]) -@pytest.mark.skip("no longer needed") def test_prompt_gateway_default_target(stream): body = { "messages": [ From 2e2680c98c933c2bb0ddf89723302aa6e2b6074c Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Tue, 4 Mar 2025 12:49:34 -0800 Subject: [PATCH 11/37] Salanap/java debug ai (#416) * stashing changes on my local branch * updated the java demo with debug points and jaeger tracing --------- Co-authored-by: Salman Paracha --- archgw.code-workspace | 4 ++ .../weather_forcecast_service/.classpath | 49 +++++++++++++++++++ .../weather_forcecast_service/.project | 34 +++++++++++++ .../org.eclipse.core.resources.prefs | 4 ++ .../.settings/org.eclipse.jdt.apt.core.prefs | 2 + .../.settings/org.eclipse.jdt.core.prefs | 10 ++++ .../.settings/org.eclipse.m2e.core.prefs | 4 ++ .../weather_forcecast_service/Dockerfile | 7 ++- .../arch_config.yaml | 4 ++ .../docker-compose.yaml | 9 ++++ .../weather_forcecast_service/pom.xml | 9 ++++ 11 files changed, 135 insertions(+), 1 deletion(-) create mode 100644 demos/samples_java/weather_forcecast_service/.classpath create mode 100644 demos/samples_java/weather_forcecast_service/.project create mode 100644 demos/samples_java/weather_forcecast_service/.settings/org.eclipse.core.resources.prefs create mode 100644 demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.apt.core.prefs create mode 100644 demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.core.prefs create mode 100644 demos/samples_java/weather_forcecast_service/.settings/org.eclipse.m2e.core.prefs diff --git a/archgw.code-workspace b/archgw.code-workspace index 78c124e2..840bd2dd 100644 --- a/archgw.code-workspace +++ b/archgw.code-workspace @@ -31,6 +31,10 @@ { "name": "chatbot_ui", "path": "demos/shared/chatbot_ui" + }, + { + "name": "java_demo", + "path": "demos/samples_java/weather_forcecast_service" } ], "settings": { diff --git a/demos/samples_java/weather_forcecast_service/.classpath b/demos/samples_java/weather_forcecast_service/.classpath new file mode 100644 index 00000000..39abf1c5 --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.classpath @@ -0,0 +1,49 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/demos/samples_java/weather_forcecast_service/.project b/demos/samples_java/weather_forcecast_service/.project new file mode 100644 index 00000000..51363145 --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.project @@ -0,0 +1,34 @@ + + + weather-forecast-service + + + + + + org.eclipse.jdt.core.javabuilder + + + + + org.eclipse.m2e.core.maven2Builder + + + + + + org.eclipse.jdt.core.javanature + org.eclipse.m2e.core.maven2Nature + + + + 1739479945236 + + 30 + + org.eclipse.core.resources.regexFilterMatcher + node_modules|.git|__CREATED_BY_JAVA_LANGUAGE_SERVER__ + + + + diff --git a/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.core.resources.prefs b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.core.resources.prefs new file mode 100644 index 00000000..abdea9ac --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.core.resources.prefs @@ -0,0 +1,4 @@ +eclipse.preferences.version=1 +encoding//src/main/java=UTF-8 +encoding//src/main/resources=UTF-8 +encoding/=UTF-8 diff --git a/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.apt.core.prefs b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.apt.core.prefs new file mode 100644 index 00000000..d4313d4b --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.apt.core.prefs @@ -0,0 +1,2 @@ +eclipse.preferences.version=1 +org.eclipse.jdt.apt.aptEnabled=false diff --git a/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.core.prefs b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.core.prefs new file mode 100644 index 00000000..951833c6 --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.jdt.core.prefs @@ -0,0 +1,10 @@ +eclipse.preferences.version=1 +org.eclipse.jdt.core.compiler.codegen.methodParameters=generate +org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.8 +org.eclipse.jdt.core.compiler.compliance=1.8 +org.eclipse.jdt.core.compiler.problem.enablePreviewFeatures=disabled +org.eclipse.jdt.core.compiler.problem.forbiddenReference=warning +org.eclipse.jdt.core.compiler.problem.reportPreviewFeatures=ignore +org.eclipse.jdt.core.compiler.processAnnotations=disabled +org.eclipse.jdt.core.compiler.release=disabled +org.eclipse.jdt.core.compiler.source=1.8 diff --git a/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.m2e.core.prefs b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.m2e.core.prefs new file mode 100644 index 00000000..f897a7f1 --- /dev/null +++ b/demos/samples_java/weather_forcecast_service/.settings/org.eclipse.m2e.core.prefs @@ -0,0 +1,4 @@ +activeProfiles= +eclipse.preferences.version=1 +resolveWorkspaceProjects=true +version=1 diff --git a/demos/samples_java/weather_forcecast_service/Dockerfile b/demos/samples_java/weather_forcecast_service/Dockerfile index 1f536c5a..909d9796 100644 --- a/demos/samples_java/weather_forcecast_service/Dockerfile +++ b/demos/samples_java/weather_forcecast_service/Dockerfile @@ -14,5 +14,10 @@ WORKDIR /app # Copy the built jar from the previous stage COPY --from=build /app/target/weather-forecast-service-0.0.1-SNAPSHOT.jar app.jar # Expose the port on which the app runs (default Spring Boot is 8080) + +# Expose the application port and the debug port EXPOSE 8081 -ENTRYPOINT ["java", "-jar", "app.jar"] +EXPOSE 5005 + +# Start the application with remote debugging enabled +ENTRYPOINT ["java", "-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:5005", "-jar", "app.jar"] diff --git a/demos/samples_java/weather_forcecast_service/arch_config.yaml b/demos/samples_java/weather_forcecast_service/arch_config.yaml index 0e3007e2..8228d0f4 100644 --- a/demos/samples_java/weather_forcecast_service/arch_config.yaml +++ b/demos/samples_java/weather_forcecast_service/arch_config.yaml @@ -45,3 +45,7 @@ prompt_targets: name: weather_forecast_service path: /weather http_method: POST + +tracing: + random_sampling: 100 + trace_arch_internal: true diff --git a/demos/samples_java/weather_forcecast_service/docker-compose.yaml b/demos/samples_java/weather_forcecast_service/docker-compose.yaml index 998800b7..61bebd4c 100644 --- a/demos/samples_java/weather_forcecast_service/docker-compose.yaml +++ b/demos/samples_java/weather_forcecast_service/docker-compose.yaml @@ -5,6 +5,7 @@ services: dockerfile: Dockerfile ports: - "18081:8081" + - "5005:5005" chatbot_ui: build: @@ -18,3 +19,11 @@ services: - "host.docker.internal:host-gateway" volumes: - ./arch_config.yaml:/app/arch_config.yaml + + jaeger: + build: + context: ../../shared/jaeger + ports: + - "16686:16686" + - "4317:4317" + - "4318:4318" diff --git a/demos/samples_java/weather_forcecast_service/pom.xml b/demos/samples_java/weather_forcecast_service/pom.xml index c2fed928..db65d95a 100644 --- a/demos/samples_java/weather_forcecast_service/pom.xml +++ b/demos/samples_java/weather_forcecast_service/pom.xml @@ -35,6 +35,15 @@ org.springframework.boot spring-boot-maven-plugin + + org.apache.maven.plugins + maven-compiler-plugin + 3.8.1 + + true + lines,vars,source + + From 09c9d3706e28c842ef307e3ad56b0c8977a1837b Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Tue, 4 Mar 2025 14:16:03 -0800 Subject: [PATCH 12/37] publish docker release images (#422) * add release docker publish * more testing * fix more --- .../{docker-push.yml => docker-push-main.yml} | 2 +- .github/workflows/docker-push-release.yml | 87 +++++++++++++++++++ 2 files changed, 88 insertions(+), 1 deletion(-) rename .github/workflows/{docker-push.yml => docker-push-main.yml} (98%) create mode 100644 .github/workflows/docker-push-release.yml diff --git a/.github/workflows/docker-push.yml b/.github/workflows/docker-push-main.yml similarity index 98% rename from .github/workflows/docker-push.yml rename to .github/workflows/docker-push-main.yml index ae1cbfe8..8e0090e7 100644 --- a/.github/workflows/docker-push.yml +++ b/.github/workflows/docker-push-main.yml @@ -1,4 +1,4 @@ -name: Publish Docker image +name: Publish docker image (latest) env: DOCKER_IMAGE: katanemo/archgw diff --git a/.github/workflows/docker-push-release.yml b/.github/workflows/docker-push-release.yml new file mode 100644 index 00000000..6d9cf294 --- /dev/null +++ b/.github/workflows/docker-push-release.yml @@ -0,0 +1,87 @@ +name: Publish docker image (release) + +on: + release: + types: [published] + +jobs: + # Build ARM64 image on native ARM64 runner + build-arm64: + runs-on: [linux-arm64] + steps: + - name: Checkout Repository + uses: actions/checkout@v4 + + - name: Log in to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.DOCKER_IMAGE }} + + - name: Build and Push ARM64 Image + uses: docker/build-push-action@v5 + with: + context: . + file: ./arch/Dockerfile + platforms: linux/arm64 + push: true + tags: ${{ steps.meta.outputs.tags }}-arm64 + + # Build AMD64 image on GitHub's AMD64 runner + build-amd64: + runs-on: ubuntu-latest + steps: + - name: Checkout Repository + uses: actions/checkout@v4 + + - name: Log in to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.DOCKER_IMAGE }} + + - name: Build and Push AMD64 Image + uses: docker/build-push-action@v5 + with: + context: . + file: ./arch/Dockerfile + platforms: linux/amd64 + push: true + tags: ${{ steps.meta.outputs.tags }}-amd64 + + + # Combine ARM64 and AMD64 images into a multi-arch manifest + create-manifest: + runs-on: ubuntu-latest + needs: [build-arm64, build-amd64] # Wait for both builds + steps: + - name: Log in to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.DOCKER_IMAGE }} + + - name: Create Multi-Arch Manifest + run: | + # Combine the architecture-specific images into a single manifest + docker buildx imagetools create -t ${{ steps.meta.outputs.tags }} \ + ${{ env.DOCKER_IMAGE }}:arm64 \ + ${{ env.DOCKER_IMAGE }}:amd64 From d8b833fe69dc7639607d488df68f0bb4b93ece51 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Tue, 4 Mar 2025 14:30:44 -0800 Subject: [PATCH 13/37] release 0.2.3 (#423) --- README.md | 2 +- arch/tools/README.md | 2 +- arch/tools/poetry.lock | 212 ++++++++++++------------- arch/tools/pyproject.toml | 4 +- docs/source/conf.py | 2 +- docs/source/get_started/quickstart.rst | 2 +- model_server/poetry.lock | 102 ++++++------ model_server/pyproject.toml | 3 +- 8 files changed, 165 insertions(+), 164 deletions(-) diff --git a/README.md b/README.md index e3eca933..e9f5b270 100644 --- a/README.md +++ b/README.md @@ -73,7 +73,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. ```console $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate -$ pip install archgw==0.2.2 +$ pip install archgw==0.2.3 ``` ### Build AI Agent with Arch Gateway diff --git a/arch/tools/README.md b/arch/tools/README.md index 240e3ba3..eb4dcb64 100644 --- a/arch/tools/README.md +++ b/arch/tools/README.md @@ -19,7 +19,7 @@ source venv/bin/activate ### Step 3: Run the build script ```bash -pip install archgw==0.2.2 +pip install archgw==0.2.3 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index 5ff3eaa4..5f7fcbd6 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -2,7 +2,7 @@ [[package]] name = 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--------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index 5598eb33..a7e6b639 100644 --- a/docs/source/get_started/quickstart.rst +++ b/docs/source/get_started/quickstart.rst @@ -25,7 +25,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate - $ pip install archgw==0.2.2 + $ pip install archgw==0.2.3 Build AI Agent with Arch Gateway diff --git a/model_server/poetry.lock b/model_server/poetry.lock index a02b4b2c..60a07b5d 100644 --- a/model_server/poetry.lock +++ b/model_server/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "accelerate" -version = "1.3.0" +version = "1.4.0" description = "Accelerate" optional = false python-versions = ">=3.9.0" files = [ - {file = 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["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.14.*)", "pytest-mypy"] +test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] +type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (>=1.12,<1.14)", "pytest-mypy"] [[package]] name = "six" @@ -1977,18 +1977,18 @@ telegram = ["requests"] [[package]] name = "transformers" -version = "4.48.3" +version = "4.49.0" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" optional = false python-versions = ">=3.9.0" files = [ - {file = "transformers-4.48.3-py3-none-any.whl", hash = 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(>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision"] +all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av", "codecarbon (>=2.8.1)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision"] audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] benchmark = ["optimum-benchmark (>=0.3.0)"] codecarbon = ["codecarbon (>=2.8.1)"] deepspeed = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"] deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] -dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] +dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.21,<0.22)", "urllib3 (<2.0.0)"] dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"] flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"] @@ -2040,8 +2040,8 @@ tokenizers = ["tokenizers (>=0.21,<0.22)"] torch = ["accelerate (>=0.26.0)", "torch (>=2.0)"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] -torchhub = ["filelock", "huggingface-hub (>=0.24.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"] -video = ["av (==9.2.0)"] +torchhub = ["filelock", "huggingface-hub (>=0.26.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"] +video = ["av"] vision = ["Pillow (>=10.0.1,<=15.0)"] [[package]] @@ -2268,4 +2268,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "b8e46140dfec3638e577f0e40f6f46dfc35d46390fb63e7ac687323009f2dbce" +content-hash = "88cf76348bd82068cfc2e48d082ac09c9ae50c829f6c9bcb6e07b879214d6f0d" diff --git a/model_server/pyproject.toml b/model_server/pyproject.toml index c1acf272..56be1dc0 100644 --- a/model_server/pyproject.toml +++ b/model_server/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw_modelserver" -version = "0.2.2" +version = "0.2.3" description = "A model server for serving models" authors = ["Katanemo Labs, Inc "] license = "Apache 2.0" @@ -29,6 +29,7 @@ opentelemetry-instrumentation-fastapi = "^0.49b0" overrides = "^7.7.0" pytest-retry = "^1.6.3" pytest-httpserver = "^1.1.0" +setuptools = "75.5.0" [tool.poetry.scripts] archgw_modelserver = "src.cli:main" From 2d357ddd5ee154d451d8013e425502e85c24f566 Mon Sep 17 00:00:00 2001 From: Pat Thibodeau <55401734+pthibodeau11@users.noreply.github.com> Date: Wed, 5 Mar 2025 15:21:35 -0600 Subject: [PATCH 14/37] Update discord server invite url (#428) --- CONTRIBUTING.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 92f3fc17..8f2525a2 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,4 +1,5 @@ -# Contribution +# Contribution + We would love feedback on our [Roadmap](https://github.com/orgs/katanemo/projects/1) and we welcome contributions to **Arch**! Whether you're fixing bugs, adding new features, improving documentation, or creating tutorials, your help is much appreciated. @@ -22,7 +23,9 @@ $ cd arch ``` ### 3. Create a branch + Use a descriptive name for your branch (e.g., fix-bug-123, add-feature-x). + ```bash $ git checkout -b ``` @@ -32,6 +35,7 @@ $ git checkout -b Make your changes in the relevant files. If you're adding new features or fixing bugs, please include tests where applicable. ### 5. Test your changes + ```bash cd arch cargo test @@ -51,4 +55,4 @@ Contribution Guidelines Follow the existing coding style. Update documentation as needed. -To get in touch with us, please join our [discord server](https://discord.gg/rbjqVbpa). We will be monitoring that actively and offering support there. +To get in touch with us, please join our [discord server](https://discord.gg/pGZf2gcwEc). We will be monitoring that actively and offering support there. From ed3845040ef4cdd337f0061ab125d2b185c88b9f Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Wed, 5 Mar 2025 14:08:06 -0800 Subject: [PATCH 15/37] add demo for deepseek (#426) --- crates/llm_gateway/src/stream_context.rs | 10 ++++++---- crates/llm_gateway/tests/integration.rs | 2 +- demos/use_cases/llm_routing/arch_config.yaml | 7 +++++++ 3 files changed, 14 insertions(+), 5 deletions(-) diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index a3f67dfc..8e879eda 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -87,9 +87,11 @@ impl StreamContext { )); debug!( - "request received: llm provider hint: {:?}, selected llm: {}", - self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER), - self.llm_provider.as_ref().unwrap().name + "request received: llm provider hint: {}, selected llm: {}, model: {}", + self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER) + .unwrap_or_default(), + self.llm_provider.as_ref().unwrap().name, + self.llm_provider.as_ref().unwrap().model ); } @@ -494,7 +496,7 @@ impl HttpContext for StreamContext { //HACK: add support for tokenizing mistral and other models //filed issue https://github.com/katanemo/arch/issues/222 if !model.as_ref().unwrap().starts_with("gpt") { - warn!( + trace!( "tiktoken_rs: unsupported model: {}, using gpt-4 to compute token count", model.as_ref().unwrap() ); diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index 777d3790..b18a0d29 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -25,7 +25,7 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { Some("x-arch-llm-provider-hint"), ) .returning(None) - .expect_log(Some(LogLevel::Debug), Some("request received: llm provider hint: Some(\"default\"), selected llm: open-ai-gpt-4")) + .expect_log(Some(LogLevel::Debug), Some("request received: llm provider hint: default, selected llm: open-ai-gpt-4, model: gpt-4")) .expect_add_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider"), diff --git a/demos/use_cases/llm_routing/arch_config.yaml b/demos/use_cases/llm_routing/arch_config.yaml index e3238484..b4f87698 100644 --- a/demos/use_cases/llm_routing/arch_config.yaml +++ b/demos/use_cases/llm_routing/arch_config.yaml @@ -29,5 +29,12 @@ llm_providers: provider_interface: mistral model: ministral-3b-latest + - name: deepseek + access_key: $DEEPSEEK_API_KEY + provider_interface: openai + model: deepseek-reasoner + endpoint: api.deepseek.com + protocol: https + tracing: random_sampling: 100 From e8dc7f18d321a5ca820cf78634b4c1e4e3b2de9c Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Wed, 5 Mar 2025 17:20:04 -0800 Subject: [PATCH 16/37] start using base_url in place of endpoint (#430) --- arch/arch_config_schema.yaml | 5 +++- arch/tools/cli/config_generator.py | 28 ++++++++++++++++++++ demos/use_cases/llm_routing/arch_config.yaml | 3 +-- 3 files changed, 33 insertions(+), 3 deletions(-) diff --git a/arch/arch_config_schema.yaml b/arch/arch_config_schema.yaml index 1432c0b9..cab5cf17 100644 --- a/arch/arch_config_schema.yaml +++ b/arch/arch_config_schema.yaml @@ -62,7 +62,7 @@ properties: properties: name: type: string - # this field is deprecated, use provider_interface instead + # provider field is deprecated, use provider_interface instead provider: type: string enum: @@ -78,8 +78,11 @@ properties: type: string default: type: boolean + # endpoint field is deprecated, use base_url instead endpoint: type: string + base_url: + type: string protocol: type: string enum: diff --git a/arch/tools/cli/config_generator.py b/arch/tools/cli/config_generator.py index 7392849e..f0aae28a 100644 --- a/arch/tools/cli/config_generator.py +++ b/arch/tools/cli/config_generator.py @@ -3,6 +3,7 @@ import os from jinja2 import Environment, FileSystemLoader import yaml from jsonschema import validate +from urllib.parse import urlparse ENVOY_CONFIG_TEMPLATE_FILE = os.getenv( "ENVOY_CONFIG_TEMPLATE_FILE", "envoy.template.yaml" @@ -91,6 +92,9 @@ def validate_and_render_schema(): del llm_provider["provider"] updated_llm_providers.append(llm_provider) + if llm_provider.get("endpoint") and llm_provider.get("base_url"): + raise Exception("Please provide either endpoint or base_url, not both") + if llm_provider.get("endpoint", None): endpoint = llm_provider["endpoint"] protocol = llm_provider.get("protocol", "http") @@ -98,6 +102,30 @@ def validate_and_render_schema(): endpoint, protocol ) llms_with_endpoint.append(llm_provider) + elif llm_provider.get("base_url", None): + base_url = llm_provider["base_url"] + urlparse_result = urlparse(base_url) + if llm_provider.get("port"): + raise Exception("Please provider port in base_url") + if urlparse_result.scheme == "" or urlparse_result.scheme not in [ + "http", + "https", + ]: + raise Exception( + "Please provide a valid URL with scheme (http/https) in base_url" + ) + protocol = urlparse_result.scheme + port = urlparse_result.port + if port is None: + if protocol == "http": + port = 80 + else: + port = 443 + endpoint = urlparse_result.hostname + llm_provider["endpoint"] = endpoint + llm_provider["port"] = port + llm_provider["protocol"] = protocol + llms_with_endpoint.append(llm_provider) config_yaml["llm_providers"] = updated_llm_providers diff --git a/demos/use_cases/llm_routing/arch_config.yaml b/demos/use_cases/llm_routing/arch_config.yaml index b4f87698..4cccd718 100644 --- a/demos/use_cases/llm_routing/arch_config.yaml +++ b/demos/use_cases/llm_routing/arch_config.yaml @@ -33,8 +33,7 @@ llm_providers: access_key: $DEEPSEEK_API_KEY provider_interface: openai model: deepseek-reasoner - endpoint: api.deepseek.com - protocol: https + base_url: https://api.deepseek.com/ tracing: random_sampling: 100 From ffb8566c361087d5095f07a6078f93f152e57fff Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Sat, 8 Mar 2025 14:29:11 -0800 Subject: [PATCH 17/37] updating the network agent to work agin (#425) Co-authored-by: Salman Paracha --- .../arch_config.yaml | 26 +++++---- .../docker-compose.yaml | 8 +++ .../network_switch_operator_agent/main.py | 55 ++++++++----------- .../network_switch_operator_agent/run_demo.sh | 3 +- 4 files changed, 47 insertions(+), 45 deletions(-) diff --git a/demos/samples_python/network_switch_operator_agent/arch_config.yaml b/demos/samples_python/network_switch_operator_agent/arch_config.yaml index 40d529a2..fa830d0b 100644 --- a/demos/samples_python/network_switch_operator_agent/arch_config.yaml +++ b/demos/samples_python/network_switch_operator_agent/arch_config.yaml @@ -11,7 +11,7 @@ llm_providers: - name: OpenAI provider_interface: openai access_key: $OPENAI_API_KEY - model: gpt-3.5-turbo + model: gpt-4o default: true # default system prompt used by all prompt targets @@ -26,25 +26,26 @@ prompt_targets: path: /agent/device_summary http_method: POST parameters: - - name: device_ids - type: list - description: A list of device identifiers (IDs) to retrieve statistics for. + - name: device_id + type: str + description: A device identifier to retrieve statistics for. required: true # device_ids are required to get device statistics - name: days type: int description: The number of days for which to gather device statistics. - default: "7" - - name: reboot_devices - description: Reboot a list of devices + default: 7 + - name: reboot_device + description: Reboot a device endpoint: name: app_server path: /agent/device_reboot http_method: POST parameters: - - name: device_ids - type: list - description: A list of device identifiers (IDs). + - name: device_id + type: str + description: the device identifier required: true + system_prompt: You will get a status JSON object. Simply summarize it # Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem. endpoints: @@ -55,3 +56,8 @@ endpoints: endpoint: host.docker.internal:18083 # max time to wait for a connection to be established connect_timeout: 0.005s + + +tracing: + random_sampling: 100 + trace_arch_internal: true diff --git a/demos/samples_python/network_switch_operator_agent/docker-compose.yaml b/demos/samples_python/network_switch_operator_agent/docker-compose.yaml index 90b5c084..237afa4f 100644 --- a/demos/samples_python/network_switch_operator_agent/docker-compose.yaml +++ b/demos/samples_python/network_switch_operator_agent/docker-compose.yaml @@ -18,3 +18,11 @@ services: - "host.docker.internal:host-gateway" volumes: - ./arch_config.yaml:/app/arch_config.yaml + + jaeger: + build: + context: ../../shared/jaeger + ports: + - "16686:16686" + - "4317:4317" + - "4318:4318" diff --git a/demos/samples_python/network_switch_operator_agent/main.py b/demos/samples_python/network_switch_operator_agent/main.py index b9676c45..a7a07ab4 100644 --- a/demos/samples_python/network_switch_operator_agent/main.py +++ b/demos/samples_python/network_switch_operator_agent/main.py @@ -13,7 +13,7 @@ DEMO_DESCRIPTION = """This demo illustrates how **Arch** can be used to perform # Define the request model class DeviceSummaryRequest(BaseModel): - device_ids: List[int] + device_id: str time_range: Optional[int] = Field( default=7, description="Time range in days, defaults to 7" ) @@ -21,7 +21,7 @@ class DeviceSummaryRequest(BaseModel): # Define the response model class DeviceStatistics(BaseModel): - device_id: int + device_id: str time_range: str data: str @@ -33,7 +33,7 @@ class DeviceSummaryResponse(BaseModel): class DeviceRebootRequest(BaseModel): - device_ids: List[int] + device_id: str # Response model for the device reboot @@ -49,24 +49,21 @@ def reboot_network_device(request_data: DeviceRebootRequest): """ # Access data from the Pydantic model - device_ids = request_data.device_ids + device_id = request_data.device_id - # Validate 'device_ids' + # Validate 'device_id' # (This is already validated by Pydantic, but additional logic can be added if needed) - if not device_ids: - raise HTTPException( - status_code=400, detail="'device_ids' parameter is required" - ) + if not device_id: + raise HTTPException(status_code=400, detail="'device_id' parameter is required") # Simulate reboot operation and return the response statistics = [] - for device_id in device_ids: - # Placeholder for actual data retrieval or device reboot logic - stats = {"data": f"Device {device_id} has been successfully rebooted."} - statistics.append(stats) + # Placeholder for actual data retrieval or device reboot logic + stats = {"data": f"Device {device_id} has been successfully rebooted."} + statistics.append(stats) # Return the response with a summary - return CoverageResponse(status="success", summary={"device_ids": device_ids}) + return CoverageResponse(status="success", summary={"device_id": device_id}) # Post method for device summary @@ -76,28 +73,20 @@ def get_device_summary(request: DeviceSummaryRequest): Endpoint to retrieve device statistics based on device IDs and an optional time range. """ - # Extract 'device_ids' and 'time_range' from the request - device_ids = request.device_ids + # Extract 'device_id' and 'time_range' from the request + device_id = request.device_id time_range = request.time_range # Simulate retrieving statistics for the given device IDs and time range statistics = [] - minutes = 1 - for device_id in device_ids: - stats = { - "device_id": device_id, - "time_range": f"Last {time_range} days", - "data": f"""Device {device_id} over the last {time_range} days experienced {minutes} - minutes of downtime.""", - } - minutes += 1 - statistics.append(DeviceStatistics(**stats)) + minutes = 4 + stats = { + "device_id": device_id, + "time_range": f"Last {time_range} days", + "data": f"""Device {device_id} over the last {time_range} days experienced {minutes} + minutes of downtime.""", + } + + statistics.append(DeviceStatistics(**stats)) return DeviceSummaryResponse(statistics=statistics) - - -CHAT_COMPLETION_ENDPOINT = os.getenv("CHAT_COMPLETION_ENDPOINT") -client = OpenAI( - api_key="--", - base_url=CHAT_COMPLETION_ENDPOINT, -) diff --git a/demos/samples_python/network_switch_operator_agent/run_demo.sh b/demos/samples_python/network_switch_operator_agent/run_demo.sh index 6995e7d0..eb47dce6 100644 --- a/demos/samples_python/network_switch_operator_agent/run_demo.sh +++ b/demos/samples_python/network_switch_operator_agent/run_demo.sh @@ -22,9 +22,8 @@ start_demo() { echo "Starting Arch with arch_config.yaml..." archgw up arch_config.yaml - # Step 4: Start Network Agent + # Step 4: Start developer services echo "Starting Network Agent using Docker Compose..." - cd build docker compose up -d # Run in detached mode } From 5526314b3cf77e6d72456cc85f993258d2e869cb Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Mon, 17 Mar 2025 11:50:14 -0700 Subject: [PATCH 18/37] fix ollama demo - add egress endpoint for llm routing (#433) --- demos/use_cases/ollama/arch_config.yaml | 4 ++-- demos/use_cases/ollama/docker-compose.yaml | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/demos/use_cases/ollama/arch_config.yaml b/demos/use_cases/ollama/arch_config.yaml index 394d3d6c..c933841d 100644 --- a/demos/use_cases/ollama/arch_config.yaml +++ b/demos/use_cases/ollama/arch_config.yaml @@ -1,9 +1,9 @@ version: v0.1 listeners: - ingress_traffic: + egress_traffic: address: 0.0.0.0 - port: 10000 + port: 12000 message_format: openai timeout: 30s diff --git a/demos/use_cases/ollama/docker-compose.yaml b/demos/use_cases/ollama/docker-compose.yaml index ee5465a5..44fb20b7 100644 --- a/demos/use_cases/ollama/docker-compose.yaml +++ b/demos/use_cases/ollama/docker-compose.yaml @@ -6,7 +6,7 @@ services: - "18080:8080" environment: # this is only because we are running the sample app in the same docker container environemtn as archgw - - CHAT_COMPLETION_ENDPOINT=http://host.docker.internal:10000/v1 + - CHAT_COMPLETION_ENDPOINT=http://host.docker.internal:12000/v1 extra_hosts: - "host.docker.internal:host-gateway" volumes: From 6072d6ef3019391e7ff922a394bca0c73b6c3215 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Mon, 17 Mar 2025 14:07:06 -0700 Subject: [PATCH 19/37] updating the docs to improve usage guide for prompt_targets and function calling (#434) Co-authored-by: Salman Paracha --- docs/source/concepts/prompt_target.rst | 27 ++++++++++++------------- docs/source/guides/function_calling.rst | 3 +++ 2 files changed, 16 insertions(+), 14 deletions(-) diff --git a/docs/source/concepts/prompt_target.rst b/docs/source/concepts/prompt_target.rst index b489b0c1..d8f8df91 100644 --- a/docs/source/concepts/prompt_target.rst +++ b/docs/source/concepts/prompt_target.rst @@ -53,29 +53,28 @@ A prompt target configuration includes the following elements: - ``endpoint``: The API endpoint or function that handles the prompt. - ``parameters`` (Optional): A list of parameters to extract from the prompt. +.. _defining_prompt_target_parameters: + Defining Parameters ~~~~~~~~~~~~~~~~~~~ Parameters are the pieces of information that Arch needs to extract from the user's prompt to perform the desired action. -Each parameter can be marked as required or optional. -Here is a full list of parameter attributes that Arch can support: +Each parameter can be marked as required or optional. Here is a full list of parameter attributes that Arch can support: .. table:: :width: 100% - ==================== ============================================================================ + ======================== ============================================================================ **Attribute** **Description** - ==================== ============================================================================ - ``name`` Specifies identifier of parameters - ``type`` Specifies the data type of the parameter. - ``description`` Provides a human-readable explanation of the parameter's purpose. - ``required`` Indicates whether the parameter is mandatory or optional + ======================== ============================================================================ + ``name (req.)`` Specifies name of the parameter. + ``description (req.)`` Provides a human-readable explanation of the parameter's purpose. + ``type (req.)`` Specifies the data type. Supported types include: **int**, **str**, **float**, **bool**, **list**, **set**, **dict**, **tuple** ``default`` Specifies a default value for the parameter if not provided by the user. - ``items`` Used in the context of arrays to define the schema of items within an array. - ``format`` Specifies a format for the parameter value, e.g., date and email - ``enum`` Lists the allowable values for the parameter. - ``minimum`` Defines the minimum acceptable value for numeric parameters. - ``maximum`` Specifies the maximum acceptable value for numeric parameters. - ==================== ============================================================================ + ``format`` Specifies a format for the parameter value. For example: `2019-12-31` for a date value. + ``enum`` Lists of allowable values for the parameter with data type matching the ``type`` attribute. **Usage Example**: ``enum: ["celsius`", "fahrenheit"]`` + ``items`` Specifies the attribute of the elements when type euqals **list**, **set**, **dict**, **tuple**. **Usage Example**: ``items: {"type": "str"}`` + ``required`` Indicates whether the parameter is mandatory or optional. Valid values: **true** or **false** + ======================== ============================================================================ Example Configuration ~~~~~~~~~~~~~~~~~~~~~ diff --git a/docs/source/guides/function_calling.rst b/docs/source/guides/function_calling.rst index 036d0e00..072571d2 100644 --- a/docs/source/guides/function_calling.rst +++ b/docs/source/guides/function_calling.rst @@ -118,6 +118,9 @@ Specify the parameters your function needs and how Arch should interpret these. name: api_server path: /weather +.. Note:: + For a complete refernce of attributes that you can configure in a prompt target, see :ref:`here `. + Step 3: Arch Takes Over ~~~~~~~~~~~~~~~~~~~~~~~ Once you have defined the functions and configured the prompt targets, Arch Gateway takes care of the remaining work. From d2cb1427fb5c7b68fbc49b2c000174bc57fce4aa Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Mon, 17 Mar 2025 14:21:41 -0700 Subject: [PATCH 20/37] add hurl tests for currency exchange demo (#435) --- .github/workflows/e2e_test_demos.yml | 5 +++++ .../currency_exchange/hurl_tests/simple.hurl | 19 ++++++++++++++++ .../hurl_tests/simple_stream.hurl | 17 ++++++++++++++ demos/shared/test_runner/run_demo_tests.sh | 10 +++++---- tests/model_tests/arch_fc.hurl | 22 +++++++++++++++++++ 5 files changed, 69 insertions(+), 4 deletions(-) create mode 100644 demos/samples_python/currency_exchange/hurl_tests/simple.hurl create mode 100644 demos/samples_python/currency_exchange/hurl_tests/simple_stream.hurl create mode 100644 tests/model_tests/arch_fc.hurl diff --git a/.github/workflows/e2e_test_demos.yml b/.github/workflows/e2e_test_demos.yml index 0dfe3dd7..9033ca29 100644 --- a/.github/workflows/e2e_test_demos.yml +++ b/.github/workflows/e2e_test_demos.yml @@ -32,6 +32,11 @@ jobs: run: | python -m venv venv + - name: install hurl + run: | + curl --location --remote-name https://github.com/Orange-OpenSource/hurl/releases/download/4.0.0/hurl_4.0.0_amd64.deb + sudo dpkg -i hurl_4.0.0_amd64.deb + - name: install model server, arch gateway and test dependencies run: | source venv/bin/activate diff --git a/demos/samples_python/currency_exchange/hurl_tests/simple.hurl b/demos/samples_python/currency_exchange/hurl_tests/simple.hurl new file mode 100644 index 00000000..579de34a --- /dev/null +++ b/demos/samples_python/currency_exchange/hurl_tests/simple.hurl @@ -0,0 +1,19 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "convert 100 eur" + } + ] +} +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o/ +jsonpath "$.metadata.x-arch-state" != null +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/demos/samples_python/currency_exchange/hurl_tests/simple_stream.hurl b/demos/samples_python/currency_exchange/hurl_tests/simple_stream.hurl new file mode 100644 index 00000000..8315236c --- /dev/null +++ b/demos/samples_python/currency_exchange/hurl_tests/simple_stream.hurl @@ -0,0 +1,17 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "convert 100 eur" + } + ], + "stream": true +} +HTTP 200 +[Asserts] +header "content-type" matches /text\/event-stream/ +body matches /^data: .*?currency_exchange.*?\n/ +body matches /^data: .*?EUR.*?\n/ diff --git a/demos/shared/test_runner/run_demo_tests.sh b/demos/shared/test_runner/run_demo_tests.sh index a029345f..5b930565 100644 --- a/demos/shared/test_runner/run_demo_tests.sh +++ b/demos/shared/test_runner/run_demo_tests.sh @@ -8,11 +8,13 @@ do echo "Running tests for $demo ..." echo "****************************************" cd ../../samples_python/$demo + echo "starting archgw" archgw up arch_config.yaml - docker compose up -d - cd ../../shared/test_runner - TEST_DATA=../../samples_python/$demo/test_data.yaml poetry run pytest - cd ../../samples_python/$demo + echo "starting docker containers" + docker compose up -d 2>&1 > /dev/null + echo "starting hurl tests" + hurl --test hurl_tests/*.hurl + echo "stopping docker containers and archgw" archgw down docker compose down -v cd ../../shared/test_runner diff --git a/tests/model_tests/arch_fc.hurl b/tests/model_tests/arch_fc.hurl new file mode 100644 index 00000000..a16cdb92 --- /dev/null +++ b/tests/model_tests/arch_fc.hurl @@ -0,0 +1,22 @@ +POST https://archfc.katanemo.dev/v1/chat/completions +Content-Type: application/json + +{ + "model": "Arch-Intent", + "messages": [ + { + "role": "system", + "content": "You are a helpful assistant.\n\nYou task is to check if there are any tools that can be used to help the last user message in conversations according to the available tools listed below.\n\n\n{\"index\": \"T0\", \"type\": \"function\", \"function\": {\"name\": \"weather_forecast\", \"parameters\": {\"type\": \"object\", \"properties\": {\"city\": {\"type\": \"str\"}, \"days\": {\"type\": \"int\"}}, \"required\": [\"city\", \"days\"]}}}\n\n\nProvide your tool assessment for ONLY THE LAST USER MESSAGE in the above conversation:\n- First line must read 'Yes' or 'No'.\n- If yes, a second line must include a comma-separated list of tool indexes.\n" + }, + { "role": "user", "content": "how is the weather in seattle? Are there any tools can help?" } + ], + "stream": false +} + +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^Arch-Function/ +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" matches /Yes/ +jsonpath "$.choices[0].message.role" == "assistant" From c43513caffa81c04fc26f497c1960c76b1b6a944 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Tue, 18 Mar 2025 22:34:42 -0700 Subject: [PATCH 21/37] updating README to better describe the problems we are solving (#437) * updating README to better describe the problems we are solving * fixing formatting issues --------- Co-authored-by: Salman Paracha --- README.md | 29 +++++++++++++++++++---------- 1 file changed, 19 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index e9f5b270..c9912a04 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,9 @@
-_Arch is an intelligent (edge and LLM) proxy designed for agentic applications - to help you protect, observe, and build agentic tasks by simply connecting (existing) APIs._ + +_The intelligent (edge and LLM) proxy server for agentic applications._

+Move faster by letting Arch handle the **pesky** heavy lifting in building agetns: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs. [Quickstart](#Quickstart) • [Demos](#Demos) • @@ -16,25 +18,32 @@ _Arch is an intelligent (edge and LLM) proxy designed for agentic applications - [![rust tests (prompt and llm gateway)](https://github.com/katanemo/arch/actions/workflows/rust_tests.yml/badge.svg)](https://github.com/katanemo/arch/actions/workflows/rust_tests.yml) [![e2e tests](https://github.com/katanemo/arch/actions/workflows/e2e_tests.yml/badge.svg)](https://github.com/katanemo/arch/actions/workflows/e2e_tests.yml) [![Build and Deploy Documentation](https://github.com/katanemo/arch/actions/workflows/static.yml/badge.svg)](https://github.com/katanemo/arch/actions/workflows/static.yml) + +
