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699677f 0b2d478 699677f 0b2d478 699677f 0b2d478 699677f 2bb7b65 699677f 0b2d478 699677f af380f4 699677f 0b2d478 699677f b9457bc 699677f 0b2d478 b9457bc 0b2d478 b9457bc 0b2d478 699677f ee0e82d b9457bc 2bb7b65 0b2d478 2bb7b65 0b2d478 2bb7b65 0b2d478 2bb7b65 699677f 2bb7b65 699677f b9457bc 0b2d478 b9457bc 0b2d478 b9457bc 0b2d478 b9457bc 699677f 2bb7b65 699677f b9457bc 0b2d478 ee0e82d b9457bc 0b2d478 b9457bc 0b2d478 b9457bc 2bb7b65 699677f 3e66461 0b2d478 3e66461 0b2d478 3e66461 0b2d478 3e66461 2bb7b65 af380f4 2bb7b65 3e66461 699677f 3e66461 699677f ee0e82d 699677f 0b2d478 699677f ee0e82d a9430e5 ee0e82d 699677f a9430e5 699677f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 | """API routes for the voice agent."""
from __future__ import annotations
import json
import uuid
from pathlib import Path
import shutil
import anyio
from fastapi import APIRouter, File, Form, UploadFile, WebSocket, WebSocketDisconnect
from fastapi.responses import FileResponse, JSONResponse
from starlette.websockets import WebSocketState
from ..core.errors import SpeechError, ValidationError, LLMError
from ..core.logging import get_logger
from ..services.pipeline import VoicePipeline
from ..services.agent.agent_pipeline import AgentPipeline
from ..services.stt import SpeechToTextService
from ..services.vad import SileroVADStream
from ..utils.audio import encode_base64
from ..core.config import get_settings
router = APIRouter()
MAX_FILE_SIZE_BYTES = 15 * 1024 * 1024
DEFAULT_STREAM_CONTENT_TYPE = "audio/ogg"
NO_MATCH_REPLY = "Sorry, I didn't catch that. Please try again."
@router.get("/health")
async def health() -> dict[str, str]:
"""Health check endpoint."""
return {"status": "ok"}
@router.get("/ws-demo")
async def ws_demo() -> FileResponse:
"""Serve a simple WebSocket streaming demo page."""
demo_path = Path(__file__).resolve().parent.parent / "utils" / "ws_demo.html"
return FileResponse(demo_path)
@router.post("/v1/agent/upload")
async def agent_upload(files: list[UploadFile] = File(...)) -> JSONResponse:
"""Upload files for local RAG indexing."""
settings = get_settings()
data_dir = Path(settings.data_dir)
data_dir.mkdir(parents=True, exist_ok=True)
saved: list[str] = []
for file in files:
content = await file.read()
if not content:
continue
target = data_dir / file.filename
target.write_bytes(content)
saved.append(file.filename)
await AgentPipeline().rebuild_rag()
return JSONResponse({"status": "ok", "files": saved})
@router.post("/v1/agent/reset")
async def agent_reset() -> JSONResponse:
"""Reset local RAG + memory storage."""
settings = get_settings()
data_dir = Path(settings.data_dir)
store_dir = Path(settings.vector_store_dir)
if data_dir.exists():
shutil.rmtree(data_dir, ignore_errors=True)
if store_dir.exists():
shutil.rmtree(store_dir, ignore_errors=True)
data_dir.mkdir(parents=True, exist_ok=True)
store_dir.mkdir(parents=True, exist_ok=True)
AgentPipeline().reset()
return JSONResponse({"status": "ok"})
@router.post("/v1/voice/file")
async def voice_file(
file: UploadFile = File(...),
prompt: str | None = Form(default=None),
return_audio: bool = Form(default=True),
llm_provider: str | None = Form(default=None),
) -> JSONResponse:
"""Process uploaded audio file and return transcript + reply."""
request_id = str(uuid.uuid4())
log = get_logger(request_id=request_id, endpoint="/v1/voice/file")
if not file:
raise ValidationError(code="file_missing", message="Audio file is required.")
audio_bytes = await file.read()
if not audio_bytes:
raise ValidationError(code="file_empty", message="Audio file is empty.")
if len(audio_bytes) > MAX_FILE_SIZE_BYTES:
raise ValidationError(code="file_too_large", message="File exceeds 15MB limit.")
