requirements.txt

fastapi>=0.104.0
uvicorn[standard]>=0.24.0
httpx>=0.25.0
qdrant-client>=1.6.0
ollama>=0.1.0
toml>=0.10.2
tiktoken>=0.5.0
apscheduler>=3.10.0
pytest>=7.0.0
pytest-asyncio>=0.21.0
Initial commit: Vera-AI v2 with async Qdrant, singleton pattern, monthly curation, and configurable UID/GID/TZ Features: - AsyncQdrantClient for non-blocking Qdrant operations - Singleton pattern for QdrantService - Monthly full curation (day 1 at 03:00) - Configurable UID/GID for Docker - Timezone support via TZ env var - Configurable log directory (VERA_LOG_DIR) - Volume mounts for config/, prompts/, logs/ - Standard Docker format with .env file Fixes: - Removed unused system_token_budget - Added semantic_score_threshold config - Fixed streaming response handling - Python-based healthcheck (no curl dependency) 2026-03-26 12:37:25 -05:00			`fastapi>=0.104.0`
			`uvicorn[standard]>=0.24.0`
			`httpx>=0.25.0`
			`qdrant-client>=1.6.0`
			`ollama>=0.1.0`
			`toml>=0.10.2`
			`tiktoken>=0.5.0`
			`apscheduler>=3.10.0`
v2.0.3: Improve error handling, add tests, cleanup - Fix bare except clauses in curator.py and main.py - Change embedding model to snowflake-arctic-embed2 - Increase semantic_score_threshold to 0.6 - Add memory context explanation to systemprompt.md - Add pytest dependencies to requirements.txt - Remove unused context_handler.py and .env.example - Add project documentation (CLAUDE.md) and test files Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> 2026-03-30 08:47:56 -05:00			`pytest>=7.0.0`
			`pytest-asyncio>=0.21.0`