# Overview -Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt +Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt +Past the thrill of a quick AI demo, have you ever found yourself hitting these walls 🧱? You know, the all-too-familiar ones: -Arch Gateway was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: +- You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff+** code? +- You want multiple LLMs, but struggle to **quickly and safely add new models** without integration code? +- You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively? +- You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently? ->Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems for personalization – outside core business logic.* +And you think to youself, can't I move faster and just focus on higher-level objectives in a language and framework agnostic way? Yes, you can! +**Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: - -Arch is engineered with purpose-built LLMs to handle critical but pesky tasks related to the handling and processing of prompts. This includes detecting and rejecting [jailbreak](https://github.com/verazuo/jailbreak_llms) attempts, intent-based routing for improved task accuracy, mapping user request into "backend" functions, and managing the observability of prompts and LLM API calls in a centralized way. +>Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems to improve speed and accuracy for common agentic scenarios – all outside core application logic.* **Core Features**: - - **Intent-based prompt routing & fast ⚡ function-calling via APIs**. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) to handle fast, cost-effective, and accurate prompt-based tasks like function/API calling, and parameter extraction from prompts to build more task-accurate agentic applications. - - **Prompt [Guard](https://huggingface.co/collections/katanemo/arch-guard-6702bdc08b889e4bce8f446d)**: Arch centralizes guardrails to prevent jailbreak attempts and ensure safe user interactions without writing a single line of code. - - **LLM Routing & Traffic Management**: Arch centralizes calls to LLMs used by your applications, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability. - - **Observability**: Arch uses the W3C Trace Context standard to enable complete request tracing across applications, ensuring compatibility with observability tools, and provides metrics to monitor latency, token usage, and error rates, helping optimize AI application performance. + - **Agent Routing**. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) for blazng fast (<100ms) routing and hand-off decisions to downstream agents. + - **Blazing Fast ⚡ Function Calling**: For common agentic scenarios, expose tools as APIs and let Arch detect, clarify and convert prompts to structured APIs + - **Prompt [Guardrails](https://huggingface.co/collections/katanemo/arch-guard-6702bdc08b889e4bce8f446d)**: Centralizes guardrails to prevent jailbreak attempts and harmful outcomes, and ensure safe user interactions without writing a single line of code. + - **Unified Access to (any) LLM**: Arch centralizes calls to LLMs used by your applications, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability. + - **Rich Observability**: Arch uses the W3C Trace Context standard to enable complete request tracing across applications, ensuring compatibility with observability tools, and provides metrics to monitor latency, token usage, and error rates, helping optimize AI application performance. - **Built on [Envoy](https://envoyproxy.io)**: Arch runs alongside application servers as a separate containerized process, and builds on top of Envoy's proven HTTP management and scalability features to handle ingress and egress traffic related to prompts and LLMs. **High-Level Sequence Diagram**: From 852ecf73f265665fb3260a3a93e24efdd81c8d90 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Tue, 18 Mar 2025 22:37:24 -0700 Subject: [PATCH 22/37] fixing typos --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index c9912a04..87f11dc6 100644 --- a/README.md +++ b/README.md @@ -25,10 +25,10 @@ Move faster by letting Arch handle the **pesky** heavy lifting in building agetn # Overview Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt -Past the thrill of a quick AI demo, have you ever found yourself hitting these walls 🧱? You know, the all-too-familiar ones: +Past the thrill of a quick AI demo, have you ever found yourself hitting these walls? You know, the all-too-familiar ones: -- You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff+** code? -- You want multiple LLMs, but struggle to **quickly and safely add new models** without integration code? +- You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff** code? +- You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code? - You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively? - You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently? From 85c8299a2b6161627db16dcffc689cd6ecda0d95 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Wed, 19 Mar 2025 13:45:35 -0700 Subject: [PATCH 23/37] Update README.md (#438) fixed typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 87f11dc6..d0223693 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ _The intelligent (edge and LLM) proxy server for agentic applications._

-Move faster by letting Arch handle the **pesky** heavy lifting in building agetns: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs. +Move faster by letting Arch handle the **pesky** heavy lifting in building agents: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs. [Quickstart](#Quickstart) • [Demos](#Demos) • From 8d66fefdedfe7a1cd60fe34c9064d4bc59287990 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Wed, 19 Mar 2025 14:19:49 -0700 Subject: [PATCH 24/37] Update README.md (#439) * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md --- README.md | 17 ++++++++--------- 1 file changed, 8 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index d0223693..d3b13d69 100644 --- a/README.md +++ b/README.md @@ -25,26 +25,25 @@ Move faster by letting Arch handle the **pesky** heavy lifting in building agent # Overview Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt -Past the thrill of a quick AI demo, have you ever found yourself hitting these walls? You know, the all-too-familiar ones: +Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones: - You go from one BIG prompt to specialized prompts, but get stuck building **routing and handoff** code? - You want use new LLMs, but struggle to **quickly and safely add LLMs** without writing integration code? - You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively? - You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently? -And you think to youself, can't I move faster and just focus on higher-level objectives in a language and framework agnostic way? Yes, you can! -**Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: +And you think to youself, can't I move faster by focusing on higher-level objectives in a language/framework agnostic way? Well, you can! **Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: >Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems to improve speed and accuracy for common agentic scenarios – all outside core application logic.* **Core Features**: - - **Agent Routing**. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) for blazng fast (<100ms) routing and hand-off decisions to downstream agents. - - **Blazing Fast ⚡ Function Calling**: For common agentic scenarios, expose tools as APIs and let Arch detect, clarify and convert prompts to structured APIs - - **Prompt [Guardrails](https://huggingface.co/collections/katanemo/arch-guard-6702bdc08b889e4bce8f446d)**: Centralizes guardrails to prevent jailbreak attempts and harmful outcomes, and ensure safe user interactions without writing a single line of code. - - **Unified Access to (any) LLM**: Arch centralizes calls to LLMs used by your applications, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability. - - **Rich Observability**: Arch uses the W3C Trace Context standard to enable complete request tracing across applications, ensuring compatibility with observability tools, and provides metrics to monitor latency, token usage, and error rates, helping optimize AI application performance. - - **Built on [Envoy](https://envoyproxy.io)**: Arch runs alongside application servers as a separate containerized process, and builds on top of Envoy's proven HTTP management and scalability features to handle ingress and egress traffic related to prompts and LLMs. + - `🚦 Routing`. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) for fast (<100ms) agent routing and hand-off scenarios + - `⚡ Tools Use`: For common agentic scenarios let Arch instantly clarfiy and convert prompts to tools/API calls + - `⛨ Guardrails`: Centrally configure and prevent harmful outcomes and ensure safe user interactions + - `🔗 Access to LLMs`: Centralize access and traffic to LLMs with smart retries for continuous availability + - `🕵 Observability`: W3C compatible request tracing and LLM metrics that instantly plugin with popular tools + - `🧱 Built on Envoy`: Arch runs alongside app servers as a containerized process, and builds on top of [Envoy's](https://envoyproxy.io) proven HTTP management and scalability features to handle ingress and egress traffic related to prompts and LLMs. **High-Level Sequence Diagram**: ![alt text](docs/source/_static/img/arch_network_diagram_high_level.png) From 84cd1df7bf774b87b6e17c9ee83cda5b9a34c38f Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Wed, 19 Mar 2025 15:21:34 -0700 Subject: [PATCH 25/37] add preliminary support for llm agents (#432) --- arch/Dockerfile | 1 + arch/arch_config_schema.yaml | 3 +- arch/envoy.template.yaml | 13 + arch/tools/cli/config_generator.py | 23 +- crates/common/src/api/open_ai.rs | 2 +- crates/common/src/configuration.rs | 3 +- crates/llm_gateway/src/filter_context.rs | 5 + crates/llm_gateway/src/stream_context.rs | 116 ++-- crates/llm_gateway/tests/integration.rs | 21 +- crates/prompt_gateway/src/filter_context.rs | 8 +- crates/prompt_gateway/src/http_context.rs | 36 +- crates/prompt_gateway/src/stream_context.rs | 102 +++- crates/prompt_gateway/src/tools.rs | 9 +- crates/prompt_gateway/tests/integration.rs | 15 +- .../weather_forecast/hurl_tests/simple.hurl | 19 + .../hurl_tests/simple_stream.hurl | 17 + .../use_cases/orchestrating_agents/Dockerfile | 41 ++ .../orchestrating_agents/arch_config.yaml | 46 ++ .../orchestrating_agents/docker-compose.yaml | 29 + .../hurl_tests/simple.hurl | 19 + .../hurl_tests/simple_stream.hurl | 16 + demos/use_cases/orchestrating_agents/main.py | 105 ++++ .../orchestrating_agents/poetry.lock | 573 ++++++++++++++++++ .../orchestrating_agents/pyproject.toml | 20 + .../orchestrating_agents/run_demo.sh | 47 ++ model_server/src/commons/globals.py | 7 + model_server/src/core/function_calling.py | 152 +++-- model_server/src/main.py | 44 +- tests/hurl/llm_gateway_simple.hurl | 17 + 29 files changed, 1388 insertions(+), 121 deletions(-) create mode 100644 demos/samples_python/weather_forecast/hurl_tests/simple.hurl create mode 100644 demos/samples_python/weather_forecast/hurl_tests/simple_stream.hurl create mode 100644 demos/use_cases/orchestrating_agents/Dockerfile create mode 100644 demos/use_cases/orchestrating_agents/arch_config.yaml create mode 100644 demos/use_cases/orchestrating_agents/docker-compose.yaml create mode 100644 demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl create mode 100644 demos/use_cases/orchestrating_agents/hurl_tests/simple_stream.hurl create mode 100644 demos/use_cases/orchestrating_agents/main.py create mode 100644 demos/use_cases/orchestrating_agents/poetry.lock create mode 100644 demos/use_cases/orchestrating_agents/pyproject.toml create mode 100644 demos/use_cases/orchestrating_agents/run_demo.sh create mode 100644 tests/hurl/llm_gateway_simple.hurl diff --git a/arch/Dockerfile b/arch/Dockerfile index 2c3c8744..98a113ad 100644 --- a/arch/Dockerfile +++ b/arch/Dockerfile @@ -28,4 +28,5 @@ COPY arch/arch_config_schema.yaml . RUN pip install requests RUN touch /var/log/envoy.log +# ENTRYPOINT ["sh","-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --log-level trace 2>&1 | tee /var/log/envoy.log"] ENTRYPOINT ["sh","-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --component-log-level wasm:debug 2>&1 | tee /var/log/envoy.log"] diff --git a/arch/arch_config_schema.yaml b/arch/arch_config_schema.yaml index cab5cf17..59276589 100644 --- a/arch/arch_config_schema.yaml +++ b/arch/arch_config_schema.yaml @@ -93,7 +93,6 @@ properties: additionalProperties: false required: - name - - model overrides: type: object properties: @@ -101,6 +100,8 @@ properties: type: number optimize_context_window: type: boolean + use_agent_orchestrator: + type: boolean system_prompt: type: string prompt_targets: diff --git a/arch/envoy.template.yaml b/arch/envoy.template.yaml index ca722b7c..cac17187 100644 --- a/arch/envoy.template.yaml +++ b/arch/envoy.template.yaml @@ -142,6 +142,19 @@ static_resources: cluster: {{ llm_cluster_name }} timeout: 60s {% endfor %} + + {% if agent_orchestrator %} + - match: + prefix: "/" + headers: + - name: "x-arch-llm-provider" + string_match: + exact: {{ agent_orchestrator }} + route: + auto_host_rewrite: true + cluster: {{ agent_orchestrator }} + timeout: 60s + {% endif %} http_filters: - name: envoy.filters.http.compressor typed_config: diff --git a/arch/tools/cli/config_generator.py b/arch/tools/cli/config_generator.py index f0aae28a..44ceda27 100644 --- a/arch/tools/cli/config_generator.py +++ b/arch/tools/cli/config_generator.py @@ -48,7 +48,7 @@ def validate_and_render_schema(): arch_config_schema = file.read() config_yaml = yaml.safe_load(arch_config) - config_schema_yaml = yaml.safe_load(arch_config_schema) + _ = yaml.safe_load(arch_config_schema) inferred_clusters = {} endpoints = config_yaml.get("endpoints", {}) @@ -150,6 +150,26 @@ def validate_and_render_schema(): if llm_gateway_listener.get("timeout") == None: llm_gateway_listener["timeout"] = "10s" + use_agent_orchestrator = config_yaml.get("overrides", {}).get( + "use_agent_orchestrator", False + ) + + agent_orchestrator = None + if use_agent_orchestrator: + print("Using agent orchestrator") + + if len(endpoints) == 0: + raise Exception( + "Please provide agent orchestrator in the endpoints section in your arch_config.yaml file" + ) + elif len(endpoints) > 1: + raise Exception( + "Please provide single agent orchestrator in the endpoints section in your arch_config.yaml file" + ) + else: + agent_orchestrator = list(endpoints.keys())[0] + + print("agent_orchestrator: ", agent_orchestrator) data = { "prompt_gateway_listener": prompt_gateway_listener, "llm_gateway_listener": llm_gateway_listener, @@ -159,6 +179,7 @@ def validate_and_render_schema(): "arch_llm_providers": config_yaml["llm_providers"], "arch_tracing": arch_tracing, "local_llms": llms_with_endpoint, + "agent_orchestrator": agent_orchestrator, } rendered = template.render(data) diff --git a/crates/common/src/api/open_ai.rs b/crates/common/src/api/open_ai.rs index f318ebc4..d71b0d58 100644 --- a/crates/common/src/api/open_ai.rs +++ b/crates/common/src/api/open_ai.rs @@ -189,7 +189,7 @@ pub struct ToolCall { #[derive(Debug, Clone, Serialize, Deserialize)] pub struct FunctionCallDetail { pub name: String, - pub arguments: HashMap, + pub arguments: Option>, } #[derive(Debug, Deserialize, Serialize)] diff --git a/crates/common/src/configuration.rs b/crates/common/src/configuration.rs index 1b954c3d..2065b1aa 100644 --- a/crates/common/src/configuration.rs +++ b/crates/common/src/configuration.rs @@ -25,6 +25,7 @@ pub struct Configuration { pub struct Overrides { pub prompt_target_intent_matching_threshold: Option, pub optimize_context_window: Option, + pub use_agent_orchestrator: Option, } #[derive(Debug, Clone, Serialize, Deserialize, Default)] @@ -159,7 +160,7 @@ pub struct LlmProvider { pub name: String, pub provider_interface: LlmProviderType, pub access_key: Option, - pub model: String, + pub model: Option, pub default: Option, pub stream: Option, pub endpoint: Option, diff --git a/crates/llm_gateway/src/filter_context.rs b/crates/llm_gateway/src/filter_context.rs index 0edba456..fc31355a 100644 --- a/crates/llm_gateway/src/filter_context.rs +++ b/crates/llm_gateway/src/filter_context.rs @@ -1,6 +1,7 @@ use crate::metrics::Metrics; use crate::stream_context::StreamContext; use common::configuration::Configuration; +use common::configuration::Overrides; use common::consts::OTEL_COLLECTOR_HTTP; use common::consts::OTEL_POST_PATH; use common::http::CallArgs; @@ -31,6 +32,7 @@ pub struct FilterContext { callouts: RefCell>, llm_providers: Option>, traces_queue: Arc>>, + overrides: Rc>, } impl FilterContext { @@ -40,6 +42,7 @@ impl FilterContext { metrics: Rc::new(Metrics::new()), llm_providers: None, traces_queue: Arc::new(Mutex::new(VecDeque::new())), + overrides: Rc::new(None), } } } @@ -69,6 +72,7 @@ impl RootContext for FilterContext { }; ratelimit::ratelimits(Some(config.ratelimits.unwrap_or_default())); + self.overrides = Rc::new(config.overrides); match config.llm_providers.try_into() { Ok(llm_providers) => self.llm_providers = Some(Rc::new(llm_providers)), @@ -93,6 +97,7 @@ impl RootContext for FilterContext { .expect("LLM Providers must exist when Streams are being created"), ), Arc::clone(&self.traces_queue), + Rc::clone(&self.overrides), ))) } diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 8e879eda..b4a05575 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -3,7 +3,7 @@ use common::api::open_ai::{ ChatCompletionStreamResponseServerEvents, ChatCompletionsRequest, ChatCompletionsResponse, Message, StreamOptions, }; -use common::configuration::LlmProvider; +use common::configuration::{LlmProvider, LlmProviderType, Overrides}; use common::consts::{ ARCH_PROVIDER_HINT_HEADER, ARCH_ROUTING_HEADER, CHAT_COMPLETIONS_PATH, HEALTHZ_PATH, RATELIMIT_SELECTOR_HEADER_KEY, REQUEST_ID_HEADER, TRACE_PARENT_HEADER, @@ -42,6 +42,7 @@ pub struct StreamContext { request_body_sent_time: Option, user_message: Option, traces_queue: Arc>>, + overrides: Rc>, } impl StreamContext { @@ -50,10 +51,12 @@ impl StreamContext { metrics: Rc, llm_providers: Rc, traces_queue: Arc>>, + overrides: Rc>, ) -> Self { StreamContext { context_id, metrics, + overrides, ratelimit_selector: None, streaming_response: false, response_tokens: 0, @@ -91,7 +94,12 @@ impl StreamContext { self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER) .unwrap_or_default(), self.llm_provider.as_ref().unwrap().name, - self.llm_provider.as_ref().unwrap().model + self.llm_provider + .as_ref() + .unwrap() + .model + .as_ref() + .unwrap_or(&String::new()) ); } @@ -151,11 +159,11 @@ impl StreamContext { // Tokenize and record token count. let token_count = tokenizer::token_count(model, json_string).unwrap_or(0); + trace!("Recorded input token count: {}", token_count); // Record the token count to metrics. self.metrics .input_sequence_length .record(token_count as u64); - trace!("Recorded input token count: {}", token_count); // Check if rate limiting needs to be applied. if let Some(selector) = self.ratelimit_selector.take() { @@ -184,24 +192,41 @@ impl HttpContext for StreamContext { return Action::Continue; } - self.select_llm_provider(); + let routing_header_value = self.get_http_request_header(ARCH_ROUTING_HEADER); - // if endpoint is not set then use provider name as routing header so envoy can resolve the cluster name - if self.llm_provider().endpoint.is_none() { + let use_agent_orchestrator = match self.overrides.as_ref() { + Some(overrides) => overrides.use_agent_orchestrator.unwrap_or_default(), + None => false, + }; + + if let Some(routing_header_value) = routing_header_value.as_ref() { + debug!("routing header already set: {}", routing_header_value); + self.llm_provider = Some(Rc::new(LlmProvider { + name: routing_header_value.to_string(), + provider_interface: LlmProviderType::OpenAI, + access_key: None, + endpoint: None, + model: None, + default: None, + stream: None, + port: None, + rate_limits: None, + })); + } else { + self.select_llm_provider(); self.add_http_request_header( ARCH_ROUTING_HEADER, &self.llm_provider().provider_interface.to_string(), ); - } else { - self.add_http_request_header(ARCH_ROUTING_HEADER, &self.llm_provider().name); - } - - if let Err(error) = self.modify_auth_headers() { - // ensure that the provider has an endpoint if the access key is missing else return a bad request - if self.llm_provider.as_ref().unwrap().endpoint.is_none() { - self.send_server_error(error, Some(StatusCode::BAD_REQUEST)); + if let Err(error) = self.modify_auth_headers() { + // ensure that the provider has an endpoint if the access key is missing else return a bad request + if self.llm_provider.as_ref().unwrap().endpoint.is_none() && !use_agent_orchestrator + { + self.send_server_error(error, Some(StatusCode::BAD_REQUEST)); + } } } + self.delete_content_length_header(); self.save_ratelimit_header(); @@ -230,34 +255,38 @@ impl HttpContext for StreamContext { return Action::Continue; } + let body_bytes = match self.get_http_request_body(0, body_size) { + Some(body_bytes) => body_bytes, + None => { + self.send_server_error( + ServerError::LogicError(format!( + "Failed to obtain body bytes even though body_size is {}", + body_size + )), + None, + ); + return Action::Pause; + } + }; + // Deserialize body into spec. // Currently OpenAI API. let mut deserialized_body: ChatCompletionsRequest = - match self.get_http_request_body(0, body_size) { - Some(body_bytes) => match serde_json::from_slice(&body_bytes) { - Ok(deserialized) => deserialized, - Err(e) => { - self.send_server_error( - ServerError::Deserialization(e), - Some(StatusCode::BAD_REQUEST), - ); - return Action::Pause; - } - }, - None => { + match serde_json::from_slice(&body_bytes) { + Ok(deserialized) => deserialized, + Err(e) => { + debug!("body str: {}", String::from_utf8_lossy(&body_bytes)); self.send_server_error( - ServerError::LogicError(format!( - "Failed to obtain body bytes even though body_size is {}", - body_size - )), - None, + ServerError::Deserialization(e), + Some(StatusCode::BAD_REQUEST), ); return Action::Pause; } }; // remove metadata from the request body - deserialized_body.metadata = None; + //TODO: move this to prompt gateway + // deserialized_body.metadata = None; // delete model key from message array for message in deserialized_body.messages.iter_mut() { message.model = None; @@ -270,10 +299,16 @@ impl HttpContext for StreamContext { .last() .cloned(); - // override model name from the llm provider - deserialized_body - .model - .clone_from(&self.llm_provider.as_ref().unwrap().model); + let model_name = match self.llm_provider.as_ref() { + Some(llm_provider) => match llm_provider.model.as_ref() { + Some(model) => model, + None => "--", + }, + None => "--", + }; + + deserialized_body.model = model_name.to_string(); + let chat_completion_request_str = serde_json::to_string(&deserialized_body).unwrap(); trace!( @@ -469,6 +504,10 @@ impl HttpContext for StreamContext { }; if self.streaming_response { + if body_utf8 == "data: [DONE]\n" { + return Action::Continue; + } + let chat_completions_chunk_response_events = match ChatCompletionStreamResponseServerEvents::try_from(body_utf8.as_str()) { Ok(response) => response, @@ -482,7 +521,10 @@ impl HttpContext for StreamContext { }; if chat_completions_chunk_response_events.events.is_empty() { - debug!("empty streaming response"); + debug!( + "cound't parse any streaming events: body str: {}", + body_utf8 + ); return Action::Continue; } diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index b18a0d29..71ec2e16 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -20,6 +20,11 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { .call_proxy_on_request_headers(http_context, 0, false) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some(":path")) .returning(Some("/v1/chat/completions")) + .expect_get_header_map_value( + Some(MapType::HttpRequestHeaders), + Some("x-arch-llm-provider"), + ) + .returning(None) .expect_get_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider-hint"), @@ -36,6 +41,7 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { Some("Authorization"), Some("Bearer secret_key"), ) + .expect_remove_header_map_value(Some(MapType::HttpRequestHeaders), Some("content-length")) .expect_get_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider-hint"), @@ -48,8 +54,6 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { .returning(Some("selector-key")) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some("selector-key")) .returning(Some("selector-value")) - .expect_get_header_map_pairs(Some(MapType::HttpRequestHeaders)) - .returning(None) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some(":path")) .returning(Some("/v1/chat/completions")) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some("x-request-id")) @@ -223,8 +227,8 @@ fn llm_gateway_successful_request_to_open_ai_chat_completions() { .returning(Some(chat_completions_request_body)) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) - .expect_metric_record("input_sequence_length", 21) .expect_log(Some(LogLevel::Trace), None) + .expect_metric_record("input_sequence_length", 21) .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) @@ -266,7 +270,7 @@ fn llm_gateway_bad_request_to_open_ai_chat_completions() { {\ \"messages\": [\ {\ - \"role\": \"system\",\ + \"role\": \"system\"\ },\ {\ \"role\": \"user\",\ @@ -283,14 +287,19 @@ fn llm_gateway_bad_request_to_open_ai_chat_completions() { ) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(incomplete_chat_completions_request_body)) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) .expect_send_local_response( Some(StatusCode::BAD_REQUEST.as_u16().into()), None, None, None, ) - .execute_and_expect(ReturnType::Action(Action::Pause)) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_metric_record("input_sequence_length", 14) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); } diff --git a/crates/prompt_gateway/src/filter_context.rs b/crates/prompt_gateway/src/filter_context.rs index f782dea2..d5368686 100644 --- a/crates/prompt_gateway/src/filter_context.rs +++ b/crates/prompt_gateway/src/filter_context.rs @@ -1,6 +1,8 @@ use crate::metrics::Metrics; use crate::stream_context::StreamContext; -use common::configuration::{Configuration, Overrides, PromptGuards, PromptTarget, Tracing}; +use common::configuration::{ + Configuration, Endpoint, Overrides, PromptGuards, PromptTarget, Tracing, +}; use common::http::Client; use common::stats::Gauge; use log::trace; @@ -21,6 +23,7 @@ pub struct FilterContext { overrides: Rc>, system_prompt: Rc>, prompt_targets: Rc>, + endpoints: Rc>>, prompt_guards: Rc, tracing: Rc>, } @@ -34,6 +37,7 @@ impl FilterContext { prompt_targets: Rc::new(HashMap::new()), overrides: Rc::new(None), prompt_guards: Rc::new(PromptGuards::default()), + endpoints: Rc::new(None), tracing: Rc::new(None), } } @@ -73,6 +77,7 @@ impl RootContext for FilterContext { } self.system_prompt = Rc::new(config.system_prompt); self.prompt_targets = Rc::new(prompt_targets); + self.endpoints = Rc::new(config.endpoints); if let Some(prompt_guards) = config.prompt_guards { self.prompt_guards = Rc::new(prompt_guards) @@ -94,6 +99,7 @@ impl RootContext for FilterContext { Rc::clone(&self.metrics), Rc::clone(&self.system_prompt), Rc::clone(&self.prompt_targets), + Rc::clone(&self.endpoints), Rc::clone(&self.overrides), Rc::clone(&self.tracing), ))) diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index 53a2d25b..b8eb2797 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -4,7 +4,7 @@ use common::{ self, ArchState, ChatCompletionStreamResponse, ChatCompletionTool, ChatCompletionsRequest, }, consts::{ - ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_STATE_HEADER, + ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_ROUTING_HEADER, ARCH_STATE_HEADER, ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, CHAT_COMPLETIONS_PATH, HEALTHZ_PATH, MODEL_SERVER_NAME, MODEL_SERVER_REQUEST_TIMEOUT_MS, REQUEST_ID_HEADER, TOOL_ROLE, TRACE_PARENT_HEADER, USER_ROLE, @@ -33,6 +33,27 @@ impl HttpContext for StreamContext { // manipulate the body in benign ways e.g., compression. self.set_http_request_header("content-length", None); + if let Some(overrides) = self.overrides.as_ref() { + if overrides.use_agent_orchestrator.unwrap_or_default() { + // get endpoint that has agent_orchestrator set to true + if let Some(endpoints) = self.endpoints.as_ref() { + if endpoints.len() == 1 { + let (name, _) = endpoints.iter().next().unwrap(); + debug!("Setting ARCH_PROVIDER_HINT_HEADER to {}", name); + self.set_http_request_header(ARCH_ROUTING_HEADER, Some(name)); + } else { + warn!("Need single endpoint when use_agent_orchestrator is set"); + self.send_server_error( + ServerError::LogicError( + "Need single endpoint when use_agent_orchestrator is set".to_string(), + ), + None, + ); + } + } + } + } + let request_path = self.get_http_request_header(":path").unwrap_or_default(); if request_path == HEALTHZ_PATH { self.send_http_response(200, vec![], None); @@ -49,6 +70,7 @@ impl HttpContext for StreamContext { self.request_id = self.get_http_request_header(REQUEST_ID_HEADER); self.traceparent = self.get_http_request_header(TRACE_PARENT_HEADER); + Action::Continue } @@ -152,6 +174,18 @@ impl HttpContext for StreamContext { } } + if let Some(overrides) = self.overrides.as_ref() { + if overrides.use_agent_orchestrator.unwrap_or_default() { + if metadata.is_none() { + metadata = Some(HashMap::new()); + } + metadata + .as_mut() + .unwrap() + .insert("use_agent_orchestrator".to_string(), "true".to_string()); + } + } + let arch_fc_chat_completion_request = ChatCompletionsRequest { messages: deserialized_body.messages.clone(), metadata, diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index 87cf3ee9..fddb3b20 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -4,7 +4,7 @@ use common::api::open_ai::{ to_server_events, ArchState, ChatCompletionStreamResponse, ChatCompletionsRequest, ChatCompletionsResponse, Message, ToolCall, }; -use common::configuration::{Overrides, PromptTarget, Tracing}; +use common::configuration::{Endpoint, Overrides, PromptTarget, Tracing}; use common::consts::{ API_REQUEST_TIMEOUT_MS, ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, DEFAULT_TARGET_REQUEST_TIMEOUT_MS, MESSAGES_KEY, @@ -46,6 +46,7 @@ pub struct StreamCallContext { pub struct StreamContext { system_prompt: Rc>, pub prompt_targets: Rc>, + pub endpoints: Rc>>, pub overrides: Rc>, pub metrics: Rc, pub callouts: RefCell>, @@ -72,6 +73,7 @@ impl StreamContext { metrics: Rc, system_prompt: Rc>, prompt_targets: Rc>, + endpoints: Rc>>, overrides: Rc>, tracing: Rc>, ) -> Self { @@ -80,6 +82,7 @@ impl StreamContext { metrics, system_prompt, prompt_targets, + endpoints, callouts: RefCell::new(HashMap::new()), chat_completions_request: None, tool_calls: None, @@ -312,12 +315,59 @@ impl StreamContext { callout_context.prompt_target_name = Some(self.tool_calls.as_ref().unwrap()[0].function.name.clone()); + if let Some(overrides) = self.overrides.as_ref() { + if overrides.use_agent_orchestrator.unwrap_or_default() { + let mut metadata = HashMap::new(); + metadata.insert("use_agent_orchestrator".to_string(), "true".to_string()); + + metadata.insert( + "agent-name".to_string(), + callout_context + .prompt_target_name + .as_ref() + .unwrap() + .to_string(), + ); + + if let Some(overrides) = self.overrides.as_ref() { + if overrides.optimize_context_window.unwrap_or_default() { + metadata.insert("optimize_context_window".to_string(), "true".to_string()); + } + } + + if let Some(overrides) = self.overrides.as_ref() { + if overrides.use_agent_orchestrator.unwrap_or_default() { + metadata.insert("use_agent_orchestrator".to_string(), "true".to_string()); + } + } + + let messages = self.construct_llm_messages(&callout_context); + + let chat_completion_request = ChatCompletionsRequest { + model: callout_context.request_body.model.clone(), + messages, + tools: None, + stream: callout_context.request_body.stream, + stream_options: callout_context.request_body.stream_options.clone(), + metadata: Some(metadata), + }; + + let body_str = serde_json::to_string(&chat_completion_request).unwrap(); + debug!("sending request to llm agent: {}", body_str); + self.set_http_request_body(0, self.request_body_size, body_str.as_bytes()); + self.resume_http_request(); + return; + } + } + self.schedule_api_call_request(callout_context); } fn schedule_api_call_request(&mut self, mut callout_context: StreamCallContext) { + // Construct messages early to avoid mutable borrow conflicts + let tools_call_name = self.tool_calls.as_ref().unwrap()[0].function.name.clone(); - let prompt_target = self.prompt_targets.get(&tools_call_name).unwrap(); + let prompt_target = self.prompt_targets.get(&tools_call_name).unwrap().clone(); let tool_params = &self.tool_calls.as_ref().unwrap()[0].function.arguments; let endpoint_details = prompt_target.endpoint.as_ref().unwrap(); let endpoint_path: String = endpoint_details @@ -329,7 +379,7 @@ impl StreamContext { let http_method = endpoint_details.method.clone().unwrap_or_default(); let prompt_target_params = prompt_target.parameters.clone().unwrap_or_default(); - let (path, body) = match compute_request_path_body( + let (path, api_call_body) = match compute_request_path_body( &endpoint_path, tool_params, &prompt_target_params, @@ -346,6 +396,8 @@ impl StreamContext { } }; + debug!("api call body {:?}", api_call_body); + let timeout_str = API_REQUEST_TIMEOUT_MS.to_string(); let http_method_str = http_method.to_string(); @@ -375,11 +427,12 @@ impl StreamContext { headers.insert(key.as_str(), value.as_str()); } + let call_args = CallArgs::new( ARCH_INTERNAL_CLUSTER_NAME, &path, headers.into_iter().collect(), - body.as_deref().map(|s| s.as_bytes()), + api_call_body.as_deref().map(|s| s.as_bytes()), vec![], Duration::from_secs(5), ); @@ -406,6 +459,11 @@ impl StreamContext { "developer api call response received: status code: {}", http_status ); + let prompt_target = self + .prompt_targets + .get(callout_context.prompt_target_name.as_ref().unwrap()) + .unwrap() + .clone(); if http_status != StatusCode::OK.as_str() { warn!( "api server responded with non 2xx status code: {}", @@ -441,6 +499,40 @@ impl StreamContext { } }; + if !prompt_target + .auto_llm_dispatch_on_response + .unwrap_or(true) + { + let tool_call_response = self.tool_call_response.as_ref().unwrap().clone(); + + let direct_response_str = if self.streaming_response { + let chunks = vec![ + ChatCompletionStreamResponse::new( + None, + Some(ASSISTANT_ROLE.to_string()), + Some(ARCH_FC_MODEL_NAME.to_owned()), + None, + ), + ChatCompletionStreamResponse::new( + Some(tool_call_response.clone()), + None, + Some(ARCH_FC_MODEL_NAME.to_owned()), + None, + ), + ]; + + to_server_events(chunks) + } else { + tool_call_response + }; + + return self.send_http_response( + StatusCode::OK.as_u16().into(), + vec![], + Some(direct_response_str.as_bytes()), + ); + } + let final_prompt = format!( "{}\ncontext: {}", user_message.content.unwrap(), @@ -565,7 +657,7 @@ impl StreamContext { // check if the default target should be dispatched to the LLM provider if !prompt_target .auto_llm_dispatch_on_response - .unwrap_or_default() + .unwrap_or(true) { let default_target_response_str = if self.streaming_response { let chat_completion_response = diff --git a/crates/prompt_gateway/src/tools.rs b/crates/prompt_gateway/src/tools.rs index b3b3d07e..c909a2dd 100644 --- a/crates/prompt_gateway/src/tools.rs +++ b/crates/prompt_gateway/src/tools.rs @@ -4,8 +4,13 @@ use std::collections::HashMap; use serde_yaml::Value; // only add params that are of string, number and bool type -pub fn filter_tool_params(tool_params: &HashMap) -> HashMap { +pub fn filter_tool_params(tool_params: &Option>) -> HashMap { + if tool_params.is_none() { + return HashMap::new(); + } tool_params + .as_ref() + .unwrap() .iter() .filter(|(_, value)| value.is_number() || value.is_string() || value.is_bool()) .map(|(key, value)| match value { @@ -22,7 +27,7 @@ pub fn filter_tool_params(tool_params: &HashMap) -> HashMap, + tool_params: &Option>, prompt_target_params: &[Parameter], http_method: &HttpMethod, ) -> Result<(String, Option), String> { diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index c5d23297..1673ac16 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -352,10 +352,10 @@ fn prompt_gateway_request_to_llm_gateway() { tool_type: ToolType::Function, function: FunctionCallDetail { name: String::from("weather_forecast"), - arguments: HashMap::from([( + arguments: Some(HashMap::from([( String::from("city"), Value::String(String::from("seattle")), - )]), + )])), }, }]), model: None, @@ -381,8 +381,8 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) .expect_http_call( Some("arch_internal"), Some(vec![ @@ -400,6 +400,7 @@ fn prompt_gateway_request_to_llm_gateway() { ) .returning(Some(2)) .expect_metric_increment("active_http_calls", 1) + .expect_log(Some(LogLevel::Trace), None) .execute_and_expect(ReturnType::None) .unwrap(); @@ -499,10 +500,10 @@ fn prompt_gateway_request_no_intent_match() { tool_type: ToolType::Function, function: FunctionCallDetail { name: String::from("weather_forecast"), - arguments: HashMap::from([( + arguments: Some(HashMap::from([( String::from("city"), Value::String(String::from("seattle")), - )]), + )])), }, }]), model: None, @@ -655,10 +656,10 @@ fn prompt_gateway_request_no_intent_match_default_target() { tool_type: ToolType::Function, function: FunctionCallDetail { name: String::from("weather_forecast"), - arguments: HashMap::from([( + arguments: Some(HashMap::from([( String::from("city"), Value::String(String::from("seattle")), - )]), + )])), }, }]), model: None, diff --git a/demos/samples_python/weather_forecast/hurl_tests/simple.hurl b/demos/samples_python/weather_forecast/hurl_tests/simple.hurl new file mode 100644 index 00000000..d1243d20 --- /dev/null +++ b/demos/samples_python/weather_forecast/hurl_tests/simple.hurl @@ -0,0 +1,19 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "how is the weather in seattle for next 5 days" + } + ] +} +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o/ +jsonpath "$.metadata.x-arch-state" != null +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" matches /Seattle/ +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/demos/samples_python/weather_forecast/hurl_tests/simple_stream.hurl b/demos/samples_python/weather_forecast/hurl_tests/simple_stream.hurl new file mode 100644 index 00000000..51844c2d --- /dev/null +++ b/demos/samples_python/weather_forecast/hurl_tests/simple_stream.hurl @@ -0,0 +1,17 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "how is the weather in seattle for next 5 days" + } + ], + "stream": true +} +HTTP 200 +[Asserts] +header "content-type" matches /text\/event-stream/ +body matches "(?s).*\"name\":\"get_current_weather\".*" +body matches "(?s).*\"model\":\"gpt-4o-mini.