Add streaming STT spec

openapi.yaml

@@ -3661,6 +3661,239 @@ paths:
               schema:
                 $ref: '#/components/schemas/ErrorData'
 
+  /realtime:
+    get:
+      tags: ['Audio']
+      summary: Real-time audio transcription via WebSocket
+      description: |
+        Establishes a WebSocket connection for real-time audio transcription. This endpoint uses WebSocket protocol (wss://api.together.ai/v1/realtime) for bidirectional streaming communication.
+
+        **Connection Setup:**
+        - Protocol: WebSocket (wss://)
+        - Authentication: Pass API key as Bearer token in Authorization header
+        - Parameters: Sent as query parameters (model, input_audio_format)
+
+        **Client Events:**
+        - `input_audio_buffer.append`: Send audio chunks as base64-encoded data
+          ```json
+          {
+            "type": "input_audio_buffer.append",
+            "audio": "<base64_encoded_audio_chunk>"
+          }
+          ```
+        - `input_audio_buffer.commit`: Signal end of audio stream
+          ```json
+          {
+            "type": "input_audio_buffer.commit"
+          }
+          ```
+
+        **Server Events:**
+        - `session.created`: Initial session confirmation (sent first)
+          ```json
+          {
+            "type": "session.created",
+            "session": {
+              "id": "session-id",
+              "object": "realtime.session",
+              "modalities": ["audio"],
+              "model": "openai/whisper-large-v3"
+            }
+          }
+          ```
+        - `conversation.item.input_audio_transcription.delta`: Partial transcription results
+          ```json
+          {
+            "type": "conversation.item.input_audio_transcription.delta",
+            "delta": "The quick brown"
+          }
+          ```
+        - `conversation.item.input_audio_transcription.completed`: Final transcription
+          ```json
+          {
+            "type": "conversation.item.input_audio_transcription.completed",
+            "transcript": "The quick brown fox jumps over the lazy dog"
+          }
+          ```
+        - `conversation.item.input_audio_transcription.failed`: Error occurred
+          ```json
+          {
+            "type": "conversation.item.input_audio_transcription.failed",
+            "error": {
+              "message": "Error description",
+              "type": "invalid_request_error",
+              "param": null,
+              "code": "invalid_api_key"
+            }
+          }
+          ```
+
+        **Error Codes:**
+        - `invalid_api_key`: Invalid API key provided (401)
+        - `missing_api_key`: Authorization header missing (401)
+        - `model_not_available`: Invalid or unavailable model (400)
+        - Unsupported audio format errors (400)
+
+      operationId: realtime-transcription
+      x-codeSamples:
+        - lang: Python
+          label: Python WebSocket Client
+          source: |
+            import asyncio
+            import websockets
+            import json
+            import base64
+            import os
+
+            async def transcribe_audio():
+                api_key = os.environ.get("TOGETHER_API_KEY")
+                url = "wss://api.together.ai/v1/realtime?model=openai/whisper-large-v3&input_audio_format=pcm_s16le_16000"
+
+                headers = {
+                    "Authorization": f"Bearer {api_key}"
+                }
+
+                async with websockets.connect(url, additional_headers=headers) as ws:
+                    # Read audio file
+                    with open("audio.wav", "rb") as f:
+                        audio_data = f.read()
+
+                    # Send audio in chunks with delay to simulate real-time
+                    chunk_size = 8192
+                    bytes_per_second = 16000 * 2  # 16kHz * 2 bytes (16-bit)
+                    delay_per_chunk = chunk_size / bytes_per_second
+
+                    for i in range(0, len(audio_data), chunk_size):
+                        chunk = audio_data[i:i+chunk_size]
+                        base64_chunk = base64.b64encode(chunk).decode('utf-8')
+                        await ws.send(json.dumps({
+                            "type": "input_audio_buffer.append",
+                            "audio": base64_chunk
+                        }))
+                        # Simulate real-time streaming
+                        if i + chunk_size < len(audio_data):
+                            await asyncio.sleep(delay_per_chunk)
+
+                    # Commit the audio buffer
+                    await ws.send(json.dumps({
+                        "type": "input_audio_buffer.commit"
