Ollama Runtime:
- Add ollama_client.py for Ollama API integration
- Support for dots-ocr model via Ollama
- Add OLLAMA_BASE_URL configuration
- Update inference.py to support Ollama runtime (RUNTIME_TYPE=ollama)
- Update endpoints to handle async Ollama calls
- Alternative to local transformers model
RAG Implementation Plan:
- Create TODO-RAG.md with detailed Haystack integration plan
- Document Store setup (pgvector)
- Embedding model selection
- Ingest pipeline (PARSER → RAG)
- Query pipeline (RAG → LLM)
- Integration with DAGI Router
- Bot commands (/upload_doc, /ask_doc)
- Testing strategy
Now supports three runtime modes:
1. Local transformers (RUNTIME_TYPE=local)
2. Ollama (RUNTIME_TYPE=ollama)
3. Dummy (USE_DUMMY_PARSER=true)
G.2.5 - Tests:
- Add pytest test suite with fixtures
- test_preprocessing.py - PDF/image loading, normalization, validation
- test_postprocessing.py - chunks, QA pairs, markdown generation
- test_inference.py - dummy parser and inference functions
- test_api.py - API endpoint tests
- Add pytest.ini configuration
G.1.3 - dots.ocr Integration:
- Update model_loader.py with real model loading code
- Support for AutoModelForVision2Seq and AutoProcessor
- Device handling (CUDA/CPU/MPS) with fallback
- Error handling with dummy fallback option
- Update inference.py with real model inference
- Process images through model
- Generate and decode outputs
- Parse model output to blocks
- Add model_output_parser.py
- Parse JSON or plain text model output
- Convert to structured blocks
- Layout detection support (placeholder)
Dependencies:
- Add pytest, pytest-asyncio, httpx for testing
- Replace Whisper subprocess calls with direct qwen3_asr_toolkit API
- Remove subprocess dependencies, use pure Python API
- Update to use DASHSCOPE_API_KEY instead of WHISPER_MODEL
- Cleaner code without CLI calls
- Better Ukrainian language recognition quality
- Add STT service with Whisper support (faster-whisper, whisper CLI, OpenAI API)
- Update Gateway to handle Telegram voice/audio/video_note messages
- Add STT service to docker-compose.yml
- Gateway now converts voice → text → DAGI Router → text response
- Remove all FK constraints from models (users, teams, channels, agents)
- Keep fields as optional nullable String for testing DAARWIZZ
- Update SQL migration to remove all REFERENCES
- Fix metadata -> meta in migration
- Allows service to work without base tables for testing
- Remove FK constraint from UserFact.team_id (teams table may not exist)
- Update SQL migration to remove FK constraint
- team_id remains optional String field without FK
- Fix DialogSummary.metadata -> DialogSummary.meta
- Fix AgentMemoryFactsVector.metadata -> AgentMemoryFactsVector.meta
- All metadata fields now renamed to meta
- Rename metadata to meta in all models (UserFact, DialogSummary, AgentMemoryFactsVector)
- Update schemas to use meta instead of metadata
- Update SQL migration to use meta column name
- Fixes SQLAlchemy reserved name conflict
- Add memory-service as a service (not under networks:)
- Create Dockerfile for memory-service
- Configure depends_on city-db with healthcheck condition
- Set DATABASE_URL to connect to city-db
- Move models.py, schemas.py, crud.py, main.py to app/
- Update imports to use app.* prefix
- Update README with new structure
- Fix uvicorn run command for new structure
- Fixed Gateway to extract response from data.text field
- GPU working: RTX 4000 Ada, response time 7-10s (was 30-40s)
- DAARWIZZ now responds correctly with full personality
- Started Memory Service structure