*" diff --git a/demos/use_cases/orchestrating_agents/Dockerfile b/demos/use_cases/orchestrating_agents/Dockerfile new file mode 100644 index 00000000..b53cb719 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/Dockerfile @@ -0,0 +1,41 @@ +# took inspiration from https://medium.com/@albertazzir/blazing-fast-python-docker-builds-with-poetry-a78a66f5aed0 + +# The builder image, used to build the virtual environment +FROM python:3.10 as builder + +RUN pip install poetry==1.8.3 + +ENV POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_IN_PROJECT=1 \ + POETRY_VIRTUALENVS_CREATE=1 \ + POETRY_CACHE_DIR=/tmp/poetry_cache + +WORKDIR /code + +COPY pyproject.toml poetry.lock ./ +RUN touch README.md + +RUN poetry install --no-root && rm -rf $POETRY_CACHE_DIR + +# The runtime image, used to just run the code provided its virtual environment +FROM python:3.10-slim as runtime + +RUN apt-get update && apt-get install -y curl + +WORKDIR /code + +ENV VIRTUAL_ENV=/code/.venv \ + PATH="/code/.venv/bin:$PATH" + +COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV} + +COPY main.py ./ + +HEALTHCHECK \ + --interval=5s \ + --timeout=1s \ + --start-period=1s \ + --retries=3 \ + CMD curl http://localhost:80/healthz + +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "80", "--log-level", "debug"] diff --git a/demos/use_cases/orchestrating_agents/arch_config.yaml b/demos/use_cases/orchestrating_agents/arch_config.yaml new file mode 100644 index 00000000..7cffa101 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/arch_config.yaml @@ -0,0 +1,46 @@ +version: "0.1-beta" + +listeners: + ingress_traffic: + address: 0.0.0.0 + port: 10000 + message_format: openai + timeout: 30s + + egress_traffic: + address: 0.0.0.0 + port: 12000 + message_format: openai + timeout: 30s + +overrides: + use_agent_orchestrator: true + +endpoints: + agent_gateway: + endpoint: host.docker.internal:18083 + connect_timeout: 0.005s + +llm_providers: + - name: gpt-4o-mini + access_key: $OPENAI_API_KEY + provider_interface: openai + model: gpt-4o-mini + default: true + +system_prompt: | + You are a helpful assistant. + +prompt_targets: + - name: sales_agent + description: handles queries related to sales and purchases + + - name: issues_and_repairs + description: handles issues, repairs, or refunds + + - name: escalate_to_human + description: escalates to human agent + +tracing: + random_sampling: 100 + trace_arch_internal: true diff --git a/demos/use_cases/orchestrating_agents/docker-compose.yaml b/demos/use_cases/orchestrating_agents/docker-compose.yaml new file mode 100644 index 00000000..288ecf30 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/docker-compose.yaml @@ -0,0 +1,29 @@ +services: + triage_service: + build: + context: ./ + environment: + - OLTP_HOST=http://jaeger:4317 + extra_hosts: + - "host.docker.internal:host-gateway" + ports: + - "18083:80" + + chatbot_ui: + build: + context: ../../shared/chatbot_ui + ports: + - "18080:8080" + environment: + # this is only because we are running the sample app in the same docker container environemtn as archgw + - CHAT_COMPLETION_ENDPOINT=http://host.docker.internal:10000/v1 + extra_hosts: + - "host.docker.internal:host-gateway" + + jaeger: + build: + context: ../../shared/jaeger + ports: + - "16686:16686" + - "4317:4317" + - "4318:4318" diff --git a/demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl b/demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl new file mode 100644 index 00000000..4db2c67c --- /dev/null +++ b/demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl @@ -0,0 +1,19 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "I want to sell red shoes" + } + ] +} +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o-mini/ +jsonpath "$.metadata.x-arch-state" != null +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/demos/use_cases/orchestrating_agents/hurl_tests/simple_stream.hurl b/demos/use_cases/orchestrating_agents/hurl_tests/simple_stream.hurl new file mode 100644 index 00000000..f060fed0 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/hurl_tests/simple_stream.hurl @@ -0,0 +1,16 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "I want to sell red shoes" + } + ], + "stream": true +} +HTTP 200 +[Asserts] +header "content-type" matches /text\/event-stream/ +body matches /^data: .*?sales_agent.*?\n/ diff --git a/demos/use_cases/orchestrating_agents/main.py b/demos/use_cases/orchestrating_agents/main.py new file mode 100644 index 00000000..27a9598a --- /dev/null +++ b/demos/use_cases/orchestrating_agents/main.py @@ -0,0 +1,105 @@ +import logging +import json +from typing import List, Dict, Any +from fastapi import FastAPI, Request +from fastapi.responses import StreamingResponse +from pydantic import BaseModel +import openai + +# Setup logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger("uvicorn.error") + +app = FastAPI() + + +class Message(BaseModel): + role: str + content: str + + +class ChatCompletionsRequest(BaseModel): + messages: List[Message] + model: str + metadata: Dict[str, Any] = {} + stream: bool = False + + +openai_client = openai.OpenAI( + api_key="None", # archgw picks the API key from the config file + base_url="http://host.docker.internal:12000/v1", +) + + +def call_openai(messages: List[Dict[str, str]], stream: bool): + completion = openai_client.chat.completions.create( + model="None", # archgw picks the default LLM configured in the config file + messages=messages, + stream=stream, + ) + + if stream: + + def stream(): + for line in completion: + if line.choices and len(line.choices) > 0 and line.choices[0].delta: + chunk_response_str = json.dumps(line.model_dump()) + yield "data: " + chunk_response_str + "\n\n" + yield "data: [DONE]" + "\n\n" + + return StreamingResponse(stream(), media_type="text/event-stream") + else: + return completion + + +class Agent: + def __init__(self, role: str, instructions: str): + self.system_prompt = f"You are a {role}.\n{instructions}" + + def handle(self, req: ChatCompletionsRequest): + messages = [{"role": "system", "content": self.get_system_prompt()}] + [ + message.model_dump() for message in req.messages + ] + return call_openai(messages, req.stream) + + def get_system_prompt(self) -> str: + return self.system_prompt + + +# Define your agents +AGENTS = { + "sales_agent": Agent( + role="sales agent", + instructions=( + "Always answer in a sentence or less.\n" + "Follow the following routine with the user:\n" + "1. Engage\n" + "2. Quote ridiculous price\n" + "3. Reveal caveat if user agrees." + ), + ), + "issues_and_repairs": Agent( + role="issues and repairs agent", + instructions="Propose a solution, offer refund if necessary.", + ), + "escalate_to_human": Agent( + role="human escalation agent", instructions="Escalate issues to a human." + ), + "unknown_agent": Agent( + role="general assistant", instructions="Assist the user in general queries." + ), +} + + +@app.post("/v1/chat/completions") +def completion_api(req: ChatCompletionsRequest, request: Request): + agent_name = req.metadata.get("agent-name", "unknown_agent") + agent = AGENTS.get(agent_name) + logger.info(f"Routing to agent: {agent_name}") + + return agent.handle(req) + + +@app.get("/healthz") +async def healthz(): + return {"status": "ok"} diff --git a/demos/use_cases/orchestrating_agents/poetry.lock b/demos/use_cases/orchestrating_agents/poetry.lock new file mode 100644 index 00000000..929a5c86 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/poetry.lock @@ -0,0 +1,573 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"websockets (>=10.4)"] + +[metadata] +lock-version = "2.0" +python-versions = "^3.10" +content-hash = "d005d82268b6f8c2a68b26c454bced5c34bf3c971c0cbfefde3fc0c45c675f55" diff --git a/demos/use_cases/orchestrating_agents/pyproject.toml b/demos/use_cases/orchestrating_agents/pyproject.toml new file mode 100644 index 00000000..7b422438 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/pyproject.toml @@ -0,0 +1,20 @@ +[tool.poetry] +name = "api-server" +version = "0.1.0" +description = "" +authors = ["Adil Hafeez "] +readme = "README.md" + +[tool.poetry.dependencies] +python = "^3.10" +fastapi = "^0.115.4" +pyyaml = "^6.0.2" +uvicorn = "^0.34.0" +openai = "^1.66.5" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" + +[tool.poetry.scripts] +api-server = "api_server.main:app" diff --git a/demos/use_cases/orchestrating_agents/run_demo.sh b/demos/use_cases/orchestrating_agents/run_demo.sh new file mode 100644 index 00000000..eb47dce6 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/run_demo.sh @@ -0,0 +1,47 @@ +#!/bin/bash +set -e + +# Function to start the demo +start_demo() { + # Step 1: Check if .env file exists + if [ -f ".env" ]; then + echo ".env file already exists. Skipping creation." + else + # Step 2: Create `.env` file and set OpenAI key + if [ -z "$OPENAI_API_KEY" ]; then + echo "Error: OPENAI_API_KEY environment variable is not set for the demo." + exit 1 + fi + + echo "Creating .env file..." + echo "OPENAI_API_KEY=$OPENAI_API_KEY" > .env + echo ".env file created with OPENAI_API_KEY." + fi + + # Step 3: Start Arch + echo "Starting Arch with arch_config.yaml..." + archgw up arch_config.yaml + + # Step 4: Start developer services + echo "Starting Network Agent using Docker Compose..." + docker compose up -d # Run in detached mode +} + +# Function to stop the demo +stop_demo() { + # Step 1: Stop Docker Compose services + echo "Stopping Network Agent using Docker Compose..." + docker compose down + + # Step 2: Stop Arch + echo "Stopping Arch..." + archgw down +} + +# Main script logic +if [ "$1" == "down" ]; then + stop_demo +else + # Default action is to bring the demo up + start_demo +fi diff --git a/model_server/src/commons/globals.py b/model_server/src/commons/globals.py index 2f533024..49dce5e7 100644 --- a/model_server/src/commons/globals.py +++ b/model_server/src/commons/globals.py @@ -3,6 +3,8 @@ from openai import OpenAI from src.commons.utils import get_model_server_logger from src.core.guardrails import get_guardrail_handler from src.core.function_calling import ( + ArchAgentConfig, + ArchAgentHandler, ArchIntentConfig, ArchIntentHandler, ArchFunctionConfig, @@ -18,10 +20,12 @@ logger = get_model_server_logger() ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "https://archfc.katanemo.dev/v1") ARCH_API_KEY = "EMPTY" ARCH_CLIENT = OpenAI(base_url=ARCH_ENDPOINT, api_key=ARCH_API_KEY) +ARCH_AGENT_CLIENT = ARCH_CLIENT # Define model names ARCH_INTENT_MODEL_ALIAS = "Arch-Intent" ARCH_FUNCTION_MODEL_ALIAS = "Arch-Function" +ARCH_AGENT_MODEL_ALIAS = ARCH_FUNCTION_MODEL_ALIAS ARCH_GUARD_MODEL_ALIAS = "katanemo/Arch-Guard" # Define model handlers @@ -32,5 +36,8 @@ handler_map = { "Arch-Function": ArchFunctionHandler( ARCH_CLIENT, ARCH_FUNCTION_MODEL_ALIAS, ArchFunctionConfig ), + "Arch-Agent": ArchAgentHandler( + ARCH_AGENT_CLIENT, ARCH_AGENT_MODEL_ALIAS, ArchAgentConfig + ), "Arch-Guard": get_guardrail_handler(ARCH_GUARD_MODEL_ALIAS), } diff --git a/model_server/src/core/function_calling.py b/model_server/src/core/function_calling.py index e1cc1b94..8c01493a 100644 --- a/model_server/src/core/function_calling.py +++ b/model_server/src/core/function_calling.py @@ -1,4 +1,5 @@ import ast +import copy import json import random import builtins @@ -221,6 +222,15 @@ class ArchFunctionConfig: SUPPORT_DATA_TYPES = ["int", "float", "bool", "str", "list", "tuple", "set", "dict"] +class ArchAgentConfig(ArchFunctionConfig): + GENERATION_PARAMS = { + "temperature": 0.01, + "stop_token_ids": [151645], + "logprobs": True, + "top_logprobs": 10, + } + + class ArchFunctionHandler(ArchBaseHandler): def __init__( self, @@ -358,16 +368,17 @@ class ArchFunctionHandler(ArchBaseHandler): is_valid, error_message = False, e break - tool_calls.append( - { - "id": f"call_{random.randint(1000, 10000)}", - "type": "function", - "function": { - "name": tool_content["name"], - "arguments": tool_content["arguments"], - }, - } - ) + tool = { + "id": f"call_{random.randint(1000, 10000)}", + "type": "function", + "function": { + "name": tool_content["name"], + }, + } + if "arguments" in tool_content: + tool["function"]["arguments"] = tool_content["arguments"] + + tool_calls.append(tool) flag = False @@ -415,7 +426,9 @@ class ArchFunctionHandler(ArchBaseHandler): break func_name = tool_call["function"]["name"] - func_args = tool_call["function"]["arguments"] + func_args = tool_call["function"].get("arguments") + if not func_args: + func_args = {} # Check whether the function is available or not if func_name not in functions: @@ -430,12 +443,14 @@ class ArchFunctionHandler(ArchBaseHandler): if required_param not in func_args: is_valid = False invalid_tool_call = tool_call - error_message = f"`{required_param}` is requiried by the function `{func_name}` but not found in the tool call!" + error_message = f"`{required_param}` is required by the function `{func_name}` but not found in the tool call!" break # Verify the data type of each parameter in the tool calls function_properties = functions[func_name]["properties"] + logger.info("== func_args ==") + logger.info(func_args) for param_name in func_args: if param_name not in function_properties: is_valid = False @@ -523,7 +538,9 @@ class ArchFunctionHandler(ArchBaseHandler): req.messages, req.tools, metadata=req.metadata ) - logger.info(f"[request to arch-fc]: {json.dumps(messages)}") + logger.info( + f"[request to arch-fc]: model: {self.model_name}, extra_body: {self.generation_params}, body: {json.dumps(messages)}" + ) # always enable `stream=True` to collect model responses response = self.client.chat.completions.create( @@ -533,42 +550,48 @@ class ArchFunctionHandler(ArchBaseHandler): extra_body=self.generation_params, ) - # initialize the hallucination handler, which is an iterator - self.hallucination_state = HallucinationState( - response_iterator=response, function=req.tools - ) - + use_agent_orchestrator = req.metadata.get("use_agent_orchestrator", False) model_response = "" + if use_agent_orchestrator: + for chunk in response: + if len(chunk.choices) > 0 and chunk.choices[0].delta.content: + model_response += chunk.choices[0].delta.content + logger.info(f"[Agent Orchestrator]: response received: {model_response}") + else: + # initialize the hallucination handler, which is an iterator + self.hallucination_state = HallucinationState( + response_iterator=response, function=req.tools + ) - has_tool_calls, has_hallucination = None, False - for _ in self.hallucination_state: - # check if the first token is - if len(self.hallucination_state.tokens) > 0 and has_tool_calls is None: - if self.hallucination_state.tokens[0] == "": - has_tool_calls = True - else: - has_tool_calls = False + has_tool_calls, has_hallucination = None, False + for _ in self.hallucination_state: + # check if the first token is + if len(self.hallucination_state.tokens) > 0 and has_tool_calls is None: + if self.hallucination_state.tokens[0] == "": + has_tool_calls = True + else: + has_tool_calls = False + break + + # if the model is hallucinating, start parameter gathering + if self.hallucination_state.hallucination is True: + has_hallucination = True break - # if the model is hallucinating, start parameter gathering - if self.hallucination_state.hallucination is True: - has_hallucination = True - break - - if has_tool_calls: - if has_hallucination: - # start prompt prefilling if hallcuination is found in tool calls - logger.info( - f"[Hallucination]: {self.hallucination_state.error_message}" - ) + if has_tool_calls: + if has_hallucination: + # start prompt prefilling if hallcuination is found in tool calls + logger.info( + f"[Hallucination]: {self.hallucination_state.error_message}" + ) + prefill_response = self._engage_parameter_gathering(messages) + model_response = prefill_response.choices[0].message.content + else: + model_response = "".join(self.hallucination_state.tokens) + else: + # start parameter gathering if the model is not generating tool calls prefill_response = self._engage_parameter_gathering(messages) model_response = prefill_response.choices[0].message.content - else: - model_response = "".join(self.hallucination_state.tokens) - else: - # start parameter gathering if the model is not generating tool calls - prefill_response = self._engage_parameter_gathering(messages) - model_response = prefill_response.choices[0].message.content # Extract tool calls from model response extracted = self._extract_tool_calls(model_response) @@ -576,9 +599,14 @@ class ArchFunctionHandler(ArchBaseHandler): if extracted["status"]: # Response with tool calls if len(extracted["result"]): - verified = self._verify_tool_calls( - tools=req.tools, tool_calls=extracted["result"] - ) + verified = {} + if use_agent_orchestrator: + # skip tool call verification if using agent orchestrator + verified = {"status": True, "message": ""} + else: + verified = self._verify_tool_calls( + tools=req.tools, tool_calls=extracted["result"] + ) if verified["status"]: logger.info( @@ -601,3 +629,35 @@ class ArchFunctionHandler(ArchBaseHandler): logger.info(f"[response]: {json.dumps(chat_completion_response.model_dump())}") return chat_completion_response + + +class ArchAgentHandler(ArchFunctionHandler): + def __init__(self, client: OpenAI, model_name: str, config: ArchAgentConfig): + super().__init__(client, model_name, config) + + @override + def _convert_tools(self, tools: List[Dict[str, Any]]) -> str: + """ + Converts a list of tools into JSON format. + + Args: + tools (List[Dict[str, Any]]): A list of tools represented as dictionaries. + + Returns: + str: A string representation of converted tools. + """ + + converted = [] + # delete parameters key if its empty in tool + for tool in tools: + if ( + "parameters" in tool["function"] + and "properties" in tool["function"]["parameters"] + and not tool["function"]["parameters"]["properties"] + ): + tool_copy = copy.deepcopy(tool) + del tool_copy["function"]["parameters"] + converted.append(json.dumps(tool_copy)) + else: + converted.append(json.dumps(tool)) + return "\n".join(converted) diff --git a/model_server/src/main.py b/model_server/src/main.py index 081ee241..1763b015 100644 --- a/model_server/src/main.py +++ b/model_server/src/main.py @@ -5,6 +5,7 @@ import logging import src.commons.utils as utils from src.commons.globals import ARCH_ENDPOINT, handler_map +from src.core.function_calling import ArchFunctionHandler from src.core.utils.model_utils import ( ChatMessage, ChatCompletionResponse, @@ -76,33 +77,51 @@ async def function_calling(req: ChatMessage, res: Response): error_messages = None try: - intent_start_time = time.perf_counter() - intent_response = await handler_map["Arch-Intent"].chat_completion(req) - intent_latency = time.perf_counter() - intent_start_time + intent_detected = False + use_agent_orchestrator = req.metadata.get("use_agent_orchestrator", False) + logger.info(f"Use agent orchestrator: {use_agent_orchestrator}") + if not use_agent_orchestrator: + intent_start_time = time.perf_counter() + intent_response = await handler_map["Arch-Intent"].chat_completion(req) + intent_latency = time.perf_counter() - intent_start_time + intent_detected = handler_map["Arch-Intent"].detect_intent(intent_response) - if handler_map["Arch-Intent"].detect_intent(intent_response): + if use_agent_orchestrator or intent_detected: # TODO: measure agreement between intent detection and function calling try: function_start_time = time.perf_counter() - final_response = await handler_map["Arch-Function"].chat_completion(req) + handler_name = ( + "Arch-Agent" if use_agent_orchestrator else "Arch-Function" + ) + function_calling_handler: ArchFunctionHandler = handler_map[ + handler_name + ] + final_response = await function_calling_handler.chat_completion(req) function_latency = time.perf_counter() - function_start_time final_response.metadata = { - "intent_latency": str(round(intent_latency * 1000, 3)), "function_latency": str(round(function_latency * 1000, 3)), - "hallucination": str( - handler_map["Arch-Function"].hallucination_state.hallucination - ), } + + if not use_agent_orchestrator: + final_response.metadata["intent_latency"] = str( + round(intent_latency * 1000, 3) + ) + final_response.metadata["hallucination"] = str( + function_calling_handler.hallucination_state.hallucination + ) except ValueError as e: res.statuscode = 503 - error_messages = f"[Arch-Function] - Error in tool call extraction: {e}" + error_messages = ( + f"[{handler_name}] - Error in tool call extraction: {e}" + ) except StopIteration as e: res.statuscode = 500 - error_messages = f"[Arch-Function] - Error in hallucination check: {e}" + error_messages = f"[{handler_name}] - Error in hallucination check: {e}" except Exception as e: res.status_code = 500 - error_messages = f"[Arch-Function] - Error in ChatCompletion: {e}" + error_messages = f"[{handler_name}] - Error in ChatCompletion: {e}" + raise else: # no intent matched intent_response.metadata = { @@ -113,6 +132,7 @@ async def function_calling(req: ChatMessage, res: Response): except Exception as e: res.status_code = 500 error_messages = f"[Arch-Intent] - Error in ChatCompletion: {e}" + raise if error_messages is not None: logger.error(error_messages) diff --git a/tests/hurl/llm_gateway_simple.hurl b/tests/hurl/llm_gateway_simple.hurl new file mode 100644 index 00000000..f16e0074 --- /dev/null +++ b/tests/hurl/llm_gateway_simple.hurl @@ -0,0 +1,17 @@ +POST http://localhost:12000/v1/chat/completions +Content-Type: application/json + +{ + "model": "--", + "messages": [ + { + "role": "system", + "content": "You are a helpful assistant.\n" + }, + { + "role": "user", + "content": "I want to sell red shoes" + } + ], + "stream": true +} From bd8004d1ae0ba6e71da8ad4921050131b48f0fc4 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Thu, 20 Mar 2025 13:57:33 -0700 Subject: [PATCH 26/37] updated docs to reflect agent routing and hand off (#443) * updated docs to reflect agent routing and hand off * updated prompt targets based on review --------- Co-authored-by: Salman Paracha --- docs/source/concepts/prompt_target.rst | 59 +++++++----- docs/source/conf.py | 2 +- docs/source/get_started/intro_to_arch.rst | 17 ++-- docs/source/get_started/overview.rst | 6 +- docs/source/guides/agent_routing.rst | 105 ++++++++++++++++++++++ docs/source/index.rst | 7 +- 6 files changed, 166 insertions(+), 30 deletions(-) create mode 100644 docs/source/guides/agent_routing.rst diff --git a/docs/source/concepts/prompt_target.rst b/docs/source/concepts/prompt_target.rst index d8f8df91..8e5994c7 100644 --- a/docs/source/concepts/prompt_target.rst +++ b/docs/source/concepts/prompt_target.rst @@ -3,14 +3,13 @@ Prompt Target ============== -**Prompt Targets** are a fundamental component of Arch, enabling developers to define how different types of user prompts are processed and routed within their generative AI applications. -This section provides an in-depth look at prompt targets, including their purpose, configuration, usage, and best practices to help you effectively leverage this feature in your projects. +**Prompt Targets** are a core concept in Arch, empowering developers to clearly define how user prompts are interpreted, processed, and routed within their generative AI applications. Prompts can seamlessly be routed either to specialized AI agents capable of handling sophisticated, context-driven tasks or to targeted tools provided by your application, offering users a fast, precise, and personalized experience. + +This section covers the essentials of prompt targets—what they are, how to configure them, their practical uses, and recommended best practices—to help you fully utilize this feature in your applications. What Are Prompt Targets? ------------------------ -Prompt targets are predefined endpoints within Arch that handle specific types of user prompts. -They act as the bridge between user inputs and your backend services or APIs, enabling Arch to route, process, and manage prompts efficiently. -By defining prompt targets, you can separate your application's business logic from the complexities of prompt processing, ensuring a cleaner and more maintainable codebase. +Prompt targets are endpoints within Arch that handle specific types of user prompts. They act as the bridge between user inputs and your backend agemts or tools (APIs), enabling Arch to route, process, and manage prompts efficiently. Defining prompt targets helps you decouple your application's core logic from processing and handling complexities, leading to clearer code organization, better scalability, and easier maintenance. .. table:: @@ -21,7 +20,7 @@ By defining prompt targets, you can separate your application's business logic f ==================== ============================================ Intent Recognition Identify the purpose of a user prompt. Parameter Extraction Extract necessary data from the prompt. - API Invocation Call relevant backend services or functions. + Invocation Call relevant backend agents or tools (APIs). Response Handling Process and return responses to the user. ==================== ============================================ @@ -30,16 +29,15 @@ Key Features Below are the key features of prompt targets that empower developers to build efficient, scalable, and personalized GenAI solutions: -- **Modular Design**: Define multiple prompt targets to handle diverse functionalities. -- **Parameter Management**: Specify required and optional parameters for each target. -- **Function Integration**: Seamlessly connect prompts to backend APIs or functions. +- **Design Scenarios**: Define prompt targets to effectively handle specific agentic scenarios. +- **Input Management**: Specify required and optional parameters for each target. +- **Tools Integration**: Seamlessly connect prompts to backend APIs or functions. - **Error Handling**: Direct errors to designated handlers for streamlined troubleshooting. - **Metadata Enrichment**: Attach additional context to prompts for enhanced processing. Configuring Prompt Targets -------------------------- -Configuring prompt targets involves defining them in Arch's configuration file. -Each Prompt target specifies how a particular type of prompt should be handled, including the endpoint to invoke and any parameters required. +Configuring prompt targets involves defining them in Arch's configuration file. Each Prompt target specifies how a particular type of prompt should be handled, including the endpoint to invoke and any parameters required. Basic Configuration ~~~~~~~~~~~~~~~~~~~ @@ -50,7 +48,7 @@ A prompt target configuration includes the following elements: - ``name``: A unique identifier for the prompt target. - ``description``: A brief explanation of what the prompt target does. -- ``endpoint``: The API endpoint or function that handles the prompt. +- ``endpoint``: Required if you want to call a tool or specific API. ``name`` and ``path`` ``http_method`` are the three attributes of the endpoint. - ``parameters`` (Optional): A list of parameters to extract from the prompt. .. _defining_prompt_target_parameters: @@ -69,6 +67,7 @@ Each parameter can be marked as required or optional. Here is a full list of par ``name (req.)`` Specifies name of the parameter. ``description (req.)`` Provides a human-readable explanation of the parameter's purpose. ``type (req.)`` Specifies the data type. Supported types include: **int**, **str**, **float**, **bool**, **list**, **set**, **dict**, **tuple** + ``in_path`` Indicates whether the parameter is part of the path in the endpoint url. Valid values: **true** or **false** ``default`` Specifies a default value for the parameter if not provided by the user. ``format`` Specifies a format for the parameter value. For example: `2019-12-31` for a date value. ``enum`` Lists of allowable values for the parameter with data type matching the ``type`` attribute. **Usage Example**: ``enum: ["celsius`", "fahrenheit"]`` @@ -76,10 +75,11 @@ Each parameter can be marked as required or optional. Here is a full list of par ``required`` Indicates whether the parameter is mandatory or optional. Valid values: **true** or **false** ======================== ============================================================================ -Example Configuration -~~~~~~~~~~~~~~~~~~~~~ +Example Configuration For Tools +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: yaml + :caption: Tools and Function Calling Configuration Example prompt_targets: - name: get_weather @@ -98,16 +98,35 @@ Example Configuration name: api_server path: /weather +Example Configuration For Agents +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: yaml + :caption: Agent Orchestration Configuration Example + + overrides: + use_agent_orchestrator: true + + prompt_targets: + - name: sales_agent + description: handles queries related to sales and purchases + + - name: issues_and_repairs + description: handles issues, repairs, or refunds + + - name: escalate_to_human + description: escalates to human agent + +.. note:: + Today, you can use Arch to coordinate more specific agentic scenarios via tools and function calling, or use it for high-level agent routing and hand off scenarios. In the future, we plan to offer you the ability to combine these two approaches for more complex scenarios. Please see `github issues `_ for more details. Routing Logic ------------- -Prompt targets determine where and how user prompts are processed. -Arch uses intelligent routing logic to ensure that prompts are directed to the appropriate targets based on their intent and context. +Prompt targets determine where and how user prompts are processed. Arch uses intelligent routing logic to ensure that prompts are directed to the appropriate targets based on their intent and context. Default Targets ~~~~~~~~~~~~~~~ -For general-purpose prompts that do not match any specific prompt target, Arch routes them to a designated default target. -This is useful for handling open-ended queries like document summarization or information extraction. +For general-purpose prompts that do not match any specific prompt target, Arch routes them to a designated default target. This is useful for handling open-ended queries like document summarization or information extraction. Intent Matching ~~~~~~~~~~~~~~~ @@ -124,5 +143,5 @@ For example: Summary -------- Prompt targets are essential for defining how user prompts are handled within your generative AI applications using Arch. -By carefully configuring prompt targets, you can ensure that prompts are accurately routed, necessary parameters are extracted, and backend services are invoked seamlessly. -This modular approach not only simplifies your application's architecture but also enhances scalability, maintainability, and overall user experience. + +By carefully configuring prompt targets, you can ensure that prompts are accurately routed, necessary parameters are extracted, and backend services are invoked seamlessly. This modular approach not only simplifies your application's architecture but also enhances scalability, maintainability, and overall user experience. diff --git a/docs/source/conf.py b/docs/source/conf.py index 399566f0..91a182c1 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -15,7 +15,7 @@ from sphinxawesome_theme.postprocess import Icons project = "Arch Docs" copyright = "2025, Katanemo Labs, Inc" author = "Katanemo Labs, Inc" -release = " v0.2.3" +release = " v0.2.4" # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration diff --git a/docs/source/get_started/intro_to_arch.rst b/docs/source/get_started/intro_to_arch.rst index 97188ab1..14a84bab 100644 --- a/docs/source/get_started/intro_to_arch.rst +++ b/docs/source/get_started/intro_to_arch.rst @@ -3,10 +3,17 @@ Intro to Arch ============= -Arch is an intelligent `(Layer 7) `_ gateway designed for generative AI apps, agents, copilots that work with prompts. -Engineered with purpose-built large language models (LLMs), Arch handles all the critical but undifferentiated tasks related to the handling and processing of prompts, including -detecting and rejecting jailbreak attempts, intelligently calling “backend” APIs to fulfill the user's request represented in a prompt, routing to and offering disaster recovery -between upstream LLMs, and managing the observability of prompts and LLM interactions in a centralized way. +Arch is an intelligent proxy server designed agentic applications. **Move faster** by letting Arch handle the **pesky heavy lifting** in building agents: +fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs. + +Past the thrill of an AI demo, have you found yourself hitting these walls? You know, the all too familiar ones: + +- You break a prompt into specialized ones, but **get stuck writing routing** and handoff logic? +- You want use new LLMs, but **struggle to quickly add LLMs** without writing integration logic? +- You're **trapped in tedious prompting work** to clarify inputs and user intents? +- You're **wasting cycles** choosing and integrating **code for observability** instead of it just happening transparently? + +And you think to youself, can't I move faster by focusing on higher-level objectives in a language and framework agnostic way? Well, you can! .. figure:: /_static/img/arch_network_diagram_high_level.png :width: 100% @@ -15,7 +22,7 @@ between upstream LLMs, and managing the observability of prompts and LLM interac High-level network flow of where Arch Gateway sits in your agentic stack. Designed for both ingress and egress prompt traffic. -**The project was born out of the belief that:** +**Arch Gateway was built by the contributors of Envoy Proxy with the belief that:** *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) diff --git a/docs/source/get_started/overview.rst b/docs/source/get_started/overview.rst index 07a347af..0f1930b1 100644 --- a/docs/source/get_started/overview.rst +++ b/docs/source/get_started/overview.rst @@ -3,7 +3,11 @@ Overview ============ -Welcome to Arch, the intelligent prompt gateway designed to help developers build **fast**, **secure**, and **personalized** generative AI apps at ANY scale. +Welcome to Arch, The intelligent (edge and LLM) proxy server for agentic applications. + +Move **faster** by letting Arch handle the pesky heavy lifting in building agents: **fast input clarification**, **agent routing**, +seamless integration of prompts with **tools for common tasks**, and **unified access and observability of LLMs**. + In this documentation, you will learn how to quickly set up Arch to trigger API calls via prompts, apply prompt guardrails without writing any application-level logic, simplify the interaction with upstream LLMs, and improve observability all while simplifying your application development process. diff --git a/docs/source/guides/agent_routing.rst b/docs/source/guides/agent_routing.rst new file mode 100644 index 00000000..418d674d --- /dev/null +++ b/docs/source/guides/agent_routing.rst @@ -0,0 +1,105 @@ +.. _agent_routing: + +Agent Routing and Hand Off +=========================== + +Agent Routing and Hand Off is a key feature in Arch that enables intelligent routing of user prompts to specialized AI agents or human agents based on the nature and complexity of the user's request. + +This capability significantly enhances the efficiency and personalization of interactions, ensuring each prompt receives the most appropriate and effective handling. The following section describes +the workflow, configuration, and implementation of Agent routing and hand off in Arch. + +#. **Agent Selection** + When a user submits a prompt, Arch analyzes the input to determine the intent and complexity. Based on the analysis, Arch selects the most suitable agent configured within your application to handle the specific category of the user's request—such as sales inquiries, technical issues, or complex scenarios requiring human attention. + +#. **Prompt Routing** + After selecting the appropriate agent, Arch routes the user's prompt to the designated agent's endpoint and waits for the agent to respond back with the processed output or further instructions. + +#. **Hand Off** + Based on follow-up queries from the user, Arch repeats the process of analysis, agent selection, and routing to ensure a seamless hand off between AI agents as needed. + +.. code-block:: yaml + :caption: Agent Routing and Hand Off Configuration Example + + prompt_targets: + - name: sales_agent + description: Handles queries related to sales and purchases + + - name: issues_and_repairs + description: handles issues, repairs, or refunds + + - name: escalate_to_human + description: escalates to human agent + +.. code-block:: python + :caption: Agent Routing and Hand Off Implementation Example via FastAPI + + class Agent: + def __init__(self, role: str, instructions: str): + self.system_prompt = f"You are a {role}.\n{instructions}" + + def handle(self, req: ChatCompletionsRequest): + messages = [{"role": "system", "content": self.get_system_prompt()}] + [ + message.model_dump() for message in req.messages + ] + return call_openai(messages, req.stream) #call_openai is a placeholder for the actual API call + + def get_system_prompt(self) -> str: + return self.system_prompt + + # Define your agents + AGENTS = { + "sales_agent": Agent( + role="sales agent", + instructions=( + "Always answer in a sentence or less.\n" + "Follow the following routine with the user:\n" + "1. Engage\n" + "2. Quote ridiculous price\n" + "3. Reveal caveat if user agrees." + ), + ), + "issues_and_repairs": Agent( + role="issues and repairs agent", + instructions="Propose a solution, offer refund if necessary.", + ), + "escalate_to_human": Agent( + role="human escalation agent", instructions="Escalate issues to a human." + ), + "unknown_agent": Agent( + role="general assistant", instructions="Assist the user in general queries." + ), + } + + #handle the request from arch gateway + @app.post("/v1/chat/completions") + def completion_api(req: ChatCompletionsRequest, request: Request): + + agent_name = req.metadata.get("agent-name", "unknown_agent") + agent = AGENTS.get(agent_name) + logger.info(f"Routing to agent: {agent_name}") + + return agent.handle(req) + +.. note:: + The above example demonstrates a simple implementation of Agent Routing and Hand Off using FastAPI. For the full implemenation of this example + please see our `GitHub demo `_. + +Example Use Cases +----------------- +Agent Routing and Hand Off is particularly beneficial in scenarios such as: + +- **Customer Support**: Routing common customer queries to automated support agents, while escalating complex or sensitive issues to human support staff. +- **Sales and Marketing**: Automatically directing potential leads and sales inquiries to specialized sales agents for timely and targeted follow-ups. +- **Technical Assistance**: Managing user-reported issues, repairs, or refunds by assigning them to the correct technical or support agent efficiently. + +Best Practices and Tips +------------------------ +When implementing Agent Routing and Hand Off in your applications, consider these best practices: + +- Clearly Define Agent Responsibilities: Ensure each agent or human endpoint has a clear, specific description of the prompts they handle, reducing misrouting. +- Monitor and Optimize Routes: Regularly review how prompts are routed to adjust and optimize agent definitions and configurations. + +.. note:: + To observe traffic to and from agents, please read more about :ref:`observabiliuty ` in Arch. + +By carefully configuring and managing your Agent routing and hand off, you can significantly improve your application's responsiveness, performance, and overall user satisfaction. diff --git a/docs/source/index.rst b/docs/source/index.rst index 3588382d..aefc63bf 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -12,11 +12,11 @@ Welcome to Arch!

