diff --git a/README.md b/README.md index c35ebcb8..184aecaf 100644 --- a/README.md +++ b/README.md @@ -19,11 +19,14 @@ Engineered with purpose-built LLMs, Arch handles the critical but undifferentiat **Core Features**: - 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. - - Function Calling for fast Agents and RAG apps. 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. + - Intent Routing & Fast Function Calling. 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 smarter more 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. - - Routing & Traffic Management: Arch manages LLM calls, offering smart retries, automatic cutover, and resilient upstream connections for continuous availability. + - 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. +**High-Level Network Flow**: +![alt text](docs/source/_static/img/arch_network_diagram_high_level.png) + **Jump to our [docs](https://docs.archgw.com)** to learn how you can use Arch to improve the speed, security and personalization of your GenAI apps. > [!IMPORTANT] @@ -57,7 +60,7 @@ 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==0.1.7 +$ pip install archgw==0.1.8 ``` ### Build AI Agent with Arch Gateway @@ -187,7 +190,7 @@ llm_providers: - name: ministral-3b access_key: $MISTRAL_API_KEY - provider: mistral + provider: openai model: ministral-3b-latest ``` diff --git a/arch/arch_config_schema.yaml b/arch/arch_config_schema.yaml index 0fe980dd..e8c7e348 100644 --- a/arch/arch_config_schema.yaml +++ b/arch/arch_config_schema.yaml @@ -43,19 +43,27 @@ properties: properties: name: type: string + # this field is deprecated, use provider_interface instead provider: type: string + enum: + - openai + provider_interface: + type: string + enum: + - openai + - mistral access_key: type: string model: type: string default: type: boolean + endpoint: + type: string additionalProperties: false required: - name - - provider - - access_key - model overrides: type: object diff --git a/arch/envoy.template.yaml b/arch/envoy.template.yaml index 5eac257f..17147cc7 100644 --- a/arch/envoy.template.yaml +++ b/arch/envoy.template.yaml @@ -125,15 +125,21 @@ static_resources: - "*" routes: {% for provider in arch_llm_providers %} + # if endpoint is set then use custom cluster for upstream llm + {% if provider.endpoint %} + {% set llm_cluster_name = provider.name %} + {% else %} + {% set llm_cluster_name = provider.provider_interface %} + {% endif %} - match: prefix: "/" headers: - name: "x-arch-llm-provider" string_match: - exact: {{ provider.name }} + exact: {{ llm_cluster_name }} route: auto_host_rewrite: true - cluster: {{ provider.provider }} + cluster: {{ llm_cluster_name }} timeout: 60s {% endfor %} http_filters: @@ -237,16 +243,16 @@ static_resources: domains: - "*" routes: - {% for internal_clustrer in ["arch_fc", "model_server"] %} + {% for internal_cluster in ["arch_fc", "model_server"] %} - match: prefix: "/" headers: - name: "x-arch-upstream" string_match: - exact: {{ internal_clustrer }} + exact: {{ internal_cluster }} route: auto_host_rewrite: true - cluster: {{ internal_clustrer }} + cluster: {{ internal_cluster }} timeout: 60s {% endfor %} @@ -370,15 +376,21 @@ static_resources: cluster: openai timeout: 60s {% for provider in arch_llm_providers %} + # if endpoint is set then use custom cluster for upstream llm + {% if provider.endpoint %} + {% set llm_cluster_name = provider.name %} + {% else %} + {% set llm_cluster_name = provider.provider_interface %} + {% endif %} - match: prefix: "/" headers: - name: "x-arch-llm-provider" string_match: - exact: {{ provider.name }} + exact: {{ llm_cluster_name }} route: auto_host_rewrite: true - cluster: {{ provider.provider }} + cluster: {{ llm_cluster_name }} timeout: 60s {% endfor %} - match: @@ -538,6 +550,24 @@ static_resources: tls_maximum_protocol_version: TLSv1_3 {% endif %} {% endfor %} + +{% for local_llm_provider in local_llms %} + - name: {{ local_llm_provider.name }} + connect_timeout: 5s + type: LOGICAL_DNS + dns_lookup_family: V4_ONLY + lb_policy: ROUND_ROBIN + load_assignment: + cluster_name: {{ local_llm_provider.name }} + endpoints: + - lb_endpoints: + - endpoint: + address: + socket_address: + address: {{ local_llm_provider.endpoint }} + port_value: {{ local_llm_provider.port }} + hostname: {{ local_llm_provider.endpoint }} +{% endfor %} - name: arch_internal connect_timeout: 5s type: LOGICAL_DNS diff --git a/arch/tools/README.md b/arch/tools/README.md index a679520e..f8cfc0b3 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==0.1.7 +pip install archgw==0.1.8 ``` ## Uninstall Instructions: archgw CLI diff --git a/arch/tools/cli/config_generator.py b/arch/tools/cli/config_generator.py index 3393bb5c..e535894b 100644 --- a/arch/tools/cli/config_generator.py +++ b/arch/tools/cli/config_generator.py @@ -16,18 +16,6 @@ ARCH_CONFIG_SCHEMA_FILE = os.getenv( ) -def add_secret_key_to_llm_providers(config_yaml): - llm_providers = [] - for llm_provider in config_yaml.get("llm_providers", []): - access_key_env_var = llm_provider.get("access_key", False) - access_key_value = os.getenv(access_key_env_var, False) - if access_key_env_var and access_key_value: - llm_provider["access_key"] = access_key_value - llm_providers.append(llm_provider) - config_yaml["llm_providers"] = llm_providers - return config_yaml - - def validate_and_render_schema(): env = Environment(loader=FileSystemLoader("./")) template = env.get_template("envoy.template.yaml") @@ -70,18 +58,42 @@ def validate_and_render_schema(): f"Unknown endpoint {name}, please add it in endpoints section in your arch_config.yaml file" ) - arch_llm_providers = config_yaml["llm_providers"] arch_tracing = config_yaml.get("tracing", {}) + + llms_with_endpoint = [] + + updated_llm_providers = [] + for llm_provider in config_yaml["llm_providers"]: + provider = None + if llm_provider.get("provider") and llm_provider.get("provider_interface"): + raise Exception( + "Please provide either provider or provider_interface, not both" + ) + if llm_provider.get("provider"): + provider = llm_provider["provider"] + llm_provider["provider_interface"] = provider + del llm_provider["provider"] + updated_llm_providers.append(llm_provider) + + if llm_provider.get("endpoint", None): + endpoint = llm_provider["endpoint"] + if len(endpoint.split(":")) > 1: + llm_provider["endpoint"] = endpoint.split(":")[0] + llm_provider["port"] = int(endpoint.split(":")[1]) + llms_with_endpoint.append(llm_provider) + + config_yaml["llm_providers"] = updated_llm_providers + arch_config_string = yaml.dump(config_yaml) - config_yaml["mode"] = "llm" arch_llm_config_string = yaml.dump(config_yaml) data = { "arch_config": arch_config_string, "arch_llm_config": arch_llm_config_string, "arch_clusters": inferred_clusters, - "arch_llm_providers": arch_llm_providers, + "arch_llm_providers": config_yaml["llm_providers"], "arch_tracing": arch_tracing, + "local_llms": llms_with_endpoint, } rendered = template.render(data) diff --git a/arch/tools/poetry.lock b/arch/tools/poetry.lock index 3e7c46b9..81ab0a39 100644 --- a/arch/tools/poetry.lock +++ b/arch/tools/poetry.lock @@ -1,19 +1,8 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. - -[[package]] -name = "annotated-types" -version = "0.7.0" -description = "Reusable constraint types to use with typing.Annotated" -optional = false -python-versions = ">=3.8" -files = [ - {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, - {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, -] +# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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"^3.1.4" jsonschema = "^4.23.0" setuptools = "75.5.0" -huggingface_hub = "^0.26.0" docker = "^7.1.0" python-dotenv = "^1.0.1" diff --git a/archgw.code-workspace b/archgw.code-workspace index 3c968e72..78c124e2 100644 --- a/archgw.code-workspace +++ b/archgw.code-workspace @@ -1,9 +1,9 @@ { "folders": [ - { + { "name": "root", - "path": "." - }, + "path": "." + }, { "name": "crates", "path": "crates" @@ -41,15 +41,16 @@ }, "extensions": { "recommendations": [ - "ms-python.python", - "ms-python.debugpy", - "rust-lang.rust-analyzer", - "humao.rest-client", - "github.copilot", "eamodio.gitlens", - "ms-python.black-formatter", - "tamasfe.even-better-toml", "esbenp.prettier-vscode", + "github.copilot", + "github.vscode-pull-request-github", + "humao.rest-client", + "ms-python.black-formatter", + "ms-python.debugpy", + "ms-python.python", + "rust-lang.rust-analyzer", + "tamasfe.even-better-toml", ] } } diff --git a/crates/common/src/configuration.rs b/crates/common/src/configuration.rs index e83c1117..fbafe7b9 100644 --- a/crates/common/src/configuration.rs +++ b/crates/common/src/configuration.rs @@ -162,15 +162,34 @@ pub struct EmbeddingProviver { pub model: String, } +#[derive(Debug, Clone, Serialize, Deserialize)] +pub enum LlmProviderType { + #[serde(rename = "openai")] + OpenAI, + #[serde(rename = "mistral")] + Mistral, +} + +impl Display for LlmProviderType { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + match self { + LlmProviderType::OpenAI => write!(f, "openai"), + LlmProviderType::Mistral => write!