feat(stt): support multi-model STT with parallel execution and consensus NLU extraction

This commit is contained in:
2026-09-29 02:10:03 +03:30
parent da68fc683f
commit 0a7db5ebe9
4 changed files with 171 additions and 31 deletions
+67 -3
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@@ -37,9 +37,30 @@ class Settings(BaseSettings):
LLM_MODEL: str = "gpt-4o-mini"
LLM_TIMEOUT_SECONDS: float = 60.0
# STT provider — any OpenAI-compatible /audio/transcriptions endpoint.
# Falls back to the LLM provider when unset. Note: some providers
# (e.g. DeepSeek) have no audio API — voice stays disabled gracefully.
# STT providers — support multiple models/APIs in parallel.
# 1. JSON list: [{"name": "m1", "base_url": "...", "api_key": "...", "model": "..."}, ...]
STT_PROVIDERS_JSON: str = ""
# 2. Individual provider variables (up to 3 distinct STT models)
STT_PROVIDER_1_NAME: str = "model-1"
STT_PROVIDER_1_BASE_URL: str = ""
STT_PROVIDER_1_API_KEY: str = ""
STT_PROVIDER_1_MODEL: str = ""
STT_PROVIDER_1_LANGUAGE: str = "fa"
STT_PROVIDER_2_NAME: str = "model-2"
STT_PROVIDER_2_BASE_URL: str = ""
STT_PROVIDER_2_API_KEY: str = ""
STT_PROVIDER_2_MODEL: str = ""
STT_PROVIDER_2_LANGUAGE: str = "fa"
STT_PROVIDER_3_NAME: str = "model-3"
STT_PROVIDER_3_BASE_URL: str = ""
STT_PROVIDER_3_API_KEY: str = ""
STT_PROVIDER_3_MODEL: str = ""
STT_PROVIDER_3_LANGUAGE: str = "fa"
# Legacy single STT provider fallback:
STT_BASE_URL: str = ""
STT_API_KEY: str = ""
STT_MODEL: str = "whisper-1"
@@ -53,6 +74,49 @@ class Settings(BaseSettings):
def stt_api_key(self) -> str:
return self.STT_API_KEY or self.AI_API_KEY
@property
def stt_providers(self) -> list[dict]:
import json
if self.STT_PROVIDERS_JSON:
try:
data = json.loads(self.STT_PROVIDERS_JSON)
if isinstance(data, list) and len(data) > 0:
return data
except Exception:
pass
# Check explicit STT_PROVIDER_1 / 2 / 3
custom_list: list[dict] = []
for idx in (1, 2, 3):
b_url = getattr(self, f"STT_PROVIDER_{idx}_BASE_URL")
key = getattr(self, f"STT_PROVIDER_{idx}_API_KEY")
model = getattr(self, f"STT_PROVIDER_{idx}_MODEL")
name = getattr(self, f"STT_PROVIDER_{idx}_NAME")
lang = getattr(self, f"STT_PROVIDER_{idx}_LANGUAGE") or "fa"
if b_url and key:
custom_list.append({
"name": name or f"model-{idx}",
"base_url": b_url,
"api_key": key,
"model": model or self.STT_MODEL,
"language": lang,
"timeout": 30.0,
})
if custom_list:
return custom_list
# Fallback to single legacy STT provider if set
if self.stt_base_url and self.stt_api_key:
return [{
"name": "default",
"base_url": self.stt_base_url,
"api_key": self.stt_api_key,
"model": self.STT_MODEL,
"language": self.STT_LANGUAGE,
"timeout": 30.0,
}]
return []
