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Code Issues Projects Releases Packages Wiki Activity Actions 3

Rename all arch references to plano (#745)

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* Rename all arch references to plano across the codebase

Complete rebrand from "Arch"/"archgw" to "Plano" including:
- Config files: arch_config_schema.yaml, workflow, demo configs
- Environment variables: ARCH_CONFIG_* → PLANO_CONFIG_*
- Python CLI: variables, functions, file paths, docker mounts
- Rust crates: config paths, log messages, metadata keys
- Docker/build: Dockerfile, supervisord, .dockerignore, .gitignore
- Docker Compose: volume mounts and env vars across all demos/tests
- GitHub workflows: job/step names
- Shell scripts: log messages
- Demos: Python code, READMEs, VS Code configs, Grafana dashboard
- Docs: RST includes, code comments, config references
- Package metadata: package.json, pyproject.toml, uv.lock

External URLs (docs.archgw.com, github.com/katanemo/archgw) left as-is.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Update remaining arch references in docs

- Rename RST cross-reference labels: arch_access_logging, arch_overview_tracing, arch_overview_threading → plano_*
- Update label references in request_lifecycle.rst
- Rename arch_config_state_storage_example.yaml → plano_config_state_storage_example.yaml
- Update config YAML comments: "Arch creates/uses" → "Plano creates/uses"
- Update "the Arch gateway" → "the Plano gateway" in configuration_reference.rst
- Update arch_config_schema.yaml reference in provider_models.py
- Rename arch_agent_router → plano_agent_router in config example

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix remaining arch references found in second pass

- config/docker-compose.dev.yaml: ARCH_CONFIG_FILE → PLANO_CONFIG_FILE,
  arch_config.yaml → plano_config.yaml, archgw_logs → plano_logs
- config/test_passthrough.yaml: container mount path
- tests/e2e/docker-compose.yaml: source file path (was still arch_config.yaml)
- cli/planoai/core.py: comment and log message
- crates/brightstaff/src/tracing/constants.rs: doc comment
- tests/{e2e,archgw}/common.py: get_arch_messages → get_plano_messages,
  arch_state/arch_messages variables renamed
- tests/{e2e,archgw}/test_prompt_gateway.py: updated imports and usages
- demos/shared/test_runner/{common,test_demos}.py: same renames
- tests/e2e/test_model_alias_routing.py: docstring
- .dockerignore: archgw_modelserver → plano_modelserver
- demos/use_cases/claude_code_router/pretty_model_resolution.sh: container name

Note: x-arch-* HTTP header values and Rust constant names intentionally
preserved for backwards compatibility with existing deployments.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Adil Hafeez 2026-02-13 15:16:56 -08:00 • committed by GitHub
parent 0557f7ff98
commit ba651aaf71
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
115 changed files with 504 additions and 505 deletions
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6
.dockerignore
View file

@ -33,8 +33,8 @@ cli/__pycache__/
cli/planoai/__pycache__/
# Python model server
archgw_modelserver/
arch_tools/
plano_modelserver/
plano_tools/
# Misc
*.md
@ -44,4 +44,4 @@ turbo.json
package.json
*.sh
!cli/build_cli.sh
arch_config.yaml_rendered
plano_config.yaml_rendered

2
.github/workflows/e2e_plano_tests.yml vendored
View file

@ -28,7 +28,7 @@ jobs:
python-version: ${{ matrix.python-version }}
cache: "pip" # auto-caches based on requirements files
- name: build arch docker image
- name: build plano docker image
run: |
cd ../../ && docker build -f Dockerfile . -t katanemo/plano -t katanemo/plano:0.4.6 -t katanemo/plano:latest

2
.github/workflows/e2e_test_currency_convert.yml vendored
View file

@ -38,7 +38,7 @@ jobs:
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 arch gateway and test dependencies
- name: install plano gateway and test dependencies
run: |
source venv/bin/activate
cd cli && echo "installing plano cli" && uv sync && uv tool install .

4
.github/workflows/e2e_test_preference_based_routing.yml vendored
View file

@ -22,7 +22,7 @@ jobs:
with:
python-version: "3.12"
- name: build arch docker image
- name: build plano docker image
run: |
docker build -f Dockerfile . -t katanemo/plano -t katanemo/plano:0.4.6
@ -38,7 +38,7 @@ jobs:
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 arch gateway and test dependencies
- name: install plano gateway and test dependencies
run: |
source venv/bin/activate
cd cli && echo "installing plano cli" && uv sync && uv tool install .

8
.github/workflows/validate_arch_config.yml → .github/workflows/validate_plano_config.yml vendored
View file

@ -1,4 +1,4 @@
name: arch config tests
name: plano config tests
on:
push:
@ -7,7 +7,7 @@ on:
pull_request:
jobs:
validate_arch_config:
validate_plano_config:
runs-on: ubuntu-latest
defaults:
run:
@ -22,10 +22,10 @@ jobs:
with:
python-version: "3.12"
- name: build arch docker image
- name: build plano docker image
run: |
docker build -f Dockerfile . -t katanemo/plano -t katanemo/plano:0.4.6
- name: validate arch config
- name: validate plano config
run: |
bash config/validate_plano_config.sh

14
.gitignore vendored
View file

@ -107,30 +107,30 @@ venv.bak/
# =========================================
# Arch
# Plano
cli/config
cli/build
# Archgw - Docs
# Plano - Docs
docs/build/
# Archgw - Demos
# Plano - Demos
demos/function_calling/ollama/models/
demos/function_calling/ollama/id_ed*
demos/function_calling/open-webui/
demos/function_calling/open-webui/
demos/shared/signoz/data
# Arch - Miscellaneous
# Plano - Miscellaneous
grafana-data
prom_data
arch_log/
arch_logs/
plano_log/
plano_logs/
crates/*/target/
crates/target/
build.log
archgw.log
plano.log
# Next.js / Turborepo
.next/

2
CLAUDE.md
View file

@ -96,7 +96,7 @@ Entry point: `cli/planoai/main.py`. Container lifecycle in `core.py`. Docker ope
### Configuration System (config/)
- `arch_config_schema.yaml` — JSON Schema (draft-07) for validating user config files
- `plano_config_schema.yaml` — JSON Schema (draft-07) for validating user config files
- `envoy.template.yaml` — Jinja2 template rendered into Envoy proxy config
- `supervisord.conf` — Process supervisor for Envoy + brightstaff in the container

2
Dockerfile
View file

@ -69,7 +69,7 @@ RUN uv run pip install --no-cache-dir .
COPY cli/planoai planoai/
COPY config/envoy.template.yaml .
COPY config/arch_config_schema.yaml .
COPY config/plano_config_schema.yaml .
COPY config/supervisord.conf /etc/supervisor/conf.d/supervisord.conf
COPY --from=wasm-builder /arch/target/wasm32-wasip1/release/prompt_gateway.wasm /etc/envoy/proxy-wasm-plugins/prompt_gateway.wasm

3
apps/www/src/lib/metadata.ts
View file

@ -115,7 +115,6 @@ export const siteConfig = {
// Brand (minimal, necessary)
"Plano AI",
"Plano gateway",
"Arch gateway",
],
authors: [{ name: "Katanemo", url: "https://github.com/katanemo/plano" }],
creator: "Katanemo",
@ -240,7 +239,7 @@ export const pageMetadata = {
"agentic AI",
"Plano blog",
"Plano blog posts",
"Arch gateway blog",
"Plano gateway blog",
],
}),

72
cli/planoai/config_generator.py
View file

@ -53,34 +53,34 @@ def validate_and_render_schema():
ENVOY_CONFIG_TEMPLATE_FILE = os.getenv(
"ENVOY_CONFIG_TEMPLATE_FILE", "envoy.template.yaml"
)
ARCH_CONFIG_FILE = os.getenv("ARCH_CONFIG_FILE", "/app/arch_config.yaml")
ARCH_CONFIG_FILE_RENDERED = os.getenv(
"ARCH_CONFIG_FILE_RENDERED", "/app/arch_config_rendered.yaml"
PLANO_CONFIG_FILE = os.getenv("PLANO_CONFIG_FILE", "/app/plano_config.yaml")
PLANO_CONFIG_FILE_RENDERED = os.getenv(
"PLANO_CONFIG_FILE_RENDERED", "/app/plano_config_rendered.yaml"
)
ENVOY_CONFIG_FILE_RENDERED = os.getenv(
"ENVOY_CONFIG_FILE_RENDERED", "/etc/envoy/envoy.yaml"
)
ARCH_CONFIG_SCHEMA_FILE = os.getenv(
"ARCH_CONFIG_SCHEMA_FILE", "arch_config_schema.yaml"
PLANO_CONFIG_SCHEMA_FILE = os.getenv(
"PLANO_CONFIG_SCHEMA_FILE", "plano_config_schema.yaml"
)
env = Environment(loader=FileSystemLoader(os.getenv("TEMPLATE_ROOT", "./")))
template = env.get_template(ENVOY_CONFIG_TEMPLATE_FILE)
try:
validate_prompt_config(ARCH_CONFIG_FILE, ARCH_CONFIG_SCHEMA_FILE)
validate_prompt_config(PLANO_CONFIG_FILE, PLANO_CONFIG_SCHEMA_FILE)
except Exception as e:
print(str(e))
exit(1) # validate_prompt_config failed. Exit
with open(ARCH_CONFIG_FILE, "r") as file:
arch_config = file.read()
with open(PLANO_CONFIG_FILE, "r") as file:
plano_config = file.read()
with open(ARCH_CONFIG_SCHEMA_FILE, "r") as file:
arch_config_schema = file.read()
with open(PLANO_CONFIG_SCHEMA_FILE, "r") as file:
plano_config_schema = file.read()
config_yaml = yaml.safe_load(arch_config)
_ = yaml.safe_load(arch_config_schema)
config_yaml = yaml.safe_load(plano_config)
_ = yaml.safe_load(plano_config_schema)
inferred_clusters = {}
# Convert legacy llm_providers to model_providers
@ -145,7 +145,7 @@ def validate_and_render_schema():
inferred_clusters[name]["port"],
) = get_endpoint_and_port(endpoint, protocol)
print("defined clusters from arch_config.yaml: ", json.dumps(inferred_clusters))
print("defined clusters from plano_config.yaml: ", json.dumps(inferred_clusters))
if "prompt_targets" in config_yaml:
for prompt_target in config_yaml["prompt_targets"]:
@ -154,13 +154,13 @@ def validate_and_render_schema():
continue
if name not in inferred_clusters:
raise Exception(
f"Unknown endpoint {name}, please add it in endpoints section in your arch_config.yaml file"
f"Unknown endpoint {name}, please add it in endpoints section in your plano_config.yaml file"
)
arch_tracing = config_yaml.get("tracing", {})
plano_tracing = config_yaml.get("tracing", {})
# Resolution order: config yaml > OTEL_TRACING_GRPC_ENDPOINT env var > hardcoded default
opentracing_grpc_endpoint = arch_tracing.get(
opentracing_grpc_endpoint = plano_tracing.get(
"opentracing_grpc_endpoint",
os.environ.get(
"OTEL_TRACING_GRPC_ENDPOINT", DEFAULT_OTEL_TRACING_GRPC_ENDPOINT
@ -172,7 +172,7 @@ def validate_and_render_schema():
print(
f"Resolved opentracing_grpc_endpoint to {opentracing_grpc_endpoint} after expanding environment variables"
)
arch_tracing["opentracing_grpc_endpoint"] = opentracing_grpc_endpoint
plano_tracing["opentracing_grpc_endpoint"] = opentracing_grpc_endpoint
# ensure that opentracing_grpc_endpoint is a valid URL if present and start with http and must not have any path
if opentracing_grpc_endpoint:
urlparse_result = urlparse(opentracing_grpc_endpoint)
@ -436,8 +436,8 @@ def validate_and_render_schema():
f"Model alias 2 - '{alias_name}' targets '{target}' which is not defined as a model. Available models: {', '.join(sorted(model_name_keys))}"
)
arch_config_string = yaml.dump(config_yaml)
arch_llm_config_string = yaml.dump(config_yaml)
plano_config_string = yaml.dump(config_yaml)
plano_llm_config_string = yaml.dump(config_yaml)
use_agent_orchestrator = config_yaml.get("overrides", {}).get(
"use_agent_orchestrator", False
@ -449,11 +449,11 @@ def validate_and_render_schema():
if len(endpoints) == 0:
raise Exception(
"Please provide agent orchestrator in the endpoints section in your arch_config.yaml file"
"Please provide agent orchestrator in the endpoints section in your plano_config.yaml file"
)
elif len(endpoints) > 1:
raise Exception(
"Please provide single agent orchestrator in the endpoints section in your arch_config.yaml file"
"Please provide single agent orchestrator in the endpoints section in your plano_config.yaml file"
)
else:
agent_orchestrator = list(endpoints.keys())[0]
@ -463,11 +463,11 @@ def validate_and_render_schema():
data = {
"prompt_gateway_listener": prompt_gateway,
"llm_gateway_listener": llm_gateway,
"arch_config": arch_config_string,
"arch_llm_config": arch_llm_config_string,
"arch_clusters": inferred_clusters,
"arch_model_providers": updated_model_providers,
"arch_tracing": arch_tracing,
"plano_config": plano_config_string,
"plano_llm_config": plano_llm_config_string,
"plano_clusters": inferred_clusters,
"plano_model_providers": updated_model_providers,
"plano_tracing": plano_tracing,
"local_llms": llms_with_endpoint,
"agent_orchestrator": agent_orchestrator,
"listeners": listeners,
@ -479,25 +479,25 @@ def validate_and_render_schema():
with open(ENVOY_CONFIG_FILE_RENDERED, "w") as file:
file.write(rendered)
with open(ARCH_CONFIG_FILE_RENDERED, "w") as file:
file.write(arch_config_string)
with open(PLANO_CONFIG_FILE_RENDERED, "w") as file:
file.write(plano_config_string)
def validate_prompt_config(arch_config_file, arch_config_schema_file):
with open(arch_config_file, "r") as file:
arch_config = file.read()
def validate_prompt_config(plano_config_file, plano_config_schema_file):
with open(plano_config_file, "r") as file:
plano_config = file.read()
with open(arch_config_schema_file, "r") as file:
arch_config_schema = file.read()
with open(plano_config_schema_file, "r") as file:
plano_config_schema = file.read()
config_yaml = yaml.safe_load(arch_config)
config_schema_yaml = yaml.safe_load(arch_config_schema)
config_yaml = yaml.safe_load(plano_config)
config_schema_yaml = yaml.safe_load(plano_config_schema)
try:
validate(config_yaml, config_schema_yaml)
except Exception as e:
print(
f"Error validating arch_config file: {arch_config_file}, schema file: {arch_config_schema_file}, error: {e}"
f"Error validating plano_config file: {plano_config_file}, schema file: {plano_config_schema_file}, error: {e}"
)
raise e