(f, "mistral"), + } + } +} + #[derive(Debug, Clone, Serialize, Deserialize)] //TODO: use enum for model, but if there is a new model, we need to update the code pub struct LlmProvider { pub name: String, - pub provider: String, + pub provider_interface: LlmProviderType, pub access_key: Option, pub model: String, pub default: Option, pub stream: Option, + pub endpoint: Option, + pub port: Option, pub rate_limits: Option, } diff --git a/crates/llm_gateway/src/stream_context.rs b/crates/llm_gateway/src/stream_context.rs index 6cbd6c23..292d8a70 100644 --- a/crates/llm_gateway/src/stream_context.rs +++ b/crates/llm_gateway/src/stream_context.rs @@ -80,7 +80,7 @@ impl StreamContext { fn select_llm_provider(&mut self) { let provider_hint = self .get_http_request_header(ARCH_PROVIDER_HINT_HEADER) - .map(|provider_name| provider_name.into()); + .map(|llm_name| llm_name.into()); debug!("llm provider hint: {:?}", provider_hint); self.llm_provider = Some(routing::get_llm_provider( @@ -174,10 +174,22 @@ impl HttpContext for StreamContext { // the lifecycle of the http request and response. fn on_http_request_headers(&mut self, _num_headers: usize, _end_of_stream: bool) -> Action { self.select_llm_provider(); - self.add_http_request_header(ARCH_ROUTING_HEADER, &self.llm_provider().name); + + // 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() { + 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() { - self.send_server_error(error, Some(StatusCode::BAD_REQUEST)); + // 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)); + } } self.delete_content_length_header(); self.save_ratelimit_header(); @@ -385,11 +397,13 @@ impl HttpContext for StreamContext { self.llm_provider().name.to_string(), ); - llm_span.add_event(Event::new( - "time_to_first_token".to_string(), - self.ttft_time.unwrap(), - )); - trace_data.add_span(llm_span); + if self.ttft_time.is_some() { + llm_span.add_event(Event::new( + "time_to_first_token".to_string(), + self.ttft_time.unwrap(), + )); + trace_data.add_span(llm_span); + } self.traces_queue.lock().unwrap().push_back(trace_data); } diff --git a/crates/llm_gateway/tests/integration.rs b/crates/llm_gateway/tests/integration.rs index cbaedad3..7a74dfa8 100644 --- a/crates/llm_gateway/tests/integration.rs +++ b/crates/llm_gateway/tests/integration.rs @@ -23,11 +23,15 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { Some("x-arch-llm-provider-hint"), ) .returning(Some("default")) - .expect_log(Some(LogLevel::Debug), None) + .expect_log( + Some(LogLevel::Debug), + Some("llm provider hint: Some(Default)"), + ) + .expect_log(Some(LogLevel::Debug), Some("selected llm: open-ai-gpt-4")) .expect_add_header_map_value( Some(MapType::HttpRequestHeaders), Some("x-arch-llm-provider"), - Some("open-ai-gpt-4"), + Some("openai"), ) .expect_replace_header_map_value( Some(MapType::HttpRequestHeaders), @@ -46,8 +50,6 @@ fn request_headers_expectations(module: &mut Tester, http_context: i32) { .returning(None) .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::Debug), None) .expect_get_header_map_value(Some(MapType::HttpRequestHeaders), Some("x-request-id")) .returning(None) @@ -110,12 +112,12 @@ endpoints: llm_providers: - name: open-ai-gpt-4 - provider: openai + provider_interface: openai access_key: secret_key model: gpt-4 default: true - name: open-ai-gpt-4o - provider: openai + provider_interface: openai access_key: secret_key model: gpt-4o diff --git a/crates/prompt_gateway/src/stream_context.rs b/crates/prompt_gateway/src/stream_context.rs index ad93a0ba..7a8f84c3 100644 --- a/crates/prompt_gateway/src/stream_context.rs +++ b/crates/prompt_gateway/src/stream_context.rs @@ -263,6 +263,10 @@ impl StreamContext { ); } + // update prompt target name from the tool call + callout_context.prompt_target_name = + Some(self.tool_calls.as_ref().unwrap()[0].function.name.clone()); + self.schedule_api_call_request(callout_context); } @@ -359,8 +363,8 @@ impl StreamContext { let http_status = self .get_http_call_response_header(":status") .unwrap_or(StatusCode::OK.as_str().to_string()); - debug!("api_call_response_handler: http_status: {}", http_status); - if http_status != StatusCode::OK.as_str() { + debug!("api_call_response_handler: http_status: {}", http_status); + if http_status != StatusCode::OK.as_str() { warn!( "api server responded with non 2xx status code: {}", http_status diff --git a/crates/prompt_gateway/tests/integration.rs b/crates/prompt_gateway/tests/integration.rs index cb9054f3..1a6ed0e6 100644 --- a/crates/prompt_gateway/tests/integration.rs +++ b/crates/prompt_gateway/tests/integration.rs @@ -131,7 +131,7 @@ endpoints: llm_providers: - name: open-ai-gpt-4 - provider: openai + provider_interface: openai access_key: secret_key model: gpt-4 default: true diff --git a/demos/currency_exchange_ollama/README.md b/demos/currency_exchange_ollama/README.md new file mode 100644 index 00000000..ef121a75 --- /dev/null +++ b/demos/currency_exchange_ollama/README.md @@ -0,0 +1,3 @@ +This demo shows how you can use ollama as upstream LLM. + +Before you can start the demo please make sure you have ollama up and running. You can use command `ollama run llama3.2` to start llama 3.2 (3b) model locally at port `11434`. diff --git a/demos/currency_exchange_ollama/arch_config.yaml b/demos/currency_exchange_ollama/arch_config.yaml new file mode 100644 index 00000000..5936ff17 --- /dev/null +++ b/demos/currency_exchange_ollama/arch_config.yaml @@ -0,0 +1,53 @@ +version: v0.1 + +listener: + address: 0.0.0.0 + port: 10000 + message_format: huggingface + connect_timeout: 0.005s + +llm_providers: + - name: local-llama + provider_interface: openai + model: llama3.2 + endpoint: host.docker.internal:11434 + default: true + +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 for currency exchange. + +prompt_targets: + - name: currency_exchange + description: Get currency exchange rate from USD to other currencies + parameters: + - name: currency_symbol + description: the currency that needs conversion + required: true + type: str + in_path: true + endpoint: + name: frankfurther_api + path: /v1/latest?base=USD&symbols={currency_symbol} + system_prompt: | + You are a helpful assistant. Show me the currency symbol you want to convert from USD. + + - name: get_supported_currencies + description: Get list of supported currencies for conversion + endpoint: + name: frankfurther_api + path: /v1/currencies + +endpoints: + frankfurther_api: + endpoint: api.frankfurter.dev:443 + protocol: https + +tracing: + random_sampling: 100 + trace_arch_internal: true diff --git a/demos/currency_exchange_ollama/docker-compose.yaml b/demos/currency_exchange_ollama/docker-compose.yaml new file mode 100644 index 00000000..32e52c40 --- /dev/null +++ b/demos/currency_exchange_ollama/docker-compose.yaml @@ -0,0 +1,21 @@ +services: + 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" + volumes: + - ./arch_config.yaml:/app/arch_config.yaml + + jaeger: + build: + context: ../shared/jaeger + ports: + - "16686:16686" + - "4317:4317" + - "4318:4318" diff --git a/demos/currency_exchange_ollama/run_demo.sh b/demos/currency_exchange_ollama/run_demo.sh new file mode 100644 index 00000000..eb47dce6 --- /dev/null +++ b/demos/currency_exchange_ollama/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/docs/source/_static/img/arch_network_diagram_high_level.png b/docs/source/_static/img/arch_network_diagram_high_level.png new file mode 100644 index 00000000..8a66686f Binary files /dev/null and b/docs/source/_static/img/arch_network_diagram_high_level.png differ diff --git a/docs/source/conf.py b/docs/source/conf.py index 7151fee7..8359b195 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -13,9 +13,9 @@ from sphinxawesome_theme import ThemeOptions from sphinxawesome_theme.postprocess import Icons project = "Arch Docs" -copyright = "2024, Katanemo Labs, Inc" +copyright = "2025, Katanemo Labs, Inc" author = "Katanemo Labs, Inc" -release = " v0.1.7" +release = " v0.1.8" # -- 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 9bd78f1e..97188ab1 100644 --- a/docs/source/get_started/intro_to_arch.rst +++ b/docs/source/get_started/intro_to_arch.rst @@ -8,10 +8,13 @@ Engineered with purpose-built large language models (LLMs), Arch handles all the 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. -.. image:: /_static/img/arch-logo.png +.. figure:: /_static/img/arch_network_diagram_high_level.png :width: 100% :align: center + 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:** *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests diff --git a/docs/source/get_started/overview.rst b/docs/source/get_started/overview.rst index 60b63b1f..07a347af 100644 --- a/docs/source/get_started/overview.rst +++ b/docs/source/get_started/overview.rst @@ -7,6 +7,12 @@ Welcome to Arch, the intelligent prompt gateway designed to help developers buil 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. +.. figure:: /_static/img/arch_network_diagram_high_level.png + :width: 100% + :align: center + + High-level network flow of where Arch Gateway sits in your agentic stack. Designed for both ingress and egress prompt traffic. + Get Started ----------- diff --git a/docs/source/get_started/quickstart.rst b/docs/source/get_started/quickstart.rst index 1e572544..fd9f592c 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==0.1.7 + $ pip install