# CLAUDE.md This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository. ## Project Overview CamTalk is a multimodal real-time AI visual dialogue assistant. Users interact via camera and microphone — the app captures visual scenes and voice input, sends them to AI services, and responds with both text and speech. The project is currently in the design-document phase; source code is being built incrementally. **Design docs (Chinese):** `docs/` contains the full architecture, API contracts, user stories, cost control strategies, and technology selection rationale. Read these before implementing any feature. ## Architecture Three-layer system: 1. **Browser Client** (React 18 + TypeScript, Vite) — media capture, edge preprocessing (VAD via `@ricky0123/vad-web`, keyframe detection via ONNX Runtime Web), UI rendering. Core hook: `useVisionSession()`. 2. **Go Gateway** (gorilla/websocket, Redis, Viper, Zap) — WebSocket server, session management, model routing, AI orchestration, rate limiting. One goroutine per WebSocket connection. 3. **Cloud AI Services** — GPT-4o (LLM), Deepgram (STT), OpenAI TTS. Accessed only through the Go gateway, never directly from the browser. **Key pattern:** LLM text chunks and TTS audio are streamed in parallel to the client to minimize perceived latency. **Storage:** Cold/hot separation — Redis for real-time session state, PostgreSQL for conversation history and usage stats (deferred past MVP). Repository interface pattern (`HistoryRepository`, `UsageRepository`) with in-memory MVP implementations. ## Tech Stack | Layer | Tech | |-------|------| | Frontend | React 18, TypeScript, Vite, ONNX Runtime Web, @ricky0123/vad-web | | Backend | Go, gorilla/websocket, Redis, Viper, Zap | | LLM | GPT-4o (primary), Claude Sonnet (backup) | | STT | Deepgram (primary), FunASR (self-hosted backup) | | TTS | OpenAI TTS (primary), Edge TTS (free alternative) | | Model routing | GPT-4o-mini for lightweight classification | ## Build & Run Commands ```bash # Frontend cd frontend && npm install npm run dev # Vite dev server npm run build # Production build npm run lint # ESLint npm run test # Vitest # Backend cd backend && go mod download go run ./cmd/server # Start gateway on :8080 go build -o bin/camtalk ./cmd/server go test ./... # Run all tests go test -run TestName ./path # Run single test go vet ./... # Static analysis ``` Infrastructure: Redis required for session state. PostgreSQL optional for MVP (in-memory fallback). ## WebSocket Protocol Endpoint: `ws://localhost:8080/ws` All messages are JSON text frames with `{type, request_id?, timestamp?}` envelope. See `docs/AI 视觉对话助手/项目实现/接口文档.md` for the full contract. **Client → Server:** `query` (image Base64 + audio Base64), `config`, `interrupt`, `ping` **Server → Client:** `connected`, `stt_result`, `llm_chunk`, `llm_done`, `tts_audio`, `error`, `pong` **Heartbeat:** Client pings every 30s. Server disconnects after 60s of silence. **Reconnection:** Exponential backoff with jitter — 1s, 2s, 4s, 8s… max 30s. ## REST API (Auxiliary) - `GET /api/health` — health check (version, uptime, active sessions) - `POST /api/sessions` — create session (optional, MVP auto-creates on WS connect) - `DELETE /api/sessions/{id}` — destroy session ## Error Codes `INVALID_MESSAGE`, `SESSION_NOT_FOUND`, `RATE_LIMITED`, `IMAGE_TOO_LARGE`, `AUDIO_TOO_SHORT`, `LLM_TIMEOUT`, `LLM_ERROR`, `STT_ERROR`, `TTS_ERROR`, `INTERNAL_ERROR` ## Frontend Component Structure | Component | Responsibility | |-----------|---------------| | `CameraManager` | Camera stream capture | | `MicManager` | Microphone audio capture | | `EdgeProcessor` | VAD + keyframe detection (ONNX Runtime) | | `WebSocketManager` | WS connection lifecycle | | `ChatPanel` | Message display | | `VideoPreview` | Camera feed display | ## Backend Module Structure | Module | Responsibility | |--------|---------------| | WebSocket Hub | Connection management, broadcast/direct push | | Session Manager | Session state, conversation history (Redis + TTL) | | Model Router | Select AI model per request (rule engine + cost threshold) | | AI Orchestrator | Parallel/sequential AI calls with context timeout | | Rate Limiter | Per-user token bucket rate limiting | ## Coding Conventions - **Go:** Follow standard Go conventions. Use `context.Context` for cancellation/timeout in all AI calls. Use `sync.RWMutex` for concurrent map access. Struct tags use `json:"snake_case"`. - **TypeScript:** Strict mode. Interfaces for all data models. WebSocket message types as discriminated unions (`type` field). - **Commit messages:** Use conventional commits format: `feat:`, `fix:`, `docs:`, `refactor:`, `test:`, `chore:` - **No auto-push:** Do not push to remote unless explicitly asked. - **Docs-first:** When implementing a feature, update the relevant interface doc in `docs/` if the implementation diverges from the spec.