pipeline = VoicePipeline()
if llm_provider and llm_provider not in {
"foundry_agent",
"azure_openai",
"local_agent",
}:
raise ValidationError(
code="llm_provider",
message="LLM provider must be 'foundry_agent', 'azure_openai', or 'local_agent'.",
)
if llm_provider == "local_agent":
agent = AgentPipeline()
result = await agent.run_audio(
audio_bytes=audio_bytes,
filename=file.filename,
content_type=file.content_type,
prompt=prompt,
return_audio=return_audio,
llm_provider="azure_openai",
)
else:
result = await pipeline.run(
audio_bytes=audio_bytes,
filename=file.filename,
content_type=file.content_type,
prompt=prompt,
return_audio=return_audio,
llm_provider=llm_provider,
)
reply_audio_base64 = (
encode_base64(result.reply_audio) if result.reply_audio else None
)
response_body = {
"transcript": result.transcript,
"reply_text": result.reply_text,
"audio_format": "wav",
"reply_audio_base64": reply_audio_base64,
"timings_ms": result.timings_ms,
}
log.info(
"voice_request_complete",
file_name=file.filename,
file_size=len(audio_bytes),
timings_ms=result.timings_ms,
return_audio=return_audio,
)
return JSONResponse(response_body)
@router.websocket("/ws/voice")
async def voice_stream(websocket: WebSocket) -> None:
"""Stream audio over WebSocket, then process on 'stop'."""
await websocket.accept()
request_id = str(uuid.uuid4())
log = get_logger(request_id=request_id, endpoint="/ws/voice")
buffer = bytearray()
content_type: str | None = DEFAULT_STREAM_CONTENT_TYPE
prompt: str | None = None
return_audio = True
stt_session = None
frames_sent: int | None = None
avg_rms: float | None = None
llm_provider: str | None = None
vad_stream: SileroVADStream | None = None
segment_processing = False
session_id: str | None = None
async def _finalize_segment() -> None:
nonlocal stt_session, segment_processing, vad_stream
if stt_session is None:
raise ValidationError(
code="stt_not_started", message="STT session not started."
)
if not buffer:
return
segment_processing = True
try:
stt_result = await anyio.to_thread.run_sync(stt_session.finish)
except SpeechError as exc:
if exc.code in {"stt_empty", "stt_no_match"}:
try:
stt_result = await anyio.to_thread.run_sync(
SpeechToTextService().transcribe,
bytes(buffer),
None,
content_type,
)
except SpeechError as exc_fallback:
if exc_fallback.code in {"stt_empty", "stt_no_match"}:
await websocket.send_json(
{
"event": "result",
"transcript": "",
"reply_text": NO_MATCH_REPLY,
"audio_format": "wav",
"reply_audio_base64": None,
"timings_ms": {"stt": 0, "llm": 0, "tts": 0, "total": 0},
}
)
buffer.clear()
stt_session = SpeechToTextService().start_streaming(
end_silence_ms=1400, initial_silence_ms=5000
)
vad_stream = SileroVADStream()
return
raise
else:
raise
await websocket.send_json(
{"event": "transcript", "transcript": stt_result.transcript}
)
if llm_provider == "local_agent":
agent = AgentPipeline()
result = await agent.run_with_transcript(
transcript=stt_result.transcript,
language=stt_result.language,
prompt=prompt,
return_audio=return_audio,
llm_provider="azure_openai",
session_id=session_id,
)
else:
pipeline = VoicePipeline()
result = await pipeline.run(
audio_bytes=bytes(buffer),
filename=None,
content_type=content_type,
prompt=prompt,
return_audio=return_audio,
transcript_override=stt_result.transcript,
language_override=stt_result.language,
llm_provider=llm_provider,
)
response_body = {
"event": "result",
"transcript": result.transcript,
"reply_text": result.reply_text,
"audio_format": "wav",
"reply_audio_base64": None,
"timings_ms": result.timings_ms,
}
log.info(
"voice_stream_complete",
bytes_received=len(buffer),
timings_ms=result.timings_ms,
return_audio=return_audio,
content_type=content_type,
frames_sent=frames_sent,
avg_rms=avg_rms,
)
await websocket.send_json(response_body)
if result.reply_audio and return_audio:
await websocket.send_bytes(result.reply_audio)
buffer.clear()
stt_session = SpeechToTextService().start_streaming(
end_silence_ms=1200, initial_silence_ms=5000
)
vad_stream = SileroVADStream()
segment_processing = False
try:
while True:
try:
message = await websocket.receive()
except RuntimeError:
log.info("voice_stream_disconnect")
break
if "bytes" in message and message["bytes"] is not None:
chunk = message["bytes"]
if stt_session is not None:
stt_session.write(chunk)
buffer.extend(chunk)
if vad_stream is not None and not segment_processing:
decision = vad_stream.update(chunk)
if decision.speech_ended:
await _finalize_segment()
if len(buffer) > MAX_FILE_SIZE_BYTES:
raise ValidationError(
code="file_too_large", message="Stream exceeds 15MB limit."