archgw==0.1.8 Build AI Agent with Arch Gateway diff --git a/docs/source/guides/function_calling.rst b/docs/source/guides/function_calling.rst index cb09bc6b..036d0e00 100644 --- a/docs/source/guides/function_calling.rst +++ b/docs/source/guides/function_calling.rst @@ -61,21 +61,6 @@ Key Features Parallel & Multiple Perform both parallel and multiple function calling ========================= =============================================================== - -Supported Languages -~~~~~~~~~~~~~~~~~~~ -.. table:: - :width: 100% - - ========================= =========================================================================================================================================== - **Language** **Data Type** - ========================= =========================================================================================================================================== - Python ``int``, ``str``, ``float``, ``bool``, ``list``, ``set``, ``dict``, ``tuple`` - Java ``byte``, ``short``, ``int``, ``long``, ``float``, ``double``, ``boolean``, ``char``, ``Array``, ``ArrayList``, ``Set``, ``HashMap``, ``Hashtable``, ``Queue``, ``Stack`` - Javascript ``Number``, ``Bigint``, ``String``, ``Boolean``, ``Object``, ``Array``, ``Date`` - ========================= =========================================================================================================================================== - - Implementing Function Calling ----------------------------- @@ -86,7 +71,6 @@ Step 1: Define the Function First, create or identify the backend function you want Arch to call. This could be an API endpoint, a script, or any other executable backend logic. .. code-block:: python - :caption: Example Function import requests @@ -136,63 +120,21 @@ Specify the parameters your function needs and how Arch should interpret these. Step 3: Arch Takes Over ~~~~~~~~~~~~~~~~~~~~~~~ -Once you have defined the functions and configured the prompt targets, Arch takes care of the remaining work. -It will automatically validate parameters validate parameters and ensure that the required parameters (e.g., location) are present in the prompt, and add validation rules if necessary. -Here is ane example validation schema using the `jsonschema `_ library +Once you have defined the functions and configured the prompt targets, Arch Gateway takes care of the remaining work. +It will automatically validate parameters, and ensure that the required parameters (e.g., location) are present in the prompt, and add validation rules if necessary. -.. code-block:: python - :caption: Example Validation Schema +.. figure:: /_static/img/arch_network_diagram_high_level.png + :width: 100% + :align: center - import requests - from jsonschema import validate, ValidationError - - # Define the JSON Schema for parameter validation - weather_validation_schema = { - "type": "object", - "properties": { - "location": { - "type": "string", - "minLength": 1, - "description": "The city and state, e.g. 'San Francisco, New York'" - }, - "unit": { - "type": "string", - "enum": ["celsius", "fahrenheit"], - "description": "The unit of temperature to return" - } - }, - "required": ["location"], - "additionalProperties": False - } - - def get_weather(location: str, unit: str = "fahrenheit"): - # Create the data object for validation - params = { - "location": location, - "unit": unit - } - - # Validate parameters using JSON Schema - try: - validate(instance=params, schema=weather_validation_schema) - except ValidationError as e: - raise ValueError(f"Invalid input: {e.message}") - - # Prepare the API request - api_server = "https://api.yourweatherapp.com" - endpoint = f"{api_server}/weather" - - # Make the API request - response = requests.get(endpoint, params=params) - return response.json() - - # Example usage - weather_info = get_weather("Seattle, WA", "celsius") - print(weather_info) + High-level network flow of where Arch Gateway sits in your agentic stack. Managing incoming and outgoing prompt traffic -Once the functions are called, Arch formats the response and deliver back to users. -By completing these setup steps, you enable Arch to manage the process from validation to response, ensuring users receive consistent, reliable results. +Once a downstream function (API) is called, Arch Gateway takes the response and sends it an upstream LLM to complete the request (for summarization, Q/A, text generation tasks). +For more details on how Arch Gateway enables you to centralize usage of LLMs, please read :ref:`LLM providers `. + +By completing these steps, you enable Arch to manage the process from validation to response, ensuring users receive consistent, reliable results - and that you are focused +on the stuff that matters most. Example Use Cases ----------------- diff --git a/docs/source/resources/includes/arch_config_full_reference.yaml b/docs/source/resources/includes/arch_config_full_reference.yaml index 291f68e5..f21fc1f5 100644 --- a/docs/source/resources/includes/arch_config_full_reference.yaml +++ b/docs/source/resources/includes/arch_config_full_reference.yaml @@ -31,7 +31,7 @@ endpoints: # Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way llm_providers: - name: OpenAI - provider: openai + provider_interface: openai access_key: $OPENAI_API_KEY model: gpt-4o default: true @@ -46,12 +46,12 @@ llm_providers: unit: minute - name: Mistral8x7b - provider: mistral + provider_interface: openai access_key: $MISTRAL_API_KEY model: mistral-8x7b - name: MistralLocal7b - provider: local + provider_interface: openai model: mistral-7b-instruct endpoint: mistral_local diff --git a/model_server/poetry.lock b/model_server/poetry.lock index feb420a7..c08f77ca 100644 --- a/model_server/poetry.lock +++ b/model_server/poetry.lock @@ -54,6 +54,7 @@ files = [ ] [package.dependencies] +exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} idna = ">=2.8" sniffio = ">=1.1" typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""} @@ -74,6 +75,9 @@ files = [ {file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"}, ] +[package.dependencies] +typing-extensions = {version = ">=4", markers = "python_version < \"3.11\""} + [package.extras] tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"] @@ -264,6 +268,20 @@ files = [ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, ] +[[package]] +name = "exceptiongroup" +version = "1.2.2" +description = "Backport of PEP 654 (exception groups)" +optional = false +python-versions = ">=3.7" +files = [ + {file = "exceptiongroup-1.2.2-py3-none-any.whl", hash = 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"b8e46140dfec3638e577f0e40f6f46dfc35d46390fb63e7ac687323009f2dbce" diff --git a/model_server/pyproject.toml b/model_server/pyproject.toml index 351fb482..63c5a045 100644 --- a/model_server/pyproject.toml +++ b/model_server/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "archgw_modelserver" -version = "0.1.7" +version = "0.1.8" description = "A model server for serving models" authors = ["Katanemo Labs, Inc "] license = "Apache 2.0" @@ -10,17 +10,15 @@ packages = [ ] [tool.poetry.dependencies] -python = "^3.12" +python = "^3.10" fastapi = "0.115.0" torch = "2.4.1" uvicorn = "0.31.0" -transformers = "*" -pyyaml = "6.0.2" -accelerate = "*" -psutil = "6.0.0" -pandas = "*" +transformers = "^4.37.0" +accelerate = "^1.0.0" +pydantic = "^2.10.1" dateparser = "*" -openai = "1.50.2" +openai = "^1.50.2" httpx = "0.27.2" # https://community.openai.com/t/typeerror-asyncclient-init-got-an-unexpected-keyword-argument-proxies/1040287 pytest-asyncio = "*" pytest = "*" @@ -33,7 +31,7 @@ pytest-retry = "^1.6.3" pytest-httpserver = "^1.1.0" [tool.poetry.scripts] -archgw_modelserver = "src.cli:run_server" +archgw_modelserver = "src.cli:main" [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/model_server/src/cli.py b/model_server/src/cli.py index 89fd82c0..5245873e 100644 --- a/model_server/src/cli.py +++ b/model_server/src/cli.py @@ -1,22 +1,17 @@ import importlib -import logging -from os import path import os -from signal import SIGKILL import sys import subprocess import argparse +import signal import tempfile import time - import requests -logging.basicConfig( - level=logging.INFO, - format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", -) +import src.commons.utils as utils -logger = logging.getLogger(__name__) + +logger = utils.get_model_server_logger() def get_version(): @@ -42,76 +37,9 @@ def wait_for_health_check(url, timeout=300): return False -def parse_args(): - parser = argparse.ArgumentParser(description="Manage the Uvicorn server.") - parser.add_argument( - "action", - choices=["start", "stop", "restart"], - default="start", - nargs="?", - help="Action to perform on the server (default: start).", - ) - parser.add_argument( - "--port", - type=int, - default=51000, - help="Port number for the server (default: 51000).", - ) - - parser.add_argument( - "--foreground", - default=False, - action="store_true", - help="Run the server in the foreground (default: False).", - ) - - return parser.parse_args() - - def get_pid_file(): temp_dir = tempfile.gettempdir() - return path.join(temp_dir, "model_server.pid") - - -def stop_server(): - """Stop the Uvicorn server.""" - pid_file = get_pid_file() - if os.path.exists(pid_file): - logger.info(f"PID file found, shutting down the server.") - # read pid from file - with open(pid_file, "r") as f: - pid = int(f.read()) - logger.info(f"Killing model server {pid}") - try: - os.kill(pid, SIGKILL) - except ProcessLookupError: - logger.info(f"Process {pid} not found") - os.remove(pid_file) - else: - logger.info("No PID file found, server is not running.") - - -def restart_server(port=51000, foreground=False): - """Restart the Uvicorn server.""" - stop_server() - start_server(port, foreground) - - -def run_server(): - """Start, stop, or restart the Uvicorn server based on command-line arguments.""" - - args = parse_args() - action = args.action - - if action == "start": - start_server(args.port, args.foreground) - elif action == "stop": - stop_server() - elif action == "restart": - restart_server(args.port, args.foreground) - else: - logger.info(f"Unknown action: {action}") - sys.exit(1) + return os.path.join(temp_dir, "model_server.pid") def ensure_killed(process): @@ -131,7 +59,7 @@ def ensure_killed(process): def start_server(port=51000, foreground=False): """Start the Uvicorn server.""" - logging.info("model server version: %s", get_version()) + logger.info("model server version: %s", get_version()) stop_server() @@ -196,6 +124,57 @@ def start_server(port=51000, foreground=False): ensure_killed(process) +def stop_server(): + """Stop the Uvicorn server.""" + + pid_file = get_pid_file() + if os.path.exists(pid_file): + logger.info("PID file found, shutting down the server.") + # read pid from file + with open(pid_file, "r") as f: + pid = int(f.read()) + logger.info(f"Killing model server {pid}") + try: + os.kill(pid, signal.SIGKILL) + except ProcessLookupError: + logger.info(f"Process {pid} not found") + os.remove(pid_file) + else: + logger.info("No PID file found, server is not running.") + + +def restart_server(port=51000, foreground=False): + """Restart the Uvicorn server.""" + stop_server() + start_server(port, foreground) + + +def parse_args(): + parser = argparse.ArgumentParser(description="Manage the Uvicorn server.") + parser.add_argument( + "action", + choices=["start", "stop", "restart"], + default="start", + nargs="?", + help="Action to perform on the server (default: start).", + ) + parser.add_argument( + "--port", + type=int, + default=51000, + help="Port number for the server (default: 51000).", + ) + + parser.add_argument( + "--foreground", + default=False, + action="store_true", + help="Run the server in the foreground (default: False).", + ) + + return parser.parse_args() + + def main(): """ Start, stop, or restart the Uvicorn server based on command-line arguments. @@ -204,11 +183,14 @@ def main(): args = parse_args() if args.action == "start": + logger.info("[CLI] - Starting server") start_server(args.port, args.foreground) elif args.action == "stop": + logger.info("[CLI] - Stopping server") stop_server() elif args.action == "restart": + logger.info("[CLI] - Restarting server") restart_server(args.port) else: - logger.error(f"Unknown action: {args.action}") + logger.error(f"[CLI] - Unknown action: {args.action}") sys.exit(1) diff --git a/model_server/src/commons/globals.py b/model_server/src/commons/globals.py index 46ac1fef..68c2e53a 100644 --- a/model_server/src/commons/globals.py +++ b/model_server/src/commons/globals.py @@ -22,9 +22,7 @@ ARCH_CLIENT = OpenAI(base_url=ARCH_ENDPOINT, api_key=ARCH_API_KEY) # Define model names ARCH_INTENT_MODEL_ALIAS = "Arch-Intent" ARCH_FUNCTION_MODEL_ALIAS = "Arch-Function" - -logger.info("loading prompt guard model ...") -arch_guard_model = get_guardrail_handler() +ARCH_GUARD_MODEL_ALIAS = "katanemo/Arch-Guard" # Define model handlers handler_map = { @@ -34,5 +32,5 @@ handler_map = { "Arch-Function": ArchFunctionHandler( ARCH_CLIENT, ARCH_FUNCTION_MODEL_ALIAS, ArchFunctionConfig ), - "Arch-Guard": arch_guard_model, + "Arch-Guard": get_guardrail_handler(ARCH_GUARD_MODEL_ALIAS), } diff --git a/model_server/src/commons/utils.py b/model_server/src/commons/utils.py index fff7911d..76e46d13 100644 --- a/model_server/src/commons/utils.py +++ b/model_server/src/commons/utils.py @@ -1,87 +1,50 @@ -import os -import sys -import time +import torch import logging -import requests -import subprocess -import importlib + +from datetime import datetime -PROJ_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) - - -# Default log directory and file -DEFAULT_LOG_DIR = os.path.join(PROJ_DIR, ".logs") -DEFAULT_LOG_FILE = "modelserver.log" - - -def get_model_server_logger(log_dir=None, log_file=None): +def get_model_server_logger(): """ Get or initialize the logger instance for the model server. - Parameters: - - log_dir (str): Custom directory to store the log file. Defaults to `./.logs`. - - log_file (str): Custom log file name. Defaults to `modelserver.log`. - Returns: - logging.Logger: Configured logger instance. """ - log_dir = log_dir or DEFAULT_LOG_DIR - log_file = log_file or DEFAULT_LOG_FILE - log_file_path = os.path.join(log_dir, log_file) # Check if the logger is already configured - logger = logging.getLogger("model_server_logger") + logger = logging.getLogger("model_server") + + # Return existing logger instance if already configured if logger.hasHandlers(): - # Return existing logger instance if already configured return logger - # Ensure the log directory exists, create it if necessary - try: - # Create directory if it doesn't exist - os.makedirs(log_dir, exist_ok=True) - - # Check for write permissions - if not os.access(log_dir, os.W_OK): - raise PermissionError(f"No write permission for the directory: {log_dir}") - except (PermissionError, OSError) as e: - raise RuntimeError(f"Failed to initialize logger: {e}") - - # Configure logging to file + # Configure logging to only log to console logging.basicConfig( level=logging.INFO, - format="%(asctime)s - %(levelname)s - %(message)s", - handlers=[ - # logging.FileHandler(log_file_path, mode="w"), # Overwrite logs in the file - logging.StreamHandler(), # Also log to console - ], + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", + handlers=[logging.StreamHandler()], ) return logger -logger = get_model_server_logger() - -logging.info("initializing torch device ...") -import torch - - def get_device(): - available_device = { - "cpu": True, - "cuda": torch.cuda.is_available(), - "mps": ( - torch.backends.mps.is_available() - if hasattr(torch.backends, "mps") - else False - ), - } - - if available_device["cuda"]: + if torch.cuda.is_available(): device = "cuda" - elif available_device["mps"]: + elif torch.backends.mps.is_available(): device = "mps" else: device = "cpu" return device + + +def get_today_date(): + # Get today's date + today = datetime.now() + + # Get full date with day of week + full_date = today.strftime("%Y-%m-%d") + + return full_date diff --git a/model_server/src/core/function_calling.py b/model_server/src/core/function_calling.py index e29dd3f1..25c83818 100644 --- a/model_server/src/core/function_calling.py +++ b/model_server/src/core/function_calling.py @@ -1,22 +1,24 @@ +import ast import json import random import builtins import textwrap +import src.commons.utils as utils from openai import OpenAI from typing import Any, Dict, List from overrides import override -from src.commons.utils import get_model_server_logger -from src.core.model_utils import ( +from src.core.utils.hallucination_utils import HallucinationState +from src.core.utils.model_utils import ( Message, ChatMessage, Choice, ChatCompletionResponse, ArchBaseHandler, ) -from src.core.hallucination import HallucinationStateHandler -logger = get_model_server_logger() + +logger = utils.get_model_server_logger() class ArchIntentConfig: @@ -74,7 +76,6 @@ class ArchIntentHandler(ArchBaseHandler): ) self.extra_instruction = config.EXTRA_INSTRUCTION - self.prompt_prefilling = False @override def _convert_tools(self, tools: List[Dict[str, Any]]) -> str: @@ -122,15 +123,19 @@ class ArchIntentHandler(ArchBaseHandler): 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]: {json.dumps(messages)}") + model_response = self.client.chat.completions.create( messages=messages, model=self.model_name, @@ -138,9 +143,7 @@ class ArchIntentHandler(ArchBaseHandler): extra_body=self.generation_params, ) - logger.info( - "arch_intent response: %s", json.dumps(model_response.model_dump()) - ) + logger.info(f"[response]: {json.dumps(model_response.model_dump())}") model_response = Message( content=model_response.choices[0].message.content, tool_calls=[] @@ -160,7 +163,11 @@ class ArchFunctionConfig: TASK_PROMPT = textwrap.dedent( """ You are a helpful assistant. - """ + + Today's date: {} + """.format( + utils.get_today_date() + ) ).strip() TOOL_PROMPT_TEMPLATE = textwrap.dedent( @@ -189,7 +196,7 @@ class ArchFunctionConfig: "temperature": 0.6, "top_p": 1.0, "top_k": 10, - "max_tokens": 512, + "max_tokens": 1024, "stop_token_ids": [151645], "logprobs": True, "top_logprobs": 10, @@ -241,10 +248,11 @@ class ArchFunctionHandler(ArchBaseHandler): self.prefill_params = config.PREFILL_CONFIG["prefill_params"] self.prefill_prefix = config.PREFILL_CONFIG["prefill_prefix"] - self.prompt_prefilling = False + + self.hallucination_state = None # Predefine data types for