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📝 OpenAI Realtime Transcription

\n Transcribe audio in real-time using OpenAI's Realtime API. \n View source\n

\n\n

\n Model\n \n

\n \n

\n Language\n \n

\n \n

\n VAD\n \n

\n \n

\n \n \n \n

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Your voice is captured via WebRTC\n2. Audio is streamed to OpenAI's transcription service\n3. Transcriptions are returned in real-time\n4. No AI responses are generated (transcription only)\n\n## Model Differences\n\n- **GPT-4o Transcribe**: Streaming transcription with incremental updates\n- **GPT-4o Mini Transcribe**: Smaller model, streaming transcription \n- **Whisper-1**: Complete transcription after each speech segment (no streaming)\n\n## Configuration Options\n\n- **Model**: Select the transcription model\n- **Language**: Choose the primary language for better accuracy\n- **VAD**: Enable/disable automatic voice activity detection\n- **Logprobs**: Include confidence scores (for advanced use)\n\n## Usage\n\n1. Click \"Start\" to begin transcription\n2. Allow microphone access when prompted\n3. Start speaking - transcriptions appear in real-time\n4. Partial transcriptions update as you speak\n5. Final transcriptions are marked in green\n6. Click \"Stop\" to end the session\n\n## API Endpoints\n\n- `GET /` - Serves the transcription interface\n- `POST /rtc` - Creates a WebRTC transcription session\n- `POST /observer/:callId` - WebSocket observer for transcription events\n\n## Environment Variables\n\nSet in your Val Town environment:\n- `OPENAI_API_KEY` - Your OpenAI API key (required)\n\n## Local Development\n\n```bash\n# Install Deno\ncurl -fsSL https://deno.land/install.sh | sh\n\n# Run locally\ndeno run --allow-all main.tsx\n```\n\n## Val Town Deployment\n\n1. Fork/remix this val on Val Town\n2. Add your `OPENAI_API_KEY` to Val Town secrets\n3. Your app will be available at `https://[your-val-name].val.run`\n\n## Technical Details\n\nThe app uses OpenAI's Realtime API in transcription mode:\n- Session type: `transcription` (not `realtime`)\n- Audio format: PCM16\n- Noise reduction: Near-field (optimized for close microphones)\n- WebRTC data channel for receiving transcription events\n\n## Event Flow\n\n1. `input_audio_buffer.committed` - Audio chunk received\n2. `conversation.item.input_audio_transcription.delta` - Partial transcription\n3. `conversation.item.input_audio_transcription.completed` - Final transcription\n\n## Credits\n\nBuilt with OpenAI's Realtime API for transcription-only use cases.",[],[112],"ab37af24-895f-11f0-a0eb-0224a6c84d84",".vtignore","01991399-632f-7218-92fe-05e5d1f164d5",["D",1756970443473],".git\n.vscode\n.cursorrules\n.DS_Store\nnode_modules\nvendor",[],[119],"ab37ad8a-895f-11f0-a0eb-0224a6c84d84",".gitattributes","01991399-632f-7218-92fe-0233da43ed39",["D",1756970443473],"# Auto detect text files 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\"gpt-4o-transcribe\" | \"gpt-4o-mini-transcribe\" | \"whisper-1\" | \"gpt-realtime-whisper\";\n language?: string;\n enableVAD?: boolean;\n}\n\nexport function makeTranscriptionSession(config: TranscriptionConfig = {}) {\n const {\n model = \"gpt-4o-transcribe\",\n language = \"en\",\n enableVAD = true,\n } = config;\n\n // Create transcription session config (based on Justin Uberti's working implementation)\n return {\n type: \"transcription\",\n audio: {\n input: {\n transcription: { model, language },\n turn_detection: enableVAD ? { type: \"server_vad\" } : null,\n },\n },\n };\n}",[],[133,141],"f3f99820-8a37-11f0-a608-0224a6c84d84","rtc.ts","01991399-632f-7218-92fd-f412c0084bc0",["D",1757063336938],4,"import { Hono } from \"npm:hono\";\nimport { makeHeaders, makeTranscriptionSession } from \"./utils.ts\";\n\nconst rtc = new Hono();\n\n// POST /rtc : create a new transcription call\nrtc.post(\"/\", async (c) => {\n // Get transcription configuration from query params\n const sessionConfig = makeTranscriptionSession({\n model: c.req.query(\"model\") as any || \"gpt-4o-transcribe\",\n language: c.req.query(\"language\") || \"en\",\n enableVAD: c.req.query(\"vad\") !== \"false\",\n });\n\n const realtimeUrl = \"https://api.openai.com/v1/realtime/calls\";\n const formData = new FormData();\n formData.set(\"sdp\", await c.req.text());\n formData.set(\"session\", JSON.stringify(sessionConfig));\n const sdpResp = await fetch(realtimeUrl, {\n method: \"POST\",\n headers: makeHeaders(),\n body: formData,\n });\n\n if (!sdpResp.ok) {\n const errText = await sdpResp.text().catch(() => \"\");\n console.error(\n `🔴 Failed to establish WebRTC connection: ${sdpResp.status} ${errText}`,\n );\n return c.text(\"Internal error\", 500);\n }\n\n return c.newResponse(sdpResp.body, {\n headers: { \"Content-Type\": sdpResp.headers.get(\"Content-Type\") },\n });\n});\n\nexport default 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