)
continue
if "text" in message and message["text"] is not None:
try:
payload = json.loads(message["text"])
except json.JSONDecodeError as exc:
raise ValidationError(
code="invalid_message", message="Invalid JSON message."
) from exc
event = str(payload.get("event", "")).lower()
if event == "start":
content_type = payload.get("content_type") or content_type
prompt = payload.get("prompt")
return_audio = payload.get("return_audio", True)
llm_provider = payload.get("llm_provider", llm_provider)
session_id = payload.get("session_id", session_id) or request_id
if llm_provider and llm_provider not in {
"foundry_agent",
"azure_openai",
"local_agent",
}:
raise ValidationError(
code="llm_provider",
message=(
"LLM provider must be 'foundry_agent', 'azure_openai', or 'local_agent'."
),
)
stt_session = SpeechToTextService().start_streaming(
end_silence_ms=1200, initial_silence_ms=5000
)
vad_stream = SileroVADStream()
continue
if event == "stop":
if not buffer:
raise ValidationError(
code="file_empty", message="Audio stream is empty."
)
if stt_session is None:
raise ValidationError(
code="stt_not_started",
message="STT session not started.",
)
prompt = payload.get("prompt", prompt)
return_audio = payload.get("return_audio", return_audio)
llm_provider = payload.get("llm_provider", llm_provider)
session_id = payload.get("session_id", session_id) or request_id
frames_sent = payload.get("frames_sent", frames_sent)
avg_rms = payload.get("avg_rms", avg_rms)
if llm_provider and llm_provider not in {
"foundry_agent",
"azure_openai",
"local_agent",
}:
raise ValidationError(
code="llm_provider",
message=(
"LLM provider must be 'foundry_agent', 'azure_openai', or 'local_agent'."
),
)
await _finalize_segment()
break
if event == "segment_end":
if not buffer:
continue
prompt = payload.get("prompt", prompt)
return_audio = payload.get("return_audio", return_audio)
llm_provider = payload.get("llm_provider", llm_provider)
session_id = payload.get("session_id", session_id) or request_id
frames_sent = payload.get("frames_sent", frames_sent)
avg_rms = payload.get("avg_rms", avg_rms)
if llm_provider and llm_provider not in {
"foundry_agent",
"azure_openai",
"local_agent",
}:
raise ValidationError(
code="llm_provider",
message=(
"LLM provider must be 'foundry_agent', 'azure_openai', or 'local_agent'."
),
)
if vad_stream is not None and not vad_stream.has_speech():
await websocket.send_json(
{
"event": "result",
"transcript": "",
"reply_text": NO_MATCH_REPLY,
"audio_format": "wav",
"reply_audio_base64": None,
"timings_ms": {"stt": 0, "llm": 0, "tts": 0, "total": 0},
}
)
buffer.clear()
vad_stream.reset()
continue
await _finalize_segment()
continue
raise ValidationError(
code="invalid_event",
message="Event must be 'start', 'stop', or 'segment_end'.",
)
except WebSocketDisconnect:
log.info("voice_stream_disconnect")
except ValidationError as exc:
log.warning(
"voice_stream_error",
code=exc.code,
message=exc.message,
bytes_received=len(buffer),
frames_sent=frames_sent,
avg_rms=avg_rms,
)
if websocket.application_state == WebSocketState.CONNECTED:
await websocket.send_json(
{"event": "error", "error": {"code": exc.code, "message": exc.message}}
)
await websocket.close()
except LLMError as exc:
log.warning(
"voice_stream_error",
code=exc.code,
message=exc.message,
details=exc.details,
bytes_received=len(buffer),
frames_sent=frames_sent,
avg_rms=avg_rms,
)
if websocket.application_state == WebSocketState.CONNECTED:
await websocket.send_json(
{
"event": "error",
"error": {"code": exc.code, "message": exc.message},
}
)
if exc.code != "llm_guardrail":
await websocket.close()
return
except SpeechError as exc:
log.warning(
"voice_stream_error",
code=exc.code,
message=exc.message,
details=exc.details,
bytes_received=len(buffer),
frames_sent=frames_sent,
avg_rms=avg_rms,
)
if websocket.application_state == WebSocketState.CONNECTED:
await websocket.send_json(
{
"event": "error",
"error": {
"code": exc.code,
"message": exc.message,
"details": exc.details,
},
}
)
await websocket.close()
except Exception as exc: # pragma: no cover - safety net
log.error("voice_stream_unhandled", error=repr(exc))
if websocket.application_state == WebSocketState.CONNECTED:
await websocket.send_json(
{
"event": "error",
"error": {"code": "internal_error", "message": "Server error."},
}
)
await websocket.close()
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