38
cli/planoai/core.py
View file

@ -24,17 +24,17 @@ from planoai.docker_cli import (
log = getLogger(__name__)
def _get_gateway_ports(arch_config_file: str) -> list[int]:
def _get_gateway_ports(plano_config_file: str) -> list[int]:
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)
# parse plano_config_file yaml file and get prompt_gateway_port
plano_config_dict = {}
with open(plano_config_file) as f:
plano_config_dict = yaml.safe_load(f)
listeners, _, _ = convert_legacy_listeners(
arch_config_dict.get("listeners"), arch_config_dict.get("llm_providers")
plano_config_dict.get("listeners"), plano_config_dict.get("llm_providers")
)
all_ports = [listener.get("port") for listener in listeners]
@ -45,7 +45,7 @@ def _get_gateway_ports(arch_config_file: str) -> list[int]:
return all_ports
def start_arch(arch_config_file, env, log_timeout=120, foreground=False):
def start_plano(plano_config_file, env, log_timeout=120, foreground=False):
"""
Start Docker Compose in detached mode and stream logs until services are healthy.
@ -54,7 +54,7 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False):
log_timeout (int): Time in seconds to show logs before checking for healthy state.
"""
log.info(
f"Starting arch gateway, image name: {PLANO_DOCKER_NAME}, tag: {PLANO_DOCKER_IMAGE}"
f"Starting plano gateway, image name: {PLANO_DOCKER_NAME}, tag: {PLANO_DOCKER_IMAGE}"
)
try:
@ -64,10 +64,10 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False):
docker_stop_container(PLANO_DOCKER_NAME)
docker_remove_container(PLANO_DOCKER_NAME)
gateway_ports = _get_gateway_ports(arch_config_file)
gateway_ports = _get_gateway_ports(plano_config_file)
return_code, _, plano_stderr = docker_start_plano_detached(
arch_config_file,
plano_config_file,
env,
gateway_ports,
)
@ -117,7 +117,7 @@ def start_arch(arch_config_file, env, log_timeout=120, foreground=False):
stream_gateway_logs(follow=True)
except KeyboardInterrupt:
log.info("Keyboard interrupt received, stopping arch gateway service.")
log.info("Keyboard interrupt received, stopping plano gateway service.")
stop_docker_container()
@ -144,15 +144,15 @@ def stop_docker_container(service=PLANO_DOCKER_NAME):
log.info(f"Failed to shut down services: {str(e)}")
def start_cli_agent(arch_config_file=None, settings_json="{}"):
def start_cli_agent(plano_config_file=None, settings_json="{}"):
"""Start a CLI client connected to Plano."""
with open(arch_config_file, "r") as file:
arch_config = file.read()
arch_config_yaml = yaml.safe_load(arch_config)
with open(plano_config_file, "r") as file:
plano_config = file.read()
plano_config_yaml = yaml.safe_load(plano_config)
# Get egress listener configuration
egress_config = arch_config_yaml.get("listeners", {}).get("egress_traffic", {})
egress_config = plano_config_yaml.get("listeners", {}).get("egress_traffic", {})
host = egress_config.get("host", "127.0.0.1")
port = egress_config.get("port", 12000)
@ -167,7 +167,7 @@ def start_cli_agent(arch_config_file=None, settings_json="{}"):
env = os.environ.copy()
env.update(
{
"ANTHROPIC_AUTH_TOKEN": "test", # Use test token for arch
"ANTHROPIC_AUTH_TOKEN": "test", # Use test token for plano
"ANTHROPIC_API_KEY": "",
"ANTHROPIC_BASE_URL": f"http://{host}:{port}",
"NO_PROXY": host,
@ -184,7 +184,7 @@ def start_cli_agent(arch_config_file=None, settings_json="{}"):
]
else:
# Check if arch.claude.code.small.fast alias exists in model_aliases
model_aliases = arch_config_yaml.get("model_aliases", {})
model_aliases = plano_config_yaml.get("model_aliases", {})
if "arch.claude.code.small.fast" in model_aliases:
env["ANTHROPIC_SMALL_FAST_MODEL"] = "arch.claude.code.small.fast"
else:
@ -220,7 +220,7 @@ def start_cli_agent(arch_config_file=None, settings_json="{}"):
# Use claude from PATH
claude_path = "claude"
log.info(f"Connecting Claude Code Agent to Arch at {host}:{port}")
log.info(f"Connecting Claude Code Agent to Plano at {host}:{port}")
try:
subprocess.run([claude_path] + claude_args, env=env, check=True)

8
cli/planoai/docker_cli.py
View file

@ -41,7 +41,7 @@ def docker_remove_container(container: str) -> str:
def docker_start_plano_detached(
arch_config_file: str,
plano_config_file: str,
env: dict,
gateway_ports: list[int],
) -> str:
@ -58,7 +58,7 @@ def docker_start_plano_detached(
port_mappings_args = [item for port in port_mappings for item in ("-p", port)]
volume_mappings = [
f"{arch_config_file}:/app/arch_config.yaml:ro",
f"{plano_config_file}:/app/plano_config.yaml:ro",
]
volume_mappings_args = [
item for volume in volume_mappings for item in ("-v", volume)
@ -115,7 +115,7 @@ def stream_gateway_logs(follow, service="plano"):
log.info(f"Failed to stream logs: {str(e)}")
def docker_validate_plano_schema(arch_config_file):
def docker_validate_plano_schema(plano_config_file):
import os
env = os.environ.copy()
@ -129,7 +129,7 @@ def docker_validate_plano_schema(arch_config_file):
"--rm",
*env_args,
"-v",
f"{arch_config_file}:/app/arch_config.yaml:ro",
f"{plano_config_file}:/app/plano_config.yaml:ro",
"--entrypoint",
"python",
PLANO_DOCKER_IMAGE,

56
cli/planoai/main.py
View file

@ -22,7 +22,7 @@ from planoai.utils import (
find_repo_root,
)
from planoai.core import (
start_arch,
start_plano,
stop_docker_container,
start_cli_agent,
)
@ -200,12 +200,12 @@ def up(file, path, foreground, with_tracing, tracing_port):
_print_cli_header(console)
# Use the utility function to find config file
arch_config_file = find_config_file(path, file)
plano_config_file = find_config_file(path, file)
# Check if the file exists
if not os.path.exists(arch_config_file):
if not os.path.exists(plano_config_file):
console.print(
f"[red]✗[/red] Config file not found: [dim]{arch_config_file}[/dim]"
f"[red]✗[/red] Config file not found: [dim]{plano_config_file}[/dim]"
)
sys.exit(1)
@ -216,7 +216,7 @@ def up(file, path, foreground, with_tracing, tracing_port):
validation_return_code,
_,
validation_stderr,
) = docker_validate_plano_schema(arch_config_file)
) = docker_validate_plano_schema(plano_config_file)
if validation_return_code != 0:
console.print(f"[red]✗[/red] Validation failed")
@ -234,7 +234,7 @@ def up(file, path, foreground, with_tracing, tracing_port):
env.pop("PATH", None)
# Check access keys
access_keys = get_llm_provider_access_keys(arch_config_file=arch_config_file)
access_keys = get_llm_provider_access_keys(plano_config_file=plano_config_file)
access_keys = set(access_keys)
access_keys = [item[1:] if item.startswith("$") else item for item in access_keys]
@ -302,7 +302,7 @@ def up(file, path, foreground, with_tracing, tracing_port):
env.update(env_stage)
try:
start_arch(arch_config_file, env, foreground=foreground)
start_plano(plano_config_file, env, foreground=foreground)
# When tracing is enabled but --foreground is not, keep the process
# alive so the OTLP collector continues to receive spans.
@ -363,35 +363,35 @@ def generate_prompt_targets(file):
def logs(debug, follow):
"""Stream logs from access logs services."""
archgw_process = None
plano_process = None
try:
if debug:
archgw_process = multiprocessing.Process(
plano_process = multiprocessing.Process(
target=stream_gateway_logs, args=(follow,)
)
archgw_process.start()
plano_process.start()
archgw_access_logs_process = multiprocessing.Process(
plano_access_logs_process = multiprocessing.Process(
target=stream_access_logs, args=(follow,)
)
archgw_access_logs_process.start()
archgw_access_logs_process.join()
plano_access_logs_process.start()
plano_access_logs_process.join()
if archgw_process:
archgw_process.join()
if plano_process:
plano_process.join()
except KeyboardInterrupt:
log.info("KeyboardInterrupt detected. Exiting.")
if archgw_access_logs_process.is_alive():
archgw_access_logs_process.terminate()
if archgw_process and archgw_process.is_alive():
archgw_process.terminate()
if plano_access_logs_process.is_alive():
plano_access_logs_process.terminate()
if plano_process and plano_process.is_alive():
plano_process.terminate()
@click.command()
@click.argument("type", type=click.Choice(["claude"]), required=True)
@click.argument("file", required=False) # Optional file argument
@click.option(
"--path", default=".", help="Path to the directory containing arch_config.yaml"
"--path", default=".", help="Path to the directory containing plano_config.yaml"
)
@click.option(
"--settings",
@ -405,20 +405,20 @@ def cli_agent(type, file, path, settings):
"""
# Check if plano docker container is running
archgw_status = docker_container_status(PLANO_DOCKER_NAME)
if archgw_status != "running":
log.error(f"plano docker container is not running (status: {archgw_status})")
plano_status = docker_container_status(PLANO_DOCKER_NAME)
if plano_status != "running":
log.error(f"plano docker container is not running (status: {plano_status})")
log.error("Please start plano using the 'planoai up' command.")
sys.exit(1)
# Determine arch_config.yaml path
arch_config_file = find_config_file(path, file)
if not os.path.exists(arch_config_file):
log.error(f"Config file not found: {arch_config_file}")
# Determine plano_config.yaml path
plano_config_file = find_config_file(path, file)
if not os.path.exists(plano_config_file):
log.error(f"Config file not found: {plano_config_file}")
sys.exit(1)
try:
start_cli_agent(arch_config_file, settings)
start_cli_agent(plano_config_file, settings)
except SystemExit:
# Re-raise SystemExit to preserve exit codes
raise