Build fast, observable, and personalized GenAI apps

- Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt + Arch - Build fast, hyper-personalized agents with intelligent infra | Product Hunt -`Arch `_ is an intelligent gateway for agents - an infrastructure primitive for GenAI (built by the contributors of `Envoy `_ ). The project was born out of the belief that: +`Arch `_ is an intelligent (edge and LLM) proxy, exclusively designed for prompts and agents - and built by the contributors of the widely adopted and loved `Envoy `_ ). - *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems for personalization - all outside business logic.* +**Move faster** by letting Arch handle the **pesky heavy lifting** in building agents: fast input clarification, agent routing, seamless integration of prompts with tools for common tasks, and unified access and observability of LLMs - all outside business logic. .. tab-set:: @@ -50,6 +50,7 @@ Welcome to Arch! :maxdepth: 2 guides/prompt_guard + guides/agent_routing guides/function_calling guides/observability/observability From eb48f3d5bb9b1f057a27ff1f4e746f7f6553d061 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 21 Mar 2025 15:56:17 -0700 Subject: [PATCH 27/37] use passed in model name in chat completion request (#445) --- README.md | 2 +- arch/tools/cli/docker_cli.py | 1 + crates/common/src/ratelimit.rs | 8 +- crates/common/src/tokenizer.rs | 38 ++-- crates/llm_gateway/src/stream_context.rs | 60 +++-- crates/llm_gateway/tests/integration.rs | 209 +++++++++++++++++- crates/prompt_gateway/src/http_context.rs | 5 +- crates/prompt_gateway/src/stream_context.rs | 11 +- .../weather_forcecast_service/.project | 4 +- demos/shared/chatbot_ui/common.py | 2 +- demos/shared/chatbot_ui/run_stream.py | 4 +- demos/use_cases/llm_routing/arch_config.yaml | 5 - .../hurl_tests/simple_issues_repairs.hurl | 19 ++ .../{simple.hurl => simple_sale_agent.hurl} | 0 demos/use_cases/orchestrating_agents/main.py | 20 +- ...url => llm_gateway_model_default_llm.hurl} | 11 +- .../llm_gateway_model_explicit_model.hurl | 25 +++ tests/hurl/llm_gateway_model_hint.hurl | 25 +++ tests/rest/api_model_server.rest | 2 +- tests/rest/api_prompt_gateway.rest | 2 +- 20 files changed, 364 insertions(+), 89 deletions(-) create mode 100644 demos/use_cases/orchestrating_agents/hurl_tests/simple_issues_repairs.hurl rename demos/use_cases/orchestrating_agents/hurl_tests/{simple.hurl => simple_sale_agent.hurl} (100%) rename tests/hurl/{llm_gateway_simple.hurl => llm_gateway_model_default_llm.hurl} (51%) create mode 100644 tests/hurl/llm_gateway_model_explicit_model.hurl create mode 100644 tests/hurl/llm_gateway_model_hint.hurl diff --git a/README.md b/README.md index d3b13d69..81d88e01 100644 --- a/README.md +++ b/README.md @@ -249,7 +249,7 @@ client = OpenAI( response = client.chat.completions.create( # we select model from arch_config file - model="--", + model="None", messages=[{"role": "user", "content": "What is the capital of France?"}], ) diff --git a/arch/tools/cli/docker_cli.py b/arch/tools/cli/docker_cli.py index 59a0553c..6edfb8dc 100644 --- a/arch/tools/cli/docker_cli.py +++ b/arch/tools/cli/docker_cli.py @@ -56,6 +56,7 @@ def docker_start_archgw_detached( volume_mappings = [ f"{logs_path_abs}:/var/log:rw", f"{arch_config_file}:/app/arch_config.yaml:ro", + # "/Users/adilhafeez/src/intelligent-prompt-gateway/crates/target/wasm32-wasip1/release:/etc/envoy/proxy-wasm-plugins:ro", ] volume_mappings_args = [ item for volume in volume_mappings for item in ("-v", volume) diff --git a/crates/common/src/ratelimit.rs b/crates/common/src/ratelimit.rs index 66c3facd..8825fd01 100644 --- a/crates/common/src/ratelimit.rs +++ b/crates/common/src/ratelimit.rs @@ -1,7 +1,7 @@ use crate::configuration; use configuration::{Limit, Ratelimit, TimeUnit}; use governor::{DefaultKeyedRateLimiter, InsufficientCapacity, Quota}; -use log::debug; +use log::trace; use std::fmt::Display; use std::num::{NonZero, NonZeroU32}; use std::sync::RwLock; @@ -99,9 +99,11 @@ impl RatelimitMap { selector: Header, tokens_used: NonZeroU32, ) -> Result<(), Error> { - debug!( + trace!( "Checking limit for provider={}, with selector={:?}, consuming tokens={:?}", - provider, selector, tokens_used + provider, + selector, + tokens_used ); let provider_limits = match self.datastore.get(&provider) { diff --git a/crates/common/src/tokenizer.rs b/crates/common/src/tokenizer.rs index c424e344..d2611375 100644 --- a/crates/common/src/tokenizer.rs +++ b/crates/common/src/tokenizer.rs @@ -1,19 +1,25 @@ use log::trace; -#[derive(thiserror::Error, Debug, PartialEq, Eq)] #[allow(dead_code)] -pub enum Error { - #[error("Unknown model: {model_name}")] - UnknownModel { model_name: String }, -} - -#[allow(dead_code)] -pub fn token_count(model_name: &str, text: &str) -> Result { +pub fn token_count(model_name: &str, text: &str) -> Result { trace!("getting token count model={}", model_name); + //HACK: add support for tokenizing mistral and other models + //filed issue https://github.com/katanemo/arch/issues/222 + + let updated_model = match model_name.starts_with("gpt") { + false => { + trace!( + "tiktoken_rs: unsupported model: {}, using gpt-4 to compute token count", + model_name + ); + + "gpt-4" + } + true => model_name, + }; + // Consideration: is it more expensive to instantiate the BPE object every time, or to contend the singleton? - let bpe = tiktoken_rs::get_bpe_from_model(model_name).map_err(|_| Error::UnknownModel { - model_name: model_name.to_string(), - })?; + let bpe = tiktoken_rs::get_bpe_from_model(updated_model).map_err(|e| e.to_string())?; Ok(bpe.encode_ordinary(text).len()) } @@ -30,14 +36,4 @@ mod test { token_count(model_name, text).expect("correct tokenization") ); } - - #[test] - fn unrecognized_model() { - assert_eq!( - Error::UnknownModel { - model_name: "unknown".to_string() - }, - token_count("unknown", "").expect_err("unknown model") - ) - } } diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index b4a05575..20ca9d62 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -89,7 +89,7 @@ impl StreamContext { provider_hint, )); - debug!( + trace!( "request received: llm provider hint: {}, selected llm: {}, model: {}", self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER) .unwrap_or_default(), @@ -167,7 +167,7 @@ impl StreamContext { // Check if rate limiting needs to be applied. if let Some(selector) = self.ratelimit_selector.take() { - log::debug!("Applying ratelimit for model: {}", model); + log::trace!("Applying ratelimit for model: {}", model); ratelimit::ratelimits(None).read().unwrap().check_limit( model.to_owned(), selector, @@ -300,22 +300,45 @@ impl HttpContext for StreamContext { .cloned(); let model_name = match self.llm_provider.as_ref() { - Some(llm_provider) => match llm_provider.model.as_ref() { - Some(model) => model, - None => "--", - }, - None => "--", + Some(llm_provider) => llm_provider.model.as_ref(), + None => None, }; - deserialized_body.model = model_name.to_string(); + let use_agent_orchestrator = match self.overrides.as_ref() { + Some(overrides) => overrides.use_agent_orchestrator.unwrap_or_default(), + None => false, + }; + + let model_requested = deserialized_body.model.clone(); + if deserialized_body.model.is_empty() || deserialized_body.model.to_lowercase() == "none" { + deserialized_body.model = match model_name { + Some(model_name) => model_name.clone(), + None => { + if use_agent_orchestrator { + "agent_orchestrator".to_string() + } else { + self.send_server_error( + ServerError::BadRequest { + why: format!("No model specified in request and couldn't determine model name from arch_config. Model name in req: {}, arch_config, provider: {}, model: {:?}", deserialized_body.model, self.llm_provider().name, self.llm_provider().model).to_string(), + }, + Some(StatusCode::BAD_REQUEST), + ); + return Action::Continue; + } + } + } + } + + debug!( + "provider: {:?}, model requested: {}, model selected: {:?}", + self.llm_provider().name, + model_requested, + model_name, + ); let chat_completion_request_str = serde_json::to_string(&deserialized_body).unwrap(); - trace!( - "arch => {:?}, body: {}", - deserialized_body.model, - chat_completion_request_str - ); + trace!("request body: {}", chat_completion_request_str); if deserialized_body.stream { self.streaming_response = true; @@ -528,22 +551,13 @@ impl HttpContext for StreamContext { return Action::Continue; } - let mut model = chat_completions_chunk_response_events + let model = chat_completions_chunk_response_events .events .first() .unwrap() .model .clone(); let tokens_str = chat_completions_chunk_response_events.to_string(); - //HACK: add support for tokenizing mistral and other models - //filed issue https://github.com/katanemo/arch/issues/222 - if !model.as_ref().unwrap().starts_with("gpt") { - trace!( - "tiktoken_rs: unsupported model: {}, using gpt-4 to compute token count", - model.as_ref().unwrap() - ); - } - model = Some("gpt-4".to_string()); let token_count = match tokenizer::token_count(model.as_ref().unwrap().as_str(), tokens_str.as_str()) diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index 71ec2e16..9d87c00c 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -30,7 +30,7 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { Some("x-arch-llm-provider-hint"), ) .returning(None) - .expect_log(Some(LogLevel::Debug), Some("request received: llm provider hint: default, selected llm: open-ai-gpt-4, model: gpt-4")) + .expect_log(Some(LogLevel::Trace), Some("request received: llm provider hint: default, selected llm: open-ai-gpt-4, model: gpt-4")) .expect_add_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider"), @@ -225,12 +225,13 @@ fn llm_gateway_successful_request_to_open_ai_chat_completions() { ) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) + .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 21) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -287,7 +288,7 @@ fn llm_gateway_bad_request_to_open_ai_chat_completions() { ) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(incomplete_chat_completions_request_body)) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) .expect_send_local_response( Some(StatusCode::BAD_REQUEST.as_u16().into()), None, @@ -296,9 +297,10 @@ fn llm_gateway_bad_request_to_open_ai_chat_completions() { ) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 14) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); } @@ -351,13 +353,14 @@ fn llm_gateway_request_ratelimited() { .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 107) .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), Some("server error occurred: exceeded limit provider=gpt-4, selector=Header { key: \"selector-key\", value: \"selector-value\" }, tokens_used=107")) .expect_send_local_response( Some(StatusCode::TOO_MANY_REQUESTS.as_u16().into()), None, @@ -417,12 +420,196 @@ fn llm_gateway_request_not_ratelimited() { .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 29) .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) + .execute_and_expect(ReturnType::Action(Action::Continue)) + .unwrap(); +} + +#[test] +#[serial] +fn llm_gateway_override_model_name() { + let args = tester::MockSettings { + wasm_path: wasm_module(), + quiet: false, + allow_unexpected: false, + }; + let mut module = tester::mock(args).unwrap(); + + module + .call_start() + .execute_and_expect(ReturnType::None) + .unwrap(); + + // Setup Filter + let filter_context = setup_filter(&mut module, default_config()); + + // Setup HTTP Stream + let http_context = 2; + + normal_flow(&mut module, filter_context, http_context); + + // give shorter body to avoid rate limiting + let chat_completions_request_body = "\ +{\ + \"model\": \"o1-mini\",\ + \"messages\": [\ + {\ + \"role\": \"system\",\ + \"content\": \"You are a poetic assistant, skilled in explaining complex programming concepts with creative flair.\"\ + },\ + {\ + \"role\": \"user\",\ + \"content\": \"Compose a poem that explains the concept of recursion in programming.\"\ + }\ + ] +}"; + + module + .call_proxy_on_request_body( + http_context, + chat_completions_request_body.len() as i32, + true, + ) + .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) + .returning(Some(chat_completions_request_body)) + // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Debug), Some("provider: \"open-ai-gpt-4\", model requested: o1-mini, model selected: Some(\"gpt-4\")")) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_metric_record("input_sequence_length", 29) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) + .execute_and_expect(ReturnType::Action(Action::Continue)) + .unwrap(); +} + +#[test] +#[serial] +fn llm_gateway_override_use_default_model() { + let args = tester::MockSettings { + wasm_path: wasm_module(), + quiet: false, + allow_unexpected: false, + }; + let mut module = tester::mock(args).unwrap(); + + module + .call_start() + .execute_and_expect(ReturnType::None) + .unwrap(); + + // Setup Filter + let filter_context = setup_filter(&mut module, default_config()); + + // Setup HTTP Stream + let http_context = 2; + + normal_flow(&mut module, filter_context, http_context); + + // give shorter body to avoid rate limiting + let chat_completions_request_body = "\ +{\ + \"messages\": [\ + {\ + \"role\": \"system\",\ + \"content\": \"You are a poetic assistant, skilled in explaining complex programming concepts with creative flair.\"\ + },\ + {\ + \"role\": \"user\",\ + \"content\": \"Compose a poem that explains the concept of recursion in programming.\"\ + }\ + ] +}"; + + module + .call_proxy_on_request_body( + http_context, + chat_completions_request_body.len() as i32, + true, + ) + .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) + .returning(Some(chat_completions_request_body)) + // The actual call is not important in this test, we just need to grab the token_id + .expect_log( + Some(LogLevel::Debug), + Some("provider: \"open-ai-gpt-4\", model requested: , model selected: Some(\"gpt-4\")"), + ) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_metric_record("input_sequence_length", 29) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) + .execute_and_expect(ReturnType::Action(Action::Continue)) + .unwrap(); +} + +#[test] +#[serial] +fn llm_gateway_override_use_model_name_none() { + let args = tester::MockSettings { + wasm_path: wasm_module(), + quiet: false, + allow_unexpected: false, + }; + let mut module = tester::mock(args).unwrap(); + + module + .call_start() + .execute_and_expect(ReturnType::None) + .unwrap(); + + // Setup Filter + let filter_context = setup_filter(&mut module, default_config()); + + // Setup HTTP Stream + let http_context = 2; + + normal_flow(&mut module, filter_context, http_context); + + // give shorter body to avoid rate limiting + let chat_completions_request_body = "\ +{\ + \"model\": \"none\",\ + \"messages\": [\ + {\ + \"role\": \"system\",\ + \"content\": \"You are a poetic assistant, skilled in explaining complex programming concepts with creative flair.\"\ + },\ + {\ + \"role\": \"user\",\ + \"content\": \"Compose a poem that explains the concept of recursion in programming.\"\ + }\ + ] +}"; + + module + .call_proxy_on_request_body( + http_context, + chat_completions_request_body.len() as i32, + true, + ) + .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) + .returning(Some(chat_completions_request_body)) + // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Debug), Some("provider: \"open-ai-gpt-4\", model requested: none, model selected: Some(\"gpt-4\")")) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_metric_record("input_sequence_length", 29) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Trace), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index b8eb2797..9580e934 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -45,7 +45,8 @@ impl HttpContext for StreamContext { warn!("Need single endpoint when use_agent_orchestrator is set"); self.send_server_error( ServerError::LogicError( - "Need single endpoint when use_agent_orchestrator is set".to_string(), + "Need single endpoint when use_agent_orchestrator is set" + .to_string(), ), None, ); @@ -190,7 +191,7 @@ impl HttpContext for StreamContext { messages: deserialized_body.messages.clone(), metadata, stream: deserialized_body.stream, - model: "--".to_string(), + model: deserialized_body.model.clone(), stream_options: deserialized_body.stream_options.clone(), tools: Some(tool_calls), }; diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index fddb3b20..4a968d43 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -427,7 +427,6 @@ impl StreamContext { headers.insert(key.as_str(), value.as_str()); } - let call_args = CallArgs::new( ARCH_INTERNAL_CLUSTER_NAME, &path, @@ -499,10 +498,7 @@ impl StreamContext { } }; - if !prompt_target - .auto_llm_dispatch_on_response - .unwrap_or(true) - { + if !prompt_target.auto_llm_dispatch_on_response.unwrap_or(true) { let tool_call_response = self.tool_call_response.as_ref().unwrap().clone(); let direct_response_str = if self.streaming_response { @@ -655,10 +651,7 @@ impl StreamContext { .clone(); // check if the default target should be dispatched to the LLM provider - if !prompt_target - .auto_llm_dispatch_on_response - .unwrap_or(true) - { + if !prompt_target.auto_llm_dispatch_on_response.unwrap_or(true) { let default_target_response_str = if self.streaming_response { let chat_completion_response = match serde_json::from_slice::(&body) { diff --git a/demos/samples_java/weather_forcecast_service/.project b/demos/samples_java/weather_forcecast_service/.project index 51363145..efcdddf7 100644 --- a/demos/samples_java/weather_forcecast_service/.project +++ b/demos/samples_java/weather_forcecast_service/.project @@ -22,12 +22,12 @@ - 1739479945236 + 1742579142020 30 org.eclipse.core.resources.regexFilterMatcher - node_modules|.git|__CREATED_BY_JAVA_LANGUAGE_SERVER__ + node_modules|\.git|__CREATED_BY_JAVA_LANGUAGE_SERVER__ diff --git a/demos/shared/chatbot_ui/common.py b/demos/shared/chatbot_ui/common.py index cfcc6556..42e50bd4 100644 --- a/demos/shared/chatbot_ui/common.py +++ b/demos/shared/chatbot_ui/common.py @@ -38,7 +38,7 @@ def chat( try: response = client.chat.completions.create( # we select model from arch_config file - model="--", + model="None", messages=history, temperature=1.0, stream=True, diff --git a/demos/shared/chatbot_ui/run_stream.py b/demos/shared/chatbot_ui/run_stream.py index 407d4c05..b406e147 100644 --- a/demos/shared/chatbot_ui/run_stream.py +++ b/demos/shared/chatbot_ui/run_stream.py @@ -54,13 +54,13 @@ def chat( if model_selector and model_selector != "": headers["x-arch-llm-provider-hint"] = model_selector client = OpenAI( - api_key="--", + api_key="None", base_url=CHAT_COMPLETION_ENDPOINT, default_headers=headers, ) response = client.chat.completions.create( # we select model from arch_config file - model="--", + model="None", messages=history, temperature=1.0, stream=True, diff --git a/demos/use_cases/llm_routing/arch_config.yaml b/demos/use_cases/llm_routing/arch_config.yaml index 4cccd718..289d8bf2 100644 --- a/demos/use_cases/llm_routing/arch_config.yaml +++ b/demos/use_cases/llm_routing/arch_config.yaml @@ -14,11 +14,6 @@ llm_providers: model: gpt-4o-mini default: true - - name: gpt-3.5-turbo-0125 - access_key: $OPENAI_API_KEY - provider_interface: openai - model: gpt-3.5-turbo-0125 - - name: gpt-4o access_key: $OPENAI_API_KEY provider_interface: openai diff --git a/demos/use_cases/orchestrating_agents/hurl_tests/simple_issues_repairs.hurl b/demos/use_cases/orchestrating_agents/hurl_tests/simple_issues_repairs.hurl new file mode 100644 index 00000000..3820de57 --- /dev/null +++ b/demos/use_cases/orchestrating_agents/hurl_tests/simple_issues_repairs.hurl @@ -0,0 +1,19 @@ +POST http://localhost:10000/v1/chat/completions +Content-Type: application/json + +{ + "messages": [ + { + "role": "user", + "content": "I bought a package recently and it not working properly" + } + ] +} +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o-2/ +jsonpath "$.metadata.x-arch-state" != null +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl b/demos/use_cases/orchestrating_agents/hurl_tests/simple_sale_agent.hurl similarity index 100% rename from demos/use_cases/orchestrating_agents/hurl_tests/simple.hurl rename to demos/use_cases/orchestrating_agents/hurl_tests/simple_sale_agent.hurl diff --git a/demos/use_cases/orchestrating_agents/main.py b/demos/use_cases/orchestrating_agents/main.py index 27a9598a..4f288e50 100644 --- a/demos/use_cases/orchestrating_agents/main.py +++ b/demos/use_cases/orchestrating_agents/main.py @@ -31,9 +31,10 @@ openai_client = openai.OpenAI( ) -def call_openai(messages: List[Dict[str, str]], stream: bool): +def call_openai(messages: List[Dict[str, str]], stream: bool, model: str): + logger.info(f"llm agent model: {model}") completion = openai_client.chat.completions.create( - model="None", # archgw picks the default LLM configured in the config file + model=model, messages=messages, stream=stream, ) @@ -53,14 +54,19 @@ def call_openai(messages: List[Dict[str, str]], stream: bool): class Agent: - def __init__(self, role: str, instructions: str): + def __init__(self, role: str, instructions: str, model: str = ""): + self.model = model self.system_prompt = f"You are a {role}.\n{instructions}" def handle(self, req: ChatCompletionsRequest): messages = [{"role": "system", "content": self.get_system_prompt()}] + [ message.model_dump() for message in req.messages ] - return call_openai(messages, req.stream) + + model = req.model + if self.model: + model = self.model + return call_openai(messages, req.stream, model) def get_system_prompt(self) -> str: return self.system_prompt @@ -77,13 +83,17 @@ AGENTS = { "2. Quote ridiculous price\n" "3. Reveal caveat if user agrees." ), + model="gpt-4o-mini", ), "issues_and_repairs": Agent( role="issues and repairs agent", instructions="Propose a solution, offer refund if necessary.", + model="gpt-4o", ), "escalate_to_human": Agent( - role="human escalation agent", instructions="Escalate issues to a human." + role="human escalation agent", + instructions="Escalate issues to a human.", + # skipping model name here as arch gateway will pick the default model from the config file ), "unknown_agent": Agent( role="general assistant", instructions="Assist the user in general queries." diff --git a/tests/hurl/llm_gateway_simple.hurl b/tests/hurl/llm_gateway_model_default_llm.hurl similarity index 51% rename from tests/hurl/llm_gateway_simple.hurl rename to tests/hurl/llm_gateway_model_default_llm.hurl index f16e0074..0bca20c8 100644 --- a/tests/hurl/llm_gateway_simple.hurl +++ b/tests/hurl/llm_gateway_model_default_llm.hurl @@ -2,7 +2,6 @@ POST http://localhost:12000/v1/chat/completions Content-Type: application/json { - "model": "--", "messages": [ { "role": "system", @@ -13,5 +12,13 @@ Content-Type: application/json "content": "I want to sell red shoes" } ], - "stream": true + "stream": false } + +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o-mini/ +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/tests/hurl/llm_gateway_model_explicit_model.hurl b/tests/hurl/llm_gateway_model_explicit_model.hurl new file mode 100644 index 00000000..8ba7ccd1 --- /dev/null +++ b/tests/hurl/llm_gateway_model_explicit_model.hurl @@ -0,0 +1,25 @@ +POST http://localhost:12000/v1/chat/completions +Content-Type: application/json + +{ + "model": "gpt-3.5-turbo", + "messages": [ + { + "role": "system", + "content": "You are a helpful assistant.\n" + }, + { + "role": "user", + "content": "I want to sell red shoes" + } + ], + "stream": false +} + +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-3.5-turbo/ +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/tests/hurl/llm_gateway_model_hint.hurl b/tests/hurl/llm_gateway_model_hint.hurl new file mode 100644 index 00000000..9f45c670 --- /dev/null +++ b/tests/hurl/llm_gateway_model_hint.hurl @@ -0,0 +1,25 @@ +POST http://localhost:12000/v1/chat/completions +Content-Type: application/json +x-arch-llm-provider-hint: gpt-4o + +{ + "messages": [ + { + "role": "system", + "content": "You are a helpful assistant.\n" + }, + { + "role": "user", + "content": "I want to sell red shoes" + } + ], + "stream": false +} + +HTTP 200 +[Asserts] +header "content-type" == "application/json" +jsonpath "$.model" matches /^gpt-4o-2/ +jsonpath "$.usage" != null +jsonpath "$.choices[0].message.content" != null +jsonpath "$.choices[0].message.role" == "assistant" diff --git a/tests/rest/api_model_server.rest b/tests/rest/api_model_server.rest index 3e5d2f47..5fdbf968 100644 --- a/tests/rest/api_model_server.rest +++ b/tests/rest/api_model_server.rest @@ -238,7 +238,7 @@ POST {{model_server_endpoint}}/function_calling HTTP/1.1 Content-Type: application/json { - "model": "--", + "model": "None", "messages": [ { "role": "user", diff --git a/tests/rest/api_prompt_gateway.rest b/tests/rest/api_prompt_gateway.rest index db06cafe..f28690c9 100644 --- a/tests/rest/api_prompt_gateway.rest +++ b/tests/rest/api_prompt_gateway.rest @@ -82,7 +82,7 @@ POST {{prompt_endpoint}}/v1/chat/completions HTTP/1.1 Content-Type: application/json { - "model": "--", + "model": "None", "messages": [ { "role": "user", From 9f599430410d2c52def51b76f8554309064cc086 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Fri, 21 Mar 2025 16:08:59 -0700 Subject: [PATCH 28/37] update code to use 0.2.4 release (#446) * update code to use 0.2.4 release * update lock file --- README.md | 2 +- arch/tools/README.md | 2 +- arch/tools/poetry.lock | 18 +++++++++--------- arch/tools/pyproject.toml | 4 ++-- docs/source/get_started/quickstart.rst | 2 +- model_server/pyproject.toml | 2 +- 6 files changed, 15 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 81d88e01..e4d637e9 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. ```console $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate -$ pip install archgw==0.2.3 +$ pip install archgw==0.2.4 ``` ### Build AI Agent with Arch Gateway diff --git a/arch/tools/README.md b/arch/tools/README.md index eb4dcb64..eadf3da8 100644 --- a/arch/tools/README.md +++ b/arch/tools/README.md @@ -19,7 +19,7 @@ source venv/bin/activate ### Step 3: Run the build script ```bash -pip install archgw==0.2.3 +pip install archgw==0.2.4 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index 5f7fcbd6..bb70350b 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -2,7 +2,7 @@ [[package]] name = "archgw_modelserver" -version = "0.2.3" +version = "0.2.4" description = "A model server for serving models" optional = false python-versions = "*" @@ -15,20 +15,20 @@ url = "../../model_server" [[package]] name = "attrs" -version = "25.1.0" +version = "25.3.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.8" files = [ - {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"}, - {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"}, + {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, + {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, ] [package.extras] benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] -docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"] tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] @@ -59,13 +59,13 @@ files = [ [[package]] name = "jinja2" -version = "3.1.5" +version = "3.1.6" description = "A very fast and expressive template engine." optional = false python-versions = ">=3.7" files = [ - {file = "jinja2-3.1.5-py3-none-any.whl", hash = "sha256:aba0f4dc9ed8013c424088f68a5c226f7d6097ed89b246d7749c2ec4175c6adb"}, - {file = "jinja2-3.1.5.tar.gz", hash = "sha256:8fefff8dc3034e27bb80d67c671eb8a9bc424c0ef4c0826edbff304cceff43bb"}, + {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"}, + {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"}, ] [package.dependencies] @@ -403,4 +403,4 @@ files = [ [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "de54ecf7f336fee4bba7a0b1b950a895a0187a5e4280ba7850294a571f03edc0" +content-hash = "310b3efa304f598b1711fdf0716698d28a4dc1365e18a5ecaedd17c31b3ea14d" diff --git a/arch/tools/pyproject.toml b/arch/tools/pyproject.toml index d99b1286..75438e11 100644 --- a/arch/tools/pyproject.toml +++ b/arch/tools/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw" -version = "0.2.3" +version = "0.2.4" description = "Python-based CLI tool to manage Arch Gateway." authors = ["Katanemo Labs, Inc."] packages = [ @@ -10,7 +10,7 @@ readme = "README.md" [tool.poetry.dependencies] python = "^3.10" -archgw_modelserver = "^0.2.3" +archgw_modelserver = "^0.2.4" click = "^8.1.7" jinja2 = "^3.1.4" jsonschema = "^4.23.0" diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index a7e6b639..dbc18935 100644 --- a/docs/source/get_started/quickstart.rst +++ b/docs/source/get_started/quickstart.rst @@ -25,7 +25,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate - $ pip install archgw==0.2.3 + $ pip install archgw==0.2.4 Build AI Agent with Arch Gateway diff --git a/model_server/pyproject.toml b/model_server/pyproject.toml index 56be1dc0..d7c38adb 100644 --- a/model_server/pyproject.toml +++ b/model_server/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw_modelserver" -version = "0.2.3" +version = "0.2.4" description = "A model server for serving models" authors = ["Katanemo Labs, Inc "] license = "Apache 2.0" From 76ec5cda68dc08aa5fe609b94dbccd99f50dd752 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Wed, 26 Mar 2025 11:01:32 -0700 Subject: [PATCH 29/37] fix ollama demo (#450) --- crates/llm_gateway/src/stream_context.rs | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 20ca9d62..c621393f 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -214,10 +214,17 @@ impl HttpContext for StreamContext { })); } else { self.select_llm_provider(); - self.add_http_request_header( - ARCH_ROUTING_HEADER, - &self.llm_provider().provider_interface.to_string(), - ); + if self.llm_provider().endpoint.is_some() { + self.add_http_request_header( + ARCH_ROUTING_HEADER, + &self.llm_provider().name.to_string(), + ); + } else { + self.add_http_request_header( + ARCH_ROUTING_HEADER, + &self.llm_provider().provider_interface.to_string(), + ); + } if let Err(error) = self.modify_auth_headers() { // ensure that the provider has an endpoint if the access key is missing else return a bad request if self.llm_provider.as_ref().unwrap().endpoint.is_none() && !use_agent_orchestrator From de221525dea8cd804b024e997277f7717cd0c988 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Thu, 27 Mar 2025 10:40:20 -0700 Subject: [PATCH 30/37] Use better logs (#452) --- README.md | 27 ++++++ arch/Dockerfile | 2 +- crates/common/src/http.rs | 4 +- crates/common/src/ratelimit.rs | 4 +- crates/common/src/tokenizer.rs | 6 +- crates/llm_gateway/src/stream_context.rs | 91 ++++++++++++--------- crates/llm_gateway/tests/integration.rs | 91 +++++++++++---------- crates/prompt_gateway/src/http_context.rs | 39 ++++----- crates/prompt_gateway/src/stream_context.rs | 34 ++++---- crates/prompt_gateway/tests/integration.rs | 58 ++++++------- 10 files changed, 200 insertions(+), 156 deletions(-) diff --git a/README.md b/README.md index e4d637e9..b733bbd5 100644 --- a/README.md +++ b/README.md @@ -309,6 +309,33 @@ Arch is designed to support best-in class observability by supporting open stand ![alt text](docs/source/_static/img/tracing.png) +## Debugging + +When debugging issues / errors application logs and access logs provide key information to give you more context on whats going on with the system. Arch gateway runs in info log level and following is a typical output you could see in a typical interaction between developer and arch gateway, + +``` +$ archgw up --service archgw --foreground +... +[2025-03-26 18:32:01.350][26][info] prompt_gateway: on_http_request_body: sending request to model server +[2025-03-26 18:32:01.851][26][info] prompt_gateway: on_http_call_response: model server response received +[2025-03-26 18:32:01.852][26][info] prompt_gateway: on_http_call_response: dispatching api call to developer endpoint: weather_forecast_service, path: /weather, method: POST +[2025-03-26 18:32:01.882][26][info] prompt_gateway: on_http_call_response: developer api call response received: status code: 200 +[2025-03-26 18:32:01.882][26][info] prompt_gateway: on_http_call_response: sending request to upstream llm +[2025-03-26 18:32:01.883][26][info] llm_gateway: on_http_request_body: provider: gpt-4o-mini, model requested: None, model selected: gpt-4o-mini +[2025-03-26 18:32:02.818][26][info] llm_gateway: on_http_response_body: time to first token: 1468ms +[2025-03-26 18:32:04.532][26][info] llm_gateway: on_http_response_body: request latency: 3183ms +... +``` + +Log level can be changed to debug to get more details. To enable debug logs edit (Dockerfile)[arch/Dockerfile], change the log level `--component-log-level wasm:info` to `--component-log-level wasm:debug`. And after that you need to rebuild docker image and restart the arch gateway using following set of commands, + +``` +# make sure you are at the root of the repo +$ archgw build +# go to your service that has arch_config.yaml file and issue following command, +$ archgw up --service archgw --foreground +``` + ## Contribution We would love feedback on our [Roadmap](https://github.com/orgs/katanemo/projects/1) and we welcome contributions to **Arch**! Whether you're fixing bugs, adding new features, improving documentation, or creating tutorials, your help is much appreciated. diff --git a/arch/Dockerfile b/arch/Dockerfile index 98a113ad..7f933da5 100644 --- a/arch/Dockerfile +++ b/arch/Dockerfile @@ -29,4 +29,4 @@ RUN pip install requests RUN touch /var/log/envoy.log # ENTRYPOINT ["sh","-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --log-level trace 2>&1 | tee /var/log/envoy.log"] -ENTRYPOINT ["sh","-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --component-log-level wasm:debug 2>&1 | tee /var/log/envoy.log"] +ENTRYPOINT ["sh","-c", "python config_generator.py && envsubst < /etc/envoy/envoy.yaml > /etc/envoy.env_sub.yaml && envoy -c /etc/envoy.env_sub.yaml --component-log-level wasm:info 2>&1 | tee /var/log/envoy.log"] diff --git a/crates/common/src/http.rs b/crates/common/src/http.rs index 85626f9b..8ef176b2 100644 --- a/crates/common/src/http.rs +++ b/crates/common/src/http.rs @@ -3,7 +3,7 @@ use crate::{ stats::{Gauge, IncrementingMetric}, }; use derivative::Derivative; -use log::trace; +use log::debug; use proxy_wasm::traits::Context; use serde::Serialize; use std::{cell::RefCell, collections::HashMap, fmt::Debug, time::Duration}; @@ -48,7 +48,7 @@ pub trait Client: Context { call_args: CallArgs, call_context: Self::CallContext, ) -> Result { - trace!( + debug!( "dispatching http call with args={:?} context={:?}", call_args, call_context diff --git a/crates/common/src/ratelimit.rs b/crates/common/src/ratelimit.rs index 8825fd01..ef4e5d08 100644 --- a/crates/common/src/ratelimit.rs +++ b/crates/common/src/ratelimit.rs @@ -1,7 +1,7 @@ use crate::configuration; use configuration::{Limit, Ratelimit, TimeUnit}; use governor::{DefaultKeyedRateLimiter, InsufficientCapacity, Quota}; -use log::trace; +use log::debug; use std::fmt::Display; use std::num::{NonZero, NonZeroU32}; use std::sync::RwLock; @@ -99,7 +99,7 @@ impl RatelimitMap { selector: Header, tokens_used: NonZeroU32, ) -> Result<(), Error> { - trace!( + debug!( "Checking limit for provider={}, with selector={:?}, consuming tokens={:?}", provider, selector, diff --git a/crates/common/src/tokenizer.rs b/crates/common/src/tokenizer.rs index d2611375..e9431521 100644 --- a/crates/common/src/tokenizer.rs +++ b/crates/common/src/tokenizer.rs @@ -1,14 +1,14 @@ -use log::trace; +use log::{debug}; #[allow(dead_code)] pub fn token_count(model_name: &str, text: &str) -> Result { - trace!("getting token count model={}", model_name); + debug!("getting token count model={}", model_name); //HACK: add support for tokenizing mistral and other models //filed issue https://github.com/katanemo/arch/issues/222 let updated_model = match model_name.starts_with("gpt") { false => { - trace!( + debug!( "tiktoken_rs: unsupported model: {}, using gpt-4 to compute token count", model_name ); diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index c621393f..78d7e21e 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -15,7 +15,7 @@ use common::stats::{IncrementingMetric, RecordingMetric}; use common::tracing::{Event, Span, TraceData, Traceparent}; use common::{ratelimit, routing, tokenizer}; use http::StatusCode; -use log::{debug, trace, warn}; +use log::{debug, info, warn}; use proxy_wasm::hostcalls::get_current_time; use proxy_wasm::traits::*; use proxy_wasm::types::*; @@ -89,7 +89,7 @@ impl StreamContext { provider_hint, )); - trace!