Initial commit: AI Video Assistant fullstack platform.
Add pipecat-based backend with WebRTC/WS voice routes, Next.js frontend, and Docker Compose orchestration. Co-authored-by: Cursor <cursoragent@cursor.com>
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backend/.env.example
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35
backend/.env.example
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# 复制为 .env 并填入真实值。
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# 国产栈走 OpenAI 兼容协议:每类服务给一个 base_url + api_key + 模型名即可。
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# ---- LLM:DeepSeek(OpenAI 兼容,直连云端,只需 key) ----
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LLM_BASE_URL=https://api.deepseek.com/v1
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LLM_API_KEY=sk-your-deepseek-key
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LLM_MODEL=deepseek-chat
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# ---- STT:SenseVoice / FunASR ----
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# 需要本地起一个 OpenAI 兼容的语音转写服务(/v1/audio/transcriptions),
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# 例如用 funasr / sherpa-onnx / speaches 包一层。下面填那个服务地址。
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STT_BASE_URL=http://localhost:8001/v1
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STT_API_KEY=local
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STT_MODEL=sensevoice
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# ---- TTS:CosyVoice ----
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# 同样需要本地起一个 OpenAI 兼容的 TTS 服务(/v1/audio/speech)。
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TTS_BASE_URL=http://localhost:8002/v1
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TTS_API_KEY=local
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TTS_MODEL=cosyvoice
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TTS_VOICE=中文女
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# ---- Realtime 模式(可选,先不接也行) ----
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REALTIME_API_KEY=
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REALTIME_MODEL=gpt-realtime
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# ---- 数据库(Postgres) ----
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# 本地直连;docker compose 里则用 postgres:5432
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DATABASE_URL=postgresql+asyncpg://postgres:postgres@localhost:5432/postgres
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# ---- 服务监听 & 跨域 ----
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HOST=0.0.0.0
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PORT=8000
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# 前端开发地址,允许跨域
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CORS_ORIGINS=http://localhost:3000
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