46
cli/planoai/utils.py
View file

@ -68,19 +68,19 @@ def find_repo_root(start_path=None):
return None
def has_ingress_listener(arch_config_file):
"""Check if the arch config file has ingress_traffic listener configured."""
def has_ingress_listener(plano_config_file):
"""Check if the plano config file has ingress_traffic listener configured."""
try:
with open(arch_config_file) as f:
arch_config_dict = yaml.safe_load(f)
with open(plano_config_file) as f:
plano_config_dict = yaml.safe_load(f)
ingress_traffic = arch_config_dict.get("listeners", {}).get(
ingress_traffic = plano_config_dict.get("listeners", {}).get(
"ingress_traffic", {}
)
return bool(ingress_traffic)
except Exception as e:
log.error(f"Error reading config file {arch_config_file}: {e}")
log.error(f"Error reading config file {plano_config_file}: {e}")
return False
@ -161,27 +161,27 @@ def convert_legacy_listeners(
return listeners, llm_gateway_listener, prompt_gateway_listener
def get_llm_provider_access_keys(arch_config_file):
with open(arch_config_file, "r") as file:
arch_config = file.read()
arch_config_yaml = yaml.safe_load(arch_config)
def get_llm_provider_access_keys(plano_config_file):
with open(plano_config_file, "r") as file:
plano_config = file.read()
plano_config_yaml = yaml.safe_load(plano_config)
access_key_list = []
# Convert legacy llm_providers to model_providers
if "llm_providers" in arch_config_yaml:
if "model_providers" in arch_config_yaml:
if "llm_providers" in plano_config_yaml:
if "model_providers" in plano_config_yaml:
raise Exception(
"Please provide either llm_providers or model_providers, not both. llm_providers is deprecated, please use model_providers instead"
)
arch_config_yaml["model_providers"] = arch_config_yaml["llm_providers"]
del arch_config_yaml["llm_providers"]
plano_config_yaml["model_providers"] = plano_config_yaml["llm_providers"]
del plano_config_yaml["llm_providers"]
listeners, _, _ = convert_legacy_listeners(
arch_config_yaml.get("listeners"), arch_config_yaml.get("model_providers")
plano_config_yaml.get("listeners"), plano_config_yaml.get("model_providers")
)
for prompt_target in arch_config_yaml.get("prompt_targets", []):
for prompt_target in plano_config_yaml.get("prompt_targets", []):
for k, v in prompt_target.get("endpoint", {}).get("http_headers", {}).items():
if k.lower() == "authorization":
print(
@ -200,7 +200,7 @@ def get_llm_provider_access_keys(arch_config_file):
access_key_list.append(access_key)
# Extract environment variables from state_storage.connection_string
state_storage = arch_config_yaml.get("state_storage_v1_responses")
state_storage = plano_config_yaml.get("state_storage_v1_responses")
if state_storage:
connection_string = state_storage.get("connection_string")
if connection_string and isinstance(connection_string, str):
@ -251,16 +251,16 @@ def find_config_file(path=".", file=None):
# If a file is provided, process that file
return os.path.abspath(file)
else:
# If no file is provided, use the path and look for arch_config.yaml first, then config.yaml for convenience
arch_config_file = os.path.abspath(os.path.join(path, "config.yaml"))
if not os.path.exists(arch_config_file):
arch_config_file = os.path.abspath(os.path.join(path, "arch_config.yaml"))
return arch_config_file
# If no file is provided, use the path and look for plano_config.yaml first, then config.yaml for convenience
plano_config_file = os.path.abspath(os.path.join(path, "config.yaml"))
if not os.path.exists(plano_config_file):
plano_config_file = os.path.abspath(os.path.join(path, "plano_config.yaml"))
return plano_config_file
def stream_access_logs(follow):
"""
Get the archgw access logs
Get the plano access logs
"""
follow_arg = "-f" if follow else ""

112
cli/test/test_config_generator.py
View file

@ -12,14 +12,14 @@ def cleanup_env(monkeypatch):
def test_validate_and_render_happy_path(monkeypatch):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
monkeypatch.setenv("PLANO_CONFIG_FILE", "fake_plano_config.yaml")
monkeypatch.setenv("PLANO_CONFIG_SCHEMA_FILE", "fake_plano_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("PLANO_CONFIG_FILE_RENDERED", "fake_plano_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = """
plano_config = """
version: v0.1.0
listeners:
@ -50,24 +50,24 @@ llm_providers:
tracing:
random_sampling: 100
"""
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
plano_config_schema = ""
with open("../config/plano_config_schema.yaml", "r") as file:
plano_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
# Removed empty read - was causing validation failures
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(read_data=plano_config).return_value, # PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
read_data=plano_config_schema
).return_value, # PLANO_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=plano_config).return_value, # PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
read_data=plano_config_schema
).return_value, # PLANO_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # PLANO_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):
@ -75,14 +75,14 @@ tracing:
def test_validate_and_render_happy_path_agent_config(monkeypatch):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
monkeypatch.setenv("PLANO_CONFIG_FILE", "fake_plano_config.yaml")
monkeypatch.setenv("PLANO_CONFIG_SCHEMA_FILE", "fake_plano_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("PLANO_CONFIG_FILE_RENDERED", "fake_plano_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = """
plano_config = """
version: v0.3.0
agents:
@ -123,35 +123,35 @@ model_providers:
- access_key: ${OPENAI_API_KEY}
model: openai/gpt-4o
"""
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
plano_config_schema = ""
with open("../config/plano_config_schema.yaml", "r") as file:
plano_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
# Removed empty read - was causing validation failures
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
mock.mock_open(read_data=plano_config).return_value, # PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=arch_config).return_value, # ARCH_CONFIG_FILE
read_data=plano_config_schema
).return_value, # PLANO_CONFIG_SCHEMA_FILE
mock.mock_open(read_data=plano_config).return_value, # PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # ARCH_CONFIG_SCHEMA_FILE
read_data=plano_config_schema
).return_value, # PLANO_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # PLANO_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):
validate_and_render_schema()
arch_config_test_cases = [
plano_config_test_cases = [
{
"id": "duplicate_provider_name",
"expected_error": "Duplicate model_provider name",
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -176,7 +176,7 @@ llm_providers:
{
"id": "provider_interface_with_model_id",
"expected_error": "Please provide provider interface as part of model name",
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -197,7 +197,7 @@ llm_providers:
{
"id": "duplicate_model_id",
"expected_error": "Duplicate model_id",
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -219,7 +219,7 @@ llm_providers:
{
"id": "custom_provider_base_url",
"expected_error": "Must provide base_url and provider_interface",
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -237,7 +237,7 @@ llm_providers:
{
"id": "base_url_with_path_prefix",
"expected_error": None,
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -258,7 +258,7 @@ llm_providers:
{
"id": "duplicate_routeing_preference_name",
"expected_error": "Duplicate routing preference name",
"arch_config": """
"plano_config": """
version: v0.1.0
listeners:
@ -295,42 +295,42 @@ tracing:
@pytest.mark.parametrize(
"arch_config_test_case",
arch_config_test_cases,
ids=[case["id"] for case in arch_config_test_cases],
"plano_config_test_case",
plano_config_test_cases,
ids=[case["id"] for case in plano_config_test_cases],
)
def test_validate_and_render_schema_tests(monkeypatch, arch_config_test_case):
monkeypatch.setenv("ARCH_CONFIG_FILE", "fake_arch_config.yaml")
monkeypatch.setenv("ARCH_CONFIG_SCHEMA_FILE", "fake_arch_config_schema.yaml")
def test_validate_and_render_schema_tests(monkeypatch, plano_config_test_case):
monkeypatch.setenv("PLANO_CONFIG_FILE", "fake_plano_config.yaml")
monkeypatch.setenv("PLANO_CONFIG_SCHEMA_FILE", "fake_plano_config_schema.yaml")
monkeypatch.setenv("ENVOY_CONFIG_TEMPLATE_FILE", "./envoy.template.yaml")
monkeypatch.setenv("ARCH_CONFIG_FILE_RENDERED", "fake_arch_config_rendered.yaml")
monkeypatch.setenv("PLANO_CONFIG_FILE_RENDERED", "fake_plano_config_rendered.yaml")
monkeypatch.setenv("ENVOY_CONFIG_FILE_RENDERED", "fake_envoy.yaml")
monkeypatch.setenv("TEMPLATE_ROOT", "../")
arch_config = arch_config_test_case["arch_config"]
expected_error = arch_config_test_case.get("expected_error")
plano_config = plano_config_test_case["plano_config"]
expected_error = plano_config_test_case.get("expected_error")
arch_config_schema = ""
with open("../config/arch_config_schema.yaml", "r") as file:
arch_config_schema = file.read()
plano_config_schema = ""
with open("../config/plano_config_schema.yaml", "r") as file:
plano_config_schema = file.read()
m_open = mock.mock_open()
# Provide enough file handles for all open() calls in validate_and_render_schema
m_open.side_effect = [
mock.mock_open(
read_data=arch_config
).return_value, # validate_prompt_config: ARCH_CONFIG_FILE
read_data=plano_config
).return_value, # validate_prompt_config: PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # validate_prompt_config: ARCH_CONFIG_SCHEMA_FILE
read_data=plano_config_schema
).return_value, # validate_prompt_config: PLANO_CONFIG_SCHEMA_FILE
mock.mock_open(
read_data=arch_config
).return_value, # validate_and_render_schema: ARCH_CONFIG_FILE
read_data=plano_config
).return_value, # validate_and_render_schema: PLANO_CONFIG_FILE
mock.mock_open(
read_data=arch_config_schema
).return_value, # validate_and_render_schema: ARCH_CONFIG_SCHEMA_FILE
read_data=plano_config_schema
).return_value, # validate_and_render_schema: PLANO_CONFIG_SCHEMA_FILE
mock.mock_open().return_value, # ENVOY_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # ARCH_CONFIG_FILE_RENDERED (write)
mock.mock_open().return_value, # PLANO_CONFIG_FILE_RENDERED (write)
]
with mock.patch("builtins.open", m_open):
with mock.patch("planoai.config_generator.Environment"):

2
cli/uv.lock generated
View file

@ -337,7 +337,7 @@ wheels = [
[[package]]
name = "planoai"
version = "0.4.4"
version = "0.4.6"
source = { editable = "." }
dependencies = [
{ name = "click" },

6
config/docker-compose.dev.yaml
View file

@ -8,14 +8,14 @@ services:
- "12000:12000"
- "19901:9901"
volumes:
- ${ARCH_CONFIG_FILE:-../demos/samples_python/weather_forecast/arch_config.yaml}:/app/arch_config.yaml
- ${PLANO_CONFIG_FILE:-../demos/samples_python/weather_forecast/plano_config.yaml}:/app/plano_config.yaml
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
- ./envoy.template.yaml:/app/envoy.template.yaml
- ./arch_config_schema.yaml:/app/arch_config_schema.yaml
- ./plano_config_schema.yaml:/app/plano_config_schema.yaml
- ../cli/planoai/config_generator.py:/app/planoai/config_generator.py
- ../crates/target/wasm32-wasip1/release/llm_gateway.wasm:/etc/envoy/proxy-wasm-plugins/llm_gateway.wasm
- ../crates/target/wasm32-wasip1/release/prompt_gateway.wasm:/etc/envoy/proxy-wasm-plugins/prompt_gateway.wasm
- ~/archgw_logs:/var/log/
- ~/plano_logs:/var/log/
extra_hosts:
- "host.docker.internal:host-gateway"
environment:

34
config/envoy.template.yaml
View file

@ -40,7 +40,7 @@ static_resources:
- name: envoy.filters.network.http_connection_manager
typed_config:
"@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager
{% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
{% if "random_sampling" in plano_tracing and plano_tracing["random_sampling"] > 0 %}
generate_request_id: true
tracing:
provider:
@ -53,7 +53,7 @@ static_resources:
timeout: 0.250s
service_name: plano(inbound)
random_sampling:
value: {{ arch_tracing.random_sampling }}
value: {{ plano_tracing.random_sampling }}
operation: "%REQ(:METHOD)% %REQ(X-ENVOY-ORIGINAL-PATH?:PATH)%"
{% endif %}
stat_prefix: plano(inbound)
@ -114,7 +114,7 @@ static_resources:
domains:
- "*"
routes:
{% for provider in arch_model_providers %}
{% for provider in plano_model_providers %}
# if endpoint is set then use custom cluster for upstream llm
{% if provider.endpoint %}
{% set llm_cluster_name = provider.cluster_name %}
@ -166,7 +166,7 @@ static_resources:
configuration:
"@type": "type.googleapis.com/google.protobuf.StringValue"
value: |
{{ arch_config | indent(32) }}
{{ plano_config | indent(32) }}
vm_config:
runtime: "envoy.wasm.runtime.v8"
code:
@ -183,7 +183,7 @@ static_resources:
configuration:
"@type": "type.googleapis.com/google.protobuf.StringValue"
value: |
{{ arch_llm_config | indent(32) }}
{{ plano_llm_config | indent(32) }}
vm_config:
runtime: "envoy.wasm.runtime.v8"
code:
@ -215,7 +215,7 @@ static_resources:
- name: envoy.filters.network.http_connection_manager
typed_config:
"@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager
# {% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
# {% if "random_sampling" in plano_tracing and plano_tracing["random_sampling"] > 0 %}
# generate_request_id: true
# tracing:
# provider:
@ -228,7 +228,7 @@ static_resources:
# timeout: 0.250s
# service_name: tools
# random_sampling:
# value: {{ arch_tracing.random_sampling }}
# value: {{ plano_tracing.random_sampling }}
# {% endif %}
stat_prefix: outbound_api_traffic
codec_type: AUTO
@ -258,7 +258,7 @@ static_resources:
auto_host_rewrite: true
cluster: bright_staff
timeout: 300s
{% for cluster_name, cluster in arch_clusters.items() %}
{% for cluster_name, cluster in plano_clusters.items() %}
- match:
prefix: "/"
headers:
@ -290,7 +290,7 @@ static_resources:
- name: envoy.filters.network.http_connection_manager
typed_config:
"@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager
{% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
{% if "random_sampling" in plano_tracing and plano_tracing["random_sampling"] > 0 %}
generate_request_id: true
tracing:
provider:
@ -303,7 +303,7 @@ static_resources:
timeout: 0.250s
service_name: plano(inbound)
random_sampling:
value: {{ arch_tracing.random_sampling }}
value: {{ plano_tracing.random_sampling }}
operation: "%REQ(:METHOD)% %REQ(X-ENVOY-ORIGINAL-PATH?:PATH)%"
{% endif %}
stat_prefix: {{ listener.name | replace(" ", "_") }}_traffic
@ -467,7 +467,7 @@ static_resources:
- name: envoy.filters.network.http_connection_manager
typed_config:
"@type": type.googleapis.com/envoy.extensions.filters.network.http_connection_manager.v3.HttpConnectionManager
{% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
{% if "random_sampling" in plano_tracing and plano_tracing["random_sampling"] > 0 %}
generate_request_id: true
tracing:
provider:
@ -480,7 +480,7 @@ static_resources:
timeout: 0.250s
service_name: plano(outbound)
random_sampling:
value: {{ arch_tracing.random_sampling }}
value: {{ plano_tracing.random_sampling }}
operation: "%REQ(:METHOD)% %REQ(:AUTHORITY)%%REQ(X-ENVOY-ORIGINAL-PATH?:PATH)%"
{% endif %}
stat_prefix: egress_traffic
@ -501,7 +501,7 @@ static_resources:
domains:
- "*"
routes:
{% for provider in arch_model_providers %}
{% for provider in plano_model_providers %}
# if endpoint is set then use custom cluster for upstream llm
{% if provider.endpoint %}
{% set llm_cluster_name = provider.cluster_name %}
@ -564,7 +564,7 @@ static_resources:
configuration:
"@type": "type.googleapis.com/google.protobuf.StringValue"
value: |
{{ arch_llm_config | indent(32) }}
{{ plano_llm_config | indent(32) }}
vm_config:
runtime: "envoy.wasm.runtime.v8"
code:
@ -879,7 +879,7 @@ static_resources:
address: mistral_7b_instruct
port_value: 10001
hostname: "mistral_7b_instruct"
{% for cluster_name, cluster in arch_clusters.items() %}
{% for cluster_name, cluster in plano_clusters.items() %}
- name: {{ cluster_name }}
{% if cluster.connect_timeout -%}
connect_timeout: {{ cluster.connect_timeout }}
@ -1013,7 +1013,7 @@ static_resources:
port_value: 12001
hostname: arch_listener_llm
{% if "random_sampling" in arch_tracing and arch_tracing["random_sampling"] > 0 %}
{% if "random_sampling" in plano_tracing and plano_tracing["random_sampling"] > 0 %}
- name: opentelemetry_collector
type: STRICT_DNS
dns_lookup_family: V4_ONLY
@ -1030,7 +1030,7 @@ static_resources:
- endpoint:
address:
socket_address:
{% set _otel_endpoint = arch_tracing.opentracing_grpc_endpoint | default('host.docker.internal:4317') | replace("http://", "") | replace("https://", "") %}
{% set _otel_endpoint = plano_tracing.opentracing_grpc_endpoint | default('host.docker.internal:4317') | replace("http://", "") | replace("https://", "") %}
address: {{ _otel_endpoint.split(":") | first }}
port_value: {{ _otel_endpoint.split(":") | last }}
{% endif %}

0
config/arch_config_schema.yaml → config/plano_config_schema.yaml
View file

4
config/supervisord.conf
View file

@ -3,9 +3,9 @@ nodaemon=true
[program:brightstaff]
command=sh -c "\
envsubst < /app/arch_config_rendered.yaml > /app/arch_config_rendered.env_sub.yaml && \
envsubst < /app/plano_config_rendered.yaml > /app/plano_config_rendered.env_sub.yaml && \
RUST_LOG=${LOG_LEVEL:-info} \
ARCH_CONFIG_PATH_RENDERED=/app/arch_config_rendered.env_sub.yaml \
PLANO_CONFIG_PATH_RENDERED=/app/plano_config_rendered.env_sub.yaml \
/app/brightstaff 2>&1 | \
tee /var/log/brightstaff.log | \
while IFS= read -r line; do echo '[brightstaff]' \"$line\"; done"

2
config/test_passthrough.yaml
View file

@ -7,7 +7,7 @@
#
# To test:
# docker build -t plano-passthrough-test .
# docker run -d -p 10000:10000 -v $(pwd)/config/test_passthrough.yaml:/app/arch_config.yaml plano-passthrough-test
# docker run -d -p 10000:10000 -v $(pwd)/config/test_passthrough.yaml:/app/plano_config.yaml plano-passthrough-test
#
# curl http://localhost:10000/v1/chat/completions \
# -H "Authorization: Bearer sk-your-virtual-key" \

4
config/validate_plano_config.sh
View file

@ -2,10 +2,10 @@
failed_files=()
for file in $(find . -name config.yaml -o -name arch_config_full_reference.yaml); do
for file in $(find . -name config.yaml -o -name plano_config_full_reference.yaml); do
echo "Validating ${file}..."
touch $(pwd)/${file}_rendered
if ! docker run --rm -v "$(pwd)/${file}:/app/arch_config.yaml:ro" -v "$(pwd)/${file}_rendered:/app/arch_config_rendered.yaml:rw" --entrypoint /bin/sh katanemo/plano:0.4.6 -c "python -m planoai.config_generator" 2>&1 > /dev/null ; then
if ! docker run --rm -v "$(pwd)/${file}:/app/plano_config.yaml:ro" -v "$(pwd)/${file}_rendered:/app/plano_config_rendered.yaml:rw" --entrypoint /bin/sh katanemo/plano:0.4.6 -c "python -m planoai.config_generator" 2>&1 > /dev/null ; then
echo "Validation failed for $file"
failed_files+=("$file")
fi

4
crates/brightstaff/src/handlers/llm.rs
View file

@ -210,8 +210,8 @@ async fn llm_chat_inner(
// Set the model to just the model name (without provider prefix)
// This ensures upstream receives "gpt-4" not "openai/gpt-4"
client_request.set_model(model_name_only.clone());
if client_request.remove_metadata_key("archgw_preference_config") {
debug!("removed archgw_preference_config from metadata");
if client_request.remove_metadata_key("plano_preference_config") {
debug!("removed plano_preference_config from metadata");
}
// === v1/responses state management: Determine upstream API and combine input if needed ===

2
crates/brightstaff/src/handlers/router_chat.rs
View file

@ -78,7 +78,7 @@ pub async fn router_chat_get_upstream_model(
// Extract usage preferences from metadata
let usage_preferences_str: Option<String> = routing_metadata.as_ref().and_then(|metadata| {
metadata
.get("archgw_preference_config")
.get("plano_preference_config")
.map(|value| value.to_string())
});

38
crates/brightstaff/src/main.rs
View file

@ -52,57 +52,57 @@ fn empty() -> BoxBody<Bytes, hyper::Error> {
async fn main() -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
let bind_address = env::var("BIND_ADDRESS").unwrap_or_else(|_| BIND_ADDRESS.to_string());
// loading arch_config.yaml file (before tracing init so we can read tracing config)
let arch_config_path = env::var("ARCH_CONFIG_PATH_RENDERED")
.unwrap_or_else(|_| "./arch_config_rendered.yaml".to_string());
eprintln!("loading arch_config.yaml from {}", arch_config_path);
// loading plano_config.yaml file (before tracing init so we can read tracing config)
let plano_config_path = env::var("PLANO_CONFIG_PATH_RENDERED")
.unwrap_or_else(|_| "./plano_config_rendered.yaml".to_string());
eprintln!("loading plano_config.yaml from {}", plano_config_path);
let config_contents =
fs::read_to_string(&arch_config_path).expect("Failed to read arch_config.yaml");
fs::read_to_string(&plano_config_path).expect("Failed to read plano_config.yaml");
let config: Configuration =
serde_yaml::from_str(&config_contents).expect("Failed to parse arch_config.yaml");
serde_yaml::from_str(&config_contents).expect("Failed to parse plano_config.yaml");
// Initialize tracing using config.yaml tracing section
let _tracer_provider = init_tracer(config.tracing.as_ref());
info!(path = %arch_config_path, "loaded arch_config.yaml");
info!(path = %plano_config_path, "loaded plano_config.yaml");
let arch_config = Arc::new(config);
let plano_config = Arc::new(config);
// combine agents and filters into a single list of agents
let all_agents: Vec<Agent> = arch_config
let all_agents: Vec<Agent> = plano_config
.agents
.as_deref()
.unwrap_or_default()
.iter()
.chain(arch_config.filters.as_deref().unwrap_or_default())
.chain(plano_config.filters.as_deref().unwrap_or_default())
.cloned()
.collect();
// Create expanded provider list for /v1/models endpoint
let llm_providers = LlmProviders::try_from(arch_config.model_providers.clone())
let llm_providers = LlmProviders::try_from(plano_config.model_providers.clone())
.expect("Failed to create LlmProviders");
let llm_providers = Arc::new(RwLock::new(llm_providers));
let combined_agents_filters_list = Arc::new(RwLock::new(Some(all_agents)));
let listeners = Arc::new(RwLock::new(arch_config.listeners.clone()));
let listeners = Arc::new(RwLock::new(plano_config.listeners.clone()));
let llm_provider_url =
env::var("LLM_PROVIDER_ENDPOINT").unwrap_or_else(|_| "http://localhost:12001".to_string());
let listener = TcpListener::bind(bind_address).await?;
let routing_model_name: String = arch_config
let routing_model_name: String = plano_config
.routing
.as_ref()
.and_then(|r| r.model.clone())
.unwrap_or_else(|| DEFAULT_ROUTING_MODEL_NAME.to_string());
let routing_llm_provider = arch_config
let routing_llm_provider = plano_config
.routing
.as_ref()
.and_then(|r| r.model_provider.clone())
.unwrap_or_else(|| DEFAULT_ROUTING_LLM_PROVIDER.to_string());
let router_service: Arc<RouterService> = Arc::new(RouterService::new(
arch_config.model_providers.clone(),
plano_config.model_providers.clone(),
format!("{llm_provider_url}{CHAT_COMPLETIONS_PATH}"),
routing_model_name,
routing_llm_provider,
@ -113,19 +113,19 @@ async fn main() -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
PLANO_ORCHESTRATOR_MODEL_NAME.to_string(),
));
let model_aliases = Arc::new(arch_config.model_aliases.clone());
let model_aliases = Arc::new(plano_config.model_aliases.clone());
// Initialize trace collector and start background flusher
// Tracing is enabled if the tracing config is present in arch_config.yaml
// Tracing is enabled if the tracing config is present in plano_config.yaml
// Pass Some(true/false) to override, or None to use env var OTEL_TRACING_ENABLED
// OpenTelemetry automatic instrumentation is configured in utils/tracing.rs
// Initialize conversation state storage for v1/responses
// Configurable via arch_config.yaml state_storage section
// Configurable via plano_config.yaml state_storage section
// If not configured, state management is disabled
// Environment variables are substituted by envsubst before config is read
let state_storage: Option<Arc<dyn StateStorage>> =
if let Some(storage_config) = &arch_config.state_storage {
if let Some(storage_config) = &plano_config.state_storage {
let storage: Arc<dyn StateStorage> = match storage_config.storage_type {
common::configuration::StateStorageType::Memory => {
info!(