( + debug!( "request received: llm provider hint: {}, selected llm: {}, model: {}", self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER) .unwrap_or_default(), @@ -140,7 +140,7 @@ impl StreamContext { } fn send_server_error(&self, error: ServerError, override_status_code: Option) { - debug!("server error occurred: {}", error); + warn!("server error occurred: {}", error); self.send_http_response( override_status_code .unwrap_or(StatusCode::INTERNAL_SERVER_ERROR) @@ -159,7 +159,7 @@ impl StreamContext { // Tokenize and record token count. let token_count = tokenizer::token_count(model, json_string).unwrap_or(0); - trace!("Recorded input token count: {}", token_count); + debug!("Recorded input token count: {}", token_count); // Record the token count to metrics. self.metrics .input_sequence_length @@ -167,14 +167,14 @@ impl StreamContext { // Check if rate limiting needs to be applied. if let Some(selector) = self.ratelimit_selector.take() { - log::trace!("Applying ratelimit for model: {}", model); + log::debug!("Applying ratelimit for model: {}", model); ratelimit::ratelimits(None).read().unwrap().check_limit( model.to_owned(), selector, NonZero::new(token_count as u32).unwrap(), )?; } else { - trace!("No rate limit applied for model: {}", model); + debug!("No rate limit applied for model: {}", model); } Ok(()) @@ -200,7 +200,7 @@ impl HttpContext for StreamContext { }; if let Some(routing_header_value) = routing_header_value.as_ref() { - debug!("routing header already set: {}", routing_header_value); + info!("routing header already set: {}", routing_header_value); self.llm_provider = Some(Rc::new(LlmProvider { name: routing_header_value.to_string(), provider_interface: LlmProviderType::OpenAI, @@ -247,6 +247,11 @@ impl HttpContext for StreamContext { } fn on_http_request_body(&mut self, body_size: usize, end_of_stream: bool) -> Action { + debug!( + "on_http_request_body [S={}] bytes={} end_stream={}", + self.context_id, body_size, end_of_stream + ); + // Let the client send the gateway all the data before sending to the LLM_provider. // TODO: consider a streaming API. @@ -282,7 +287,10 @@ impl HttpContext for StreamContext { match serde_json::from_slice(&body_bytes) { Ok(deserialized) => deserialized, Err(e) => { - debug!("body str: {}", String::from_utf8_lossy(&body_bytes)); + debug!( + "on_http_request_body: request body: {}", + String::from_utf8_lossy(&body_bytes) + ); self.send_server_error( ServerError::Deserialization(e), Some(StatusCode::BAD_REQUEST), @@ -336,16 +344,19 @@ impl HttpContext for StreamContext { } } - debug!( - "provider: {:?}, model requested: {}, model selected: {:?}", + info!( + "on_http_request_body: provider: {}, model requested: {}, model selected: {}", self.llm_provider().name, model_requested, - model_name, + model_name.unwrap_or(&"None".to_string()), ); let chat_completion_request_str = serde_json::to_string(&deserialized_body).unwrap(); - trace!("request body: {}", chat_completion_request_str); + debug!( + "on_http_request_body: request body: {}", + chat_completion_request_str + ); if deserialized_body.stream { self.streaming_response = true; @@ -380,10 +391,9 @@ impl HttpContext for StreamContext { } fn on_http_response_headers(&mut self, _num_headers: usize, _end_of_stream: bool) -> Action { - trace!( + debug!( "on_http_response_headers [S={}] end_stream={}", - self.context_id, - _end_of_stream + self.context_id, _end_of_stream ); self.set_property( @@ -395,15 +405,18 @@ impl HttpContext for StreamContext { } fn on_http_response_body(&mut self, body_size: usize, end_of_stream: bool) -> Action { - trace!( + debug!( "on_http_response_body [S={}] bytes={} end_stream={}", - self.context_id, - body_size, - end_of_stream + self.context_id, body_size, end_of_stream ); + if self.request_body_sent_time.is_none() { + debug!("on_http_response_body: request body not sent, no doing any processing in llm filter"); + return Action::Continue; + } + if !self.is_chat_completions_request { - debug!("non-chatcompletion request"); + info!("on_http_response_body: non-chatcompletion request"); return Action::Continue; } @@ -415,7 +428,7 @@ impl HttpContext for StreamContext { Ok(duration) => { // Convert the duration to milliseconds let duration_ms = duration.as_millis(); - debug!("request latency: {}ms", duration_ms); + info!("on_http_response_body: request latency: {}ms", duration_ms); // Record the latency to the latency histogram self.metrics.request_latency.record(duration_ms as u64); @@ -426,7 +439,7 @@ impl HttpContext for StreamContext { // Record the time per output token self.metrics.time_per_output_token.record(tpot); - trace!( + debug!( "time per token: {}ms, tokens per second: {}", tpot, 1000 / tpot @@ -490,10 +503,9 @@ impl HttpContext for StreamContext { let body = if self.streaming_response { let chunk_start = 0; let chunk_size = body_size; - trace!( - "streaming response reading, {}..{}", - chunk_start, - chunk_size + debug!( + "on_http_response_body: streaming response reading, {}..{}", + chunk_start, chunk_size ); let streaming_chunk = match self.get_http_response_body(0, chunk_size) { Some(chunk) => chunk, @@ -515,7 +527,7 @@ impl HttpContext for StreamContext { } streaming_chunk } else { - trace!("non streaming response bytes read: 0:{}", body_size); + debug!("non streaming response bytes read: 0:{}", body_size); match self.get_http_response_body(0, body_size) { Some(body) => body, None => { @@ -528,7 +540,7 @@ impl HttpContext for StreamContext { let body_utf8 = match String::from_utf8(body) { Ok(body_utf8) => body_utf8, Err(e) => { - debug!("could not convert to utf8: {}", e); + warn!("could not convert to utf8: {}", e); return Action::Continue; } }; @@ -542,7 +554,7 @@ impl HttpContext for StreamContext { match ChatCompletionStreamResponseServerEvents::try_from(body_utf8.as_str()) { Ok(response) => response, Err(e) => { - debug!( + warn!( "invalid streaming response: body str: {}, {:?}", body_utf8, e ); @@ -551,8 +563,8 @@ impl HttpContext for StreamContext { }; if chat_completions_chunk_response_events.events.is_empty() { - debug!( - "cound't parse any streaming events: body str: {}", + warn!( + "couldn't parse any streaming events: body str: {}", body_utf8 ); return Action::Continue; @@ -571,7 +583,7 @@ impl HttpContext for StreamContext { { Ok(token_count) => token_count, Err(e) => { - debug!("could not get token count: {:?}", e); + warn!("could not get token count: {:?}", e); return Action::Continue; } }; @@ -585,7 +597,10 @@ impl HttpContext for StreamContext { match current_time.duration_since(self.start_time) { Ok(duration) => { let duration_ms = duration.as_millis(); - debug!("time to first token: {}ms", duration_ms); + info!( + "on_http_response_body: time to first token: {}ms", + duration_ms + ); self.ttft_duration = Some(duration); self.metrics.time_to_first_token.record(duration_ms as u64); } @@ -595,12 +610,12 @@ impl HttpContext for StreamContext { } } } else { - trace!("non streaming response"); + debug!("non streaming response"); let chat_completions_response: ChatCompletionsResponse = match serde_json::from_str(body_utf8.as_str()) { Ok(de) => de, Err(err) => { - debug!( + info!( "non chat-completion compliant response received err: {}, body: {}", err, body_utf8 ); @@ -617,11 +632,9 @@ impl HttpContext for StreamContext { } } - trace!( + debug!( "recv [S={}] total_tokens={} end_stream={}", - self.context_id, - self.response_tokens, - end_of_stream + self.context_id, self.response_tokens, end_of_stream ); Action::Continue diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index 9d87c00c..0f94d2d8 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -30,7 +30,7 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { Some("x-arch-llm-provider-hint"), ) .returning(None) - .expect_log(Some(LogLevel::Trace), Some("request received: llm provider hint: default, selected llm: open-ai-gpt-4, model: gpt-4")) + .expect_log(Some(LogLevel::Debug), Some("request received: llm provider hint: default, selected llm: open-ai-gpt-4, model: gpt-4")) .expect_add_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider"), @@ -223,15 +223,16 @@ fn llm_gateway_successful_request_to_open_ai_chat_completions() { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 21) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -289,18 +290,19 @@ fn llm_gateway_bad_request_to_open_ai_chat_completions() { .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(incomplete_chat_completions_request_body)) .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), Some("on_http_request_body: provider: open-ai-gpt-4, model requested: , model selected: gpt-4")) .expect_send_local_response( Some(StatusCode::BAD_REQUEST.as_u16().into()), None, None, None, ) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_metric_record("input_sequence_length", 14) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); } @@ -350,17 +352,18 @@ fn llm_gateway_request_ratelimited() { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 107) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), Some("server error occurred: exceeded limit provider=gpt-4, selector=Header { key: \"selector-key\", value: \"selector-value\" }, tokens_used=107")) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Warn), Some("server error occurred: exceeded limit provider=gpt-4, selector=Header { key: \"selector-key\", value: \"selector-value\" }, tokens_used=107")) .expect_send_local_response( Some(StatusCode::TOO_MANY_REQUESTS.as_u16().into()), None, @@ -417,16 +420,17 @@ fn llm_gateway_request_not_ratelimited() { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_metric_record("input_sequence_length", 29) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -480,14 +484,15 @@ fn llm_gateway_override_model_name() { .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id - .expect_log(Some(LogLevel::Debug), Some("provider: \"open-ai-gpt-4\", model requested: o1-mini, model selected: Some(\"gpt-4\")")) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), Some("on_http_request_body: provider: open-ai-gpt-4, model requested: o1-mini, model selected: gpt-4")) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_metric_record("input_sequence_length", 29) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -537,19 +542,20 @@ fn llm_gateway_override_use_default_model() { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id .expect_log( - Some(LogLevel::Debug), - Some("provider: \"open-ai-gpt-4\", model requested: , model selected: Some(\"gpt-4\")"), + Some(LogLevel::Info), + Some("on_http_request_body: provider: open-ai-gpt-4, model requested: , model selected: gpt-4"), ) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_metric_record("input_sequence_length", 29) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -603,13 +609,14 @@ fn llm_gateway_override_use_model_name_none() { .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id - .expect_log(Some(LogLevel::Debug), Some("provider: \"open-ai-gpt-4\", model requested: none, model selected: Some(\"gpt-4\")")) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), Some("on_http_request_body: provider: open-ai-gpt-4, model requested: none, model selected: gpt-4")) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_metric_record("input_sequence_length", 29) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index 9580e934..3a7dc7d9 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -14,7 +14,7 @@ use common::{ pii::obfuscate_auth_header, }; use http::StatusCode; -use log::{debug, trace, warn}; +use log::{debug, info, warn}; use proxy_wasm::{traits::HttpContext, types::Action}; use serde_json::Value; use std::{ @@ -39,7 +39,7 @@ impl HttpContext for StreamContext { if let Some(endpoints) = self.endpoints.as_ref() { if endpoints.len() == 1 { let (name, _) = endpoints.iter().next().unwrap(); - debug!("Setting ARCH_PROVIDER_HINT_HEADER to {}", name); + info!("Setting ARCH_PROVIDER_HINT_HEADER to {}", name); self.set_http_request_header(ARCH_ROUTING_HEADER, Some(name)); } else { warn!("Need single endpoint when use_agent_orchestrator is set"); @@ -63,7 +63,7 @@ impl HttpContext for StreamContext { self.is_chat_completions_request = request_path == CHAT_COMPLETIONS_PATH; - trace!( + debug!( "on_http_request_headers S[{}] req_headers={:?}", self.context_id, obfuscate_auth_header(&mut self.get_http_request_headers()) @@ -89,10 +89,9 @@ impl HttpContext for StreamContext { self.request_body_size = body_size; - trace!( + debug!( "on_http_request_body S[{}] body_size={}", - self.context_id, - body_size + self.context_id, body_size ); let body_bytes = match self.get_http_request_body(0, body_size) { @@ -109,7 +108,7 @@ impl HttpContext for StreamContext { } }; - trace!("request body: {}", String::from_utf8_lossy(&body_bytes)); + debug!("request body: {}", String::from_utf8_lossy(&body_bytes)); // Deserialize body into spec. // Currently OpenAI API. @@ -206,8 +205,8 @@ impl HttpContext for StreamContext { } }; - debug!("sending request to model server"); - trace!("request body: {}", json_data); + info!("on_http_request_body: sending request to model server"); + debug!("request body: {}", json_data); let timeout_str = MODEL_SERVER_REQUEST_TIMEOUT_MS.to_string(); @@ -248,7 +247,7 @@ impl HttpContext for StreamContext { }; if let Err(e) = self.http_call(call_args, call_context) { - debug!("http_call failed: {:?}", e); + warn!("http_call failed: {:?}", e); self.send_server_error(ServerError::HttpDispatch(e), None); } @@ -256,7 +255,7 @@ impl HttpContext for StreamContext { } fn on_http_response_headers(&mut self, _num_headers: usize, _end_of_stream: bool) -> Action { - trace!( + debug!( "on_http_response_headers recv [S={}] headers={:?}", self.context_id, self.get_http_response_headers() @@ -268,15 +267,13 @@ impl HttpContext for StreamContext { } fn on_http_response_body(&mut self, body_size: usize, end_of_stream: bool) -> Action { - trace!( + debug!( "on_http_response_body: recv [S={}] bytes={} end_stream={}", - self.context_id, - body_size, - end_of_stream + self.context_id, body_size, end_of_stream ); if !self.is_chat_completions_request { - debug!("non-gpt request"); + info!("non-gpt request"); return Action::Continue; } @@ -315,7 +312,7 @@ impl HttpContext for StreamContext { streaming_chunk } else { - debug!("non streaming response bytes read: 0:{}", body_size); + info!("non streaming response bytes read: 0:{}", body_size); match self.get_http_response_body(0, body_size) { Some(body) => body, None => { @@ -328,13 +325,13 @@ impl HttpContext for StreamContext { let body_utf8 = match String::from_utf8(body) { Ok(body_utf8) => body_utf8, Err(e) => { - debug!("could not convert to utf8: {}", e); + info!("could not convert to utf8: {}", e); return Action::Continue; } }; if self.streaming_response { - trace!("streaming response"); + debug!("streaming response"); if self.tool_calls.is_some() && !self.tool_calls.as_ref().unwrap().is_empty() { let chunks = vec![ @@ -396,13 +393,13 @@ impl HttpContext for StreamContext { serde_json::Value::String(arch_state_str), ); let data_serialized = serde_json::to_string(&data).unwrap(); - debug!("archgw <= developer: {}", data_serialized); + info!("archgw <= developer: {}", data_serialized); self.set_http_response_body(0, body_size, data_serialized.as_bytes()); }; } } - trace!("recv [S={}] end_stream={}", self.context_id, end_of_stream); + debug!("recv [S={}] end_stream={}", self.context_id, end_of_stream); Action::Continue } diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index 4a968d43..ec68c104 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -15,7 +15,7 @@ use common::http::{CallArgs, Client}; use common::stats::Gauge; use derivative::Derivative; use http::StatusCode; -use log::{debug, trace, warn}; +use log::{debug, info, warn}; use proxy_wasm::traits::*; use std::cell::RefCell; use std::collections::HashMap; @@ -128,8 +128,8 @@ impl StreamContext { mut callout_context: StreamCallContext, ) { let body_str = String::from_utf8(body).unwrap(); - debug!("model server response received"); - trace!("response body: {}", body_str); + info!("on_http_call_response: model server response received"); + debug!("response body: {}", body_str); let model_server_response: ChatCompletionsResponse = match serde_json::from_str(&body_str) { Ok(arch_fc_response) => arch_fc_response, @@ -150,14 +150,14 @@ impl StreamContext { .is_some(); if !intent_matched { - debug!("intent not matched"); + info!("intent not matched"); // check if we have a default prompt target if let Some(default_prompt_target) = self .prompt_targets .values() .find(|pt| pt.default.unwrap_or(false)) { - debug!("default prompt target found, forwarding request to default prompt target"); + info!("default prompt target found, forwarding request to default prompt target"); let endpoint = default_prompt_target.endpoint.clone().unwrap(); let upstream_path: String = endpoint.path.unwrap_or(String::from("/")); @@ -204,7 +204,7 @@ impl StreamContext { } return; } else { - debug!("no default prompt target found, forwarding request to upstream llm"); + info!("no default prompt target found, forwarding request to upstream llm"); let mut messages = Vec::new(); // add system prompt match self.system_prompt.as_ref() { @@ -242,7 +242,7 @@ impl StreamContext { let chat_completion_request_json = serde_json::to_string(&chat_completion_request).unwrap(); - debug!( + info!( "archgw => upstream llm request: {}", chat_completion_request_json ); @@ -353,7 +353,7 @@ impl StreamContext { }; let body_str = serde_json::to_string(&chat_completion_request).unwrap(); - debug!("sending request to llm agent: {}", body_str); + info!("sending request to llm agent: {}", body_str); self.set_http_request_body(0, self.request_body_size, body_str.as_bytes()); self.resume_http_request(); return; @@ -396,7 +396,7 @@ impl StreamContext { } }; - debug!("api call body {:?}", api_call_body); + debug!("on_http_call_response: api call body {:?}", api_call_body); let timeout_str = API_REQUEST_TIMEOUT_MS.to_string(); @@ -436,8 +436,8 @@ impl StreamContext { Duration::from_secs(5), ); - debug!( - "dispatching api call to developer endpoint: {}, path: {}, method: {}", + info!( + "on_http_call_response: dispatching api call to developer endpoint: {}, path: {}, method: {}", endpoint_details.name, path, http_method_str ); @@ -454,8 +454,8 @@ impl StreamContext { let http_status = self .get_http_call_response_header(":status") .unwrap_or(StatusCode::OK.as_str().to_string()); - debug!( - "developer api call response received: status code: {}", + info!( + "on_http_call_response: developer api call response received: status code: {}", http_status ); let prompt_target = self @@ -479,7 +479,7 @@ impl StreamContext { ); } self.tool_call_response = Some(String::from_utf8(body).unwrap()); - trace!( + debug!( "response body: {}", self.tool_call_response.as_ref().unwrap() ); @@ -561,8 +561,8 @@ impl StreamContext { return self.send_server_error(ServerError::Serialization(e), None); } }; - debug!("sending request to upstream llm"); - trace!("request body: {}", llm_request_str); + info!("on_http_call_response: sending request to upstream llm"); + debug!("request body: {}", llm_request_str); self.start_upstream_llm_request_time = SystemTime::now() .duration_since(UNIX_EPOCH) @@ -755,7 +755,7 @@ impl StreamContext { }; let json_resp = serde_json::to_string(&chat_completion_request).unwrap(); - debug!("archgw => (default target) llm request: {}", json_resp); + info!("archgw => (default target) llm request: {}", json_resp); self.set_http_request_body(0, self.request_body_size, json_resp.as_bytes()); self.resume_http_request(); } diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index 1673ac16..bbde10b0 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -24,12 +24,12 @@ fn wasm_module() -> String { fn request_headers_expectations(module: &mut Tester, http_context: i32) { module .call_proxy_on_request_headers(http_context, 0, false) + .expect_log(Some(LogLevel::Debug), None) .expect_remove_header_map_value(Some(MapType::HttpRequestHeaders), Some("content-length")) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some(":path")) .returning(Some("/v1/chat/completions")) .expect_get_header_map_pairs(Some(MapType::HttpRequestHeaders)) .returning(None) - .expect_log(Some(LogLevel::Trace), None) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some("x-request-id")) .returning(None) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some("traceparent")) @@ -69,10 +69,14 @@ fn normal_flow(module: &mut Tester, filter_context: i32, http_context: i32) { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) // The actual call is not important in this test, we just need to grab the token_id - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_http_call( Some("arch_internal"), Some(vec![ @@ -88,10 +92,6 @@ fn normal_flow(module: &mut Tester, filter_context: i32, http_context: i32) { Some(5000), ) .returning(Some(1)) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_metric_increment("active_http_calls", 1) .execute_and_expect(ReturnType::Action(Action::Pause)) .unwrap(); @@ -233,13 +233,13 @@ fn prompt_gateway_successful_request_to_open_ai_chat_completions() { chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(chat_completions_request_body)) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Debug), None) .expect_http_call(Some("arch_internal"), None, None, None, None) .returning(Some(4)) .expect_metric_increment("active_http_calls", 1) @@ -296,16 +296,16 @@ fn prompt_gateway_bad_request_to_open_ai_chat_completions() { incomplete_chat_completions_request_body.len() as i32, true, ) + .expect_log(Some(LogLevel::Debug), None) .expect_get_buffer_bytes(Some(BufferType::HttpRequestBody)) .returning(Some(incomplete_chat_completions_request_body)) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Debug), None) .expect_send_local_response( Some(StatusCode::BAD_REQUEST.as_u16().into()), None, None, None, ) - .expect_log(Some(LogLevel::Trace), None) .execute_and_expect(ReturnType::Action(Action::Pause)) .unwrap(); } @@ -378,11 +378,11 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) .returning(Some(&arch_fc_resp_str)) .expect_log(Some(LogLevel::Warn), None) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Debug), None) .expect_http_call( Some("arch_internal"), Some(vec![ @@ -410,14 +410,14 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_metric_increment("active_http_calls", -1) .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) .returning(Some(&body_text)) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Trace), None) .expect_get_header_map_value(Some(MapType::HttpCallResponseHeaders), Some(":status")) .returning(Some("200")) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) + .expect_log(Some(LogLevel::Debug), None) .execute_and_expect(ReturnType::None) .unwrap(); @@ -449,11 +449,11 @@ fn prompt_gateway_request_to_llm_gateway() { ) .expect_get_buffer_bytes(Some(BufferType::HttpResponseBody)) .returning(Some(chat_completion_response_str.as_str())) - .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), None) .expect_set_buffer_bytes(Some(BufferType::HttpResponseBody), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); } @@ -521,15 +521,15 @@ fn prompt_gateway_request_no_intent_match() { .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) .returning(Some(&arch_fc_resp_str)) .expect_log(Some(LogLevel::Warn), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), Some("intent not matched")) + .expect_log(Some(LogLevel::Info), Some("intent not matched")) .expect_log( - Some(LogLevel::Debug), + Some(LogLevel::Info), Some("no default prompt target found, forwarding request to upstream llm"), ) - .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Info), None) .expect_set_buffer_bytes(Some(BufferType::HttpRequestBody), None) .execute_and_expect(ReturnType::None) .unwrap(); @@ -677,15 +677,15 @@ fn prompt_gateway_request_no_intent_match_default_target() { .expect_get_buffer_bytes(Some(BufferType::HttpCallResponseBody)) .returning(Some(&arch_fc_resp_str)) .expect_log(Some(LogLevel::Warn), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Trace), None) - .expect_log(Some(LogLevel::Debug), Some("intent not matched")) + .expect_log(Some(LogLevel::Info), Some("intent not matched")) .expect_log( - Some(LogLevel::Debug), + Some(LogLevel::Info), Some("default prompt target found, forwarding request to default prompt target"), ) - .expect_log(Some(LogLevel::Trace), None) .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), None) .expect_http_call( Some("arch_internal"), Some(vec![ From 49e8216061dc9282bbc1f28e3a8653beb07b9360 Mon Sep 17 00:00:00 2001 From: Ikko Eltociear Ashimine Date: Sat, 29 Mar 2025 06:35:55 +0900 Subject: [PATCH 31/37] docs: update llm_provider.rst (#448) minor fix --- docs/source/concepts/llm_provider.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/concepts/llm_provider.rst b/docs/source/concepts/llm_provider.rst index ba9566ba..551d6074 100644 --- a/docs/source/concepts/llm_provider.rst +++ b/docs/source/concepts/llm_provider.rst @@ -4,7 +4,7 @@ LLM Provider ============ **LLM provider** is a top-level primitive in Arch, helping developers centrally define, secure, observe, -and manage the usage of of their LLMs. Arch builds on Envoy's reliable `cluster subsystem `_ +and manage the usage of their LLMs. Arch builds on Envoy's reliable `cluster subsystem `_ to manage egress traffic to LLMs, which includes intelligent routing, retry and fail-over mechanisms, ensuring high availability and fault tolerance. This abstraction also enables developers to seamlessly switching between LLM providers or upgrade LLM versions, simplifying the integration and scaling of LLMs From 8ba1f714302dbd654b0da53fdfdc3694775f3c84 Mon Sep 17 00:00:00 2001 From: Joseph D Alchemist Date: Thu, 3 Apr 2025 21:34:57 +0300 Subject: [PATCH 32/37] remove typo (#456) --- docs/source/build_with_arch/rag.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/build_with_arch/rag.rst b/docs/source/build_with_arch/rag.rst index 3f4db41f..eafd6e2b 100644 --- a/docs/source/build_with_arch/rag.rst +++ b/docs/source/build_with_arch/rag.rst @@ -46,7 +46,7 @@ Multi-Turn RAG (Follow-up Questions) Developers often `struggle `_ to efficiently handle ``follow-up`` or ``clarification`` questions. Specifically, when users ask for changes or additions to previous responses, it requires developers to re-write prompts using LLMs with precise prompt engineering techniques. This process is slow, manual, error prone and adds signifcant latency to the -user experience. Arch +user experience. Arch is highly capable of accurately detecting and processing prompts in a multi-turn scenarios so that you can buil fast and accurate RAG apps in minutes. For additional details on how to build multi-turn RAG applications please refer to our :ref:`multi-turn ` docs. From 4d2d8bd7a14eb4d4be7ee2c82222ea6e6a39ce13 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Sun, 6 Apr 2025 01:24:01 -0700 Subject: [PATCH 33/37] release 0.2.5 (#457) --- README.md | 2 +- arch/tools/README.md | 2 +- arch/tools/poetry.lock | 229 +++---- arch/tools/pyproject.toml | 4 +- docs/source/conf.py | 2 +- docs/source/get_started/quickstart.rst | 2 +- model_server/poetry.lock | 813 +++++++++++++------------ model_server/pyproject.toml | 2 +- 8 files changed, 541 insertions(+), 515 deletions(-) diff --git a/README.md b/README.md index b733bbd5..ba271dd3 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. ```console $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate -$ pip install archgw==0.2.4 +$ pip install archgw==0.2.5 ``` ### Build AI Agent with Arch Gateway diff --git a/arch/tools/README.md b/arch/tools/README.md index eadf3da8..554981ae 100644 --- a/arch/tools/README.md +++ b/arch/tools/README.md @@ -19,7 +19,7 @@ source venv/bin/activate ### Step 3: Run the build script ```bash -pip install archgw==0.2.4 +pip install archgw==0.2.5 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index bb70350b..970f3a51 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -2,7 +2,7 @@ [[package]] name = "archgw_modelserver" -version = "0.2.4" +version = "0.2.5" description = "A model server for serving models" optional = false python-versions = "*" @@ -259,114 +259,125 @@ typing-extensions = {version = ">=4.4.0", markers = "python_version < \"3.13\""} [[package]] name = "rpds-py" -version = "0.23.1" +version = "0.24.0" description = "Python bindings to Rust's persistent data structures (rpds)" optional = false python-versions = ">=3.9" files = [ - {file = "rpds_py-0.23.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = 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"uvicorn"] sigopt = ["sigopt"] sklearn = ["scikit-learn"] speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] -testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] +testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-order", "pytest-rerunfailures", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.11.2)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"] tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"] tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"] tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] @@ -2040,7 +2041,7 @@ tokenizers = ["tokenizers (>=0.21,<0.22)"] torch = ["accelerate (>=0.26.0)", "torch (>=2.0)"] torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"] torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"] -torchhub = ["filelock", "huggingface-hub (>=0.26.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"] +torchhub = ["filelock", "huggingface-hub (>=0.30.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"] video = ["av"] vision = ["Pillow (>=10.0.1,<=15.0)"] @@ -2068,35 +2069,49 @@ tutorials = ["matplotlib", "pandas", "tabulate"] [[package]] name = "typing-extensions" -version = "4.12.2" +version = "4.13.1" description = "Backported and Experimental Type Hints for Python 3.8+" optional = false python-versions = ">=3.8" files = [ - {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"}, - {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"}, + {file = "typing_extensions-4.13.1-py3-none-any.whl", hash = "sha256:4b6cf02909eb5495cfbc3f6e8fd49217e6cc7944e145cdda8caa3734777f9e69"}, + {file = "typing_extensions-4.13.1.tar.gz", hash = "sha256:98795af00fb9640edec5b8e31fc647597b4691f099ad75f469a2616be1a76dff"}, ] +[[package]] +name = "typing-inspection" +version = "0.4.0" +description = "Runtime typing introspection tools" +optional = false +python-versions = ">=3.9" +files = [ + {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"}, + {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"}, +] + +[package.dependencies] +typing-extensions = ">=4.12.0" + [[package]] name = "tzdata" -version = "2025.1" +version = "2025.2" description = "Provider of IANA time zone data" optional = false python-versions = ">=2" files = [ - {file = "tzdata-2025.1-py2.py3-none-any.whl", hash = "sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639"}, - {file = "tzdata-2025.1.tar.gz", hash = "sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694"}, + {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"}, + {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, ] [[package]] name = "tzlocal" -version = "5.3" +version = "5.3.1" description = "tzinfo object for the local timezone" optional = false python-versions = ">=3.9" files = [ - {file = "tzlocal-5.3-py3-none-any.whl", hash = "sha256:3814135a1bb29763c6e4f08fd6e41dbb435c7a60bfbb03270211bcc537187d8c"}, - {file = "tzlocal-5.3.tar.gz", hash = "sha256:2fafbfc07e9d8b49ade18f898d6bcd37ae88ce3ad6486842a2e4f03af68323d2"}, + {file = "tzlocal-5.3.1-py3-none-any.whl", hash = "sha256:eb1a66c3ef5847adf7a834f1be0800581b683b5608e74f86ecbcef8ab91bb85d"}, + {file = "tzlocal-5.3.1.tar.gz", hash = "sha256:cceffc7edecefea1f595541dbd6e990cb1ea3d19bf01b2809f362a03dd7921fd"}, ] [package.dependencies] diff --git a/model_server/pyproject.toml b/model_server/pyproject.toml index d7c38adb..920c33fb 100644 --- a/model_server/pyproject.toml +++ b/model_server/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw_modelserver" -version = "0.2.4" +version = "0.2.5" description = "A model server for serving models" authors = ["Katanemo Labs, Inc "] license = "Apache 2.0" From e7b0de2a72b0c5a6b92a2beca67e669aec68344d Mon Sep 17 00:00:00 2001 From: Mat Sylvia Date: Sun, 13 Apr 2025 02:52:20 -0400 Subject: [PATCH 34/37] Tweak readme docs for minor nits (#461) Co-authored-by: darkdatter --- README.md | 6 +++--- .../network_switch_operator_agent/README.md | 2 +- demos/samples_python/weather_forecast/README.md | 2 +- docs/source/concepts/prompt_target.rst | 4 ++-- docs/source/concepts/tech_overview/listener.rst | 6 +++--- docs/source/concepts/tech_overview/model_serving.rst | 8 ++++---- docs/source/concepts/tech_overview/prompt.rst | 8 ++++---- .../concepts/tech_overview/request_lifecycle.rst | 10 +++++----- docs/source/concepts/tech_overview/terminology.rst | 8 ++++---- docs/source/get_started/intro_to_arch.rst | 6 +++--- docs/source/guides/agent_routing.rst | 8 ++++---- docs/source/resources/configuration_reference.rst | 4 ++-- .../resources/includes/arch_config_full_reference.yaml | 4 ++-- 13 files changed, 38 insertions(+), 38 deletions(-) diff --git a/README.md b/README.md index ba271dd3..8a416d51 100644 --- a/README.md +++ b/README.md @@ -32,14 +32,14 @@ Past the thrill of an AI demo, have you found yourself hitting these walls? You - You're bogged down with prompt engineering just to **clarify user intent and validate inputs** effectively? - You're wasting cycles choosing and integrating code for **observability** instead of it happening transparently? -And you think to youself, can't I move faster by focusing on higher-level objectives in a language/framework agnostic way? Well, you can! **Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: +And you think to yourself, can't I move faster by focusing on higher-level objectives in a language/framework agnostic way? Well, you can! **Arch Gateway** was built by the contributors of [Envoy Proxy](https://www.envoyproxy.io/) with the belief that: >Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests including secure handling, intelligent routing, robust observability, and integration with backend (API) systems to improve speed and accuracy for common agentic scenarios – all outside core application logic.* **Core Features**: - `🚦 Routing`. Engineered with purpose-built [LLMs](https://huggingface.co/collections/katanemo/arch-function-66f209a693ea8df14317ad68) for fast (<100ms) agent routing and hand-off scenarios - - `⚡ Tools Use`: For common agentic scenarios let Arch instantly clarfiy and convert prompts to tools/API calls + - `⚡ Tools Use`: For common agentic scenarios let Arch instantly clarify and convert prompts to tools/API calls - `⛨ Guardrails`: Centrally configure and prevent harmful outcomes and ensure safe user interactions - `🔗 Access to LLMs`: Centralize access and traffic to LLMs with smart retries for continuous availability - `🕵 Observability`: W3C compatible request tracing and LLM metrics that instantly plugin with popular tools @@ -151,7 +151,7 @@ $ archgw up arch_config.yaml 2024-12-05 16:56:27,979 - cli.main - INFO - Starting archgw cli version: 0.1.5 ... 2024-12-05 16:56:28,485 - cli.utils - INFO - Schema validation successful! -2024-12-05 16:56:28,485 - cli.main - INFO - Starging arch model server and arch gateway +2024-12-05 16:56:28,485 - cli.main - INFO - Starting arch model server and arch gateway ... 