- Add app/api/routes/agents.py with 11 endpoints:
GET/POST/PUT/DELETE /agents/local (local directory agent configs)
GET/POST/PUT/DELETE /agents/cloud (cloud connector agent configs)
GET /agents/catalog (hardcoded agent type catalog)
GET /agents/runs (paginated run logs with agent_id/page/limit filters)
POST /agents/{id}/run (manual trigger stub, dispatch wired in step 3.4)
- Tier-gate creation via combined local+cloud batch_active limit
- Ownership checks on all mutations (404 on mismatch)
- Cascade delete of run logs via SQLAlchemy relationship
- Register agents router in app/main.py
- Fix missing import json in app/agents/task_agent.py
- Introduced new API keys for Anthropic and Google in .env.example and settings.py
- Updated llm.py to retrieve API keys directly from settings
- Modified deploy.yaml to streamline code checkout and improve deployment process
- Replaced direct instantiation of ChatOpenAI with a centralized get_llm function in CheckpointAgent, NoteAgent, ProjectAgent, and TaskAgent.
- Introduced a new llm.py module to handle LLM model instantiation and API key management.
- Updated settings.py to include LLM_MODEL and LLM_ROUTER_MODEL configurations.
- Modified orchestrator.py to use get_router_llm for intent classification.
- Updated requirements.txt to include litellm for LLM management.
- Adjusted tests to mock get_llm instead of ChatOpenAI directly.
- Updated `TestModuleSingletons` in `test_execution_plan.py` to reflect new agent templates and playbook names.
- Changed assertions in playbook tests to match updated templates and agents.
- Introduced `test_storage.py` to cover the storage layer, including encryption, BlobStore, and VectorStore functionalities.
- Added tests for S3 interactions, ensuring upload, download, delete, and list operations work as expected.
- Implemented mock tests for Pinecone and Qdrant vector stores to validate upsert, search, and delete operations.