10
crates/brightstaff/src/tracing/constants.rs
View file

@ -182,7 +182,7 @@ pub mod signals {
// Operation Names
// =============================================================================
/// Canonical operation name components for Arch Gateway
/// Canonical operation name components for Plano Gateway
pub mod operation_component {
/// Inbound request handling
pub const INBOUND: &str = "plano(inbound)";
@ -210,7 +210,7 @@ pub mod operation_component {
///
/// Format: `{method} {path} {target}`
///
/// The operation component (e.g., "archgw(llm)") is now part of the service name,
/// The operation component (e.g., "plano(llm)") is now part of the service name,
/// so the operation name focuses on the HTTP request details and target.
///
/// # Examples
@ -218,7 +218,7 @@ pub mod operation_component {
/// use brightstaff::tracing::OperationNameBuilder;
///
/// // LLM call operation: "POST /v1/chat/completions gpt-4"
/// // (service name will be "archgw(llm)")
/// // (service name will be "plano(llm)")
/// let op = OperationNameBuilder::new()
/// .with_method("POST")
/// .with_path("/v1/chat/completions")
@ -226,7 +226,7 @@ pub mod operation_component {
/// .build();
///
/// // Agent filter operation: "POST /agents/v1/chat/completions hallucination-detector"
/// // (service name will be "archgw(agent filter)")
/// // (service name will be "plano(agent filter)")
/// let op = OperationNameBuilder::new()
/// .with_method("POST")
/// .with_path("/agents/v1/chat/completions")
@ -234,7 +234,7 @@ pub mod operation_component {
/// .build();
///
/// // Routing operation: "POST /v1/chat/completions"
/// // (service name will be "archgw(routing)")
/// // (service name will be "plano(routing)")
/// let op = OperationNameBuilder::new()
/// .with_method("POST")
/// .with_path("/v1/chat/completions")

4
crates/common/src/configuration.rs
View file

@ -493,7 +493,7 @@ mod test {
#[test]
fn test_deserialize_configuration() {
let ref_config = fs::read_to_string(
"../../docs/source/resources/includes/arch_config_full_reference_rendered.yaml",
"../../docs/source/resources/includes/plano_config_full_reference_rendered.yaml",
)
.expect("reference config file not found");
@ -520,7 +520,7 @@ mod test {
#[test]
fn test_tool_conversion() {
let ref_config = fs::read_to_string(
"../../docs/source/resources/includes/arch_config_full_reference_rendered.yaml",
"../../docs/source/resources/includes/plano_config_full_reference_rendered.yaml",
)
.expect("reference config file not found");
let config: super::Configuration = serde_yaml::from_str(&ref_config).unwrap();

2
crates/llm_gateway/src/stream_context.rs
View file

@ -990,7 +990,7 @@ impl HttpContext for StreamContext {
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: {:?}",
"No model specified in request and couldn't determine model name from plano_config. Model name in req: {}, plano_config, provider: {}, model: {:?}",
model_requested,
self.llm_provider().name,
self.llm_provider().model

2
crates/prompt_gateway/src/http_context.rs
View file

@ -419,7 +419,7 @@ impl HttpContext for StreamContext {
);
}
let data_serialized = serde_json::to_string(&data).unwrap();
info!("archgw <= developer: {}", data_serialized);
info!("plano <= developer: {}", data_serialized);
self.set_http_response_body(0, body_size, data_serialized.as_bytes());
};
}

4
crates/prompt_gateway/src/stream_context.rs
View file

@ -246,7 +246,7 @@ impl StreamContext {
let chat_completion_request_json =
serde_json::to_string(&chat_completion_request).unwrap();
info!(
"archgw => upstream llm request: {}",
"plano => upstream llm request: {}",
chat_completion_request_json
);
self.set_http_request_body(
@ -799,7 +799,7 @@ impl StreamContext {
};
let json_resp = serde_json::to_string(&chat_completion_request).unwrap();
info!("archgw => (default target) llm request: {}", json_resp);
info!("plano => (default target) llm request: {}", json_resp);
self.set_http_request_body(0, self.request_body_size, json_resp.as_bytes());
self.resume_http_request();
}

2
demos/samples_java/weather_forcecast_service/docker-compose.yaml
View file

@ -18,7 +18,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

2
demos/samples_python/currency_exchange/README.md
View file

@ -1 +1 @@
This demo shows how you can use a publicly hosted rest api and interact it using arch gateway.
This demo shows how you can use a publicly hosted rest api and interact it using Plano gateway.

2
demos/samples_python/currency_exchange/docker-compose.yaml
View file

@ -10,7 +10,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

4
demos/samples_python/multi_turn_rag_agent/README.md
View file

@ -1,6 +1,6 @@
# Multi-Turn Agentic Demo (RAG)
This demo showcases how the **Arch** can be used to build accurate multi-turn RAG agent by just writing simple APIs.
This demo showcases how **Plano** can be used to build accurate multi-turn RAG agent by just writing simple APIs.
![Example of Multi-turn Interaction](mutli-turn-example.png)
@ -14,7 +14,7 @@ Provides information about various energy sources and considerations.
# Starting the demo
1. Please make sure the [pre-requisites](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites) are installed correctly
2. Start Arch
2. Start Plano
```sh
sh run_demo.sh
```

2
demos/samples_python/multi_turn_rag_agent/docker-compose.yaml
View file

@ -21,4 +21,4 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml

8
demos/samples_python/multi_turn_rag_agent/run_demo.sh
View file

@ -18,8 +18,8 @@ start_demo() {
echo ".env file created with OPENAI_API_KEY."
fi
# Step 3: Start Arch
echo "Starting Arch with config.yaml..."
# Step 3: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 4: Start Network Agent
@ -33,8 +33,8 @@ stop_demo() {
echo "Stopping HR Agent using Docker Compose..."
docker compose down -v
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

2
demos/samples_python/stock_quote/docker-compose.yaml
View file

@ -10,7 +10,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

8
demos/samples_python/stock_quote/run_demo.sh
View file

@ -18,8 +18,8 @@ start_demo() {
echo ".env file created with OPENAI_API_KEY."
fi
# Step 3: Start Arch
echo "Starting Arch with config.yaml..."
# Step 3: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 4: Start developer services
@ -33,8 +33,8 @@ stop_demo() {
echo "Stopping Network Agent using Docker Compose..."
docker compose down
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

8
demos/samples_python/weather_forecast/README.md
View file

@ -1,11 +1,11 @@
# Function calling
This demo shows how you can use Arch's core function calling capabilities.
This demo shows how you can use Plano's core function calling capabilities.
# Starting the demo
1. Please make sure the [pre-requisites](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites) are installed correctly
2. Start Arch
2. Start Plano
3. ```sh
sh run_demo.sh
@ -15,14 +15,14 @@ This demo shows how you can use Arch's core function calling capabilities.
# 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,
Plano gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from Plano and we are using grafana to visalize the stats in dashboard. To see grafana dashboard follow instructions below,
1. Start grafana and prometheus using following command
```yaml
docker compose --profile monitoring up
```
2. Navigate to http://localhost:3000/ to open grafana UI (use admin/grafana as credentials)
3. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view arch gateway stats
3. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view Plano gateway stats
Here is a sample interaction,
<img width="575" alt="image" src="https://github.com/user-attachments/assets/e0929490-3eb2-4130-ae87-a732aea4d059">

2
demos/samples_python/weather_forecast/docker-compose-honeycomb.yaml
View file

@ -20,7 +20,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
otel-collector:
build:

2
demos/samples_python/weather_forecast/docker-compose-jaeger.yaml
View file

@ -20,7 +20,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

2
demos/samples_python/weather_forecast/docker-compose-logfire.yaml
View file

@ -20,7 +20,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
otel-collector:
build:

2
demos/samples_python/weather_forecast/docker-compose-signoz.yaml
View file

@ -23,7 +23,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
prometheus:
build:

2
demos/samples_python/weather_forecast/docker-compose.yaml
View file

@ -20,4 +20,4 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml

8
demos/samples_python/weather_forecast/run_demo.sh
View file

@ -72,8 +72,8 @@ start_demo() {
exit 1
fi
# Step 4: Start Arch
echo "Starting Arch with config.yaml..."
# Step 4: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 5: Start Network Agent with the chosen Docker Compose file
@ -91,8 +91,8 @@ stop_demo() {
docker compose -f "$compose_file" down
done
# Stop Arch
echo "Stopping Arch..."
# Stop Plano
echo "Stopping Plano..."
planoai down
}

4
demos/shared/chatbot_ui/.vscode/launch.json vendored
View file

@ -15,7 +15,7 @@
"LLM": "1",
"CHAT_COMPLETION_ENDPOINT": "http://localhost:10000/v1",
"STREAMING": "True",
"ARCH_CONFIG": "../../samples_python/weather_forecast/arch_config.yaml"
"PLANO_CONFIG": "../../samples_python/weather_forecast/plano_config.yaml"
}
},
{
@ -29,7 +29,7 @@
"LLM": "1",
"CHAT_COMPLETION_ENDPOINT": "http://localhost:12000/v1",
"STREAMING": "True",
"ARCH_CONFIG": "../../samples_python/weather_forecast/arch_config.yaml"
"PLANO_CONFIG": "../../samples_python/weather_forecast/plano_config.yaml"
}
},
]

10
demos/shared/chatbot_ui/common.py
View file

@ -37,7 +37,7 @@ def chat(
try:
response = client.chat.completions.create(
# we select model from arch_config file
# we select model from plano_config file
model="None",
messages=history,
temperature=1.0,
@ -86,7 +86,7 @@ def create_gradio_app(demo_description, client):
with gr.Column(scale=2):
chatbot = gr.Chatbot(
label="Arch Chatbot",
label="Plano Chatbot",
elem_classes="chatbot",
)
textbox = gr.Textbox(
@ -110,7 +110,7 @@ def process_stream_chunk(chunk, history):
delta = chunk.choices[0].delta
if delta.role and delta.role != history[-1]["role"]:
# create new history item if role changes
# this is likely due to arch tool call and api response
# this is likely due to Plano tool call and api response
history.append({"role": delta.role})
history[-1]["model"] = chunk.model
@ -159,7 +159,7 @@ def convert_prompt_target_to_openai_format(target):
def get_prompt_targets():
try:
with open(os.getenv("ARCH_CONFIG", "config.yaml"), "r") as file:
with open(os.getenv("PLANO_CONFIG", "config.yaml"), "r") as file:
config = yaml.safe_load(file)
available_tools = []
@ -181,7 +181,7 @@ def get_prompt_targets():
def get_llm_models():
try:
with open(os.getenv("ARCH_CONFIG", "config.yaml"), "r") as file:
with open(os.getenv("PLANO_CONFIG", "config.yaml"), "r") as file:
config = yaml.safe_load(file)
available_models = [""]

2
demos/shared/grafana/dashboards/envoy_overview.json
View file

@ -787,7 +787,7 @@
},
"timepicker": {},
"timezone": "browser",
"title": "Arch Gateway Dashboard",
"title": "Plano Gateway Dashboard",
"uid": "adt6uhx5lk8aob",
"version": 1,
"weekStart": ""

22
demos/shared/test_runner/common.py
View file

@ -19,17 +19,17 @@ def get_data_chunks(stream, n=1):
return chunks
def get_arch_messages(response_json):
arch_messages = []
def get_plano_messages(response_json):
plano_messages = []
if response_json and "metadata" in response_json:
# load arch_state from metadata
arch_state_str = response_json.get("metadata", {}).get(ARCH_STATE_HEADER, "{}")
# parse arch_state into json object
arch_state = json.loads(arch_state_str)
# load messages from arch_state
arch_messages_str = arch_state.get("messages", "[]")
# load plano_state from metadata
plano_state_str = response_json.get("metadata", {}).get(ARCH_STATE_HEADER, "{}")
# parse plano_state into json object
plano_state = json.loads(plano_state_str)
# load messages from plano_state
plano_messages_str = plano_state.get("messages", "[]")
# parse messages into json object
arch_messages = json.loads(arch_messages_str)
# append messages from arch gateway to history
return arch_messages
plano_messages = json.loads(plano_messages_str)
# append messages from plano gateway to history
return plano_messages
return []