2024-12-05 16:56:51,647 - cli.core - INFO - Container is healthy! diff --git a/demos/samples_python/network_switch_operator_agent/README.md b/demos/samples_python/network_switch_operator_agent/README.md index e7038732..848f2410 100644 --- a/demos/samples_python/network_switch_operator_agent/README.md +++ b/demos/samples_python/network_switch_operator_agent/README.md @@ -28,7 +28,7 @@ The assistant can perform several key operations, including rebooting devices, a 4. Tell me what can you do for me?" # Observability -Arch gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from arch and we are using grafana to visalize the stats in dashboard. To see grafana dashboard follow instructions below, +Arch gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from arch and we are using grafana to visualize the stats in dashboard. To see grafana dashboard follow instructions below, 1. Start grafana and prometheus using following command ```yaml diff --git a/demos/samples_python/weather_forecast/README.md b/demos/samples_python/weather_forecast/README.md index 2dfd6a8f..26eea157 100644 --- a/demos/samples_python/weather_forecast/README.md +++ b/demos/samples_python/weather_forecast/README.md @@ -1,6 +1,6 @@ # Function calling -This demo shows how you can use Arch's core function calling capabilites. +This demo shows how you can use Arch's core function calling capabilities. # Starting the demo diff --git a/docs/source/concepts/prompt_target.rst b/docs/source/concepts/prompt_target.rst index 8e5994c7..c708a9e7 100644 --- a/docs/source/concepts/prompt_target.rst +++ b/docs/source/concepts/prompt_target.rst @@ -9,7 +9,7 @@ This section covers the essentials of prompt targets—what they are, how to con What Are Prompt Targets? ------------------------ -Prompt targets are endpoints within Arch that handle specific types of user prompts. They act as the bridge between user inputs and your backend agemts or tools (APIs), enabling Arch to route, process, and manage prompts efficiently. Defining prompt targets helps you decouple your application's core logic from processing and handling complexities, leading to clearer code organization, better scalability, and easier maintenance. +Prompt targets are endpoints within Arch that handle specific types of user prompts. They act as the bridge between user inputs and your backend agents or tools (APIs), enabling Arch to route, process, and manage prompts efficiently. Defining prompt targets helps you decouple your application's core logic from processing and handling complexities, leading to clearer code organization, better scalability, and easier maintenance. .. table:: @@ -71,7 +71,7 @@ Each parameter can be marked as required or optional. Here is a full list of par ``default`` Specifies a default value for the parameter if not provided by the user. ``format`` Specifies a format for the parameter value. For example: `2019-12-31` for a date value. ``enum`` Lists of allowable values for the parameter with data type matching the ``type`` attribute. **Usage Example**: ``enum: ["celsius`", "fahrenheit"]`` - ``items`` Specifies the attribute of the elements when type euqals **list**, **set**, **dict**, **tuple**. **Usage Example**: ``items: {"type": "str"}`` + ``items`` Specifies the attribute of the elements when type equals **list**, **set**, **dict**, **tuple**. **Usage Example**: ``items: {"type": "str"}`` ``required`` Indicates whether the parameter is mandatory or optional. Valid values: **true** or **false** ======================== ============================================================================ diff --git a/docs/source/concepts/tech_overview/listener.rst b/docs/source/concepts/tech_overview/listener.rst index 632d5315..b6795ce6 100644 --- a/docs/source/concepts/tech_overview/listener.rst +++ b/docs/source/concepts/tech_overview/listener.rst @@ -5,7 +5,7 @@ Listener **Listener** is a top level primitive in Arch, which simplifies the configuration required to bind incoming connections from downstream clients, and for egress connections to LLMs (hosted or API) -Arch builds on Envoy's Listener subsystem to streamline connection managemet for developers. Arch minimizes +Arch builds on Envoy's Listener subsystem to streamline connection management for developers. Arch minimizes the complexity of Envoy's listener setup by using best-practices and exposing only essential settings, making it easier for developers to bind connections without deep knowledge of Envoy’s configuration model. This simplification ensures that connections are secure, reliable, and optimized for performance. @@ -13,7 +13,7 @@ simplification ensures that connections are secure, reliable, and optimized for Downstream (Ingress) ^^^^^^^^^^^^^^^^^^^^^^ Developers can configure Arch to accept connections from downstream clients. A downstream listener acts as the -primary entry point for incoming traffic, handling initial connection setup, including network filtering, gurdrails, +primary entry point for incoming traffic, handling initial connection setup, including network filtering, guardrails, and additional network security checks. For more details on prompt security and safety, see :ref:`here `. @@ -27,7 +27,7 @@ address like ``arch.local:12000/v1`` for outgoing traffic. For more details on L Configure Listener ^^^^^^^^^^^^^^^^^^ -To configure a Downstream (Ingress) Listner, simply add the ``listener`` directive to your configuration file: +To configure a Downstream (Ingress) Listener, simply add the ``listener`` directive to your configuration file: .. literalinclude:: ../includes/arch_config.yaml :language: yaml diff --git a/docs/source/concepts/tech_overview/model_serving.rst b/docs/source/concepts/tech_overview/model_serving.rst index da4b3341..53a4e377 100644 --- a/docs/source/concepts/tech_overview/model_serving.rst +++ b/docs/source/concepts/tech_overview/model_serving.rst @@ -5,7 +5,7 @@ Model Serving Arch is a set of `two` self-contained processes that are designed to run alongside your application servers (or on a separate host connected via a network). The first process is designated to manage low-level -networking and HTTP related comcerns, and the other process is for model serving, which helps Arch make +networking and HTTP related concerns, and the other process is for model serving, which helps Arch make intelligent decisions about the incoming prompts. The model server is designed to call the purpose-built LLMs in Arch. @@ -16,7 +16,7 @@ LLMs in Arch. Arch' is designed to be deployed in your cloud VPC, on a on-premises host, and can work on devices that don't have a GPU. Note, GPU devices are need for fast and cost-efficient use, so that Arch (model server, specifically) -can process prompts quickly and forward control back to the applicaton host. There are three modes in which Arch +can process prompts quickly and forward control back to the application host. There are three modes in which Arch can be configured to run its **model server** subsystem: Local Serving (CPU - Moderate) @@ -32,7 +32,7 @@ might not be available. Cloud Serving (GPU - Blazing Fast) ---------------------------------- The command below instructs Arch to intelligently use GPUs locally for fast intent detection, but default to -cloud serving for function calling and guardails scenarios to dramatically improve the speed and overall performance +cloud serving for function calling and guardrails scenarios to dramatically improve the speed and overall performance of your applications. .. code-block:: console @@ -40,6 +40,6 @@ of your applications. $ archgw up .. Note:: - Arch's model serving in the cloud is priced at $0.05M/token (156x cheaper than GPT-4o) with averlage latency + Arch's model serving in the cloud is priced at $0.05M/token (156x cheaper than GPT-4o) with average latency of 200ms (10x faster than GPT-4o). Please refer to our :ref:`Get Started ` to know how to generate API keys for model serving diff --git a/docs/source/concepts/tech_overview/prompt.rst b/docs/source/concepts/tech_overview/prompt.rst index d386ffd6..0ba7b316 100644 --- a/docs/source/concepts/tech_overview/prompt.rst +++ b/docs/source/concepts/tech_overview/prompt.rst @@ -8,7 +8,7 @@ Arch relies on Envoy's HTTP `connection management ` and how the LLMs are hosted in Arch. @@ -28,7 +28,7 @@ Prompt Guard ----------------- Arch is engineered with `Arch-Guard `_, an industry leading safety layer, powered by a -compact and high-performimg LLM that monitors incoming prompts to detect and reject jailbreak attempts - +compact and high-performing LLM that monitors incoming prompts to detect and reject jailbreak attempts - ensuring that unauthorized or harmful behaviors are intercepted early in the process. To add jailbreak guardrails, see example below: @@ -50,7 +50,7 @@ Prompt Targets -------------- Once a prompt passes any configured guardrail checks, Arch processes the contents of the incoming conversation -and identifies where to forwad the conversation to via its ``prompt target`` primitve. Prompt targets are endpoints +and identifies where to forward the conversation to via its ``prompt target`` primitive. Prompt targets are endpoints that receive prompts that are processed by Arch. For example, Arch enriches incoming prompts with metadata like knowing when a user's intent has changed so that you can build faster, more accurate RAG apps. @@ -72,7 +72,7 @@ Intent Matching Arch uses fast text embedding and intent recognition approaches to first detect the intent of each incoming prompt. This intent matching phase analyzes the prompt's content and matches it against predefined prompt targets, ensuring that each prompt is forwarded to the most appropriate endpoint. -Arch’s intent matching framework considers both the name and description of each prompt target, and uses a composite matching score between embedding similarity and intent classification scores to enchance accuracy in forwarding decisions. +Arch’s intent matching framework considers both the name and description of each prompt target, and uses a composite matching score between embedding similarity and intent classification scores to enhance accuracy in forwarding decisions. - **Intent Recognition**: NLI techniques further refine the matching process by evaluating the semantic alignment between the prompt and potential targets. diff --git a/docs/source/concepts/tech_overview/request_lifecycle.rst b/docs/source/concepts/tech_overview/request_lifecycle.rst index dd3bcc8f..160eb85e 100644 --- a/docs/source/concepts/tech_overview/request_lifecycle.rst +++ b/docs/source/concepts/tech_overview/request_lifecycle.rst @@ -5,7 +5,7 @@ Request Lifecycle Below we describe the events in the lifecycle of a request passing through an Arch gateway instance. We first describe how Arch fits into the request path and then the internal events that take place following -the arrival of a request at Arch from downtream clients. We follow the request until the corresponding +the arrival of a request at Arch from downstream clients. We follow the request until the corresponding dispatch upstream and the response path. .. image:: /_static/img/network-topology-ingress-egress.jpg @@ -59,7 +59,7 @@ The request processing path in Arch has three main parts: lifecycle. The downstream and upstream HTTP/2 codec lives here. * :ref:`Prompt handler subsystem ` which is responsible for selecting and forwarding prompts ``prompt_targets`` and establishes the lifecycle of any **upstream** connection to a - hosted endpoint that implements domain-specific business logic for incoming promots. This is where knowledge + hosted endpoint that implements domain-specific business logic for incoming prompts. This is where knowledge of targets and endpoint health, load balancing and connection pooling exists. * :ref:`Model serving subsystem ` which helps Arch make intelligent decisions about the incoming prompts. The model server is designed to call the purpose-built LLMs in Arch. @@ -67,7 +67,7 @@ The request processing path in Arch has three main parts: The three subsystems are bridged with either the HTTP router filter, and the cluster manager subsystems of Envoy. Also, Arch utilizes `Envoy event-based thread model `_. -A main thread is responsible forthe server lifecycle, configuration processing, stats, etc. and some number of +A main thread is responsible for the server lifecycle, configuration processing, stats, etc. and some number of :ref:`worker threads ` process requests. All threads operate around an event loop (`libevent `_) and any given downstream TCP connection will be handled by exactly one worker thread for its lifetime. Each worker thread maintains its own pool of TCP connections to upstream endpoints. @@ -99,7 +99,7 @@ A brief outline of the lifecycle of a request and response using the example con that harmful or unwanted behaviors are detected early in the request processing pipeline. 3. **Intent Matching**: - The decrypted data stream is deframed by the HTTP/2 codec in Arch's HTTP connection manager. Arch performs + The decrypted data stream is de-framed by the HTTP/2 codec in Arch's HTTP connection manager. Arch performs intent matching via is **prompt-handler** subsystem using the name and description of the defined prompt targets, determining which endpoint should handle the prompt. @@ -162,7 +162,7 @@ Post-request processing Once a request completes, the stream is destroyed. The following also takes places: * The post-request :ref:`monitoring ` are updated (e.g. timing, active requests, upgrades, health checks). - Some statistics are updated earlier however, during request processing. Stats are batchedand written by the main + Some statistics are updated earlier however, during request processing. Stats are batched and written by the main thread periodically. * :ref:`Access logs ` are written to the access log * :ref:`Trace ` spans are finalized. If our example request was traced, a diff --git a/docs/source/concepts/tech_overview/terminology.rst b/docs/source/concepts/tech_overview/terminology.rst index dff32957..0184ed40 100644 --- a/docs/source/concepts/tech_overview/terminology.rst +++ b/docs/source/concepts/tech_overview/terminology.rst @@ -7,12 +7,12 @@ A few definitions before we dive into the main architecture documentation. Also to keep things consistent in logs and traces, and introduces and clarifies concepts are is relates to LLM applications. **Agent**: An application that uses LLMs to handle wide-ranging tasks from users via prompts. This could be as simple -as retrieving or summarizing data from an API, or being able to trigger compleix actions like adjusting ad campaigns, or +as retrieving or summarizing data from an API, or being able to trigger complex actions like adjusting ad campaigns, or changing travel plans via prompts. **Arch Config**: Arch operates based on a configuration that controls the behavior of a single instance of the Arch gateway. This where you enable capabilities like LLM routing, fast function calling (via prompt_targets), applying guardrails, and enabling critical -features like metrics and tracing. For the full configuration reference of `arch_config.yaml` see :ref:`here `. +features like metrics and tracing. For the full configuration reference of `arch_config.yaml` see :ref:`here `. **Downstream(Ingress)**: An downstream client (web application, etc.) connects to Arch, sends prompts, and receives responses. @@ -37,11 +37,11 @@ code to LLMs. undifferentiated work in building generative AI apps. Prompt targets are endpoints that receive prompts that are processed by Arch. For example, Arch enriches incoming prompts with metadata like knowing when a request is a follow-up or clarifying prompt so that you can build faster, more accurate retrieval (RAG) apps. To support agentic apps, like scheduling travel plans or sharing comments on a -document - via prompts, Arch uses its function calling abilities to extract critical information fromthe incoming prompt (or a set of +document - via prompts, Arch uses its function calling abilities to extract critical information from the incoming prompt (or a set of prompts) needed by a downstream backend API or function call before calling it directly. **Model Serving**: Arch is a set of `two` self-contained processes that are designed to run alongside your application servers -(or on a separate hostconnected via a network).The :ref:`model serving ` process helps Arch make intelligent decisions +(or on a separate host connected via a network).The :ref:`model serving ` process helps Arch make intelligent decisions about the incoming prompts. The model server is designed to call the (fast) purpose-built LLMs in Arch. **Error Target**: :ref:`Error targets ` are those endpoints that receive forwarded errors from Arch when issues arise, diff --git a/docs/source/get_started/intro_to_arch.rst b/docs/source/get_started/intro_to_arch.rst index 14a84bab..de00c974 100644 --- a/docs/source/get_started/intro_to_arch.rst +++ b/docs/source/get_started/intro_to_arch.rst @@ -13,7 +13,7 @@ Past the thrill of an AI demo, have you found yourself hitting these walls? You - You're **trapped in tedious prompting work** to clarify inputs and user intents? - You're **wasting cycles** choosing and integrating **code for observability** instead of it just happening transparently? -And you think to youself, can't I move faster by focusing on higher-level objectives in a language and framework agnostic way? Well, you can! +And you think to yourself, can't I move faster by focusing on higher-level objectives in a language and framework agnostic way? Well, you can! .. figure:: /_static/img/arch_network_diagram_high_level.png :width: 100% @@ -35,7 +35,7 @@ Arch takes a dependency on Envoy and is a self-contained process that is designe Arch uses Envoy's HTTP connection management subsystem, HTTP L7 filtering and telemetry capabilities to extend the functionality exclusively for prompts and LLMs. This gives Arch several advantages: -* Arch builds on Envoy's proven success. Envoy is used at masssive scale by the leading technology companies of our time including `AirBnB `_, `Dropbox `_, `Google `_, `Reddit `_, `Stripe `_, etc. Its battle tested and scales linearly with usage and enables developers to focus on what really matters: application features and business logic. +* Arch builds on Envoy's proven success. Envoy is used at massive scale by the leading technology companies of our time including `AirBnB `_, `Dropbox `_, `Google `_, `Reddit `_, `Stripe `_, etc. Its battle tested and scales linearly with usage and enables developers to focus on what really matters: application features and business logic. * Arch works with any application language. A single Arch deployment can act as gateway for AI applications written in Python, Java, C++, Go, Php, etc. @@ -54,7 +54,7 @@ These LLMs are designed to be best-in-class for critical prompt-related tasks li With prompt guardrails you can prevent ``jailbreak attempts`` present in user's prompts without having to write a single line of code. To learn more about how to configure guardrails available in Arch, read :ref:`Prompt Guard `. -**Traffic Management:** Arch offers several capabilities for LLM calls originating from your applications, including smart retries on errors from upstream LLMs, and automatic cutover to other LLMs configured in Arch for continuous availability and disaster recovery scenarios. +**Traffic Management:** Arch offers several capabilities for LLM calls originating from your applications, including smart retries on errors from upstream LLMs, and automatic cut-over to other LLMs configured in Arch for continuous availability and disaster recovery scenarios. Arch extends Envoy's `cluster subsystem `_ to manage upstream connections to LLMs so that you can build resilient AI applications. **Front/edge Gateway:** There is substantial benefit in using the same software at the edge (observability, traffic shaping algorithms, applying guardrails, etc.) as for outbound LLM inference use cases. diff --git a/docs/source/guides/agent_routing.rst b/docs/source/guides/agent_routing.rst index 418d674d..5effad69 100644 --- a/docs/source/guides/agent_routing.rst +++ b/docs/source/guides/agent_routing.rst @@ -81,7 +81,7 @@ the workflow, configuration, and implementation of Agent routing and hand off in return agent.handle(req) .. note:: - The above example demonstrates a simple implementation of Agent Routing and Hand Off using FastAPI. For the full implemenation of this example + The above example demonstrates a simple implementation of Agent Routing and Hand Off using FastAPI. For the full implementation of this example please see our `GitHub demo `_. Example Use Cases @@ -96,10 +96,10 @@ Best Practices and Tips ------------------------ When implementing Agent Routing and Hand Off in your applications, consider these best practices: -- Clearly Define Agent Responsibilities: Ensure each agent or human endpoint has a clear, specific description of the prompts they handle, reducing misrouting. -- Monitor and Optimize Routes: Regularly review how prompts are routed to adjust and optimize agent definitions and configurations. +- Clearly define agent responsibilities: Ensure each agent or human endpoint has a clear, specific description of the prompts they handle, reducing mis-routing. +- Monitor and optimize routes: Regularly review how prompts are routed to adjust and optimize agent definitions and configurations. .. note:: - To observe traffic to and from agents, please read more about :ref:`observabiliuty ` in Arch. + To observe traffic to and from agents, please read more about :ref:`observability ` in Arch. By carefully configuring and managing your Agent routing and hand off, you can significantly improve your application's responsiveness, performance, and overall user satisfaction. diff --git a/docs/source/resources/configuration_reference.rst b/docs/source/resources/configuration_reference.rst index ef7baceb..af60a642 100644 --- a/docs/source/resources/configuration_reference.rst +++ b/docs/source/resources/configuration_reference.rst @@ -1,9 +1,9 @@ -.. _configuration_refernce: +.. _configuration_reference: Configuration Reference ======================= -The following is a complete reference of the ``arch_conifg.yml`` that controls the behavior of a single instance of +The following is a complete reference of the ``arch_config.yml`` that controls the behavior of a single instance of the Arch gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets where prompts get routed to, apply guardrails, and enable critical agent observability features. diff --git a/docs/source/resources/includes/arch_config_full_reference.yaml b/docs/source/resources/includes/arch_config_full_reference.yaml index 90bbef56..5ef2639c 100644 --- a/docs/source/resources/includes/arch_config_full_reference.yaml +++ b/docs/source/resources/includes/arch_config_full_reference.yaml @@ -48,8 +48,8 @@ llm_providers: # provides a way to override default settings for the arch system overrides: - # By default Arch uses an NLI + embedding approach to match an incomming prompt to a prompt target. - # The intent matching threshold is kept at 0.80, you can overide this behavior if you would like + # By default Arch uses an NLI + embedding approach to match an incoming prompt to a prompt target. + # The intent matching threshold is kept at 0.80, you can override this behavior if you would like prompt_target_intent_matching_threshold: 0.60 # default system prompt used by all prompt targets From f31aa59facc3cdf128fd81e1f7d54d44cbf5ccb5 Mon Sep 17 00:00:00 2001 From: Salman Paracha Date: Sun, 13 Apr 2025 14:00:16 -0700 Subject: [PATCH 35/37] =?UTF-8?q?fixed=20issue=20with=20groq=20LLMs=20that?= =?UTF-8?q?=20require=20the=20openai=20in=20the=20/v1/chat/co=E2=80=A6=20(?= =?UTF-8?q?#460)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * fixed issue with groq LLMs that require the openai in the /v1/chat/completions path. My first change * updated the GH actions with keys for Groq * adding missing groq API keys * add llama-3.2-3b-preview to the model based on addin groq to the demo --------- Co-authored-by: Salman Paracha --- .github/workflows/e2e_archgw.yml | 2 ++ .github/workflows/e2e_test_demos.yml | 1 + .github/workflows/e2e_tests.yml | 1 + crates/common/src/consts.rs | 2 +- crates/llm_gateway/src/stream_context.rs | 21 +++++++++++++++++-- crates/prompt_gateway/src/http_context.rs | 2 +- .../weather_forecast/arch_config.yaml | 12 ++++------- .../weather_forecast/docker-compose.yaml | 2 ++ tests/e2e/test_prompt_gateway.py | 8 +++---- 9 files changed, 35 insertions(+), 16 deletions(-) diff --git a/.github/workflows/e2e_archgw.yml b/.github/workflows/e2e_archgw.yml index 84ccff68..fdc43726 100644 --- a/.github/workflows/e2e_archgw.yml +++ b/.github/workflows/e2e_archgw.yml @@ -30,6 +30,7 @@ jobs: env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }} + GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }} run: | docker compose up | tee &> archgw.logs & @@ -55,5 +56,6 @@ jobs: env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }} + GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }} run: | docker compose down diff --git a/.github/workflows/e2e_test_demos.yml b/.github/workflows/e2e_test_demos.yml index 9033ca29..d353fa46 100644 --- a/.github/workflows/e2e_test_demos.yml +++ b/.github/workflows/e2e_test_demos.yml @@ -48,6 +48,7 @@ jobs: env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }} + GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }} run: | source venv/bin/activate cd demos/shared/test_runner && sh run_demo_tests.sh diff --git a/.github/workflows/e2e_tests.yml b/.github/workflows/e2e_tests.yml index f894b713..576a7fc3 100644 --- a/.github/workflows/e2e_tests.yml +++ b/.github/workflows/e2e_tests.yml @@ -29,6 +29,7 @@ jobs: env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }} + GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }} run: | python -mvenv venv source venv/bin/activate && cd tests/e2e && bash run_e2e_tests.sh diff --git a/crates/common/src/consts.rs b/crates/common/src/consts.rs index cd52220e..523f5781 100644 --- a/crates/common/src/consts.rs +++ b/crates/common/src/consts.rs @@ -11,7 +11,7 @@ pub const MODEL_SERVER_NAME: &str = "model_server"; pub const ARCH_ROUTING_HEADER: &str = "x-arch-llm-provider"; pub const MESSAGES_KEY: &str = "messages"; pub const ARCH_PROVIDER_HINT_HEADER: &str = "x-arch-llm-provider-hint"; -pub const CHAT_COMPLETIONS_PATH: &str = "/v1/chat/completions"; +pub const CHAT_COMPLETIONS_PATH: [&str; 2] = ["/v1/chat/completions", "/openai/v1/chat/completions"]; pub const HEALTHZ_PATH: &str = "/healthz"; pub const ARCH_STATE_HEADER: &str = "x-arch-state"; pub const ARCH_FC_MODEL_NAME: &str = "Arch-Function-1.5B"; diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 78d7e21e..55ee53ce 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -89,6 +89,23 @@ impl StreamContext { provider_hint, )); + // Check if we need to modify the path based on the provider's base_url + let needs_openai_prefix = self + .llm_provider + .as_ref() + .and_then(|provider| provider.endpoint.as_ref()) + .map(|url| url.contains("api.groq.com")) + .unwrap_or(false); + + if needs_openai_prefix { + if let Some(path) = self.get_http_request_header(":path") { + if path.starts_with("/v1/") { + let new_path = format!("/openai{}", path); + self.set_http_request_header(":path", Some(new_path.as_str())); + } + } + } + debug!( "request received: llm provider hint: {}, selected llm: {}, model: {}", self.get_http_request_header(ARCH_PROVIDER_HINT_HEADER) @@ -237,8 +254,8 @@ impl HttpContext for StreamContext { self.delete_content_length_header(); self.save_ratelimit_header(); - self.is_chat_completions_request = - self.get_http_request_header(":path").unwrap_or_default() == CHAT_COMPLETIONS_PATH; + let request_path = self.get_http_request_header(":path").unwrap_or_default(); + self.is_chat_completions_request = CHAT_COMPLETIONS_PATH.contains(&request_path.as_str()); self.request_id = self.get_http_request_header(REQUEST_ID_HEADER); self.traceparent = self.get_http_request_header(TRACE_PARENT_HEADER); diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index 3a7dc7d9..6fc23921 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -61,7 +61,7 @@ impl HttpContext for StreamContext { return Action::Continue; } - self.is_chat_completions_request = request_path == CHAT_COMPLETIONS_PATH; + self.is_chat_completions_request = CHAT_COMPLETIONS_PATH.contains(&request_path.as_str()); debug!( "on_http_request_headers S[{}] req_headers={:?}", diff --git a/demos/samples_python/weather_forecast/arch_config.yaml b/demos/samples_python/weather_forecast/arch_config.yaml index 8b0f4ca0..db18eb85 100644 --- a/demos/samples_python/weather_forecast/arch_config.yaml +++ b/demos/samples_python/weather_forecast/arch_config.yaml @@ -17,17 +17,13 @@ overrides: prompt_target_intent_matching_threshold: 0.6 llm_providers: - - name: gpt-4o-mini - access_key: $OPENAI_API_KEY + - name: groq + access_key: $GROQ_API_KEY provider_interface: openai - model: gpt-4o-mini + model: llama-3.2-3b-preview + base_url: https://api.groq.com default: true - - name: gpt-3.5-turbo-0125 - access_key: $OPENAI_API_KEY - provider_interface: openai - model: gpt-3.5-turbo-0125 - - name: gpt-4o access_key: $OPENAI_API_KEY provider_interface: openai diff --git a/demos/samples_python/weather_forecast/docker-compose.yaml b/demos/samples_python/weather_forecast/docker-compose.yaml index 566dfa8d..abb69654 100644 --- a/demos/samples_python/weather_forecast/docker-compose.yaml +++ b/demos/samples_python/weather_forecast/docker-compose.yaml @@ -19,3 +19,5 @@ services: - CHAT_COMPLETION_ENDPOINT=http://host.docker.internal:10000/v1 extra_hosts: - "host.docker.internal:host-gateway" + volumes: + - ./arch_config.yaml:/app/arch_config.yaml diff --git a/tests/e2e/test_prompt_gateway.py b/tests/e2e/test_prompt_gateway.py index f122ad30..9b804bae 100644 --- a/tests/e2e/test_prompt_gateway.py +++ b/tests/e2e/test_prompt_gateway.py @@ -62,7 +62,7 @@ def test_prompt_gateway(stream): # third..end chunk is summarization (role = assistant) response_json = json.loads(chunks[2]) - assert response_json.get("model").startswith("gpt-4o-mini") + assert response_json.get("model").startswith("llama-3.2-3b-preview") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["delta"] @@ -71,7 +71,7 @@ def test_prompt_gateway(stream): else: response_json = response.json() - assert response_json.get("model").startswith("gpt-4o-mini") + assert response_json.get("model").startswith("llama-3.2-3b-preview") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["message"] @@ -231,7 +231,7 @@ def test_prompt_gateway_param_tool_call(stream): # third..end chunk is summarization (role = assistant) response_json = json.loads(chunks[2]) - assert response_json.get("model").startswith("gpt-4o-mini") + assert response_json.get("model").startswith("llama-3.2-3b-preview") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["delta"] @@ -240,7 +240,7 @@ def test_prompt_gateway_param_tool_call(stream): else: response_json = response.json() - assert response_json.get("model").startswith("gpt-4o-mini") + assert response_json.get("model").startswith("llama-3.2-3b-preview") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["message"] From 7d4b261a68a1ed2f3ec9de0d2105271f6b5203b6 Mon Sep 17 00:00:00 2001 From: Shuguang Chen <54548843+nehcgs@users.noreply.github.com> Date: Tue, 15 Apr 2025 14:39:12 -0700 Subject: [PATCH 36/37] Integrate Arch-Function-Chat (#449) --- crates/common/src/consts.rs | 7 +- crates/common/src/http.rs | 3 +- crates/common/src/ratelimit.rs | 4 +- crates/common/src/tokenizer.rs | 2 +- crates/llm_gateway/src/stream_context.rs | 2 +- crates/prompt_gateway/src/http_context.rs | 45 +- crates/prompt_gateway/src/stream_context.rs | 137 ++++- crates/prompt_gateway/tests/integration.rs | 32 +- .../weather_forecast/arch_config.yaml | 2 +- demos/samples_python/weather_forecast/main.py | 5 +- demos/shared/chatbot_ui/.vscode/launch.json | 4 +- demos/shared/chatbot_ui/common.py | 5 +- demos/shared/chatbot_ui/run_stream.py | 16 + demos/use_cases/llm_routing/arch_config.yaml | 6 + model_server/src/commons/globals.py | 10 +- model_server/src/core/function_calling.py | 519 +++++++----------- .../src/core/utils/hallucination_utils.py | 47 +- model_server/src/core/utils/model_utils.py | 33 +- model_server/src/main.py | 93 ++-- .../tests/core/test_function_calling.py | 82 +-- model_server/tests/core/test_state.py | 40 +- tests/archgw/common.py | 13 +- tests/e2e/test_prompt_gateway.py | 44 +- tests/modelserver/test_hallucination.py | 3 + tests/modelserver/test_modelserver.py | 3 + tests/rest/api_prompt_gateway.rest | 4 +- 26 files changed, 558 insertions(+), 603 deletions(-) diff --git a/crates/common/src/consts.rs b/crates/common/src/consts.rs index 523f5781..e58bebde 100644 --- a/crates/common/src/consts.rs +++ b/crates/common/src/consts.rs @@ -13,8 +13,11 @@ pub const MESSAGES_KEY: &str = "messages"; pub const ARCH_PROVIDER_HINT_HEADER: &str = "x-arch-llm-provider-hint"; pub const CHAT_COMPLETIONS_PATH: [&str; 2] = ["/v1/chat/completions", "/openai/v1/chat/completions"]; pub const HEALTHZ_PATH: &str = "/healthz"; -pub const ARCH_STATE_HEADER: &str = "x-arch-state"; -pub const ARCH_FC_MODEL_NAME: &str = "Arch-Function-1.5B"; +pub const X_ARCH_STATE_HEADER: &str = "x-arch-state"; +pub const X_ARCH_API_RESPONSE: &str = "x-arch-api-response-message"; +pub const X_ARCH_TOOL_CALL: &str = "x-arch-tool-call-message"; +pub const X_ARCH_FC_MODEL_RESPONSE: &str = "x-arch-fc-model-response"; +pub const ARCH_FC_MODEL_NAME: &str = "Arch-Function"; pub const REQUEST_ID_HEADER: &str = "x-request-id"; pub const TRACE_PARENT_HEADER: &str = "traceparent"; pub const ARCH_INTERNAL_CLUSTER_NAME: &str = "arch_internal"; diff --git a/crates/common/src/http.rs b/crates/common/src/http.rs index 8ef176b2..e3120fc4 100644 --- a/crates/common/src/http.rs +++ b/crates/common/src/http.rs @@ -50,8 +50,7 @@ pub trait Client: Context { ) -> Result { debug!( "dispatching http call with args={:?} context={:?}", - call_args, - call_context + call_args, call_context ); match self.dispatch_http_call( diff --git a/crates/common/src/ratelimit.rs b/crates/common/src/ratelimit.rs index ef4e5d08..66c3facd 100644 --- a/crates/common/src/ratelimit.rs +++ b/crates/common/src/ratelimit.rs @@ -101,9 +101,7 @@ impl RatelimitMap { ) -> Result<(), Error> { debug!( "Checking limit for provider={}, with selector={:?}, consuming tokens={:?}", - provider, - selector, - tokens_used + provider, selector, tokens_used ); let provider_limits = match self.datastore.get(&provider) { diff --git a/crates/common/src/tokenizer.rs b/crates/common/src/tokenizer.rs index e9431521..11ce7295 100644 --- a/crates/common/src/tokenizer.rs +++ b/crates/common/src/tokenizer.rs @@ -1,4 +1,4 @@ -use log::{debug}; +use log::debug; #[allow(dead_code)] pub fn token_count(model_name: &str, text: &str) -> Result { diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 55ee53ce..5b741a43 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -428,7 +428,7 @@ impl HttpContext for StreamContext { ); if self.request_body_sent_time.is_none() { - debug!("on_http_response_body: request body not sent, no doing any processing in llm filter"); + debug!