chore: weekly Cloud API workflow to audit architecture docs; Python client + settings CLI#88
chore: weekly Cloud API workflow to audit architecture docs; Python client + settings CLI#88
Conversation
…re docs audit Includes: - Python Cloud API client (no provider LLM keys sent) - Weekly scheduled GH Action to start conversation - Entrypoint script for manual triggering - Plan README Co-authored-by: OpenHands-UNKNOWN openhands@all-hands.dev
…arate per method Co-authored-by: OpenHands-UNKNOWN openhands@all-hands.dev
Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
…t separate from weekly job) Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
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Summary of Changes
Hello @enyst, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request introduces an automated weekly workflow to audit and update architecture documentation using the OpenHands Cloud API. It includes a new Python client for the API, a dedicated script to initiate the audit conversation, and a separate CLI for managing LLM settings. The entire setup is designed with a strong focus on security, ensuring sensitive LLM keys are kept out of the continuous integration environment.
Highlights
- New Cloud API Client: A new Python client (
scripts/cloud_api.py) is introduced to interact with the OpenHands Cloud API, providing methods for managing settings and conversations. It is designed to explicitly avoid handling LLM API keys directly, enhancing security. - Automated Architecture Documentation Audit: A new weekly GitHub Action, driven by
scripts/weekly_arch_docs_task.py, is added to automatically trigger an AI agent to review and updatebackend.mdxandruntime.mdxarchitecture documentation. - Separate LLM Settings CLI: A dedicated command-line interface (
scripts/configure_cloud_llm_settings.py) is provided for one-off configuration of LLM models and base URLs on the OpenHands Cloud account, ensuring separation from the automated workflow. - Enhanced Security and Modularity: The overall design prioritizes keeping LLM provider keys out of CI by using only an
OPENHANDS_API_KEYfor the workflow and separating API methods and LLM configuration into distinct, reusable components.
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Code Review
This pull request introduces a weekly workflow to audit architecture documentation using a new Python client for the OpenHands Cloud API. The changes include the API client itself, a CLI for configuration, and the weekly task script. My review focuses on improving code maintainability and consistency. I've suggested refactoring repetitive code in the API client for building request bodies, ensuring consistent argument parsing in the CLI scripts, and adhering to Python style guidelines. These changes will make the new scripts easier to read and maintain.
…llm_api_key in /api/settings CLI + client Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
…; respond to review feedback - cloud_api.store_llm_settings: build params dict and filter None - cloud_api.create_conversation: unify optional params handling - settings CLI: strip whitespace in provider token values Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
…-url (address review) Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
…ON/text body); add requests import Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
…logs Co-authored-by: openhands <openhands@all-hands.dev> Model: GPT-5
1 participant
This PR adds a weekly GitHub Action that triggers an OpenHands Cloud conversation to audit and update the repository’s architecture docs. It is designed to keep API calls in python, separated and minimal.
What’s included
Why
How to enable
Add repository secret OPENHANDS_API_KEY in GitHub (Settings → Secrets and variables → Actions → New repository secret)
(Optional) If you want to set Cloud LLM model/base URL on your account, run:
python scripts/configure_cloud_llm_settings.py
--api-key $OPENHANDS_API_KEY
--llm-model "$LLM_MODEL"
--llm-base-url "$LLM_BASE_URL"
Optionally add provider tokens only if you explicitly want to:
--provider-token openai=$OPENAI_API_KEY
--provider-token groq=$GROQ_API_KEY
Notes
Co-authored-by: openhands openhands@all-hands.dev