10
demos/shared/test_runner/test_demos.py
View file

@ -1,6 +1,6 @@
import json
import os
from common import get_arch_messages
from common import get_plano_messages
import pytest
import requests
from deepdiff import DeepDiff
@ -46,10 +46,10 @@ def test_demos(test_data):
assert choices[0]["message"]["role"] == "assistant"
assert expected_output_contains.lower() in choices[0]["message"]["content"].lower()
# now verify arch_messages (tool call and api response) that are sent as response metadata
arch_messages = get_arch_messages(response_json)
assert len(arch_messages) == 2
tool_calls_message = arch_messages[0]
# now verify plano_messages (tool call and api response) that are sent as response metadata
plano_messages = get_plano_messages(response_json)
assert len(plano_messages) == 2
tool_calls_message = plano_messages[0]
tool_calls = tool_calls_message.get("tool_calls", [])
assert len(tool_calls) > 0

16
demos/use_cases/claude_code_router/README.md
View file

@ -1,6 +1,6 @@
# Claude Code Router - Multi-Model Access with Intelligent Routing
Arch Gateway extends Claude Code to access multiple LLM providers through a single interface. Offering two key benefits:
Plano extends Claude Code to access multiple LLM providers through a single interface. Offering two key benefits:
1. **Access to Models**: Connect to Grok, Mistral, Gemini, DeepSeek, GPT models, Claude, and local models via Ollama
2. **Intelligent Routing via Preferences for Coding Tasks**: Configure which models handle specific development tasks:
@ -21,15 +21,15 @@ Uses a [1.5B preference-aligned router LLM](https://arxiv.org/abs/2506.16655) to
## How It Works
Arch Gateway sits between Claude Code and multiple LLM providers, analyzing each request to route it to the most suitable model:
Plano sits between Claude Code and multiple LLM providers, analyzing each request to route it to the most suitable model:
```
Your Request → Arch Gateway → Suitable Model → Response
Your Request → Plano → Suitable Model → Response
↓
[Task Analysis & Model Selection]
```
**Supported Providers**: OpenAI-compatible, Anthropic, DeepSeek, Grok, Gemini, Llama, Mistral, local models via Ollama. See [full list of supported providers](https://docs.archgw.com/concepts/llm_providers/supported_providers.html).
**Supported Providers**: OpenAI-compatible, Anthropic, DeepSeek, Grok, Gemini, Llama, Mistral, local models via Ollama. See [full list of supported providers](https://docs.planoai.dev/concepts/llm_providers/supported_providers.html).
## Quick Start (5 minutes)
@ -61,7 +61,7 @@ export ANTHROPIC_API_KEY="your-anthropic-key-here"
# Add other providers as needed
```
### Step 3: Start Arch Gateway
### Step 3: Start Plano
```bash
# Install using uv (recommended)
uv tool install planoai
@ -122,7 +122,7 @@ planoai cli-agent claude --settings='{"ANTHROPIC_SMALL_FAST_MODEL": "deepseek-co
### Environment Variables
The system automatically configures these variables for Claude Code:
```bash
ANTHROPIC_BASE_URL=http://127.0.0.1:12000 # Routes through Arch Gateway
ANTHROPIC_BASE_URL=http://127.0.0.1:12000 # Routes through Plano
ANTHROPIC_SMALL_FAST_MODEL=arch.claude.code.small.fast # Uses intelligent alias
```
@ -147,6 +147,6 @@ llm_providers:
## Technical Details
**How routing works:** Arch intercepts Claude Code requests, analyzes the content using preference-aligned routing, and forwards to the configured model.
**How routing works:** Plano intercepts Claude Code requests, analyzes the content using preference-aligned routing, and forwards to the configured model.
**Research foundation:** Built on our research in [Preference-Aligned LLM Routing](https://arxiv.org/abs/2506.16655)
**Documentation:** [docs.archgw.com](https://docs.archgw.com) for advanced configuration and API details.
**Documentation:** [docs.planoai.dev](https://docs.planoai.dev) for advanced configuration and API details.

4
demos/use_cases/claude_code_router/pretty_model_resolution.sh
View file

@ -1,5 +1,5 @@
#!/usr/bin/env bash
# Pretty-print ArchGW MODEL_RESOLUTION lines from docker logs
# Pretty-print Plano MODEL_RESOLUTION lines from docker logs
# - hides Arch-Router
# - prints timestamp
# - colors MODEL_RESOLUTION red
@ -7,7 +7,7 @@
# - colors resolved_model magenta
# - removes provider and streaming
docker logs -f archgw 2>&1 \
docker logs -f plano 2>&1 \
| awk '
/MODEL_RESOLUTION:/ && $0 !~ /Arch-Router/ {
# extract timestamp between first [ and ]

4
demos/use_cases/http_filter/docker-compose.yaml
View file

@ -19,10 +19,10 @@ services:
- "12000:12000"
- "8001:8001"
environment:
- ARCH_CONFIG_PATH=/config/config.yaml
- PLANO_CONFIG_PATH=/config/config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
jaeger:
build:

14
demos/use_cases/http_filter/src/rag_agent/context_builder.py
View file

@ -22,14 +22,14 @@ logger = logging.getLogger(__name__)
### add new setup
app = FastAPI(title="RAG Agent Context Builder", version="1.0.0")
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
RAG_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
# Global variable to store the knowledge base
@ -95,15 +95,15 @@ async def find_relevant_passages(
If no passages are relevant, return "NONE"."""
try:
# Call archgw to select relevant passages
logger.info(f"Calling archgw to find relevant passages for query: '{query}'")
# Call Plano to select relevant passages
logger.info(f"Calling Plano to find relevant passages for query: '{query}'")
# Prepare extra headers if traceparent is provided
extra_headers = {"x-envoy-max-retries": "3", "x-request-id": request_id}
if traceparent:
extra_headers["traceparent"] = traceparent
response = await archgw_client.chat.completions.create(
response = await plano_client.chat.completions.create(
model=RAG_MODEL,
messages=[{"role": "system", "content": system_prompt}],
temperature=0.1,

12
demos/use_cases/http_filter/src/rag_agent/input_guards.py
View file

@ -22,14 +22,14 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
GUARD_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
app = FastAPI(title="RAG Agent Input Guards", version="1.0.0")
@ -93,13 +93,13 @@ Respond in JSON format:
]
try:
# Call archgw using OpenAI client
# Call Plano using OpenAI client
extra_headers = {"x-envoy-max-retries": "3", "x-request-id": request_id}
if traceparent_header:
extra_headers["traceparent"] = traceparent_header
logger.info(f"Validating query scope: '{last_user_message}'")
response = await archgw_client.chat.completions.create(
response = await plano_client.chat.completions.create(
model=GUARD_MODEL,
messages=guard_messages,
temperature=0.1,

16
demos/use_cases/http_filter/src/rag_agent/query_rewriter.py
View file

@ -20,20 +20,20 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
QUERY_REWRITE_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
app = FastAPI(title="RAG Agent Query Rewriter", version="1.0.0")
async def rewrite_query_with_archgw(
async def rewrite_query_with_plano(
messages: List[ChatMessage],
traceparent_header: Optional[str] = None,
request_id: Optional[str] = None,
@ -59,8 +59,8 @@ Return only the rewritten query, nothing else."""
extra_headers["traceparent"] = traceparent_header
try:
logger.info(f"Calling archgw at {LLM_GATEWAY_ENDPOINT} to rewrite query")
resp = await archgw_client.chat.completions.create(
logger.info(f"Calling Plano at {LLM_GATEWAY_ENDPOINT} to rewrite query")
resp = await plano_client.chat.completions.create(
model=QUERY_REWRITE_MODEL,
messages=rewrite_messages,
temperature=0.3,
@ -96,7 +96,7 @@ async def query_rewriter_http(
else:
logger.info("No traceparent header found")
rewritten_query = await rewrite_query_with_archgw(
rewritten_query = await rewrite_query_with_plano(
messages, traceparent_header, request_id
)
# Create updated messages with the rewritten query

14
demos/use_cases/http_filter/src/rag_agent/rag_agent.py
View file

@ -22,7 +22,7 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
RESPONSE_MODEL = "gpt-4o"
@ -38,10 +38,10 @@ Your response should:
Generate a complete response to assist the user."""
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
# FastAPI app for REST server
@ -95,9 +95,9 @@ async def stream_chat_completions(
response_messages = prepare_response_messages(request_body)
try:
# Call archgw using OpenAI client for streaming
# Call Plano using OpenAI client for streaming
logger.info(
f"Calling archgw at {LLM_GATEWAY_ENDPOINT} to generate streaming response"
f"Calling Plano at {LLM_GATEWAY_ENDPOINT} to generate streaming response"
)
# Prepare extra headers if traceparent is provided
@ -105,7 +105,7 @@ async def stream_chat_completions(
if traceparent_header:
extra_headers["traceparent"] = traceparent_header
response_stream = await archgw_client.chat.completions.create(
response_stream = await plano_client.chat.completions.create(
model=RESPONSE_MODEL,
messages=response_messages,
temperature=request_body.temperature or 0.7,