("on_http_response_body: request body not sent, not doing any processing in llm filter"); return Action::Continue; } diff --git a/crates/prompt_gateway/src/http_context.rs b/crates/prompt_gateway/src/http_context.rs index 6fc23921..c0e8df94 100644 --- a/crates/prompt_gateway/src/http_context.rs +++ b/crates/prompt_gateway/src/http_context.rs @@ -4,10 +4,11 @@ use common::{ self, ArchState, ChatCompletionStreamResponse, ChatCompletionTool, ChatCompletionsRequest, }, consts::{ - ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_ROUTING_HEADER, ARCH_STATE_HEADER, + ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_ROUTING_HEADER, ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, CHAT_COMPLETIONS_PATH, HEALTHZ_PATH, MODEL_SERVER_NAME, MODEL_SERVER_REQUEST_TIMEOUT_MS, REQUEST_ID_HEADER, TOOL_ROLE, - TRACE_PARENT_HEADER, USER_ROLE, + TRACE_PARENT_HEADER, USER_ROLE, X_ARCH_API_RESPONSE, X_ARCH_FC_MODEL_RESPONSE, + X_ARCH_STATE_HEADER, X_ARCH_TOOL_CALL, }, errors::ServerError, http::{CallArgs, Client}, @@ -125,8 +126,8 @@ impl HttpContext for StreamContext { self.arch_state = match deserialized_body.metadata { Some(ref metadata) => { - if metadata.contains_key(ARCH_STATE_HEADER) { - let arch_state_str = metadata[ARCH_STATE_HEADER].clone(); + if metadata.contains_key(X_ARCH_STATE_HEADER) { + let arch_state_str = metadata[X_ARCH_STATE_HEADER].clone(); let arch_state: Vec = serde_json::from_str(&arch_state_str).unwrap(); Some(arch_state) } else { @@ -336,10 +337,10 @@ impl HttpContext for StreamContext { if self.tool_calls.is_some() && !self.tool_calls.as_ref().unwrap().is_empty() { let chunks = vec![ ChatCompletionStreamResponse::new( - None, + self.arch_fc_response.clone(), Some(ASSISTANT_ROLE.to_string()), Some(ARCH_FC_MODEL_NAME.to_string()), - self.tool_calls.to_owned(), + None, ), ChatCompletionStreamResponse::new( self.tool_call_response.clone(), @@ -381,17 +382,39 @@ impl HttpContext for StreamContext { *metadata = Value::Object(serde_json::Map::new()); } - let fc_messages = vec![ - self.generate_toll_call_message(), - self.generate_api_response_message(), - ]; + let tool_call_message = self.generate_tool_call_message(); + let tool_call_message_str = serde_json::to_string(&tool_call_message).unwrap(); + metadata.as_object_mut().unwrap().insert( + X_ARCH_TOOL_CALL.to_string(), + serde_json::Value::String(tool_call_message_str), + ); + + let api_response_message = self.generate_api_response_message(); + let api_response_message_str = + serde_json::to_string(&api_response_message).unwrap(); + metadata.as_object_mut().unwrap().insert( + X_ARCH_API_RESPONSE.to_string(), + serde_json::Value::String(api_response_message_str), + ); + + let fc_messages = vec![tool_call_message, api_response_message]; + let fc_messages_str = serde_json::to_string(&fc_messages).unwrap(); let arch_state = HashMap::from([("messages".to_string(), fc_messages_str)]); let arch_state_str = serde_json::to_string(&arch_state).unwrap(); metadata.as_object_mut().unwrap().insert( - ARCH_STATE_HEADER.to_string(), + X_ARCH_STATE_HEADER.to_string(), serde_json::Value::String(arch_state_str), ); + + if let Some(arch_fc_response) = self.arch_fc_response.as_ref() { + metadata.as_object_mut().unwrap().insert( + X_ARCH_FC_MODEL_RESPONSE.to_string(), + serde_json::Value::String( + serde_json::to_string(arch_fc_response).unwrap(), + ), + ); + } let data_serialized = serde_json::to_string(&data).unwrap(); info!("archgw <= developer: {}", data_serialized); self.set_http_response_body(0, body_size, data_serialized.as_bytes()); diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index ec68c104..1cd2fa86 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -9,6 +9,7 @@ use common::consts::{ API_REQUEST_TIMEOUT_MS, ARCH_FC_MODEL_NAME, ARCH_INTERNAL_CLUSTER_NAME, ARCH_UPSTREAM_HOST_HEADER, ASSISTANT_ROLE, DEFAULT_TARGET_REQUEST_TIMEOUT_MS, MESSAGES_KEY, REQUEST_ID_HEADER, SYSTEM_ROLE, TOOL_ROLE, TRACE_PARENT_HEADER, USER_ROLE, + X_ARCH_FC_MODEL_RESPONSE, }; use common::errors::ServerError; use common::http::{CallArgs, Client}; @@ -64,10 +65,10 @@ pub struct StreamContext { pub time_to_first_token: Option, pub traceparent: Option, pub _tracing: Rc>, + pub arch_fc_response: Option, } impl StreamContext { - #[allow(clippy::too_many_arguments)] pub fn new( context_id: u32, metrics: Rc, @@ -98,6 +99,7 @@ impl StreamContext { _tracing: tracing, start_upstream_llm_request_time: 0, time_to_first_token: None, + arch_fc_response: None, } } @@ -142,15 +144,16 @@ impl StreamContext { } }; - // intent was matched if we see function_latency in metadata - let intent_matched = model_server_response + let intent_matched = check_intent_matched(&model_server_response); + info!("intent matched: {}", intent_matched); + + self.arch_fc_response = model_server_response .metadata .as_ref() - .and_then(|metadata| metadata.get("function_latency")) - .is_some(); + .and_then(|metadata| metadata.get(X_ARCH_FC_MODEL_RESPONSE)) + .cloned(); if !intent_matched { - info!("intent not matched"); // check if we have a default prompt target if let Some(default_prompt_target) = self .prompt_targets @@ -278,9 +281,9 @@ impl StreamContext { let direct_response_str = if self.streaming_response { let chunks = vec![ ChatCompletionStreamResponse::new( - None, + self.arch_fc_response.clone(), Some(ASSISTANT_ROLE.to_string()), - Some(ARCH_FC_MODEL_NAME.to_owned()), + Some(ARCH_FC_MODEL_NAME.to_string()), None, ), ChatCompletionStreamResponse::new( @@ -293,7 +296,7 @@ impl StreamContext { .clone(), ), None, - Some(ARCH_FC_MODEL_NAME.to_owned()), + Some(format!("{}-Chat", ARCH_FC_MODEL_NAME.to_owned())), None, ), ]; @@ -623,13 +626,24 @@ impl StreamContext { messages } - pub fn generate_toll_call_message(&mut self) -> Message { - Message { - role: ASSISTANT_ROLE.to_string(), - content: None, - model: Some(ARCH_FC_MODEL_NAME.to_string()), - tool_calls: self.tool_calls.clone(), - tool_call_id: None, + pub fn generate_tool_call_message(&mut self) -> Message { + if self.arch_fc_response.is_none() { + info!("arch_fc_response is none, generating tool call message"); + Message { + role: ASSISTANT_ROLE.to_string(), + content: None, + model: Some(ARCH_FC_MODEL_NAME.to_string()), + tool_calls: self.tool_calls.clone(), + tool_call_id: None, + } + } else { + Message { + role: ASSISTANT_ROLE.to_string(), + content: self.arch_fc_response.as_ref().cloned(), + model: Some(ARCH_FC_MODEL_NAME.to_string()), + tool_calls: None, + tool_call_id: None, + } } } @@ -761,6 +775,23 @@ impl StreamContext { } } +fn check_intent_matched(model_server_response: &ChatCompletionsResponse) -> bool { + let content = model_server_response + .choices.first() + .and_then(|choice| choice.message.content.as_ref()); + + let content_has_value = content.is_some() && !content.unwrap().is_empty(); + + let tool_calls = model_server_response + .choices.first() + .and_then(|choice| choice.message.tool_calls.as_ref()); + + // intent was matched if content has some value or tool_calls is empty + + + content_has_value || (tool_calls.is_some() && !tool_calls.unwrap().is_empty()) +} + impl Client for StreamContext { type CallContext = StreamCallContext; @@ -772,3 +803,77 @@ impl Client for StreamContext { &self.metrics.active_http_calls } } + +#[cfg(test)] +mod test { + use common::api::open_ai::{ChatCompletionsResponse, Choice, Message, ToolCall}; + + use crate::stream_context::check_intent_matched; + + #[test] + fn test_intent_matched() { + let model_server_response = ChatCompletionsResponse { + choices: vec![Choice { + message: Message { + content: Some("".to_string()), + tool_calls: Some(vec![]), + role: "assistant".to_string(), + model: None, + tool_call_id: None, + }, + finish_reason: None, + index: None, + }], + usage: None, + model: "arch-fc".to_string(), + metadata: None, + }; + + assert!(!check_intent_matched(&model_server_response)); + + let model_server_response = ChatCompletionsResponse { + choices: vec![Choice { + message: Message { + content: Some("hello".to_string()), + tool_calls: Some(vec![]), + role: "assistant".to_string(), + model: None, + tool_call_id: None, + }, + finish_reason: None, + index: None, + }], + usage: None, + model: "arch-fc".to_string(), + metadata: None, + }; + + assert!(check_intent_matched(&model_server_response)); + + let model_server_response = ChatCompletionsResponse { + choices: vec![Choice { + message: Message { + content: Some("".to_string()), + tool_calls: Some(vec![ToolCall { + id: "1".to_string(), + function: common::api::open_ai::FunctionCallDetail { + name: "test".to_string(), + arguments: None, + }, + tool_type: common::api::open_ai::ToolType::Function, + }]), + role: "assistant".to_string(), + model: None, + tool_call_id: None, + }, + finish_reason: None, + index: None, + }], + usage: None, + model: "arch-fc".to_string(), + metadata: None, + }; + + assert!(check_intent_matched(&model_server_response)); + } +} diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index bbde10b0..91b36c01 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -380,6 +380,7 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_log(Some(LogLevel::Warn), None) .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) @@ -453,6 +454,7 @@ fn prompt_gateway_request_to_llm_gateway() { .expect_log(Some(LogLevel::Info), None) .expect_set_buffer_bytes(Some(BufferType::HttpResponseBody), None) .expect_log(Some(LogLevel::Info), None) + .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) .execute_and_expect(ReturnType::Action(Action::Continue)) .unwrap(); @@ -493,19 +495,9 @@ fn prompt_gateway_request_no_intent_match() { finish_reason: Some("test".to_string()), index: Some(0), message: Message { - role: "system".to_string(), + role: "assistant".to_string(), content: None, - tool_calls: Some(vec![ToolCall { - id: String::from("test"), - tool_type: ToolType::Function, - function: FunctionCallDetail { - name: String::from("weather_forecast"), - arguments: Some(HashMap::from([( - String::from("city"), - Value::String(String::from("seattle")), - )])), - }, - }]), + tool_calls: None, model: None, tool_call_id: None, }, @@ -523,7 +515,7 @@ fn prompt_gateway_request_no_intent_match() { .expect_log(Some(LogLevel::Warn), None) .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Info), Some("intent not matched")) + .expect_log(Some(LogLevel::Info), Some("intent matched: false")) .expect_log( Some(LogLevel::Info), Some("no default prompt target found, forwarding request to upstream llm"), @@ -651,17 +643,7 @@ fn prompt_gateway_request_no_intent_match_default_target() { message: Message { role: "system".to_string(), content: None, - tool_calls: Some(vec![ToolCall { - id: String::from("test"), - tool_type: ToolType::Function, - function: FunctionCallDetail { - name: String::from("weather_forecast"), - arguments: Some(HashMap::from([( - String::from("city"), - Value::String(String::from("seattle")), - )])), - }, - }]), + tool_calls: None, model: None, tool_call_id: None, }, @@ -679,7 +661,7 @@ fn prompt_gateway_request_no_intent_match_default_target() { .expect_log(Some(LogLevel::Warn), None) .expect_log(Some(LogLevel::Info), None) .expect_log(Some(LogLevel::Debug), None) - .expect_log(Some(LogLevel::Info), Some("intent not matched")) + .expect_log(Some(LogLevel::Info), Some("intent matched: false")) .expect_log( Some(LogLevel::Info), Some("default prompt target found, forwarding request to default prompt target"), diff --git a/demos/samples_python/weather_forecast/arch_config.yaml b/demos/samples_python/weather_forecast/arch_config.yaml index db18eb85..b6463594 100644 --- a/demos/samples_python/weather_forecast/arch_config.yaml +++ b/demos/samples_python/weather_forecast/arch_config.yaml @@ -22,12 +22,12 @@ llm_providers: provider_interface: openai model: llama-3.2-3b-preview base_url: https://api.groq.com - default: true - name: gpt-4o access_key: $OPENAI_API_KEY provider_interface: openai model: gpt-4o + default: true system_prompt: | You are a helpful assistant. diff --git a/demos/samples_python/weather_forecast/main.py b/demos/samples_python/weather_forecast/main.py index 3be2f4da..84ee75e6 100644 --- a/demos/samples_python/weather_forecast/main.py +++ b/demos/samples_python/weather_forecast/main.py @@ -73,7 +73,7 @@ async def weather(req: WeatherRequest, res: Response): class DefaultTargetRequest(BaseModel): - messages: list + messages: list = [] @app.post("/default_target") @@ -86,12 +86,9 @@ async def default_target(req: DefaultTargetRequest, res: Response): "role": "assistant", "content": "I can help you with weather forecast", }, - "finish_reason": "completed", - "index": 0, } ], "model": "api_server", - "usage": {"completion_tokens": 0}, } logger.info(f"sending response: {json.dumps(resp)}") return resp diff --git a/demos/shared/chatbot_ui/.vscode/launch.json b/demos/shared/chatbot_ui/.vscode/launch.json index e7f91d36..6a470b7b 100644 --- a/demos/shared/chatbot_ui/.vscode/launch.json +++ b/demos/shared/chatbot_ui/.vscode/launch.json @@ -15,7 +15,7 @@ "LLM": "1", "CHAT_COMPLETION_ENDPOINT": "http://localhost:10000/v1", "STREAMING": "True", - "ARCH_CONFIG": "../../weather_forecast/arch_config.yaml" + "ARCH_CONFIG": "../../samples_python/weather_forecast/arch_config.yaml" } }, { @@ -29,7 +29,7 @@ "LLM": "1", "CHAT_COMPLETION_ENDPOINT": "http://localhost:12000/v1", "STREAMING": "True", - "ARCH_CONFIG": "../../llm_routing/arch_config.yaml" + "ARCH_CONFIG": "../../samples_python/weather_forecast/arch_config.yaml" } }, ] diff --git a/demos/shared/chatbot_ui/common.py b/demos/shared/chatbot_ui/common.py index 42e50bd4..1de8f94c 100644 --- a/demos/shared/chatbot_ui/common.py +++ b/demos/shared/chatbot_ui/common.py @@ -120,8 +120,11 @@ def process_stream_chunk(chunk, history): if delta.content: # append content to the last history item - history[-1]["content"] = history[-1].get("content", "") + delta.content + if history[-1]["model"] != "Arch-Function-Chat": + history[-1]["content"] = history[-1].get("content", "") + delta.content # yield content if it is from assistant + if history[-1]["model"] == "Arch-Function": + return None if history[-1]["role"] == "assistant": return delta.content diff --git a/demos/shared/chatbot_ui/run_stream.py b/demos/shared/chatbot_ui/run_stream.py index b406e147..89448355 100644 --- a/demos/shared/chatbot_ui/run_stream.py +++ b/demos/shared/chatbot_ui/run_stream.py @@ -88,6 +88,22 @@ def chat( yield "", conversation, history, debug_output, model_selector + # update assistant response to have correct format + # arch-fc 1.1 expects following format: + # { + # "response": "", + # } + # and this entire block needs to be encoded in ```json\n{json_encoded_content}\n``` + + if not history[-1]["model"].startswith("Arch"): + assistant_response = { + "response": history[-1]["content"], + } + history[-1]["content"] = "```json\n{}\n```".format( + json.dumps(assistant_response) + ) + log.info("history: {}".format(json.dumps(history))) + def main(): with gr.Blocks( diff --git a/demos/use_cases/llm_routing/arch_config.yaml b/demos/use_cases/llm_routing/arch_config.yaml index 289d8bf2..11087d3a 100644 --- a/demos/use_cases/llm_routing/arch_config.yaml +++ b/demos/use_cases/llm_routing/arch_config.yaml @@ -30,5 +30,11 @@ llm_providers: model: deepseek-reasoner base_url: https://api.deepseek.com/ + - name: groq + access_key: $GROQ_API_KEY + provider_interface: openai + model: llama-3.1-8b-instant + base_url: https://api.groq.com + tracing: random_sampling: 100 diff --git a/model_server/src/commons/globals.py b/model_server/src/commons/globals.py index 49dce5e7..a39be7c3 100644 --- a/model_server/src/commons/globals.py +++ b/model_server/src/commons/globals.py @@ -5,8 +5,6 @@ from src.core.guardrails import get_guardrail_handler from src.core.function_calling import ( ArchAgentConfig, ArchAgentHandler, - ArchIntentConfig, - ArchIntentHandler, ArchFunctionConfig, ArchFunctionHandler, ) @@ -17,7 +15,10 @@ logger = get_model_server_logger() # Define the client -ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "https://archfc.katanemo.dev/v1") +# ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "https://archfc.katanemo.dev/v1") +# use temporary endpoint until we deprecate archfc-v1.0 from archfc.katanemo.dev +# and officially release archfc-v1.1 on archfc.katanemo.dev +ARCH_ENDPOINT = os.getenv("ARCH_ENDPOINT", "http://34.72.123.163:8000/v1") ARCH_API_KEY = "EMPTY" ARCH_CLIENT = OpenAI(base_url=ARCH_ENDPOINT, api_key=ARCH_API_KEY) ARCH_AGENT_CLIENT = ARCH_CLIENT @@ -30,9 +31,6 @@ ARCH_GUARD_MODEL_ALIAS = "katanemo/Arch-Guard" # Define model handlers handler_map = { - "Arch-Intent": ArchIntentHandler( - ARCH_CLIENT, ARCH_INTENT_MODEL_ALIAS, ArchIntentConfig - ), "Arch-Function": ArchFunctionHandler( ARCH_CLIENT, ARCH_FUNCTION_MODEL_ALIAS, ArchFunctionConfig ), diff --git a/model_server/src/core/function_calling.py b/model_server/src/core/function_calling.py index 8c01493a..bec5dfdf 100644 --- a/model_server/src/core/function_calling.py +++ b/model_server/src/core/function_calling.py @@ -3,7 +3,6 @@ import copy import json import random import builtins -import textwrap import src.commons.utils as utils from openai import OpenAI @@ -22,179 +21,25 @@ from src.core.utils.model_utils import ( logger = utils.get_model_server_logger() -class ArchIntentConfig: - TASK_PROMPT = textwrap.dedent( - """ - You are a helpful assistant. - """ - ).strip() - - TOOL_PROMPT_TEMPLATE = textwrap.dedent( - """ - You task is to check if there are any tools that can be used to help the last user message in conversations according to the available tools listed below. - - - {tool_text} - - """ - ).strip() - - FORMAT_PROMPT = textwrap.dedent( - """ - Provide your tool assessment for ONLY THE LAST USER MESSAGE in the above conversation: - - First line must read 'Yes' or 'No'. - - If yes, a second line must include a comma-separated list of tool indexes. - """ - ).strip() - - EXTRA_INSTRUCTION = "Are there any tools can help?" - - GENERATION_PARAMS = { - "temperature": 0.01, - "max_tokens": 1, - "stop_token_ids": [151645], - } - - -class ArchIntentHandler(ArchBaseHandler): - def __init__(self, client: OpenAI, model_name: str, config: ArchIntentConfig): - """ - Initializes the intent handler. - - Args: - client (OpenAI): An OpenAI client instance. - model_name (str): Name of the model to use. - config (ArchIntentConfig): The configuration for Arch-Intent. - """ - - super().__init__( - client, - model_name, - config.TASK_PROMPT, - config.TOOL_PROMPT_TEMPLATE, - config.FORMAT_PROMPT, - config.GENERATION_PARAMS, - ) - - self.extra_instruction = config.EXTRA_INSTRUCTION - - @override - def _convert_tools(self, tools: List[Dict[str, Any]]) -> str: - """ - Converts a list of tools into a JSON-like format with indexed keys. - - Args: - tools (List[Dict[str, Any]]): A list of tools represented as dictionaries. - - Returns: - str: A string representation of converted tools. - """ - - converted = [ - json.dumps({"index": f"T{idx}"} | tool) for idx, tool in enumerate(tools) - ] - return "\n".join(converted) - - def detect_intent(self, content: str) -> bool: - """ - Detect if any intent match with prompts - - Args: - content: str: Model response that contains intent detection results - - Returns: - bool: A boolean value to indicate if any intent match with prompts or not - """ - if hasattr(content.choices[0].message, "content"): - return content.choices[0].message.content == "Yes" - else: - return False - - @override - async def chat_completion(self, req: ChatMessage) -> ChatCompletionResponse: - """ - Generates a chat completion for a given request. - - Args: - req (ChatMessage): A chat message request object. - - Returns: - ChatCompletionResponse: The model's response to the chat request. - - Note: - Currently only support vllm inference - """ - logger.info("[Arch-Intent] - ChatCompletion") - - # In the case that no tools are available, simply return `No` to avoid making a call - if len(req.tools) == 0: - model_response = Message(content="No", tool_calls=[]) - logger.info("No tools found, return `No` as the model response.") - else: - messages = self._process_messages( - req.messages, req.tools, self.extra_instruction - ) - - logger.info(f"[request to arch-fc (intent)]: {json.dumps(messages)}") - - model_response = self.client.chat.completions.create( - messages=messages, - model=self.model_name, - stream=False, - extra_body=self.generation_params, - ) - - logger.info(f"[response]: {json.dumps(model_response.model_dump())}") - - model_response = Message( - content=model_response.choices[0].message.content, tool_calls=[] - ) - - chat_completion_response = ChatCompletionResponse( - choices=[Choice(message=model_response)], model=self.model_name - ) - - return chat_completion_response - - -# ============================================================================================================= +# ============================================================================================================================================== class ArchFunctionConfig: - TASK_PROMPT = textwrap.dedent( - """ - You are a helpful assistant. + TASK_PROMPT = ( + "You are a helpful assistant designed to assist with the user query by making one or more function calls if needed." + "\n\nYou are provided with function signatures within XML tags:\n\n{tools}\n" + "\n\nYour task is to decide which functions are needed and collect missing parameters if necessary." + ) - Today's date: {} - """.format( - utils.get_today_date() - ) - ).strip() - - TOOL_PROMPT_TEMPLATE = textwrap.dedent( - """ - # Tools - - You may call one or more functions to assist with the user query. - - You are provided with function signatures within XML tags: - - {tool_text} - - """ - ).strip() - - FORMAT_PROMPT = textwrap.dedent( - """ - For each function call, return a json object with function name and arguments within XML tags: - - {"name": , "arguments": } - - """ - ).strip() + FORMAT_PROMPT = ( + "\n\nBased on your analysis, provide your response in one of the following JSON formats:" + '\n1. If no functions are needed:\n```json\n{"response": "Your response text here"}\n```' + '\n2. If functions are needed but some required parameters are missing:\n```json\n{"required_functions": ["func_name1", "func_name2", ...], "clarification": "Text asking for missing parameters"}\n```' + '\n3. If functions are needed and all required parameters are available:\n```json\n{"tool_calls": [{"name": "func_name1", "arguments": {"argument1": "value1", "argument2": "value2"}},... (more tool calls as required)]}\n```' + ) GENERATION_PARAMS = { - "temperature": 0.6, + "temperature": 0.1, "top_p": 1.0, "top_k": 10, "max_tokens": 1024, @@ -203,34 +48,9 @@ class ArchFunctionConfig: "top_logprobs": 10, } - PREFILL_CONFIG = { - "prefill_params": { - "continue_final_message": True, - "add_generation_prompt": False, - }, - "prefill_prefix": [ - "May", - "Could", - "Sure", - "Definitely", - "Certainly", - "Of course", - "Can", - ], - } - SUPPORT_DATA_TYPES = ["int", "float", "bool", "str", "list", "tuple", "set", "dict"] -class ArchAgentConfig(ArchFunctionConfig): - GENERATION_PARAMS = { - "temperature": 0.01, - "stop_token_ids": [151645], - "logprobs": True, - "top_logprobs": 10, - } - - class ArchFunctionHandler(ArchBaseHandler): def __init__( self, @@ -251,13 +71,17 @@ class ArchFunctionHandler(ArchBaseHandler): client, model_name, config.TASK_PROMPT, - config.TOOL_PROMPT_TEMPLATE, config.FORMAT_PROMPT, config.GENERATION_PARAMS, ) - self.prefill_params = config.PREFILL_CONFIG["prefill_params"] - self.prefill_prefix = config.PREFILL_CONFIG["prefill_prefix"] + self.generation_params = self.generation_params | { + "continue_final_message": True, + "add_generation_prompt": False, + } + + self.default_prefix = '```json\n{"' + self.clarify_prefix = '```json\n{"required_functions":' self.hallucination_state = None @@ -280,7 +104,7 @@ class ArchFunctionHandler(ArchBaseHandler): str: A string representation of converted tools. """ - converted = [json.dumps(tool) for tool in tools] + converted = [json.dumps(tool["function"], ensure_ascii=False) for tool in tools] return "\n".join(converted) def _fix_json_string(self, json_str: str) -> str: @@ -328,10 +152,14 @@ class ArchFunctionHandler(ArchBaseHandler): unmatched_opening = stack.pop() fixed_str += opening_bracket[unmatched_opening] - # Attempt to parse the corrected string to ensure it’s valid JSON - return fixed_str.replace("'", '"') + try: + fixed_str = json.loads(fixed_str) + except Exception: + fixed_str = json.loads(fixed_str.replace("'", '"')) - def _extract_tool_calls(self, content: str) -> Dict[str, any]: + return json.dumps(fixed_str) + + def _parse_model_response(self, content: str) -> Dict[str, any]: """ Extracts tool call information from a given string. @@ -340,49 +168,55 @@ class ArchFunctionHandler(ArchBaseHandler): Returns: Dict: A dictionary of extraction, including: - - "result": A list of tool call dictionaries. - - "status": A boolean indicating if the extraction was valid. - - "message": An error message or exception if extraction failed. + - "required_functions": A list of detected intents. + - "clarification": Text to collect missing parameters + - "tool_calls": A list of tool call dictionaries. + - "is_valid": A boolean indicating if the extraction was valid. + - "error_message": An error message or exception if parsing failed. """ - tool_calls, is_valid, error_message = [], True, "" + response_dict = { + "raw_response": [], + "response": [], + "required_functions": [], + "clarification": "", + "tool_calls": [], + "is_valid": True, + "error_message": "", + } - flag = False - for line in content.split("\n"): - if not is_valid: - break + try: + if content.startswith("```") and content.endswith("```"): + content = content.strip("```").strip() + if content.startswith("json"): + content = content[4:].strip() - if "" == line: - flag = True - elif "" == line: - flag = False - else: - if flag: - try: - tool_content = json.loads(line) - except Exception as e: - fixed_content = self._fix_json_string(line) - try: - tool_content = json.loads(fixed_content) - except Exception: - is_valid, error_message = False, e - break + content = self._fix_json_string(content) + response_dict["raw_response"] = f"```json\n{content}\n```" - tool = { + model_response = json.loads(content) + response_dict["response"] = model_response.get("response", "") + response_dict["required_functions"] = model_response.get( + "required_functions", [] + ) + response_dict["clarification"] = model_response.get("clarification", "") + + for tool_call in model_response.get("tool_calls", []): + response_dict["tool_calls"].append( + { "id": f"call_{random.randint(1000, 10000)}", "type": "function", "function": { - "name": tool_content["name"], + "name": tool_call.get("name", ""), + "arguments": tool_call.get("arguments", {}), }, } - if "arguments" in tool_content: - tool["function"]["arguments"] = tool_content["arguments"] + ) + except Exception as e: + response_dict["is_valid"] = False + response_dict["error_message"] = f"Fail to parse model responses: {e}" - tool_calls.append(tool) - - flag = False - - return {"result": tool_calls, "status": is_valid, "message": error_message} + return response_dict def _convert_data_type(self, value: str, target_type: str): # TODO: Add more conversion rules as needed @@ -414,36 +248,37 @@ class ArchFunctionHandler(ArchBaseHandler): - "message": An error message. """ - is_valid, invalid_tool_call, error_message = True, None, "" + verification_dict = { + "is_valid": True, + "invalid_tool_call": {}, + "error_message": "", + } functions = {} for tool in tools: - if tool["type"] == "function": - functions[tool["function"]["name"]] = tool["function"]["parameters"] + functions[tool["function"]["name"]] = tool["function"]["parameters"] for tool_call in tool_calls: - if not is_valid: + if not verification_dict["is_valid"]: break func_name = tool_call["function"]["name"] - func_args = tool_call["function"].get("arguments") - if not func_args: - func_args = {} + func_args = tool_call["function"]["arguments"] # Check whether the function is available or not if func_name not in functions: - is_valid = False - invalid_tool_call = tool_call - error_message = f"{func_name} is not defined!" - break - + verification_dict["is_valid"] = False + verification_dict["invalid_tool_call"] = tool_call + verification_dict["error_message"] = f"{func_name} is not available!" else: # Check if all the requried parameters can be found in the tool calls for required_param in functions[func_name].get("required", []): if required_param not in func_args: - is_valid = False - invalid_tool_call = tool_call - error_message = f"`{required_param}` is required by the function `{func_name}` but not found in the tool call!" + verification_dict["is_valid"] = False + verification_dict["invalid_tool_call"] = tool_call + verification_dict[ + "error_message" + ] = f"`{required_param}` is required by the function `{func_name}` but not found in the tool call!" break # Verify the data type of each parameter in the tool calls @@ -453,9 +288,11 @@ class ArchFunctionHandler(ArchBaseHandler): logger.info(func_args) for param_name in func_args: if param_name not in function_properties: - is_valid = False - invalid_tool_call = tool_call - error_message = f"Parameter `{param_name}` is not defined in the function `{func_name}`." + verification_dict["is_valid"] = False + verification_dict["invalid_tool_call"] = tool_call + verification_dict[ + "error_message" + ] = f"Parameter `{param_name}` is not defined in the function `{func_name}`." break else: param_value = func_args[param_name] @@ -469,22 +306,22 @@ class ArchFunctionHandler(ArchBaseHandler): param_value, data_type ) if not isinstance(param_value, data_type): - is_valid = False - invalid_tool_call = tool_call - error_message = f"Parameter `{param_name}` is expected to have the data type `{data_type}`, got `{type(param_value)}`." + verification_dict["is_valid"] = False + verification_dict["invalid_tool_call"] = tool_call + verification_dict[ + "error_message" + ] = f"Parameter `{param_name}` is expected to have the data type `{data_type}`, got `{type(param_value)}`." break else: - error_message = ( - f"Data type `{target_type}` is not supported." - ) + verification_dict["is_valid"] = False + verification_dict["invalid_tool_call"] = tool_call + verification_dict[ + "error_message" + ] = f"Data type `{target_type}` is not supported." - return { - "status": is_valid, - "invalid_tool_call": invalid_tool_call, - "message": error_message, - } + return verification_dict - def _add_prefill_message(self, messages: List[Dict[str, str]]): + def _prefill_message(self, messages: List[Dict[str, str]], prefill_message): """ Update messages and generation params for prompt prefilling @@ -494,29 +331,7 @@ class ArchFunctionHandler(ArchBaseHandler): Returns: prefill_messages (List[Dict[str, str]]): A list of messages. """ - - return messages + [ - { - "role": "assistant", - "content": random.choice(self.prefill_prefix), - } - ] - - def _engage_parameter_gathering(self, messages: List[Dict[str, str]]): - """ - Engage parameter gathering for tool calls - """ - - # TODO: log enaging parameter gathering - prefill_response = self.client.chat.completions.create( - messages=self._add_prefill_message(messages), - model=self.model_name, - extra_body={ - **self.generation_params, - **self.prefill_params, - }, - ) - return prefill_response + return messages + [{"role": "assistant", "content": prefill_message}] @override async def chat_completion(self, req: ChatMessage) -> ChatCompletionResponse: @@ -544,7 +359,7 @@ class ArchFunctionHandler(ArchBaseHandler): # always enable `stream=True` to collect model responses response = self.client.chat.completions.create( - messages=messages, + messages=self._prefill_message(messages, self.default_prefix), model=self.model_name, stream=True, extra_body=self.generation_params, @@ -565,72 +380,114 @@ class ArchFunctionHandler(ArchBaseHandler): has_tool_calls, has_hallucination = None, False for _ in self.hallucination_state: - # check if the first token is - if len(self.hallucination_state.tokens) > 0 and has_tool_calls is None: - if self.hallucination_state.tokens[0] == "": + # check if moodel response starts with tool calls, we do it after 5 tokens because we only check the first part of the response. + if len(self.hallucination_state.tokens) > 5 and has_tool_calls is None: + content = "".join(self.hallucination_state.tokens) + if "tool_calls" in content: has_tool_calls = True else: has_tool_calls = False - break # if the model is hallucinating, start parameter gathering if self.hallucination_state.hallucination is True: has_hallucination = True break - if has_tool_calls: - if has_hallucination: - # start prompt prefilling if hallcuination is found in tool calls - logger.info( - f"[Hallucination]: {self.hallucination_state.error_message}" - ) - prefill_response = self._engage_parameter_gathering(messages) - model_response = prefill_response.choices[0].message.content - else: - model_response = "".join(self.hallucination_state.tokens) + if has_tool_calls and has_hallucination: + # start prompt prefilling if hallcuination is found in tool calls + logger.info( + f"[Hallucination]: {self.hallucination_state.error_message}" + ) + response = self.client.chat.completions.create( + messages=self._prefill_message(messages, self.clarify_prefix), + model=self.model_name, + stream=False, + extra_body=self.generation_params, + ) + model_response = response.choices[0].message.content else: - # start parameter gathering if the model is not generating tool calls - prefill_response = self._engage_parameter_gathering(messages) - model_response = prefill_response.choices[0].message.content + model_response = "".join(self.hallucination_state.tokens) # Extract tool calls from model response - extracted = self._extract_tool_calls(model_response) + response_dict = self._parse_model_response(model_response) + logger.info(f"[arch-fc]: raw model response: {response_dict['raw_response']}") - if extracted["status"]: - # Response with tool calls - if len(extracted["result"]): - verified = {} - if use_agent_orchestrator: - # skip tool call verification if using agent orchestrator - verified = {"status": True, "message": ""} - else: - verified = self._verify_tool_calls( - tools=req.tools, tool_calls=extracted["result"] - ) - - if verified["status"]: - logger.info( - f"[Tool calls]: {json.dumps([tool_call['function'] for tool_call in extracted['result']])}" - ) - model_response = Message(content="", tool_calls=extracted["result"]) - else: - logger.error(f"Invalid tool call - {verified['message']}") - # Response without tool calls + # General model response + if response_dict.get("response", ""): + model_message = Message(content="", tool_calls=[]) + # Parameter gathering + elif response_dict.get("required_functions", []): + if not use_agent_orchestrator: + clarification = response_dict.get("clarification", "") + model_message = Message(content=clarification, tool_calls=[]) else: - model_response = Message(content=model_response, tool_calls=[]) - # Response with tool calls but contain errors + model_message = Message(content="", tool_calls=[]) + # Function Calling + elif response_dict.get("tool_calls", []): + if response_dict["is_valid"]: + if not use_agent_orchestrator: + verification_dict = self._verify_tool_calls( + tools=req.tools, tool_calls=response_dict["tool_calls"] + ) + + if verification_dict["is_valid"]: + logger.info( + f"[Tool calls]: {json.dumps([tool_call['function'] for tool_call in response_dict['tool_calls']])}" + ) + model_message = Message( + content="", tool_calls=response_dict["tool_calls"] + ) + else: + logger.error( + f"Invalid tool call - {verification_dict['error_message']}" + ) + model_message = Message(content="", tool_calls=[]) + else: + # skip tool call verification if using agent orchestrator + logger.info( + f"[Tool calls]: {json.dumps([tool_call['function'] for tool_call in response_dict['tool_calls']])}" + ) + model_message = Message( + content="", tool_calls=response_dict["tool_calls"] + ) + + else: + # Response with tool calls but invalid + model_message = Message(content="", tool_calls=[]) + # Response not in the desired format else: - logger.error(f"Tool call extraction error - {extracted['message']}") + logger.error(f"Invalid model response - {model_response}") + model_message = Message(content="", tool_calls=[]) chat_completion_response = ChatCompletionResponse( - choices=[Choice(message=model_response)], model=self.model_name + choices=[Choice(message=model_message)], + model=self.model_name, + metadata={"x-arch-fc-model-response": response_dict["raw_response"]}, + role="assistant", ) - logger.info(f"[response]: {json.dumps(chat_completion_response.model_dump())}") + logger.info( + f"[response arch-fc]: {json.dumps(chat_completion_response.model_dump(exclude_none=True))}" + ) return chat_completion_response +# ============================================================================================================================================== + + +class ArchAgentConfig(ArchFunctionConfig): + GENERATION_PARAMS = { + "temperature": 0.01, + "top_p": 1.0, + "top_k": 10, + "max_tokens": 1024, + "stop_token_ids": [151645], + "logprobs": True, + "top_logprobs": 10, + } + + class ArchAgentHandler(ArchFunctionHandler): def __init__(self, client: OpenAI, model_name: str, config: ArchAgentConfig): super().__init__(client, model_name, config) @@ -657,7 +514,7 @@ class ArchAgentHandler(ArchFunctionHandler): ): tool_copy = copy.deepcopy(tool) del tool_copy["function"]["parameters"] - converted.append(json.dumps(tool_copy)) + converted.append(json.dumps(tool_copy["function"], ensure_ascii=False)) else: - converted.append(json.dumps(tool)) + converted.append(json.dumps(tool["function"], ensure_ascii=False)) return "\n".join(converted) diff --git a/model_server/src/core/utils/hallucination_utils.py b/model_server/src/core/utils/hallucination_utils.py index 91effc92..992f8aa4 100644 --- a/model_server/src/core/utils/hallucination_utils.py +++ b/model_server/src/core/utils/hallucination_utils.py @@ -13,16 +13,15 @@ from src.commons.utils import get_model_server_logger logger = get_model_server_logger() # constants -FUNC_NAME_START_PATTERN = ('\n{"name":"', "\n{'name':'") +FUNC_NAME_START_PATTERN = ('{"name":"', "{'name':'") FUNC_NAME_END_TOKEN = ('",', "',") -TOOL_CALL_TOKEN = "" -END_TOOL_CALL_TOKEN = "" +END_TOOL_CALL_TOKEN = "}}" FIRST_PARAM_NAME_START_PATTERN = ('"arguments":{"', "'arguments':{'") -PARAMETER_NAME_END_TOKENS = ('":', ':"', "':", ":'") -PARAMETER_NAME_START_PATTERN = (',"', ",'") +PARAMETER_NAME_END_TOKENS = ('":', ':"', "':", ":'", '":"', "':'") +PARAMETER_NAME_START_PATTERN = ('","', "','") PARAMETER_VALUE_START_PATTERN = ('":', "':") -PARAMETER_VALUE_END_TOKEN = ('",', "}}\n", "',") +PARAMETER_VALUE_END_TOKEN = ('",', '"}') BRACKETS = {"(": ")", "{": "}", "[": "]"} @@ -37,16 +36,9 @@ class MaskToken(Enum): HALLUCINATION_THRESHOLD_DICT = { - MaskToken.TOOL_CALL.value: { - "entropy": 0.35, - "varentropy": 1.7, - "probability": 0.8, - }, - MaskToken.PARAMETER_VALUE.value: { - "entropy": 0.28, - "varentropy": 1.4, - "probability": 0.8, - }, + "entropy": 0.0001, + "varentropy": 0.0001, + "probability": 0.8, } @@ -160,6 +152,7 @@ class HallucinationState: self._process_function(function) self.open_bracket = False self.bracket = None + self.function_name = "" self.check_parameter_name = {} self.HALLUCINATION_THRESHOLD_DICT = HALLUCINATION_THRESHOLD_DICT @@ -208,22 +201,20 @@ class HallucinationState: r = next(self.response_iterator) if hasattr(r.choices[0].delta, "content"): token_content = r.choices[0].delta.content - if token_content: + if token_content != "": try: logprobs = [ p.logprob for p in r.choices[0].logprobs.content[0].top_logprobs ] - except Exception as e: - raise ValueError( - f"Error extracting logprobs from response: {e}" - ) - if token_content == END_TOOL_CALL_TOKEN: - self._reset_parameters() - else: self.append_and_check_token_hallucination( token_content, logprobs ) + except Exception as e: + self.append_and_check_token_hallucination( + token_content, [None] + ) + return token_content except StopIteration: raise StopIteration @@ -234,12 +225,12 @@ class HallucinationState: Detects hallucinations based on the token type and log probabilities. """ content = "".join(self.tokens).replace(" ", "") - if self.tokens[-1] == TOOL_CALL_TOKEN: - self.mask.append(MaskToken.TOOL_CALL) - self._check_logprob() # Function name extraction logic # If the state is function name and the token is not an end token, add to the mask + if content.endswith(END_TOOL_CALL_TOKEN): + self._reset_parameters() + if self.state == "function_name": if self.tokens[-1] not in FUNC_NAME_END_TOKEN: self.mask.append(MaskToken.FUNCTION_NAME) @@ -359,7 +350,7 @@ class HallucinationState: if check_threshold( entropy, varentropy, - self.HALLUCINATION_THRESHOLD_DICT[self.mask[-1].value], + self.HALLUCINATION_THRESHOLD_DICT, ): self.hallucination = True self.error_message = f"token '{self.tokens[-1]}' is uncertain. Generated response:\n{''.join(self.tokens)}" diff --git a/model_server/src/core/utils/model_utils.py b/model_server/src/core/utils/model_utils.py index 73dc6fef..9dfac528 100644 --- a/model_server/src/core/utils/model_utils.py +++ b/model_server/src/core/utils/model_utils.py @@ -1,4 +1,5 @@ import json +import src.commons.utils as utils from openai import OpenAI from pydantic import BaseModel @@ -56,7 +57,6 @@ class ArchBaseHandler: client: OpenAI, model_name: str, task_prompt: str, - tool_prompt_template: str, format_prompt: str, generation_params: Dict, ): @@ -67,7 +67,6 @@ class ArchBaseHandler: client (OpenAI): An OpenAI client instance. model_name (str): Name of the model to use. task_prompt (str): The main task prompt for the system. - tool_prompt (str): A prompt to describe tools. format_prompt (str): A prompt specifying the desired output format. generation_params (Dict): Generation parameters for the model. """ @@ -75,7 +74,6 @@ class ArchBaseHandler: self.model_name = model_name self.task_prompt = task_prompt - self.tool_prompt_template = tool_prompt_template self.format_prompt = format_prompt self.generation_params = generation_params @@ -105,13 +103,11 @@ class ArchBaseHandler: str: A formatted system prompt. """ - tool_text = self._convert_tools(tools) + today_date = utils.get_today_date() + tools = self._convert_tools(tools) system_prompt = ( - self.task_prompt - + "\n\n" - + self.tool_prompt_template.format(tool_text=tool_text) - + "\n\n" + self.task_prompt.format(today_date=today_date, tools=tools) + self.format_prompt ) @@ -146,7 +142,7 @@ class ArchBaseHandler: {"role": "system", "content": self._format_system_prompt(tools)} ) - for message in messages: + for idx, message in enumerate(messages): role, content, tool_calls = ( message.role, message.content, @@ -162,9 +158,24 @@ class ArchBaseHandler: if metadata.get("optimize_context_window", "false").lower() == "true": content = f"\n\n" else: - content = ( - f"\n{json.dumps(content)}\n" + # sample response below + # "content": "\n{'name': 'get_stock_price', 'result': '$196.66'}\n" + # msg[idx-1] contains tool call = '{"tool_calls": [{"name": "currency_exchange", "arguments": {"currency_symbol": "NZD"}}]}' + tool_call_msg = messages[idx - 1].content + if tool_call_msg.startswith("```") and tool_call_msg.endswith( + "```" + ): + tool_call_msg = tool_call_msg.strip("```").strip() + if tool_call_msg.startswith("json"): + tool_call_msg = tool_call_msg[4:].strip() + func_name = json.loads(tool_call_msg)["tool_calls"][0].get( + "name", "no_name" ) + tool_response = { + "name": func_name, + "result": content, + } + content = f"\n{json.dumps(tool_response)}\n" processed_messages.append({"role": role, "content": content}) diff --git a/model_server/src/main.py b/model_server/src/main.py index 1763b015..34856498 100644 --- a/model_server/src/main.py +++ b/model_server/src/main.py @@ -71,67 +71,58 @@ async def models(): @app.post("/function_calling") async def function_calling(req: ChatMessage, res: Response): logger.info("[Endpoint: /function_calling]") - logger.info(f"[request body]: {json.dumps(req.model_dump())}") + logger.info(f"[request body]: {json.dumps(req.model_dump(exclude_none=True))}") final_response: ChatCompletionResponse = None error_messages = None + use_agent_orchestrator = req.metadata.get("use_agent_orchestrator", False) + logger.info(f"Use agent orchestrator: {use_agent_orchestrator}") + try: - intent_detected = False - use_agent_orchestrator = req.metadata.get("use_agent_orchestrator", False) - logger.info(f"Use agent orchestrator: {use_agent_orchestrator}") - if not use_agent_orchestrator: - intent_start_time = time.perf_counter() - intent_response = await handler_map["Arch-Intent"].chat_completion(req) - intent_latency = time.perf_counter() - intent_start_time - intent_detected = handler_map["Arch-Intent"].detect_intent(intent_response) + handler_name = "Arch-Agent" if use_agent_orchestrator else "Arch-Function" + model_handler: ArchFunctionHandler = handler_map[handler_name] - if use_agent_orchestrator or intent_detected: - # TODO: measure agreement between intent detection and function calling - try: - function_start_time = time.perf_counter() - handler_name = ( - "Arch-Agent" if use_agent_orchestrator else "Arch-Function" + start_time = time.perf_counter() + final_response = await model_handler.chat_completion(req) + latency = time.perf_counter() - start_time + + if not final_response.metadata: + final_response.metadata = {} + + # Parameter gathering for detected intents + if final_response.choices[0].message.content: + final_response.metadata["function_latency"] = str(round(latency * 1000, 3)) + # Function Calling + elif final_response.choices[0].message.tool_calls: + final_response.metadata["function_latency"] = str(round(latency * 1000, 3)) + + if not use_agent_orchestrator: + final_response.metadata["hallucination"] = str( + model_handler.hallucination_state.hallucination ) - function_calling_handler: ArchFunctionHandler = handler_map[ - handler_name - ] - final_response = await function_calling_handler.chat_completion(req) - function_latency = time.perf_counter() - function_start_time - - final_response.metadata = { - "function_latency": str(round(function_latency * 1000, 3)), - } - - if not use_agent_orchestrator: - final_response.metadata["intent_latency"] = str( - round(intent_latency * 1000, 3) - ) - final_response.metadata["hallucination"] = str( - function_calling_handler.hallucination_state.hallucination - ) - except ValueError as e: - res.statuscode = 503 - error_messages = ( - f"[{handler_name}] - Error in tool call extraction: {e}" - ) - except StopIteration as e: - res.statuscode = 500 - error_messages = f"[{handler_name}] - Error in hallucination check: {e}" - except Exception as e: - res.status_code = 500 - error_messages = f"[{handler_name}] - Error in ChatCompletion: {e}" - raise + # No intent detected else: - # no intent matched - intent_response.metadata = { - "intent_latency": str(round(intent_latency * 1000, 3)), - } - final_response = intent_response + final_response.metadata["intent_latency"] = str(round(latency * 1000, 3)) + if not use_agent_orchestrator: + final_response.metadata["intent_latency"] = str(round(latency * 1000, 3)) + + final_response.metadata["hallucination"] = str( + model_handler.hallucination_state.hallucination + ) + + except ValueError as e: + res.statuscode = 503 + error_messages = f"[{handler_name}] - Error in tool call extraction: {e}" + raise + except StopIteration as e: + res.statuscode = 500 + error_messages = f"[{handler_name}] - Error in hallucination check: {e}" + raise except Exception as e: res.status_code = 500 - error_messages = f"[Arch-Intent] - Error in ChatCompletion: {e}" + error_messages = f"[{handler_name}] - Error in ChatCompletion: {e}" raise if error_messages is not None: @@ -144,7 +135,7 @@ async def function_calling(req: ChatMessage, res: Response): @app.post("/guardrails") async def guardrails(req: GuardRequest, res: Response, max_num_words=300): logger.info("[Endpoint: /guardrails] - Gateway") - logger.info(f"[request body]: {json.dumps(req.model_dump())}") + logger.info(f"[request body]: {json.dumps(req.model_dump(exclude_none=True))}") final_response: GuardResponse = None error_messages = None diff --git a/model_server/tests/core/test_function_calling.py b/model_server/tests/core/test_function_calling.py index 0f2c9995..6005d5e6 100644 --- a/model_server/tests/core/test_function_calling.py +++ b/model_server/tests/core/test_function_calling.py @@ -1,5 +1,5 @@ import pytest - +import time from src.commons.globals import handler_map from src.core.utils.model_utils import ChatMessage, Message @@ -37,26 +37,9 @@ get_weather_api = { # get_data class return request, intent, hallucination, parameter_gathering -def get_hallucination_data_complex(): +def get_hallucination_data(): # Create instances of the Message class - message1 = Message(role="user", content="How is the weather in Seattle?") - message2 = Message( - role="assistant", content="Can you specify the unit you want the weather in?" - ) - message3 = Message(role="user", content="In celcius please!") - - # Create a list of tools - tools = [get_weather_api] - - # Create an instance of the ChatMessage class - req = ChatMessage(messages=[message1, message2, message3], tools=tools) - - return req, True, True, True - - -def get_hallucination_data_medium(): - # Create instances of the Message class - message1 = Message(role="user", content="How is the weather in?") + message1 = Message(role="user", content="How is the weather in Seattle in days?") # Create a list of tools tools = [get_weather_api] @@ -65,26 +48,10 @@ def get_hallucination_data_medium(): req = ChatMessage(messages=[message1], tools=tools) # first token will not be tool call - return req, True, True, True + return req, False, True -def get_complete_data_2(): - # Create instances of the Message class - message1 = Message( - role="user", - content="what is the weather forecast for seattle in the next 10 days?", - ) - - # Create a list of tools - tools = [get_weather_api] - - # Create an instance of the ChatMessage class - req = ChatMessage(messages=[message1], tools=tools) - - return req, True, False, False - - -def get_complete_data(): +def get_success_tool_call_data(): # Create instances of the Message class message1 = Message(role="user", content="How is the weather in Seattle in 7 days?") @@ -94,7 +61,7 @@ def get_complete_data(): # Create an instance of the ChatMessage class req = ChatMessage(messages=[message1], tools=tools) - return req, True, False, False + return req, True, False def get_irrelevant_data(): @@ -107,7 +74,7 @@ def get_irrelevant_data(): # Create an instance of the ChatMessage class req = ChatMessage(messages=[message1], tools=tools) - return req, False, False, False + return req, False, False def get_greeting_data(): @@ -120,38 +87,29 @@ def get_greeting_data(): # Create an instance of the ChatMessage class req = ChatMessage(messages=[message1], tools=tools) - return req, False, False, False + return req, False, False @pytest.mark.asyncio @pytest.mark.parametrize( "get_data_func", [ - get_hallucination_data_complex, - get_complete_data, + get_hallucination_data, + get_greeting_data, get_irrelevant_data, - get_complete_data_2, + get_success_tool_call_data, ], ) async def test_function_calling(get_data_func): - req, intent, hallucination, parameter_gathering = get_data_func() + req, intent, hallucination = get_data_func() + handler_name = "Arch-Function" + use_agent_orchestrator = False + model_handler: ArchFunctionHandler = handler_map[handler_name] - intent_response = await handler_map["Arch-Intent"].chat_completion(req) + start_time = time.perf_counter() + final_response = await model_handler.chat_completion(req) + latency = time.perf_counter() - start_time - assert handler_map["Arch-Intent"].detect_intent(intent_response) == intent + assert intent == (len(final_response.choices[0].message.tool_calls) >= 1) - if intent: - function_calling_response = await handler_map["Arch-Function"].chat_completion( - req - ) - assert ( - handler_map["Arch-Function"].hallucination_state.hallucination - == hallucination - ) - response_txt = function_calling_response.choices[0].message.content - - if parameter_gathering: - prefill_prefix = handler_map["Arch-Function"].prefill_prefix - assert any( - response_txt.startswith(prefix) for prefix in prefill_prefix - ), f"Response '{response_txt}' does not start with any of the prefixes: {prefill_prefix}" + assert hallucination == model_handler.hallucination_state.hallucination diff --git a/model_server/tests/core/test_state.py b/model_server/tests/core/test_state.py index b5a0332a..331b8d3f 100644 --- a/model_server/tests/core/test_state.py +++ b/model_server/tests/core/test_state.py @@ -1,5 +1,5 @@ from src.commons.globals import handler_map -from src.core.function_calling import Message +from src.core.function_calling import ArchFunctionHandler, Message test_input_history = [ @@ -7,34 +7,19 @@ test_input_history = [ { "role": "assistant", "model": "Arch-Function", - "tool_calls": [ - { - "id": "call_3394", - "type": "function", - "function": { - "name": "weather_forecast", - "arguments": {"city": "Chicago", "days": 5}, - }, - } - ], + "content": '```json\n{"tool_calls": [{"name": "get_current_weather", "arguments": {"days": 5, "location": "Chicago, Illinois"}}]}\n```', + }, + { + "role": "tool", + "model": "Arch-Function", + "content": '{"location":"Chicago%2C%20Illinois","temperature":[{"date":"2025-04-14","temperature":{"min":53,"max":65},"units":"Farenheit","query_time":"2025-04-14 17:01:52.432817+00:00"},{"date":"2025-04-15","temperature":{"min":85,"max":97},"units":"Farenheit","query_time":"2025-04-14 17:01:52.432830+00:00"},{"date":"2025-04-16","temperature":{"min":62,"max":78},"units":"Farenheit","query_time":"2025-04-14 17:01:52.432835+00:00"},{"date":"2025-04-17","temperature":{"min":89,"max":101},"units":"Farenheit","query_time":"2025-04-14 17:01:52.432839+00:00"},{"date":"2025-04-18","temperature":{"min":86,"max":104},"units":"Farenheit","query_time":"2025-04-14 17:01:52.432843+00:00"}],"units":"Farenheit"}', }, - {"role": "tool", "content": "--", "tool_call_id": "call_3394"}, - {"role": "assistant", "content": "--", "model": "gpt-3.5-turbo-0125"}, - {"role": "user", "content": "how is the weather in chicago for next 5 days?"}, { "role": "assistant", - "tool_calls": [ - { - "id": "call_5306", - "type": "function", - "function": { - "name": "weather_forecast", - "arguments": {"city": "Chicago", "days": 5}, - }, - } - ], + "model": "gpt-4o-2024-08-06", + "content": '{"response": "Based on the forecast data you provided, here is the weather for the next 5 days in Chicago:\\n\\n- **April 14, 2025**: The temperature will range between 53\\u00b0F and 65\\u00b0F. \\n- **April 15, 2025**: The temperature will range between 85\\u00b0F and 97\\u00b0F.\\n- **April 16, 2025**: The temperature will range between 62\\u00b0F and 78\\u00b0F.\\n- **April 17, 2025**: The temperature will range between 89\\u00b0F and 101\\u00b0F.\\n- **April 18, 2025**: The temperature will range between 86\\u00b0F and 104\\u00b0F.\\n\\nPlease note that the temperatures are given in Fahrenheit."}', }, - {"role": "tool", "content": "--", "tool_call_id": "call_5306"}, + {"role": "user", "content": "what about seattle?"}, ] @@ -44,7 +29,8 @@ def test_update_fc_history(): for h in test_input_history: message_history.append(Message(**h)) - updated_history = handler_map["Arch-Function"]._process_messages(message_history) - assert len(updated_history) == 7 + handler: ArchFunctionHandler = handler_map["Arch-Function"] + updated_history = handler._process_messages(message_history) + assert len(updated_history) == 5 # ensure that tool role does not exist anymore assert all([h["role"] != "tool" for h in updated_history]) diff --git a/tests/archgw/common.py b/tests/archgw/common.py index 404d8ef9..f87f6403 100644 --- a/tests/archgw/common.py +++ b/tests/archgw/common.py @@ -47,14 +47,11 @@ TEST_CASE_FIXTURES = { "tool_call_id": "", "tool_calls": [ { - "id": "call_6009", + "id": "call_2925", "type": "function", "function": { "name": "get_current_weather", - "arguments": { - "location": "Seattle, WA", - "days": "2", - }, + "arguments": {"location": "Seattle", "days": "2"}, }, } ], @@ -63,7 +60,11 @@ TEST_CASE_FIXTURES = { } ], "model": "Arch-Function", - "metadata": {"intent_latency": "455.092", "function_latency": "312.744"}, + "metadata": { + "x-arch-fc-model-response": '{"tool_calls": [{"name": "get_current_weather", "arguments": {"location": "Seattle", "days": "2"}}]}', + "function_latency": "361.841", + "intent_latency": "361.841", + }, }, "api_server_response": [ { diff --git a/tests/e2e/test_prompt_gateway.py b/tests/e2e/test_prompt_gateway.py index 9b804bae..e6a10f3a 100644 --- a/tests/e2e/test_prompt_gateway.py +++ b/tests/e2e/test_prompt_gateway.py @@ -2,6 +2,7 @@ import json import pytest import requests from deepdiff import DeepDiff +import re from common import ( PROMPT_GATEWAY_ENDPOINT, @@ -11,6 +12,15 @@ from common import ( ) +def cleanup_tool_call(tool_call): + pattern = r"```json\n(.*?)\n```" + match = re.search(pattern, tool_call, re.DOTALL) + if match: + tool_call = match.group(1) + + return tool_call.strip() + + @pytest.mark.parametrize("stream", [True, False]) def test_prompt_gateway(stream): expected_tool_call = { @@ -42,9 +52,14 @@ def test_prompt_gateway(stream): assert "role" in choices[0]["delta"] role = choices[0]["delta"]["role"] assert role == "assistant" - tool_calls = choices[0].get("delta", {}).get("tool_calls", []) + print(f"choices: {choices}") + tool_call_str = choices[0].get("delta", {}).get("content", "") + print("tool_call_str: ", tool_call_str) + cleaned_tool_call_str = cleanup_tool_call(tool_call_str) + print("cleaned_tool_call_str: ", cleaned_tool_call_str) + tool_calls = json.loads(cleaned_tool_call_str).get("tool_calls", []) assert len(tool_calls) > 0 - tool_call = tool_calls[0]["function"] + tool_call = tool_calls[0] location = tool_call["arguments"]["location"] assert expected_tool_call["arguments"]["location"] in location.lower() del expected_tool_call["arguments"]["location"] @@ -62,7 +77,7 @@ def test_prompt_gateway(stream): # third..end chunk is summarization (role = assistant) response_json = json.loads(chunks[2]) - assert response_json.get("model").startswith("llama-3.2-3b-preview") + assert response_json.get("model").startswith("gpt-4o") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["delta"] @@ -71,18 +86,24 @@ def test_prompt_gateway(stream): else: response_json = response.json() - assert response_json.get("model").startswith("llama-3.2-3b-preview") + assert response_json.get("model").startswith("gpt-4o") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["message"] assert choices[0]["message"]["role"] == "assistant" # now verify arch_messages (tool call and api response) that are sent as response metadata arch_messages = get_arch_messages(response_json) + print("arch_messages: ", json.dumps(arch_messages)) assert len(arch_messages) == 2 tool_calls_message = arch_messages[0] - tool_calls = tool_calls_message.get("tool_calls", []) - assert len(tool_calls) > 0 - tool_call = tool_calls[0]["function"] + print("tool_calls_message: ", tool_calls_message) + tool_calls = tool_calls_message.get("content", []) + cleaned_tool_call_str = cleanup_tool_call(tool_calls) + cleaned_tool_call_json = json.loads(cleaned_tool_call_str) + print("cleaned_tool_call_json: ", json.dumps(cleaned_tool_call_json)) + tool_calls_list = cleaned_tool_call_json.get("tool_calls", []) + assert len(tool_calls_list) > 0 + tool_call = tool_calls_list[0] location = tool_call["arguments"]["location"] assert expected_tool_call["arguments"]["location"] in location.lower() del expected_tool_call["arguments"]["location"] @@ -231,7 +252,7 @@ def test_prompt_gateway_param_tool_call(stream): # third..end chunk is summarization (role = assistant) response_json = json.loads(chunks[2]) - assert response_json.get("model").startswith("llama-3.2-3b-preview") + assert response_json.get("model").startswith("gpt-4o") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["delta"] @@ -240,7 +261,7 @@ def test_prompt_gateway_param_tool_call(stream): else: response_json = response.json() - assert response_json.get("model").startswith("llama-3.2-3b-preview") + assert response_json.get("model").startswith("gpt-4o") choices = response_json.get("choices", []) assert len(choices) > 0 assert "role" in choices[0]["message"] @@ -262,7 +283,7 @@ def test_prompt_gateway_default_target(stream): "messages": [ { "role": "user", - "content": "hello, what can you do for me?", + "content": "hello", }, ], "stream": stream, @@ -273,17 +294,20 @@ def test_prompt_gateway_default_target(stream): chunks = get_data_chunks(response, n=3) assert len(chunks) > 0 response_json = json.loads(chunks[0]) + print("response_json chunks[0]: ", response_json) assert response_json.get("model").startswith("api_server") assert len(response_json.get("choices", [])) > 0 assert response_json.get("choices")[0]["delta"]["role"] == "assistant" response_json = json.loads(chunks[1]) + print("response_json chunks[1]: ", response_json) choices = response_json.get("choices", []) assert len(choices) > 0 content = choices[0]["delta"]["content"] assert content == "I can help you with weather forecast" else: response_json = response.json() + print("response_json: ", response_json) assert response_json.get("model").startswith("api_server") assert len(response_json.get("choices")) > 0 assert response_json.get("choices")[0]["message"]["role"] == "assistant" diff --git a/tests/modelserver/test_hallucination.py b/tests/modelserver/test_hallucination.py index f1a3d9b4..323db3fc 100644 --- a/tests/modelserver/test_hallucination.py +++ b/tests/modelserver/test_hallucination.py @@ -4,6 +4,9 @@ import requests import logging import yaml +pytestmark = pytest.mark.skip( + reason="Skipping entire test file as hallucination is not enabled for archfc 1.1 yet" +) MODEL_SERVER_ENDPOINT = os.getenv( "MODEL_SERVER_ENDPOINT", "http://localhost:51000/function_calling" diff --git a/tests/modelserver/test_modelserver.py b/tests/modelserver/test_modelserver.py index 75e6d27e..4596606f 100644 --- a/tests/modelserver/test_modelserver.py +++ b/tests/modelserver/test_modelserver.py @@ -5,6 +5,9 @@ import yaml from deepdiff import DeepDiff +pytestmark = pytest.mark.skip( + reason="Skipping entire test file as this these tests are heavily dependent on model output" +) MODEL_SERVER_ENDPOINT = os.getenv( "MODEL_SERVER_ENDPOINT", "http://localhost:51000/function_calling" diff --git a/tests/rest/api_prompt_gateway.rest b/tests/rest/api_prompt_gateway.rest index f28690c9..4a1f77e0 100644 --- a/tests/rest/api_prompt_gateway.rest +++ b/tests/rest/api_prompt_gateway.rest @@ -68,7 +68,7 @@ Content-Type: application/json { "role": "assistant", "content": "It seems I'm missing some information. Could you provide the following details days ?", - "model": "Arch-Function-1.5b" + "model": "Arch-Function" }, { "role": "user", @@ -91,7 +91,7 @@ Content-Type: application/json { "role": "assistant", "content": "It seems I'm missing some information. Could you provide the following details days ?", - "model": "Arch-Function-1.5b" + "model": "Arch-Function" }, { "role": "user", From c7c0553427d4e00b0254838d1a7fc0e9567645a4 Mon Sep 17 00:00:00 2001 From: Adil Hafeez Date: Tue, 15 Apr 2025 14:50:09 -0700 Subject: [PATCH 37/37] release 0.2.6 (#463) --- README.md | 2 +- arch/tools/README.md | 2 +- arch/tools/poetry.lock | 10 ++--- arch/tools/pyproject.toml | 4 +- docs/source/conf.py | 2 +- docs/source/get_started/quickstart.rst | 2 +- model_server/poetry.lock | 56 +++++++++++++------------- model_server/pyproject.toml | 2 +- 8 files changed, 40 insertions(+), 40 deletions(-) diff --git a/README.md b/README.md index 8a416d51..889b8a5d 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. ```console $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate -$ pip install archgw==0.2.5 +$ pip install archgw==0.2.6 ``` ### Build AI Agent with Arch Gateway diff --git a/arch/tools/README.md b/arch/tools/README.md index 554981ae..4ebd2da4 100644 --- a/arch/tools/README.md +++ b/arch/tools/README.md @@ -19,7 +19,7 @@ source venv/bin/activate ### Step 3: Run the build script ```bash -pip install archgw==0.2.5 +pip install archgw==0.2.6 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index 970f3a51..b71bd105 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -2,7 +2,7 @@ [[package]] name = "archgw_modelserver" -version = "0.2.5" +version = "0.2.6" description = "A model server for serving models" optional = false python-versions = "*" @@ -402,16 +402,16 @@ type = ["importlib-metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (>=1.12 [[package]] name = "typing-extensions" -version = "4.13.1" +version = "4.13.2" description = "Backported and Experimental Type Hints for Python 3.8+" optional = false python-versions = ">=3.8" files = [ - {file = "typing_extensions-4.13.1-py3-none-any.whl", hash = "sha256:4b6cf02909eb5495cfbc3f6e8fd49217e6cc7944e145cdda8caa3734777f9e69"}, - {file = "typing_extensions-4.13.1.tar.gz", hash = "sha256:98795af00fb9640edec5b8e31fc647597b4691f099ad75f469a2616be1a76dff"}, + {file = "typing_extensions-4.13.2-py3-none-any.whl", hash = "sha256:a439e7c04b49fec3e5d3e2beaa21755cadbbdc391694e28ccdd36ca4a1408f8c"}, + {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"}, ] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "a204adc8886a3e01792f4d6395bf291b62f7f78f080e2e5980da36637643177c" +content-hash = "5cc1d766ed43530c15dfbde7710346e1b157be450bf4736eb4eed2b091efef47" diff --git a/arch/tools/pyproject.toml b/arch/tools/pyproject.toml index edbfceb0..f730684e 100644 --- a/arch/tools/pyproject.toml +++ b/arch/tools/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw" -version = "0.2.5" +version = "0.2.6" description = "Python-based CLI tool to manage Arch Gateway." authors = ["Katanemo Labs, Inc."] packages = [ @@ -10,7 +10,7 @@ readme = "README.md" [tool.poetry.dependencies] python = "^3.10" -archgw_modelserver = "^0.2.5" +archgw_modelserver = "^0.2.6" click = "^8.1.7" jinja2 = "^3.1.4" jsonschema = "^4.23.0" diff --git a/docs/source/conf.py b/docs/source/conf.py index 70c0daac..8079a4c2 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -15,7 +15,7 @@ from sphinxawesome_theme.postprocess import Icons project = "Arch Docs" copyright = "2025, Katanemo Labs, Inc" author = "Katanemo Labs, Inc" -release = " v0.2.5" +release = " v0.2.6" # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index b4163f08..93ceebad 100644 --- a/docs/source/get_started/quickstart.rst +++ b/docs/source/get_started/quickstart.rst @@ -25,7 +25,7 @@ Arch's CLI allows you to manage and interact with the Arch gateway efficiently. $ python -m venv venv $ source venv/bin/activate # On Windows, use: venv\Scripts\activate - $ pip install archgw==0.2.5 + $ pip install archgw==0.2.6 Build AI Agent with Arch Gateway diff --git a/model_server/poetry.lock b/model_server/poetry.lock index 3e148949..a050d664 100644 --- a/model_server/poetry.lock +++ b/model_server/poetry.lock @@ -359,13 +359,13 @@ tqdm = ["tqdm"] [[package]] name = "googleapis-common-protos" -version = "1.69.2" +version = "1.70.0" description = "Common protobufs used in Google APIs" optional = false python-versions = ">=3.7" files = [ - {file = "googleapis_common_protos-1.69.2-py3-none-any.whl", hash = "sha256:0b30452ff9c7a27d80bfc5718954063e8ab53dd3697093d3bc99581f5fd24212"}, - {file = "googleapis_common_protos-1.69.2.tar.gz", hash = "sha256:3e1b904a27a33c821b4b749fd31d334c0c9c30e6113023d495e48979a3dc9c5f"}, + {file = "googleapis_common_protos-1.70.0-py3-none-any.whl", hash = "sha256:b8bfcca8c25a2bb253e0e0b0adaf8c00773e5e6af6fd92397576680b807e0fd8"}, + {file = "googleapis_common_protos-1.70.0.tar.gz", hash = "sha256:0e1b44e0ea153e6594f9f394fef15193a68aaaea2d843f83e2742717ca753257"}, ] [package.dependencies] @@ -450,13 +450,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.7" +version = "1.0.8" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.7-py3-none-any.whl", hash = "sha256:a3fff8f43dc260d5bd363d9f9cf1830fa3a458b332856f34282de498ed420edd"}, - {file = "httpcore-1.0.7.tar.gz", hash = "sha256:8551cb62a169ec7162ac7be8d4817d561f60e08eaa485234898414bb5a8a0b4c"}, + {file = "httpcore-1.0.8-py3-none-any.whl", hash = "sha256:5254cf149bcb5f75e9d1b2b9f729ea4a4b883d1ad7379fc632b727cec23674be"}, + {file = "httpcore-1.0.8.tar.gz", hash = "sha256:86e94505ed24ea06514883fd44d2bc02d90e77e7979c8eb71b90f41d364a1bad"}, ] [package.dependencies] @@ -496,13 +496,13 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "huggingface-hub" -version = "0.30.1" +version = "0.30.2" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" files = [ - {file = "huggingface_hub-0.30.1-py3-none-any.whl", hash = "sha256:0f6aa5ec5a4e68e5b9e45d556b4e5ea180c58f5a5ffa734e7f38c9d573028959"}, - {file = "huggingface_hub-0.30.1.tar.gz", hash = "sha256:f379e8b8d0791295602538856638460ae3cf679c7f304201eb80fb98c771950e"}, + {file = "huggingface_hub-0.30.2-py3-none-any.whl", hash = "sha256:68ff05969927058cfa41df4f2155d4bb48f5f54f719dd0390103eefa9b191e28"}, + {file = "huggingface_hub-0.30.2.tar.gz", hash = "sha256:9a7897c5b6fd9dad3168a794a8998d6378210f5b9688d0dfc180b1a228dc2466"}, ] [package.dependencies] @@ -995,13 +995,13 @@ files = [ [[package]] name = "openai" -version = "1.70.0" +version = "1.74.0" description = "The official Python library for the openai API" optional = false python-versions = ">=3.8" files = [ - {file = "openai-1.70.0-py3-none-any.whl", hash = "sha256:f6438d053fd8b2e05fd6bef70871e832d9bbdf55e119d0ac5b92726f1ae6f614"}, - {file = "openai-1.70.0.tar.gz", hash = "sha256:e52a8d54c3efeb08cf58539b5b21a5abef25368b5432965e4de88cdf4e091b2b"}, + {file = "openai-1.74.0-py3-none-any.whl", hash = "sha256:aff3e0f9fb209836382ec112778667027f4fd6ae38bdb2334bc9e173598b092a"}, + {file = "openai-1.74.0.tar.gz", hash = "sha256:592c25b8747a7cad33a841958f5eb859a785caea9ee22b9e4f4a2ec062236526"}, ] [package.dependencies] @@ -1016,7 +1016,7 @@ typing-extensions = ">=4.11,<5" [package.extras] datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"] -realtime = ["websockets (>=13,<15)"] +realtime = ["websockets (>=13,<16)"] voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"] [[package]] @@ -1300,13 +1300,13 @@ test = ["pytest", "pytest-xdist", "setuptools"] [[package]] name = "pydantic" -version = "2.11.2" +version = "2.11.3" description = "Data validation using Python type hints" optional = false python-versions = ">=3.9" files = [ - {file = "pydantic-2.11.2-py3-none-any.whl", hash = "sha256:7f17d25846bcdf89b670a86cdfe7b29a9f1c9ca23dee154221c9aa81845cfca7"}, - {file = "pydantic-2.11.2.tar.gz", hash = "sha256:2138628e050bd7a1e70b91d4bf4a91167f4ad76fdb83209b107c8d84b854917e"}, + {file = "pydantic-2.11.3-py3-none-any.whl", hash = "sha256:a082753436a07f9ba1289c6ffa01cd93db3548776088aa917cc43b63f68fa60f"}, + {file = "pydantic-2.11.3.tar.gz", hash = "sha256:7471657138c16adad9322fe3070c0116dd6c3ad8d649300e3cbdfe91f4db4ec3"}, ] [package.dependencies] @@ -1472,13 +1472,13 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"] [[package]] name = "pytest-httpserver" -version = "1.1.2" +version = "1.1.3" description = "pytest-httpserver is a httpserver for pytest" optional = false python-versions = ">=3.9" files = [ - {file = "pytest_httpserver-1.1.2-py3-none-any.whl", hash = "sha256:93009d79574fc982301e8494fdea0884f21bb0caf3bcc719151dfbd1e3a943ea"}, - {file = "pytest_httpserver-1.1.2.tar.gz", hash = "sha256:38d0b726580d05c47cbd0ced1ecb36a51668ef1596cdc6d70a9cfa2b3cc00ebd"}, + {file = "pytest_httpserver-1.1.3-py3-none-any.whl", hash = "sha256:5f84757810233e19e2bb5287f3826a71c97a3740abe3a363af9155c0f82fdbb9"}, + {file = "pytest_httpserver-1.1.3.tar.gz", hash = "sha256:af819d6b533f84b4680b9416a5b3f67f1df3701f1da54924afd4d6e4ba5917ec"}, ] [package.dependencies] @@ -1975,13 +1975,13 @@ telegram = ["requests"] [[package]] name = "transformers" -version = "4.51.0" +version = "4.51.3" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" optional = false python-versions = ">=3.9.0" files = [ - {file = "transformers-4.51.0-py3-none-any.whl", hash = "sha256:2e6baa476735ab8adccbaee6961525a0d1ce8c21d49293af30ef5ee4b082f64d"}, - {file = "transformers-4.51.0.tar.gz", hash = "sha256:2d302563ff6c2cc2d0e88ef352cf059f9a21ce18102fd43662bb1246f70b8a84"}, + {file = "transformers-4.51.3-py3-none-any.whl", hash = "sha256:fd3279633ceb2b777013234bbf0b4f5c2d23c4626b05497691f00cfda55e8a83"}, + {file = "transformers-4.51.3.tar.gz", hash = "sha256:e292fcab3990c6defe6328f0f7d2004283ca81a7a07b2de9a46d67fd81ea1409"}, ] [package.dependencies] @@ -2069,13 +2069,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"] [[package]] name = "typing-extensions" -version = "4.13.1" +version = "4.13.2" description = "Backported and Experimental Type Hints for Python 3.8+" optional = false python-versions = ">=3.8" files = [ - {file = "typing_extensions-4.13.1-py3-none-any.whl", hash = "sha256:4b6cf02909eb5495cfbc3f6e8fd49217e6cc7944e145cdda8caa3734777f9e69"}, - {file = "typing_extensions-4.13.1.tar.gz", hash = "sha256:98795af00fb9640edec5b8e31fc647597b4691f099ad75f469a2616be1a76dff"}, + {file = "typing_extensions-4.13.2-py3-none-any.whl", hash = "sha256:a439e7c04b49fec3e5d3e2beaa21755cadbbdc391694e28ccdd36ca4a1408f8c"}, + {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"}, ] [[package]] @@ -2122,13 +2122,13 @@ devenv = ["check-manifest", "pytest (>=4.3)", "pytest-cov", "pytest-mock (>=3.3) [[package]] name = "urllib3" -version = "2.3.0" +version = "2.4.0" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"}, - {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"}, + {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"}, + {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"}, ] [package.extras] diff --git a/model_server/pyproject.toml b/model_server/pyproject.toml index 920c33fb..9c471f58 100644 --- a/model_server/pyproject.toml +++ b/model_server/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw_modelserver" -version = "0.2.5" +version = "0.2.6" description = "A model server for serving models" authors = ["Katanemo Labs, Inc "] license = "Apache 2.0"