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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>
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| .. | ||
| hurl_tests | ||
| config.yaml | ||
| docker-compose.yaml | ||
| plano_config_local.yaml | ||
| README.md | ||
| test_router_endpoint.rest | ||
Usage based LLM Routing
This demo shows how you can use user preferences to route user prompts to appropriate llm. See config.yaml for details on how you can define user preferences.
How to start the demo
Make sure your machine is up to date with latest version of plano. And you have activated the virtual environment.
- start anythingllm
(venv) $ cd demos/use_cases/preference_based_routing
(venv) $ docker compose up -d
- start plano in the foreground
(venv) $ planoai up --service plano --foreground
# 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 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!
...
- open AnythingLLM http://localhost:3001/
Testing out preference based routing
We have defined two routes 1. code generation and 2. code understanding
For code generation query LLM that is better suited for code generation wil handle the request,
If you look at the logs you'd see that code generation llm was selected,
...
2025-05-31T01:02:19.382716Z INFO brightstaff::router::llm_router: router response: {'route': 'code_generation'}, response time: 203ms
...
Now if you ask for query related to code understanding you'd see llm that is better suited to handle code understanding in handled,
...
2025-05-31T01:06:33.555680Z INFO brightstaff::router::llm_router: router response: {'route': 'code_understanding'}, response time: 327ms
...