12
demos/use_cases/llm_routing/README.md
View file

@ -1,15 +1,15 @@
# LLM Routing
This demo shows how you can arch gateway to manage keys and route to upstream LLM.
This demo shows how you can use Plano gateway to manage keys and route to upstream LLM.
# Starting the demo
1. Please make sure the [pre-requisites](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites) are installed correctly
1. Start Arch
1. Start Plano
```sh
sh run_demo.sh
```
1. Navigate to http://localhost:18080/
Following screen shows an example of interaction with arch gateway showing dynamic routing. You can select between different LLMs using "override model" option in the chat UI.
Following screen shows an example of interaction with Plano gateway showing dynamic routing. You can select between different LLMs using "override model" option in the chat UI.
![LLM Routing Demo](llm_routing_demo.png)
@ -47,12 +47,12 @@ $ curl --header 'Content-Type: application/json' \
```
# 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 visualize the stats in dashboard. To see grafana dashboard follow instructions below,
Plano gateway publishes stats endpoint at http://localhost:19901/stats. In this demo we are using prometheus to pull stats from Plano and we are using grafana to visualize the stats in dashboard. To see grafana dashboard follow instructions below,
1. Navigate to http://localhost:3000/ to open grafana UI (use admin/grafana as credentials)
1. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view arch gateway stats
1. From grafana left nav click on dashboards and select "Intelligent Gateway Overview" to view Plano gateway stats
1. For tracing you can head over to http://localhost:16686/ to view recent traces.
Following is a screenshot of tracing UI showing call received by arch gateway and making upstream call to LLM,
Following is a screenshot of tracing UI showing call received by Plano gateway and making upstream call to LLM,
![Jaeger Tracing](jaeger_tracing_llm_routing.png)

4
demos/use_cases/llm_routing/docker-compose.yaml
View file

@ -8,11 +8,11 @@ services:
- "12000:12000"
- "12001:12001"
environment:
- ARCH_CONFIG_PATH=/app/arch_config.yaml
- PLANO_CONFIG_PATH=/app/plano_config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
- OTEL_TRACING_GRPC_ENDPOINT=http://host.docker.internal:4317
volumes:
- ./config.yaml:/app/arch_config.yaml:ro
- ./config.yaml:/app/plano_config.yaml:ro
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
anythingllm:

8
demos/use_cases/llm_routing/run_demo.sh
View file

@ -18,8 +18,8 @@ start_demo() {
echo ".env file created with OPENAI_API_KEY."
fi
# Step 3: Start Arch
echo "Starting Arch with config.yaml..."
# Step 3: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 4: Start LLM Routing
@ -33,8 +33,8 @@ stop_demo() {
echo "Stopping LLM Routing using Docker Compose..."
docker compose down
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

4
demos/use_cases/mcp_filter/docker-compose.yaml
View file

@ -21,10 +21,10 @@ services:
- "12000:12000"
- "8001:8001"
environment:
- ARCH_CONFIG_PATH=/config/config.yaml
- PLANO_CONFIG_PATH=/config/config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
jaeger:
build:

14
demos/use_cases/mcp_filter/src/rag_agent/context_builder.py
View file

@ -18,14 +18,14 @@ logging.basicConfig(
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
RAG_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
# Global variable to store the knowledge base
@ -91,8 +91,8 @@ async def find_relevant_passages(
If no passages are relevant, return "NONE"."""
try:
# Call archgw to select relevant passages
logger.info(f"Calling archgw to find relevant passages for query: '{query}'")
# Call Plano to select relevant passages
logger.info(f"Calling Plano to find relevant passages for query: '{query}'")
# Prepare extra headers if traceparent is provided
extra_headers = {
@ -103,7 +103,7 @@ async def find_relevant_passages(
if traceparent:
extra_headers["traceparent"] = traceparent
response = await archgw_client.chat.completions.create(
response = await plano_client.chat.completions.create(
model=RAG_MODEL,
messages=[{"role": "system", "content": system_prompt}],
temperature=0.1,

12
demos/use_cases/mcp_filter/src/rag_agent/input_guards.py
View file

@ -20,14 +20,14 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
GUARD_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
app = FastAPI()
@ -91,7 +91,7 @@ Respond in JSON format:
]
try:
# Call archgw using OpenAI client
# Call Plano using OpenAI client
extra_headers = {"x-envoy-max-retries": "3"}
if traceparent_header:
extra_headers["traceparent"] = traceparent_header
@ -100,7 +100,7 @@ Respond in JSON format:
extra_headers["x-request-id"] = request_id
logger.info(f"Validating query scope: '{last_user_message}'")
response = await archgw_client.chat.completions.create(
response = await plano_client.chat.completions.create(
model=GUARD_MODEL,
messages=guard_messages,
temperature=0.1,

22
demos/use_cases/mcp_filter/src/rag_agent/query_rewriter.py
View file

@ -19,20 +19,20 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
QUERY_REWRITE_MODEL = "gpt-4o-mini"
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
app = FastAPI()
async def rewrite_query_with_archgw(
async def rewrite_query_with_plano(
messages: List[ChatMessage],
traceparent_header: str,
request_id: Optional[str] = None,
@ -57,14 +57,14 @@ async def rewrite_query_with_archgw(
rewrite_messages.append({"role": msg.role, "content": msg.content})
try:
# Call archgw using OpenAI client
# Call Plano using OpenAI client
extra_headers = {"x-envoy-max-retries": "3"}
if traceparent_header:
extra_headers["traceparent"] = traceparent_header
if request_id:
extra_headers["x-request-id"] = request_id
logger.info(f"Calling archgw at {LLM_GATEWAY_ENDPOINT} to rewrite query")
response = await archgw_client.chat.completions.create(
logger.info(f"Calling Plano at {LLM_GATEWAY_ENDPOINT} to rewrite query")
response = await plano_client.chat.completions.create(
model=QUERY_REWRITE_MODEL,
messages=rewrite_messages,
temperature=0.3,
@ -88,7 +88,7 @@ async def rewrite_query_with_archgw(
async def query_rewriter(messages: List[ChatMessage]) -> List[ChatMessage]:
"""Chat completions endpoint that rewrites the last user query using archgw.
"""Chat completions endpoint that rewrites the last user query using Plano.
Returns a dict with a 'messages' key containing the updated message list.
"""
@ -104,8 +104,8 @@ async def query_rewriter(messages: List[ChatMessage]) -> List[ChatMessage]:
else:
logger.info("No traceparent header found")
# Call archgw to rewrite the last user query
rewritten_query = await rewrite_query_with_archgw(
# Call Plano to rewrite the last user query
rewritten_query = await rewrite_query_with_plano(
messages, traceparent_header, request_id
)

14
demos/use_cases/mcp_filter/src/rag_agent/rag_agent.py
View file

@ -22,7 +22,7 @@ logging.basicConfig(
)
logger = logging.getLogger(__name__)
# Configuration for archgw LLM gateway
# Configuration for Plano LLM gateway
LLM_GATEWAY_ENDPOINT = os.getenv("LLM_GATEWAY_ENDPOINT", "http://localhost:12000/v1")
RESPONSE_MODEL = "gpt-4o"
@ -38,10 +38,10 @@ Your response should:
Generate a complete response to assist the user."""
# Initialize OpenAI client for archgw
archgw_client = AsyncOpenAI(
# Initialize OpenAI client for Plano
plano_client = AsyncOpenAI(
base_url=LLM_GATEWAY_ENDPOINT,
api_key="EMPTY", # archgw doesn't require a real API key
api_key="EMPTY", # Plano doesn't require a real API key
)
# FastAPI app for REST server
@ -94,9 +94,9 @@ async def stream_chat_completions(
response_messages = prepare_response_messages(request_body)
try:
# Call archgw using OpenAI client for streaming
# Call Plano using OpenAI client for streaming
logger.info(
f"Calling archgw at {LLM_GATEWAY_ENDPOINT} to generate streaming response"
f"Calling Plano at {LLM_GATEWAY_ENDPOINT} to generate streaming response"
)
logger.info(f"rag_agent - request_id: {request_id}")
@ -107,7 +107,7 @@ async def stream_chat_completions(
if traceparent_header:
extra_headers["traceparent"] = traceparent_header
response_stream = await archgw_client.chat.completions.create(
response_stream = await plano_client.chat.completions.create(
model=RESPONSE_MODEL,
messages=response_messages,
temperature=request_body.temperature or 0.7,

10
demos/use_cases/model_alias_routing/README.md
View file

@ -1,6 +1,6 @@
# Model Alias Demo Suite
This directory contains demos for the model alias feature in archgw.
This directory contains demos for the model alias feature in Plano.
## Overview
@ -48,7 +48,7 @@ model_aliases:
```
## Prerequisites
- Install all dependencies as described in the main Arch README ([link](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites))
- Install all dependencies as described in the main Plano README ([link](https://github.com/katanemo/plano/?tab=readme-ov-file#prerequisites))
- Set your API keys in your environment:
- `export OPENAI_API_KEY=your-openai-key`
- `export ANTHROPIC_API_KEY=your-anthropic-key` (optional, but recommended for Anthropic tests)
@ -60,13 +60,13 @@ model_aliases:
sh run_demo.sh
```
- This will create a `.env` file with your API keys (if not present).
- Starts Arch Gateway with model alias config (`arch_config_with_aliases.yaml`).
- Starts Plano gateway with model alias config (`arch_config_with_aliases.yaml`).
2. To stop the demo:
```sh
sh run_demo.sh down
```
- This will stop Arch Gateway and any related services.
- This will stop Plano gateway and any related services.
## Example Requests
@ -145,4 +145,4 @@ curl -sS -X POST "http://localhost:12000/v1/messages" \
## Troubleshooting
- Ensure your API keys are set in your environment before running the demo.
- If you see errors about missing keys, set them and re-run the script.
- For more details, see the main Arch documentation.
- For more details, see the main Plano documentation.

10
demos/use_cases/model_alias_routing/run_demo.sh
View file

@ -24,11 +24,11 @@ start_demo() {
echo ".env file created with API keys."
fi
# Step 3: Start Arch
echo "Starting Arch with arch_config_with_aliases.yaml..."
# Step 3: Start Plano
echo "Starting Plano with arch_config_with_aliases.yaml..."
planoai up arch_config_with_aliases.yaml
echo "\n\nArch started successfully."
echo "\n\nPlano started successfully."
echo "Please run the following CURL command to test model alias routing. Additional instructions are in the README.md file. \n"
echo "curl -sS -X POST \"http://localhost:12000/v1/chat/completions\" \
-H \"Authorization: Bearer test-key\" \
@ -46,8 +46,8 @@ start_demo() {
# Function to stop the demo
stop_demo() {
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

6
demos/use_cases/model_choice_with_test_harness/README.md
View file

@ -1,6 +1,6 @@
# Model Choice Newsletter Demo
This folder demonstrates a practical workflow for rapid model adoption and safe model switching using Arch Gateway (`plano`). It includes both a minimal test harness and a sample proxy configuration.
This folder demonstrates a practical workflow for rapid model adoption and safe model switching using Plano (`plano`). It includes both a minimal test harness and a sample proxy configuration.
---
@ -85,13 +85,13 @@ See `config.yaml` for a sample configuration mapping aliases to provider models.
```
2. **Install dependencies:**
- Install all dependencies as described in the main Arch README ([link](https://github.com/katanemo/arch/?tab=readme-ov-file#prerequisites))
- Install all dependencies as described in the main Plano README ([link](https://github.com/katanemo/plano/?tab=readme-ov-file#prerequisites))
- Then run
```sh
uv sync
```
3. **Start Arch Gateway**
3. **Start Plano**
```sh
run_demo.sh
```

2
demos/use_cases/model_choice_with_test_harness/bench.py
View file

@ -3,7 +3,7 @@ import json, time, yaml, statistics as stats
from pydantic import BaseModel, ValidationError
from openai import OpenAI
# archgw endpoint (keys are handled by archgw)
# Plano endpoint (keys are handled by Plano)
client = OpenAI(base_url="http://localhost:12000/v1", api_key="n/a")
MODELS = ["arch.summarize.v1", "arch.reason.v1"]
FIXTURES = "evals_summarize.yaml"

0
demos/use_cases/model_choice_with_test_harness/arch_config_with_aliases.yaml → demos/use_cases/model_choice_with_test_harness/plano_config_with_aliases.yaml
View file

2
demos/use_cases/model_choice_with_test_harness/pyproject.toml
View file

@ -1,7 +1,7 @@
[project]
name = "model-choice-newsletter-code-snippets"
version = "0.1.0"
description = "Benchmarking model alias routing with Arch Gateway."
description = "Benchmarking model alias routing with Plano."
authors = [{name = "Your Name", email = "your@email.com"}]
license = {text = "Apache 2.0"}
readme = "README.md"

10
demos/use_cases/model_choice_with_test_harness/run_demo.sh
View file

@ -17,18 +17,18 @@ start_demo() {
echo ".env file created with API keys."
fi
# Step 3: Start Arch
echo "Starting Arch with arch_config_with_aliases.yaml..."
# Step 3: Start Plano
echo "Starting Plano with arch_config_with_aliases.yaml..."
planoai up arch_config_with_aliases.yaml
echo "\n\nArch started successfully."
echo "\n\nPlano started successfully."
echo "Please run the following command to test the setup: python bench.py\n"
}
# Function to stop the demo
stop_demo() {
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

4
demos/use_cases/multi_agent_with_crewai_langchain/docker-compose.yaml
View file

@ -8,12 +8,12 @@ services:
- "8001:8001"
- "12000:12000"
environment:
- ARCH_CONFIG_PATH=/app/arch_config.yaml
- PLANO_CONFIG_PATH=/app/plano_config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
- OTEL_TRACING_GRPC_ENDPOINT=http://jaeger:4317
- LOG_LEVEL=${LOG_LEVEL:-info}
volumes:
- ./config.yaml:/app/arch_config.yaml:ro
- ./config.yaml:/app/plano_config.yaml:ro
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
crewai-flight-agent:

2
demos/use_cases/ollama/docker-compose.yaml
View file

@ -10,7 +10,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

2
demos/use_cases/ollama/docker-compose_honeycomb.yaml
View file

@ -10,7 +10,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
otel-collector:
build:

8
demos/use_cases/ollama/run_demo.sh
View file

@ -18,8 +18,8 @@ start_demo() {
echo ".env file created with OPENAI_API_KEY."
fi
# Step 3: Start Arch
echo "Starting Arch with config.yaml..."
# Step 3: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 4: Start developer services
@ -33,8 +33,8 @@ stop_demo() {
echo "Stopping Network Agent using Docker Compose..."
docker compose down
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

2
demos/use_cases/preference_based_routing/README.md
View file

@ -17,7 +17,7 @@ Make sure your machine is up to date with [latest version of plano]([url](https:
# Or if installed with uv: uvx planoai up --service plano --foreground
2025-05-30 18:00:09,953 - planoai.main - INFO - Starting plano cli version: 0.4.6
2025-05-30 18:00:09,953 - planoai.main - INFO - Validating /Users/adilhafeez/src/intelligent-prompt-gateway/demos/use_cases/preference_based_routing/config.yaml
2025-05-30 18:00:10,422 - cli.core - INFO - Starting arch gateway, image name: plano, tag: katanemo/plano:0.4.6
2025-05-30 18:00:10,422 - cli.core - INFO - Starting plano gateway, image name: plano, tag: katanemo/plano:0.4.6
2025-05-30 18:00:10,662 - cli.core - INFO - plano status: running, health status: starting
2025-05-30 18:00:11,712 - cli.core - INFO - plano status: running, health status: starting
2025-05-30 18:00:12,761 - cli.core - INFO - plano is running and is healthy!