+                    }))
+
+                    # Receive transcription results
+                    async for message in ws:
+                        data = json.loads(message)
+                        if data["type"] == "conversation.item.input_audio_transcription.delta":
+                            print(f"Partial: {data['delta']}")
+                        elif data["type"] == "conversation.item.input_audio_transcription.completed":
+                            print(f"Final: {data['transcript']}")
+                            break
+                        elif data["type"] == "conversation.item.input_audio_transcription.failed":
+                            error = data.get("error", {})
+                            print(f"Error: {error.get('message')}")
+                            break
+
+            asyncio.run(transcribe_audio())
+        - lang: JavaScript
+          label: Node.js WebSocket Client
+          source: |
+            import WebSocket from 'ws';
+            import fs from 'fs';
+
+            const apiKey = process.env.TOGETHER_API_KEY;
+            const url = 'wss://api.together.ai/v1/realtime?model=openai/whisper-large-v3&input_audio_format=pcm_s16le_16000';
+
+            const ws = new WebSocket(url, {
+              headers: {
+                'Authorization': `Bearer ${apiKey}`
+              }
+            });
+
+            ws.on('open', async () => {
+              console.log('WebSocket connection established!');
+
+              // Read audio file
+              const audioData = fs.readFileSync('audio.wav');
+
+              // Send audio in chunks with delay to simulate real-time
+              const chunkSize = 8192;
+              const bytesPerSecond = 16000 * 2;  // 16kHz * 2 bytes (16-bit)
+              const delayPerChunk = (chunkSize / bytesPerSecond) * 1000;  // Convert to ms
+
+              for (let i = 0; i < audioData.length; i += chunkSize) {
+                const chunk = audioData.slice(i, i + chunkSize);
+                const base64Chunk = chunk.toString('base64');
+                ws.send(JSON.stringify({
+                  type: 'input_audio_buffer.append',
+                  audio: base64Chunk
+                }));
+
+                // Simulate real-time streaming
+                if (i + chunkSize < audioData.length) {
+                  await new Promise(resolve => setTimeout(resolve, delayPerChunk));
+                }
+              }
+
+              // Commit audio buffer
+              ws.send(JSON.stringify({
+                type: 'input_audio_buffer.commit'
+              }));
+            });
+
+            ws.on('message', (data) => {
+              const message = JSON.parse(data.toString());
+
+              if (message.type === 'conversation.item.input_audio_transcription.delta') {
+                console.log(`Partial: ${message.delta}`);
+              } else if (message.type === 'conversation.item.input_audio_transcription.completed') {
+                console.log(`Final: ${message.transcript}`);
+                ws.close();
+              } else if (message.type === 'conversation.item.input_audio_transcription.failed') {
+                const errorMessage = message.error?.message ?? message.message ?? 'Unknown error';
+                console.error(`Error: ${errorMessage}`);
+                ws.close();
+              }
+            });
+
+            ws.on('error', (error) => {
+              console.error('WebSocket error:', error);
+            });
+      parameters:
+        - in: query
+          name: model
+          required: true
+          schema:
+            type: string
+            enum:
+              - openai/whisper-large-v3
+            default: openai/whisper-large-v3
+          description: The Whisper model to use for transcription
+        - in: query
+          name: input_audio_format
+          required: true
+          schema:
+            type: string
+            enum:
+              - pcm_s16le_16000
+            default: pcm_s16le_16000
+          description: Audio format specification. Currently supports 16-bit PCM at 16kHz sample rate.
+      responses:
+        '101':
+          description: |
+            Switching Protocols - WebSocket connection established successfully.
+
+            Error message format:
+            ```json
+            {
+              "type": "conversation.item.input_audio_transcription.failed",
+              "error": {
+                "message": "Error description",
+                "type": "invalid_request_error",
+                "param": null,
+                "code": "error_code"
+              }
+            }
+            ```
+
 components:
   securitySchemes:
     bearerAuth: