meshai/requirements.txt

meshtastic>=2.3.0
pyyaml>=6.0
aiosqlite>=0.19.0
openai>=1.0.0
anthropic>=0.18.0
google-genai>=1.0.0
rich>=13.0.0
httpx>=0.25.0
fastembed>=0.3.0
sqlite-vec>=0.1.0
numpy
fastapi>=0.110.0
uvicorn[standard]>=0.27.0
Initial commit: MeshAI - LLM-powered Meshtastic assistant Features: - Multi-backend LLM support (OpenAI, Anthropic, Google) - Rolling summary memory for token optimization (~70-80% reduction) - Per-user conversation history with SQLite persistence - Bang commands (!help, !ping, !reset, !status, !weather) - Meshtastic integration via serial or TCP - Message chunking for mesh network constraints (150 char limit) - Rate limiting to prevent network congestion - Rich TUI configurator - Docker support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> 2025-12-15 11:53:46 -07:00			`meshtastic>=2.3.0`
			`pyyaml>=6.0`
			`aiosqlite>=0.19.0`
			`openai>=1.0.0`
			`anthropic>=0.18.0`
Migrate Google backend from deprecated google-generativeai to google-genai SDK with grounding support Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> 2026-02-24 04:44:44 +00:00			`google-genai>=1.0.0`
Initial commit: MeshAI - LLM-powered Meshtastic assistant Features: - Multi-backend LLM support (OpenAI, Anthropic, Google) - Rolling summary memory for token optimization (~70-80% reduction) - Per-user conversation history with SQLite persistence - Bang commands (!help, !ping, !reset, !status, !weather) - Meshtastic integration via serial or TCP - Message chunking for mesh network constraints (150 char limit) - Rate limiting to prevent network congestion - Rich TUI configurator - Docker support 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> 2025-12-15 11:53:46 -07:00			`rich>=13.0.0`
			`httpx>=0.25.0`
feat: Hybrid RAG knowledge base, sentence-aware chunking, MeshMonitor HTTP sync Knowledge Base: - Hybrid FTS5 + vector search using sqlite-vec and bge-small-en-v1.5 - Reciprocal Rank Fusion for result merging - Domain-aware query construction handles typos - Configurable weights for keyword vs semantic matching Message Chunking: - Sentence-aware splitting respects message boundaries - Continuation prompts for long responses - Natural follow-up detection (yes, ok, continue, more, etc.) - Per-user continuation state management MeshMonitor Integration: - HTTP API trigger sync (replaces file-based triggers.json) - Dynamic refresh interval - Trigger injection into LLM prompt Other: - Updated system prompt for better response length control - Simplified responder to handle message lists - Updated README with new features and architecture diagram - Cleaned up config.example.yaml Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> 2026-05-04 07:44:12 +00:00			`fastembed>=0.3.0`
			`sqlite-vec>=0.1.0`
			`numpy`
feat(dashboard): embedded FastAPI backend with REST API + WebSocket - FastAPI runs in MeshAI asyncio loop (no separate process) - REST API: /api/status, /api/health, /api/nodes, /api/edges, /api/regions, /api/sources, /api/config, /api/alerts - WebSocket at /ws/live pushes health updates and alerts - Config CRUD: GET/PUT per section with validation and save - DashboardConfig with port/host in config.yaml 2026-05-12 15:47:58 +00:00			`fastapi>=0.110.0`
			`uvicorn[standard]>=0.27.0`