verification. Only support Python for now. - # [TODO] Extend the list of support data types + # TODO: Extend the list of support data types self.support_data_types = { type_name: getattr(builtins, type_name) for type_name in config.SUPPORT_DATA_TYPES @@ -365,15 +373,15 @@ class ArchFunctionHandler(ArchBaseHandler): return {"result": tool_calls, "status": is_valid, "message": error_message} - def _correcting_type(self, value, target_type): + def _convert_data_type(self, value: str, target_type: str): + # TODO: Add more conversion rules as needed try: - if target_type == float and isinstance(value, int): + if target_type is float and isinstance(value, int): return float(value) - elif target_type == list and isinstance(value, str): + elif target_type is list and isinstance(value, str): return ast.literal_eval(value) - elif target_type == str and not isinstance(value, str): + elif target_type is str and not isinstance(value, str): return str(value) - # Add more conversion rules as needed except (ValueError, TypeError, json.JSONDecodeError): pass return value @@ -426,32 +434,34 @@ class ArchFunctionHandler(ArchBaseHandler): break # Verify the data type of each parameter in the tool calls + function_properties = functions[func_name]["properties"] + for param_name in func_args: - if param_name not in functions[func_name]["properties"]: + 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}`." break else: param_value = func_args[param_name] - data_type = functions[func_name]["properties"][param_name][ - "type" - ] + target_type = function_properties[param_name]["type"] - if data_type in self.support_data_types: - if not isinstance( - param_value, - self.support_data_types[data_type], - ) and not isinstance( - self._correcting_type( - param_value, self.support_data_types[data_type] - ), - self.support_data_types[data_type], - ): - is_valid = False - invalid_tool_call = tool_call - error_message = f"Parameter `{param_name}` is expected to have the data type `{self.support_data_types[data_type]}`, but got `{type(param_value)}`." - break + if target_type in self.support_data_types: + data_type = self.support_data_types[target_type] + + if not isinstance(param_value, data_type): + param_value = self._convert_data_type( + 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)}`." + break + else: + error_message = ( + f"Data type `{target_type}` is not supported." + ) return { "status": is_valid, @@ -491,51 +501,8 @@ class ArchFunctionHandler(ArchBaseHandler): **self.prefill_params, }, ) - self.prompt_prefilling = True return prefill_response - def _check_length_and_pop_messages(self, messages, max_tokens=4096): - """ - Trims the `messages` list to ensure the total token count does not exceed `max_tokens`. - - Args: - messages (list): List of message dictionaries. - max_tokens (int): Maximum allowed token count. - - Returns: - list: Trimmed list of messages. - """ - - def estimate_token_length(messages): - """Estimate the total token length of the messages.""" - total_tokens = 0 - for message in messages: - # Approximate token length: assuming ~4 characters per token on average - total_tokens += len(message["content"]) // 4 - return total_tokens - - # Calculate initial token length - total_tokens = estimate_token_length(messages) - - # Trim messages if token count exceeds the limit - while total_tokens > max_tokens and len(messages) >= 3: - # Find the first non-system message pair - for i in range(len(messages)): - if messages[i]["role"] != "system": - # Remove the 'user'/'assistant' pair - if i + 1 < len(messages) and messages[i + 1]["role"] in [ - "user", - "assistant", - ]: - del messages[i : i + 2] - else: - del messages[i] - break - # Recalculate token length - total_tokens = estimate_token_length(messages) - - return messages - @override async def chat_completion(self, req: ChatMessage) -> ChatCompletionResponse: """ @@ -550,13 +517,11 @@ class ArchFunctionHandler(ArchBaseHandler): Note: Currently only support vllm inference """ - - logger.info( - f"model_server => arch_function: request body: {json.dumps(req.model_dump())}" - ) + logger.info("[Arch-Function] - ChatCompletion") messages = self._process_messages(req.messages, req.tools) - messages = self._check_length_and_pop_messages(messages) + + logger.info(f"[request]: {json.dumps(messages)}") # always enable `stream=True` to collect model responses response = self.client.chat.completions.create( @@ -567,45 +532,39 @@ class ArchFunctionHandler(ArchBaseHandler): ) # initialize the hallucination handler, which is an iterator - self.hallu_handler = HallucinationStateHandler( + self.hallucination_state = HallucinationState( response_iterator=response, function=req.tools ) - model_response, self.has_tool_call = "", None - self.hallucination = False - for _ in self.hallu_handler: + model_response = "" + + has_tool_calls, has_hallucination = None, False + for _ in self.hallucination_state: # check if the first token is - if len(self.hallu_handler.tokens) > 0 and self.has_tool_call is None: - if self.hallu_handler.tokens[0] == "": - self.has_tool_call = True + if len(self.hallucination_state.tokens) > 0 and has_tool_calls is None: + if self.hallucination_state.tokens[0] == "": + has_tool_calls = True else: - self.has_tool_call = False + has_tool_calls = False break # if the model is hallucinating, start parameter gathering - if self.hallu_handler.hallucination is True: - self.hallucination = True - logger.info( - f"{self.hallu_handler.error_message} - start parameter gathering" - ) - logger.info( - f"Hallucinated response : {''.join(self.hallu_handler.tokens)}" - ) - # [TODO] - add break when hallucination is detected + if self.hallucination_state.hallucination is True: + has_hallucination = True break - if self.hallucination is True: - prefill_response = self._engage_parameter_gathering(messages) - model_response = prefill_response.choices[0].message.content - if self.has_tool_call and self.hallucination is False: - # [TODO] - Review: remove the following code - - model_response = "".join(self.hallu_handler.tokens) - logger.info(f"Tool call found, no hallucination detected {model_response}!") - # start parameter gathering if the model is not generating tool calls - if self.has_tool_call is False: - # [TODO] - Review: remove the following code - logger.info("No tool call found, start parameter gathering") + 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 @@ -613,21 +572,20 @@ class ArchFunctionHandler(ArchBaseHandler): extracted = self._extract_tool_calls(model_response) if len(extracted["result"]) and extracted["status"]: - # [TODO] Review: define the behavior in the case that tool call extraction fails - # if not extracted["status"]: verified = self._verify_tool_calls( tools=req.tools, tool_calls=extracted["result"] ) - # [TODO] - Review: remvoe the following code - # print(f"[Verified] - {verified}") - # [TODO] Review: In the case that tool calls are invalid, define the protocol to collect debugging output and the behavior to handle it appropriately 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"]) - log_message = f"model_server <= arch_function: (tool_calls): {json.dumps([tool_call['function'] for tool_call in extracted['result']])}" - logger.info(log_message) else: - raise ValueError(f"Invalid tool call: {verified['message']}") + logger.error(f"Invalid tool call - {verified['message']}") + # raise ValueError( + # f"[Arch-Function]: Invalid tool call - {verified['message']}" + # ) else: model_response = Message(content=model_response, tool_calls=[]) @@ -635,10 +593,6 @@ class ArchFunctionHandler(ArchBaseHandler): choices=[Choice(message=model_response)], model=self.model_name ) - # [TODO] Review: define the protocol to collect debugging output - - logger.info( - f"model_server <= arch_function: response body: {json.dumps(chat_completion_response.model_dump())}" - ) + logger.info(f"[response]: {json.dumps(chat_completion_response.model_dump())}") return chat_completion_response diff --git a/model_server/src/core/guardrails.py b/model_server/src/core/guardrails.py index 33fe38f7..0d2f34fc 100644 --- a/model_server/src/core/guardrails.py +++ b/model_server/src/core/guardrails.py @@ -1,12 +1,12 @@ -import time import torch import numpy as np import src.commons.utils as utils -from transformers import AutoTokenizer -from src.core.model_utils import GuardRequest, GuardResponse -# from optimum.intel import OVModelForSequenceClassification -from transformers import AutoModelForSequenceClassification +from transformers import AutoTokenizer, AutoModelForSequenceClassification +from src.core.utils.model_utils import GuardRequest, GuardResponse + + +logger = utils.get_model_server_logger() class ArchGuardHanlder: @@ -76,26 +76,15 @@ class ArchGuardHanlder: text, truncation=True, max_length=max_length, return_tensors="pt" ).to(self.device) - start_time = time.perf_counter() - with torch.no_grad(): logits = self.model(**inputs).logits.cpu().detach().numpy()[0] prob = ArchGuardHanlder.softmax(logits)[ self.support_tasks[task]["positive_class"] - ] + ].item() - latency = time.perf_counter() - start_time + verdict = prob > self.support_tasks[task]["threshold"] - if prob > self.support_tasks[task]["threshold"]: - verdict = True - sentence = text - else: - verdict = False - sentence = None - - return GuardResponse( - prob=[prob.item()], verdict=verdict, sentence=[sentence], latency=latency - ) + return GuardResponse(task=task, input=text, prob=prob, verdict=verdict) def predict(self, req: GuardRequest, max_num_words=300) -> GuardResponse: """ @@ -115,29 +104,37 @@ class ArchGuardHanlder: if req.task not in self.support_tasks: raise NotImplementedError(f"{req.task} is not supported!") + logger.info("[Arch-Guard] - Prediction") + logger.info(f"[request]: {req.input}") + if len(req.input.split()) < max_num_words: - return self._predict_text(req.task, req.input) + result = self._predict_text(req.task, req.input) else: + prob, verdict = 0.0, False + # split into chunks if text is long text_chunks = self._split_text_into_chunks(req.input) - prob, verdict, sentence, latency = [], False, [], 0 - for chunk in text_chunks: chunk_result = self._predict_text(req.task, chunk) if chunk_result.verdict: - prob.append(chunk_result.prob[0]) + prob = chunk_result.prob verdict = True - sentence.append(chunk_result.sentence[0]) - latency += chunk_result.latency + break - return GuardResponse( - prob=prob, verdict=verdict, sentence=sentence, latency=latency + result = GuardResponse( + task=req.task, input=req.input, prob=prob, verdict=verdict ) + logger.info( + f"[response]: {req.task}: {'True' if result.verdict else 'False'} (prob: {result.prob:.2f})" + ) -def get_guardrail_handler(device: str = None): + return result + + +def get_guardrail_handler(model_name: str = "katanemo/Arch-Guard", device: str = None): """ Initializes and returns an instance of ArchGuardHanlder based on the specified device. @@ -151,19 +148,11 @@ def get_guardrail_handler(device: str = None): if device is None: device = utils.get_device() - model_class, model_name = None, None - # if device == "cpu": - # model_class = OVModelForSequenceClassification - # model_name = "katanemo/Arch-Guard-cpu" - # else: - model_class = AutoModelForSequenceClassification - model_name = "katanemo/Arch-Guard" - guardrail_dict = { "device": device, "model_name": model_name, "tokenizer": AutoTokenizer.from_pretrained(model_name, trust_remote_code=True), - "model": model_class.from_pretrained( + "model": AutoModelForSequenceClassification.from_pretrained( model_name, device_map=device, low_cpu_mem_usage=True ), } diff --git a/model_server/src/core/utils/__init__.py b/model_server/src/core/utils/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/model_server/src/core/hallucination.py b/model_server/src/core/utils/hallucination_utils.py similarity index 97% rename from model_server/src/core/hallucination.py rename to model_server/src/core/utils/hallucination_utils.py index a7b32e73..50006224 100644 --- a/model_server/src/core/hallucination.py +++ b/model_server/src/core/utils/hallucination_utils.py @@ -127,7 +127,7 @@ def is_parameter_property( return property_name in parameter_info -class HallucinationStateHandler: +class HallucinationState: """ A class to handle the state of hallucination detection in token processing. @@ -145,7 +145,7 @@ class HallucinationStateHandler: def __init__(self, response_iterator=None, function=None): """ - Initializes the HallucinationStateHandler with default values. + Initializes the HallucinationState with default values. """ self.tokens: List[str] = [] self.logprobs: List[float] = [] @@ -173,7 +173,7 @@ class HallucinationStateHandler: def _reset_parameters(self): """ - Resets all parameters in the HallucinationStateHandler to their default values. + Resets all parameters in the HallucinationState to their default values. """ self.state = None self.parameter_name_done = False @@ -268,7 +268,7 @@ class HallucinationStateHandler: # if the parameter name is done and the token is a parameter name start token, change the state elif ( self.parameter_name_done - and self.open_bracket == False + and not self.open_bracket and content.endswith(PARAMETER_NAME_START_PATTERN) ): self.state = "parameter_name" @@ -324,7 +324,7 @@ class HallucinationStateHandler: # if the state is parameter value and the token is an end token, change the state elif ( self.state == "parameter_value" - and self.open_bracket == False + and not self.open_bracket and content.endswith(PARAMETER_VALUE_END_TOKEN) ): self.state = None @@ -354,7 +354,7 @@ class HallucinationStateHandler: self.HALLUCINATION_THRESHOLD_DICT[self.mask[-1].value], ): self.hallucination = True - self.error_message = f"Hallucination: token '{self.tokens[-1]}' is uncertain. {self.token_probs_map}" + self.error_message = f"token '{self.tokens[-1]}' is uncertain. Generated response:\n{''.join(self.tokens)}" def _count_consecutive_token(self, token=MaskToken.PARAMETER_VALUE) -> int: """ diff --git a/model_server/src/core/model_utils.py b/model_server/src/core/utils/model_utils.py similarity index 77% rename from model_server/src/core/model_utils.py rename to model_server/src/core/utils/model_utils.py index 3f6b36b0..d971d115 100644 --- a/model_server/src/core/model_utils.py +++ b/model_server/src/core/utils/model_utils.py @@ -14,8 +14,8 @@ class Message(BaseModel): class ChatMessage(BaseModel): - messages: list[Message] - tools: List[Dict[str, Any]] + messages: List[Message] = [] + tools: List[Dict[str, Any]] = [] class Choice(BaseModel): @@ -28,8 +28,8 @@ class ChatCompletionResponse(BaseModel): id: Optional[int] = 0 object: Optional[str] = "chat_completion" created: Optional[str] = "" - choices: List[Choice] - model: str + choices: List[Choice] = [] + model: str = "" metadata: Optional[Dict[str, str]] = {} @@ -39,10 +39,11 @@ class GuardRequest(BaseModel): class GuardResponse(BaseModel): - prob: List - verdict: bool - sentence: List - latency: float = 0 + task: str = "" + input: str = "" + prob: float = 0.0 + verdict: bool = False + metadata: Optional[Dict[str, str]] = {} # ================================================================================================ @@ -121,6 +122,7 @@ class ArchBaseHandler: messages: List[Message], tools: List[Dict[str, Any]] = None, extra_instruction: str = None, + max_tokens=4096, ): """ Processes a list of messages and formats them appropriately. @@ -129,6 +131,7 @@ class ArchBaseHandler: messages (List[Message]): A list of message objects. tools (List[Dict[str, Any]], optional): A list of tools to include in the system prompt. extra_instruction (str, optional): Additional instructions to append to the last user message. + max_tokens (int): Maximum allowed token count, assuming ~4 characters per token on average. Returns: List[Dict[str, Any]]: A list of processed message dictionaries. @@ -149,14 +152,12 @@ class ArchBaseHandler: ) if tool_calls: - # [TODO] Extend to support multiple function calls + # TODO: Extend to support multiple function calls role = "assistant" content = f"\n{json.dumps(tool_calls[0]['function'])}\n" - elif message.role == "tool": + elif role == "tool": role = "user" - content = ( - f"\n{json.dumps(message.content)}\n" - ) + content = f"\n{json.dumps(content)}\n" processed_messages.append({"role": role, "content": content}) @@ -165,6 +166,23 @@ class ArchBaseHandler: if extra_instruction: processed_messages[-1]["content"] += 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]]): + num_tokens, conversation_idx = 0, 0 + if messages[0]["role"] == "system": + num_tokens += len(messages[0]["content"]) // 4 + conversation_idx = 1 + + for message_idx in range(len(messages) - 1, conversation_idx - 1, -1): + num_tokens += len(messages[message_idx]["content"]) // 4 + if num_tokens >= max_tokens: + if messages[message_idx]["role"] == "user": + break + + return messages[:conversation_idx] + messages[message_idx:] + + processed_messages = truncate_messages(processed_messages) + return processed_messages async def chat_completion(self, req: ChatMessage) -> ChatCompletionResponse: diff --git a/model_server/src/main.py b/model_server/src/main.py index b09e635c..74f60011 100644 --- a/model_server/src/main.py +++ b/model_server/src/main.py @@ -1,25 +1,25 @@ import json -import logging import os import time +import logging +import src.commons.utils as utils from src.commons.globals import handler_map -from src.core.model_utils import ChatMessage, GuardRequest +from src.core.utils.model_utils import ( + ChatMessage, + ChatCompletionResponse, + GuardRequest, + GuardResponse, +) from fastapi import FastAPI, Response from opentelemetry import trace from opentelemetry.sdk.trace import TracerProvider -from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor -from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter from opentelemetry.sdk.trace.export import BatchSpanProcessor from opentelemetry.sdk.resources import Resource +from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor +from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter -logging.basicConfig( - level=logging.INFO, - format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", -) - -logger = logging.getLogger(__name__) resource = Resource.create( { @@ -31,11 +31,6 @@ resource = Resource.create( trace.set_tracer_provider(TracerProvider(resource=resource)) tracer = trace.get_tracer(__name__) - -app = FastAPI() - -FastAPIInstrumentor().instrument_app(app) - # DEFAULT_OTLP_HOST = "http://localhost:4317" DEFAULT_OTLP_HOST = "none" @@ -47,6 +42,16 @@ otlp_exporter = OTLPSpanExporter( trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(otlp_exporter)) +logger = utils.get_model_server_logger() +logging.getLogger("httpx").setLevel(logging.ERROR) +logging.getLogger("opentelemetry.exporter.otlp.proto.grpc.exporter").setLevel( + logging.ERROR +) + +app = FastAPI() +FastAPIInstrumentor().instrument_app(app) + + @app.get("/healthz") async def healthz(): return {"status": "ok"} @@ -62,73 +67,78 @@ 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())}") + + final_response: ChatCompletionResponse = None + 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 if handler_map["Arch-Intent"].detect_intent(intent_response): - # [TODO] measure agreement between intent detection and function calling + # TODO: measure agreement between intent detection and function calling try: function_start_time = time.perf_counter() - function_calling_response = await handler_map[ - "Arch-Function" - ].chat_completion(req) + final_response = await handler_map["Arch-Function"].chat_completion(req) function_latency = time.perf_counter() - function_start_time - function_calling_response.metadata = { + + 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), - "tokens_uncertainty": json.dumps( - handler_map["Arch-Function"].hallu_handler.token_probs_map - ), - "prompt_prefilling": str( - handler_map["Arch-Function"].prompt_prefilling + "hallucination": str( + handler_map["Arch-Function"].hallucination_state.hallucination ), } - - return function_calling_response except ValueError as e: res.statuscode = 503 - error_message = "Tool call extraction error" - logger.error(f" {error_message}: {e}") - return {"error": f"[Arch-Function] - {error_message} - {e}"} + error_messages = f"[Arch-Function] - Error in tool call extraction: {e}" except StopIteration as e: res.statuscode = 500 - error_message = "Hallucination iterator error" - logger.error(f" {error_message}: {e}") - return {"error": f"[Arch-Function] - {error_message} - {e}"} + error_messages = f"[Arch-Function] - Error in hallucination check: {e}" except Exception as e: - # [TODO] Review: update how to collect debugging outputs - logger.error(f"Error in chat_completion from `Arch-Function`: {e}") res.status_code = 500 - return {"error": f"[Arch-Function] - {e}"} - # [TODO] Review: define the behavior if `Arch-Intent` doesn't detect an intent + error_messages = f"[Arch-Function] - Error in ChatCompletion: {e}" else: - return { - "result": "No intent matched", - "intent_latency": round(intent_latency * 1000, 3), + intent_response.metadata = { + "intent_latency": str(round(intent_latency * 1000, 3)), } + final_response = intent_response except Exception as e: - # [TODO] Review: update how to collect debugging outputs - # logger.error(f"Error in chat_completion from `Arch-Intent`: {e}") - logger.error(f"Error in chat_completion /function_calling: {e}") res.status_code = 500 - return {"error": f"[Arch-Intent] - {e}"} + error_messages = f"[Arch-Intent] - Error in ChatCompletion: {e}" + + if error_messages is not None: + logger.error(error_messages) + final_response = ChatCompletionResponse(metadata={"error": error_messages}) + + return final_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())}") + + final_response: GuardResponse = None + error_messages = None + try: guard_start_time = time.perf_counter() - guard_result = handler_map["Arch-Guard"].predict(req) + final_response = handler_map["Arch-Guard"].predict(req) guard_latency = time.perf_counter() - guard_start_time - return { - "response": guard_result, + final_response.metadata = { "guard_latency": round(guard_latency * 1000, 3), } except Exception as e: - # [TODO] Review: update how to collect debugging outputs res.status_code = 500 - return {"error": f"[Arch-Guard] - {e}"} + error_messages = f"[Arch-Guard]: {e}" + + if error_messages is not None: + logger.error(error_messages) + final_response = GuardResponse(metadata={"error": error_messages}) + + return final_response diff --git a/model_server/tests/core/test_function_calling.py b/model_server/tests/core/test_function_calling.py index 1f213bba..3f7971d8 100644 --- a/model_server/tests/core/test_function_calling.py +++ b/model_server/tests/core/test_function_calling.py @@ -1,12 +1,8 @@ -import os +import pytest from src.commons.globals import handler_map -from src.core.model_utils import ChatMessage, Message -import pytest -from fastapi.testclient import TestClient -from unittest.mock import AsyncMock, patch -from src.main import app -from src.commons.globals import handler_map +from src.core.utils.model_utils import ChatMessage, Message + # define function get_weather_api = { @@ -163,7 +159,10 @@ async def test_function_calling(get_data_func): function_calling_response = await handler_map["Arch-Function"].chat_completion( req ) - assert handler_map["Arch-Function"].hallu_handler.hallucination == hallucination + assert ( + handler_map["Arch-Function"].hallucination_state.hallucination + == hallucination + ) response_txt = function_calling_response.choices[0].message.content if parameter_gathering: diff --git a/model_server/tests/core/test_guardrails.py b/model_server/tests/core/test_guardrails.py index e8d8ec81..74d2dc97 100644 --- a/model_server/tests/core/test_guardrails.py +++ b/model_server/tests/core/test_guardrails.py @@ -1,33 +1,6 @@ from unittest.mock import patch, MagicMock from src.core.guardrails import get_guardrail_handler -# Mock constants -arch_guard_model_type = { - "cpu": "katanemo/Arch-Guard-cpu", - "cuda": "katanemo/Arch-Guard", - "mps": "katanemo/Arch-Guard", -} - - -# [TODO] Review: check the following code to test under `cpu`, `cuda`, and `mps` -# Test for `get_guardrail_handler()` function on `cpu` -@patch("src.core.guardrails.AutoTokenizer.from_pretrained") -@patch("src.core.guardrails.AutoModelForSequenceClassification.from_pretrained") -def test_guardrail_handler_on_cpu(mock_auto_model, mock_tokenizer): - device = "cpu" - - mock_tokenizer.return_value = MagicMock() - - guardrail = get_guardrail_handler(device=device) - - mock_tokenizer.assert_called_once_with(guardrail.model_name, trust_remote_code=True) - - mock_auto_model.assert_called_once_with( - guardrail.model_name, - device_map=device, - low_cpu_mem_usage=True, - ) - # Test for `get_guardrail_handler()` function on `cuda` @patch("src.core.guardrails.AutoTokenizer.from_pretrained") diff --git a/model_server/tests/test_app.py b/model_server/tests/test_app.py index 39d377f4..0029e4b5 100644 --- a/model_server/tests/test_app.py +++ b/model_server/tests/test_app.py @@ -8,7 +8,6 @@ from src.main import app client = TestClient(app) -# [TODO] Review: check the following code. Seems something wrong with asyncio package❗ # Unit tests for the health check endpoint @pytest.mark.asyncio async def test_healthz(): @@ -17,7 +16,6 @@ async def test_healthz(): assert response.json() == {"status": "ok"} -# [TODO] Review: check the following code. Seems something wrong with asyncio package❗ # Unit test for the models endpoint @pytest.mark.asyncio async def test_models(): @@ -27,17 +25,14 @@ async def test_models(): assert len(response.json()["data"]) > 0 -# [TODO] Review: check the following code. Seems something wrong with asyncio package❗ # Unit test for the guardrail endpoint @pytest.mark.asyncio async def test_guardrail_endpoint(): request_data = {"input": "Test for jailbreak and toxicity", "task": "jailbreak"} response = client.post("/guardrails", json=request_data) assert response.status_code == 200 - assert "response" in response.json() -# [TODO] Review: check the following code. 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-763,6 +811,7 @@ files = [ ] [package.dependencies] +exceptiongroup = {version = "*", markers = "python_version < \"3.11\""} trio = ">=0.11" wsproto = ">=0.14" @@ -779,13 +828,13 @@ files = [ [[package]] name = "urllib3" -version = "2.2.3" +version = "2.3.0" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" files = [ - {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"}, - {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"}, + {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"}, + {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"}, ] [package.dependencies] @@ -846,5 +895,5 @@ h11 = ">=0.9.0,<1" [metadata] lock-version = "2.0" -python-versions = "^3.12" -content-hash = "56e809b45f1e4d0ab865523472c7ea4587d1c4b2408ee62ec16d1507aecf0e1d" +python-versions = "^3.10" +content-hash = "d0ba3f1875425991d473c9b6fee9f9cb35de5df5835fd7f7e27e3863ff7d37fe" diff --git a/tests/modelserver/pyproject.toml b/tests/modelserver/pyproject.toml index c328d3c9..af13bfd5 100644 --- a/tests/modelserver/pyproject.toml +++ b/tests/modelserver/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/modelserver/test_hallucination.py b/tests/modelserver/test_hallucination.py index 67b487f8..f1a3d9b4 100644 --- a/tests/modelserver/test_hallucination.py +++ b/tests/modelserver/test_hallucination.py @@ -1,13 +1,9 @@ -import json import os import pytest import requests -from deepdiff import DeepDiff import logging import yaml -logger = logging.getLogger(__name__) -logger.setLevel(logging.DEBUG) MODEL_SERVER_ENDPOINT = os.getenv( "MODEL_SERVER_ENDPOINT", "http://localhost:51000/function_calling" @@ -37,13 +33,9 @@ def test_model_server(test_data): response = requests.post(MODEL_SERVER_ENDPOINT, json=input) assert response.status_code == 200 - # print(json.dumps(response.json())) - # ensure that response is json assert response.headers["content-type"] == "application/json" + response_json = response.json() assert response_json - metadata = response_json.get("metadata", []) + metadata = response_json.get("metadata", {}) assert (metadata["hallucination"].lower() == "true") == expected[0]["hallucination"] - assert (metadata["prompt_prefilling"].lower() == "true") == expected[0][ - "prompt_prefilling" - ] diff --git a/tests/modelserver/test_hallucination_data.yaml b/tests/modelserver/test_hallucination_data.yaml index 9223edfa..8e6e6b26 100644 --- a/tests/modelserver/test_hallucination_data.yaml +++ b/tests/modelserver/test_hallucination_data.yaml @@ -5,8 +5,7 @@ test_cases: - role: "user" content: "what is the weather forecast for seattle?" tools: - - id: "weather-112" - type: "function" + - type: "function" function: name: "get_current_weather" description: "Get current weather at a location." @@ -14,17 +13,18 @@ test_cases: type: "object" properties: location: - type: "str" + type: "string" description: "The location to get the weather for" format: "City, State" days: - type: "int" - description: "the number of days for the request." - required: ["location", "days"] + type: "integer" + description: "The number of days for the request." + required: + - location + - days expected: - - type: "metadata" - hallucination: false - prompt_prefilling: true + - type: "metadata" + hallucination: false - id: "[WEATHER AGENT] - single turn, single tool, hallucination" input: @@ -32,8 +32,7 @@ test_cases: - role: "user" content: "what is the weather in Seattle in days?" tools: - - id: "weather-112" - type: "function" + - type: "function" function: name: "get_current_weather" description: "Get current weather at a location." @@ -51,7 +50,6 @@ test_cases: expected: - type: "metadata" hallucination: true - prompt_prefilling: true - id: "[WEATHER AGENT] - multi turn, single tool, all params passed" input: @@ -85,8 +83,6 @@ test_cases: expected: - type: "metadata" hallucination: true - prompt_prefilling: true - - id: "[WEATHER AGENT] - multi turn, single tool, clarification" input: @@ -120,7 +116,7 @@ test_cases: expected: - type: "metadata" hallucination: false - prompt_prefilling: true + - id: "[SALE AGENT] - single turn, single tool, hallucination region" input: messages: @@ -148,7 +144,6 @@ test_cases: expected: - type: "metadata" hallucination: true - prompt_prefilling: true - id: "[SALE AGENT] - single turn, single tool, hallucination industry" input: @@ -177,7 +172,6 @@ test_cases: expected: - type: "metadata" hallucination: true - prompt_prefilling: true - id: "[PRODUCT AGENT] - single turn, single tool, hallucination industry" input: @@ -261,4 +255,3 @@ test_cases: expected: - type: "metadata" hallucination: true - prompt_prefilling: true diff --git a/tests/modelserver/test_modelserver.py b/tests/modelserver/test_modelserver.py index a8031993..75e6d27e 100644 --- a/tests/modelserver/test_modelserver.py +++ b/tests/modelserver/test_modelserver.py @@ -1,13 +1,10 @@ -import json import os import pytest import requests -from deepdiff import DeepDiff -import logging import yaml -logger = logging.getLogger(__name__) -logger.setLevel(logging.DEBUG) +from deepdiff import DeepDiff + MODEL_SERVER_ENDPOINT = os.getenv( "MODEL_SERVER_ENDPOINT", "http://localhost:51000/function_calling" diff --git a/tests/modelserver/test_success_data.yaml b/tests/modelserver/test_success_data.yaml index e34076a8..36e3dcfe 100644 --- a/tests/modelserver/test_success_data.yaml +++ b/tests/modelserver/test_success_data.yaml @@ -107,50 +107,51 @@ test_cases: location: "Los Angeles, CA" days: 5 - - id: "[WEATHER AGENT] - multi turn, single tool, infer param from context" - input: - messages: - - role: "user" - content: "how is the weather in chicago for next 5 days?" - - role: "assistant" - tool_calls: - - id: "call_3394" - type: "function" - function: - name: "get_current_weather" - arguments: - city: "Chicago, IL" - days: 5 - - role: "tool" - content: "--" - tool_call_id: "call_3394" - - role: "assistant" - content: "--" - - role: "user" - content: "how is the weather in LA?" - tools: - - type: "function" - function: - name: "get_current_weather" - description: "Get current weather at a location." - parameters: - type: "object" - properties: - location: - type: "str" - description: "The location to get the weather for" - format: "City, State" - days: - type: "int" - description: "the number of days for the request." - required: ["location", "days"] - expected: - - type: "function" - function: - name: "get_current_weather" - arguments: - location: "Los Angeles, CA" - days: 5 + # Skip! + # - id: "[WEATHER AGENT] - multi turn, single tool, infer param from context" + # input: + # messages: + # - role: "user" + # content: "how is the weather in chicago for next 5 days?" + # - role: "assistant" + # tool_calls: + # - id: "call_3394" + # type: "function" + # function: + # name: "get_current_weather" + # arguments: + # location: "Chicago, IL" + # days: 5 + # - role: "tool" + # content: "--" + # tool_call_id: "call_3394" + # - role: "assistant" + # content: "--" + # - role: "user" + # content: "how is the weather in LA?" + # tools: + # - type: "function" + # function: + # name: "get_current_weather" + # description: "Get current weather at a location." + # parameters: + # type: "object" + # properties: + # location: + # type: "str" + # description: "The location to get the weather for" + # format: "City, State" + # days: + # type: "int" + # description: "the number of days for the request." + # required: ["location", "days"] + # expected: + # - type: "function" + # function: + # name: "get_current_weather" + # arguments: + # location: "Los Angeles, CA" + # days: 5 - id: "[WEATHER AGENT] - multi turn, single tool, infer param from context 2nd try" input: diff --git a/tests/rest/api_model_server.rest b/tests/rest/api_model_server.rest index dea5e884..ed86fac3 100644 --- a/tests/rest/api_model_server.rest +++ b/tests/rest/api_model_server.rest @@ -15,7 +15,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": { "name": "get_current_weather", @@ -53,32 +52,30 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", - "type": "function", - "function": { - "name": "get_current_weather", - "description": "Get current weather at a location.", - "parameters": { - "type": "object", - "properties": { - "location": { - "type": "str", - "description": "The location to get the weather for", - "format": "City, State" - }, - "unit": { - "type": "str", - "description": "The unit to return the weather in.", - "enum": ["celsius", "fahrenheit"], - "default": "celsius" - }, - "days": { - "type": "str", - "description": "the number of days for the request." - } - }, - "required": ["location", "days"] + "type": "function", + "function": { + "name": "get_current_weather", + "description": "Get current weather at a location.", + "parameters": { + "type": "object", + "properties": { + "location": { + "type": "string", + "description": "The location to get the weather for", + "format": "City, State" + }, + "unit": { + "type": "string", + "description": "The unit to return the weather in.", + "enum": ["celsius", "fahrenheit"], + "default": "celsius" + }, + "days": { + "type": "string", + "description": "The number of days for the request." } + }, + "required": ["location", "days"] } } } @@ -87,6 +84,7 @@ Content-Type: application/json + ### talk to function calling endpoint POST {{model_server_endpoint}}/function_calling HTTP/1.1 Content-Type: application/json @@ -121,7 +119,7 @@ Content-Type: application/json } ### talk to Arch-Intent directly for completion -POST https://api.fc.archgw.com/v1/chat/completions HTTP/1.1 +POST {{archfc_endpoint}}/v1/chat/completions HTTP/1.1 Content-Type: application/json { @@ -212,7 +210,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": { "name": "weather_forecast", diff --git a/tests/rest/api_prompt_gateway.rest b/tests/rest/api_prompt_gateway.rest index 537b06ac..db06cafe 100644 --- a/tests/rest/api_prompt_gateway.rest +++ b/tests/rest/api_prompt_gateway.rest @@ -100,3 +100,17 @@ Content-Type: application/json ], "stream": true } + +### currency conversion test +POST {{prompt_endpoint}}/v1/chat/completions HTTP/1.1 +Content-Type: application/json + +{ + "model": "--", + "messages": [ + { + "role": "user", + "content": "can you please convert 100 jpy" + } + ] +} diff --git a/tests/rest/insurance_agent.rest b/tests/rest/insurance_agent.rest index 0ae0def1..225c7d8a 100644 --- a/tests/rest/insurance_agent.rest +++ b/tests/rest/insurance_agent.rest @@ -31,7 +31,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": { "name": "get_current_weather", @@ -103,7 +102,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": { "name": "get_current_weather", @@ -172,7 +170,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": { @@ -374,7 +371,6 @@ Content-Type: application/json ], "tools": [ { - "id": "weather-112", "type": "function", "function": {