4
demos/use_cases/preference_based_routing/docker-compose.yaml
View file

@ -8,14 +8,14 @@ services:
- "12000:12000"
- "12001:12001"
environment:
- ARCH_CONFIG_PATH=/app/arch_config.yaml
- PLANO_CONFIG_PATH=/app/plano_config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:?ANTHROPIC_API_KEY environment variable is required but not set}
- OTEL_TRACING_GRPC_ENDPOINT=http://host.docker.internal:4317
- OTEL_TRACING_ENABLED=true
- RUST_LOG=debug
volumes:
- ./config.yaml:/app/arch_config.yaml:ro
- ./config.yaml:/app/plano_config.yaml:ro
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
anythingllm:

0
demos/use_cases/preference_based_routing/arch_config_local.yaml → demos/use_cases/preference_based_routing/plano_config_local.yaml
View file

4
demos/use_cases/spotify_bearer_auth/README.md
View file

@ -1,6 +1,6 @@
# Use Case Demo: Bearer Authorization with Spotify APIs
In this demo, we show how you can use Arch's bearer authorization capability to connect your agentic apps to third-party APIs.
In this demo, we show how you can use Plano's bearer authorization capability to connect your agentic apps to third-party APIs.
More specifically, we demonstrate how you can connect to two Spotify APIs:
- [`/v1/browse/new-releases`](https://developer.spotify.com/documentation/web-api/reference/get-new-releases)
@ -23,7 +23,7 @@ Where users can engage by asking questions like _"Show me the latest releases in
SPOTIFY_CLIENT_KEY=your_spotify_api_token
```
3. Start Arch
3. Start Plano
```sh
sh run_demo.sh
```

2
demos/use_cases/spotify_bearer_auth/docker-compose.yaml
View file

@ -10,7 +10,7 @@ services:
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
jaeger:
build:

8
demos/use_cases/spotify_bearer_auth/run_demo.sh
View file

@ -18,8 +18,8 @@ start_demo() {
echo ".env file created with OPENAI_API_KEY."
fi
# Step 3: Start Arch
echo "Starting Arch with config.yaml..."
# Step 3: Start Plano
echo "Starting Plano with config.yaml..."
planoai up config.yaml
# Step 4: Start developer services
@ -33,8 +33,8 @@ stop_demo() {
echo "Stopping Network Agent using Docker Compose..."
docker compose down
# Step 2: Stop Arch
echo "Stopping Arch..."
# Step 2: Stop Plano
echo "Stopping Plano..."
planoai down
}

4
demos/use_cases/travel_agents/docker-compose.yaml
View file

@ -8,10 +8,10 @@ services:
- "12000:12000"
- "8001:8001"
environment:
- ARCH_CONFIG_PATH=/config/config.yaml
- PLANO_CONFIG_PATH=/config/config.yaml
- OPENAI_API_KEY=${OPENAI_API_KEY:?OPENAI_API_KEY environment variable is required but not set}
volumes:
- ./config.yaml:/app/arch_config.yaml
- ./config.yaml:/app/plano_config.yaml
- /etc/ssl/cert.pem:/etc/ssl/cert.pem
weather-agent:
build:

2
docs/source/_ext/provider_models.py
View file

@ -19,7 +19,7 @@ def _on_build_finished(app: Sphinx, exception: Exception | None) -> None:
return
# Source path: provider_models.yaml is copied into the Docker image at /docs/provider_models.yaml
# This follows the pattern used for config templates like envoy.template.yaml and arch_config_schema.yaml
# This follows the pattern used for config templates like envoy.template.yaml and plano_config_schema.yaml
docs_root = Path(app.srcdir).parent # Goes from source/ to docs/
source_path = docs_root / "provider_models.yaml"

2
docs/source/build_with_plano/includes/agent/function-calling-agent.yaml
View file

@ -48,7 +48,7 @@ prompt_targets:
description: Time range in days for which to gather device statistics. Defaults to 7.
default: 7
# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
# Plano creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
endpoints:
app_server:
# value could be ip address or a hostname with port

4
docs/source/concepts/includes/plano_config.yaml
View file

@ -18,7 +18,7 @@ prompt_targets:
endpoint:
name: app_server
path: /agent/summary
# Arch uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
# Plano uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
auto_llm_dispatch_on_response: true
# override system prompt for this prompt target
system_prompt: You are a helpful information extraction assistant. Use the information that is provided to you.
@ -39,7 +39,7 @@ prompt_targets:
default: false
enum: [true, false]
# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
# Plano creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
endpoints:
app_server:
# value could be ip address or a hostname with port

4
docs/source/concepts/llm_providers/client_libraries.rst
View file

@ -54,7 +54,7 @@ The OpenAI SDK works with any provider through Plano's OpenAI-compatible endpoin
base_url="http://127.0.0.1:12000/v1"
)
# Use any model configured in your arch_config.yaml
# Use any model configured in your plano_config.yaml
completion = client.chat.completions.create(
model="gpt-4o-mini", # Or use :ref:`model aliases <model_aliases>` like "fast-model"
max_tokens=50,
@ -231,7 +231,7 @@ The Anthropic SDK works with any provider through Plano's Anthropic-compatible e
base_url="http://127.0.0.1:12000"
)
# Use any model configured in your arch_config.yaml
# Use any model configured in your plano_config.yaml
message = client.messages.create(
model="claude-3-5-sonnet-20241022",
max_tokens=50,

8
docs/source/concepts/prompt_target.rst
View file

@ -114,7 +114,7 @@ Example 1: Adjusting Retrieval
User: What are the benefits of renewable energy?
**[Plano]**: Check if there is an available <prompt_target> that can handle this user query.
**[Plano]**: Found "get_info_for_energy_source" prompt_target in arch_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
**[Plano]**: Found "get_info_for_energy_source" prompt_target in plano_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
...
Assistant: Renewable energy reduces greenhouse gas emissions, lowers air pollution, and provides sustainable power sources like solar and wind.
@ -130,13 +130,13 @@ Example 2: Switching Intent
User: What are the symptoms of diabetes?
**[Plano]**: Check if there is an available <prompt_target> that can handle this user query.
**[Plano]**: Found "diseases_symptoms" prompt_target in arch_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
**[Plano]**: Found "diseases_symptoms" prompt_target in plano_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
...
Assistant: Common symptoms include frequent urination, excessive thirst, fatigue, and blurry vision.
User: How is it diagnosed?
**[Plano]**: New intent detected.
**[Plano]**: Found "disease_diagnoses" prompt_target in arch_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
**[Plano]**: Found "disease_diagnoses" prompt_target in plano_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
...
Assistant: Diabetes is diagnosed through blood tests like fasting blood sugar, A1C, or an oral glucose tolerance test.
@ -172,7 +172,7 @@ Once the prompt targets are configured as above, handle parameters across multi-
Demo App
--------
For your convenience, we've built a `demo app <https://github.com/katanemo/archgw/tree/main/demos/samples_python/multi_turn_rag_agent>`_
For your convenience, we've built a `demo app <https://github.com/katanemo/plano/tree/main/demos/samples_python/multi_turn_rag_agent>`_
that you can test and modify locally for multi-turn RAG scenarios.
.. figure:: ../build_with_plano/includes/multi_turn/mutli-turn-example.png

4
docs/source/guides/includes/config.yaml
View file

@ -24,7 +24,7 @@ prompt_targets:
name: app_server
path: /agent/summary
http_method: POST
# Arch uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
# Plano uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
auto_llm_dispatch_on_response: true
# override system prompt for this prompt target
system_prompt: You are a helpful information extraction assistant. Use the information that is provided to you.
@ -46,7 +46,7 @@ prompt_targets:
default: false
enum: [true, false]
# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
# Plano creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
endpoints:
app_server:
# value could be ip address or a hostname with port

2
docs/source/guides/observability/access_logging.rst
View file

@ -1,4 +1,4 @@
.. _arch_access_logging:
.. _plano_access_logging:
Access Logging
==============

2
docs/source/guides/observability/tracing.rst
View file

@ -1,4 +1,4 @@
.. _arch_overview_tracing:
.. _plano_overview_tracing:
Tracing
=======

2
docs/source/guides/state.rst
View file

@ -57,7 +57,7 @@ Configuration Overview
State storage is configured in the ``state_storage`` section of your ``plano_config.yaml``:
.. literalinclude:: ../resources/includes/arch_config_state_storage_example.yaml
.. literalinclude:: ../resources/includes/plano_config_state_storage_example.yaml
:language: yaml
:lines: 21-30
:linenos:

6
docs/source/resources/configuration_reference.rst
View file

@ -4,10 +4,10 @@ Configuration Reference
=======================
The following is a complete reference of the ``plano_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
the Plano 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.
.. literalinclude:: includes/arch_config_full_reference.yaml
.. literalinclude:: includes/plano_config_full_reference.yaml
:language: yaml
:linenos:
:caption: :download:`Plano Configuration - Full Reference <includes/arch_config_full_reference.yaml>`
:caption: :download:`Plano Configuration - Full Reference <includes/plano_config_full_reference.yaml>`

2
docs/source/resources/includes/plano_config_agents_filters.yaml
View file

@ -30,7 +30,7 @@ listeners:
- type: agent
name: agent_1
port: 8001
router: arch_agent_router
router: plano_agent_router
agents:
- id: rag_agent
description: virtual assistant for retrieval augmented generation tasks

2
docs/source/resources/includes/arch_config_full_reference.yaml → docs/source/resources/includes/plano_config_full_reference.yaml
View file

@ -1,4 +1,4 @@
# Arch Gateway configuration version
# Plano Gateway configuration version
version: v0.3.0
# External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)

0
docs/source/resources/includes/arch_config_full_reference_rendered.yaml → docs/source/resources/includes/plano_config_full_reference_rendered.yaml
View file

0
docs/source/resources/includes/arch_config_state_storage_example.yaml → docs/source/resources/includes/plano_config_state_storage_example.yaml
View file

6
docs/source/resources/tech_overview/request_lifecycle.rst
View file

@ -41,7 +41,7 @@ The request processing path in Plano has three main parts:
These two subsystems are bridged with either the HTTP router filter, and the cluster manager subsystems of Envoy.
Also, Plano utilizes `Envoy event-based thread model <https://blog.envoyproxy.io/envoy-threading-model-a8d44b922310>`_. A main thread is responsible for the server lifecycle, configuration processing, stats, etc. and some number of :ref:`worker threads <arch_overview_threading>` process requests. All threads operate around an event loop (`libevent <https://libevent.org/>`_) 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.
Also, Plano utilizes `Envoy event-based thread model <https://blog.envoyproxy.io/envoy-threading-model-a8d44b922310>`_. A main thread is responsible for the server lifecycle, configuration processing, stats, etc. and some number of :ref:`worker threads <plano_overview_threading>` process requests. All threads operate around an event loop (`libevent <https://libevent.org/>`_) 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.
Worker threads rarely share state and operate in a trivially parallel fashion. This threading model
enables scaling to very high core count CPUs.
@ -130,8 +130,8 @@ Once a request completes, the stream is destroyed. The following also takes plac
* The post-request :ref:`monitoring <monitoring>` are updated (e.g. timing, active requests, upgrades, health checks).
Some statistics are updated earlier however, during request processing. Stats are batched and written by the main
thread periodically.
* :ref:`Access logs <arch_access_logging>` are written to the access log
* :ref:`Trace <arch_overview_tracing>` spans are finalized. If our example request was traced, a
* :ref:`Access logs <plano_access_logging>` are written to the access log
* :ref:`Trace <plano_overview_tracing>` spans are finalized. If our example request was traced, a
trace span, describing the duration and details of the request would be created by the HCM when
processing request headers and then finalized by the HCM during post-request processing.

2
docs/source/resources/tech_overview/threading_model.rst
View file

@ -1,4 +1,4 @@
.. _arch_overview_threading:
.. _plano_overview_threading:
Threading Model
===============

4
package-lock.json generated
View file

@ -1,11 +1,11 @@
{
"name": "archgw-monorepo",
"name": "plano-monorepo",
"version": "0.1.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "archgw-monorepo",
"name": "plano-monorepo",
"version": "0.1.0",
"workspaces": [
"apps/*",

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