mirror of
https://github.com/katanemo/plano.git
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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>
|
||
|---|---|---|
| .. | ||
| crewai | ||
| langchain | ||
| config.yaml | ||
| docker-compose.yaml | ||
| Dockerfile | ||
| openai_protocol.py | ||
| pyproject.toml | ||
| README.md | ||
| traces.png | ||
| uv.lock | ||
Travel Agents in CrewAI and LangChain - with Plano
What you'll see: A travel assistant that seamlessly combines flight booking (CrewAI) and weather forecasts (LangChain) in a single conversation - with unified routing, orchestration, moderation, and observability across both frameworks.
The Problem
Building multi-agent systems today forces developers to:
- Pick one framework - can't mix CrewAI, LangChain, or custom agents easily
- Write plumbing code - authentication, request routing, error handling
- Rebuild for changes - want to swap frameworks? Start over
- Limited observability - no unified view across different agent frameworks
Plano's Solution
Plano acts as a framework-agnostic proxy and data plane that:
- Routes requests to the right agent(s), in the right order (CrewAI, LangChain, or custom)
- Normalizes requests/responses across frameworks automatically
- Provides unified authentication, tracing, and logs
- Lets you mix and match frameworks without coupling, so that you can continue to innovate easily
How To Run
Prerequisites
-
Install Plano CLI
uv tool install planoai -
Set Environment Variables
export OPENAI_API_KEY=your_key_here export AEROAPI_KEY=your_key_here # Get your free API key at https://flightaware.com/aeroapi/
Start the Demo
# From the demo directory
cd demos/use_cases/multi_agent_with_crewai_langchain
# Build and start all services
docker-compose up -d
This starts:
- Plano (ports 12000, 8001) - routing and orchestration
- CrewAI Flight Agent (port 10520) - flight search
- LangChain Weather Agent (port 10510) - weather forecasts
- AnythingLLM (port 3001) - chat interface
- Jaeger (port 16686) - distributed tracing
Try It Out
-
Open the Chat Interface
- Navigate to http://localhost:3001
- Create an account (stored locally)
-
Ask Multi-Agent Questions
"What's the weather in San Francisco and can you find flights from Seattle to San Francisco?"Plano automatically:
- Routes the weather part to the LangChain agent
- Routes the flight part to the CrewAI agent
- Combines responses seamlessly
-
View Distributed Traces
- Open http://localhost:16686 (Jaeger UI)
- See how requests flow through both agents
Architecture
┌──────────────┐
│ AnythingLLM │ (Chat Interface)
└──────┬───────┘
│
v
┌─────────────┐
│ Plano │ (Orchestration & DataPlane)
└──────┬──────┘
│
├──────────────┬──────────────┐
v v v
┌────────────┐ ┌────────────┐ ┌──────────┐
│ CrewAI │ │ LangChain │ │ Jaeger │
│ Flight │ │ Weather │ │ (Traces) │
│ Agent │ │ Agent │ └──────────┘
└────────────┘ └────────────┘
├──────────────├
v v
┌─────────────┐
│ Plano │ (Proxy LLM calls)
└──────┬──────┘
Travel Agents
Flight Agent
- Framework: CrewAI
- Capabilities: Flight search, itinerary planning
- Tools:
resolve_airport_code,search_flights - Data Source: FlightAware AeroAPI
Weather Agent
- Framework: LangChain
- Capabilities: Weather forecasts, conditions
- Tools:
get_weather_forecast - Data Source: Open-Meteo API
Cleanup
docker-compose down
Next Steps
- Add your own agent - any framework, just expose the OpenAI-compatible endpoint
- Custom routing - modify
config.yamlto change agent selection logic - Production deployment - see Plano docs for scaling guidance
