- New app/core/langfuse_client.py: lazy singleton client, get_prompt_or_fallback()
helper (returns raw template + prompt obj for linking), extract_usage() for token
counts. No-ops when LANGFUSE_* env vars are not set.
- deep_agent.py: home-agent and floating-agent runs wrapped in spans; each ainvoke
wrapped in a generation with model/input/output/usage; prompts fetched from
Langfuse (adiuva-home-agent, adiuva-floating-agent, adiuva-floating-classifier)
with hardcoded fallback.
- agent_runner.py: step1-classifier and step2-processor LLM calls traced; batch
agent _run_agent_with_tools spans + generations; cloud-processor included.
Prompts: adiuva-step1-classifier, adiuva-step2-processor, adiuva-cloud-processor.
- agent_setup.py: journey-setup span + generation per ainvoke; prompt_obj stored
on JourneySession and reused across turns. Prompt: journey_system.
- settings.py: LANGFUSE_SECRET_KEY, LANGFUSE_PUBLIC_KEY, LANGFUSE_HOST added.
- .env.example: Langfuse section with EU/US/self-hosted host comments.
- requirements.txt: langfuse>=2.0.0.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replace deprecated Pydantic v1 `class Config:` inner class with
`model_config = SettingsConfigDict(...)` to eliminate the deprecation
warning emitted on every test run.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- 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.