# PostgreSQL — same instance/database as the api service.
DATABASE_URL: str = "postgresql+asyncpg://postgres:postgres@localhost:5432/procurement"
+20 -9
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@@ -14,8 +14,8 @@ from app import drafts as draft_store
from app.config import settings
from app.nlu import understand
from app.runtime import BotContext, LinkedUser
from app.stt import transcribe
from app.texts import CANCELLED, LINK_START, NOTHING_TO_COMMIT, STT_FAILED, UNKNOWN_HINT, VOICE_EMPTY
from app.stt import transcribe, transcribe_multi
from app.texts import CANCELLED, LINK_START, NOTHING_TO_COMMIT, STT_FAILED, UNKNOWN_HINT, VOICE_EMPTY, esc
from . import commands, callbacks, quote, supplier, material, queries, decisions
@@ -40,6 +40,7 @@ async def handle_update(ctx: BotContext, update: dict) -> None:
async def handle_message(ctx: BotContext, chat_id: int, message: dict) -> None:
text = (message.get("text") or "").strip()
source = "text"
voice_transcripts: list[dict] | None = None
if text.startswith("/"):
await commands.handle_command(ctx, chat_id, text)
@@ -51,17 +52,20 @@ async def handle_message(ctx: BotContext, chat_id: int, message: dict) -> None:
file_id = (message.get("voice") or message.get("audio") or message.get("document"))["file_id"]
try:
audio = await ctx.bale.download_file(file_id)
text = await transcribe(settings, audio,
mime_type=(message.get("voice") or {}).get("mime_type"),
filename=(message.get("voice") or {}).get("file_name"))
voice_transcripts = await transcribe_multi(
settings,
audio,
mime_type=(message.get("voice") or {}).get("mime_type"),
filename=(message.get("voice") or {}).get("file_name"),
)
except Exception as exc:
detail = "هوش مصنوعی تنظیم نشده" if "not configured" in str(exc) else str(exc)[:200]
await ctx.send(chat_id, STT_FAILED.format(detail=esc(detail)))
return
if not text:
if not voice_transcripts:
await ctx.send(chat_id, VOICE_EMPTY)
return
await ctx._log(chat_id, "in", "voice", text)
text = voice_transcripts[0]["text"]
# Pending multi-step interactions take the message first.
flow = ctx.pending.get(chat_id)
@@ -91,9 +95,16 @@ async def handle_message(ctx: BotContext, chat_id: int, message: dict) -> None:
return
draft_summary = _draft_summary(target_draft) if target_draft else None
result = await understand(settings, text, draft_summary)
input_payload = voice_transcripts if voice_transcripts else text
result = await understand(settings, input_payload, draft_summary)
intent, patch = result.get("intent"), result.get("patch") or {}
logger.info("chat %s intent=%s conf=%s (is_edit=%s)", chat_id, intent, result.get("confidence"), target_draft is not None)
consensus_text = result.get("consensus_text") or text
if source == "voice":
await ctx._log(chat_id, "in", "voice", consensus_text)
logger.info("chat %s intent=%s conf=%s consensus=%r (is_edit=%s)",
chat_id, intent, result.get("confidence"), consensus_text[:40], target_draft is not None)
if intent in ("register_quote", "update_draft"):
await quote.handle_entities(
+29 -4
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@@ -51,12 +51,19 @@ SYSTEM_PROMPT = """تو دستیار تدارکات یک ERP فارسی هستی
یک JSON و فقط JSON برگردان (بدون توضیح اضافه) با این شکل:
{
"consensus_text": "متن تجمیع‌شده و اصلاح‌شده کاربر (فارسی روان و بدون غلط شنیداری)",
"intent": یکی از {intents},
"patch": {شکل partial هر فعالیتی که کاربر داده},
"confidence": 0.0..1.0
}
قوانین:
- اگر ورودی شامل چند نسخه تبدیل گفتار به متن (STT) از یک پیام صوتی کاربر است:
۱. این نسخه‌ها از چند مدل مختلف برای افزایش دقت به دست آمده‌اند. آن‌ها را با هم مقایسه و مقابله کن.
۲. خطاهای شنیداری هر نسخه را بر مبنای منطق تدارکات (نام کالاها، برندها، مشخصات فنی و واحدهای اندازه‌گیری) تصحیح و حل تعارض کن.
۳. متن نهایی اصلاح و تجمیع‌شده را در فیلد consensus_text قرار بده.
۴. استخراج قصد (intent) و موجودیت‌ها (patch) را بر اساس همین متن دقیق انجام بده.
- اگر ورودی یک متن عادی است، همان متن را در consensus_text قرار بده.
- اگر پیام کاربر اطلاعات جدیدی به پیش‌نویسِ باز اضافه می‌کند یا اصلاح می‌کند → intent="update_draft" و patch شامل فقط فیلدهای جدید/تغییریافته.
- اگر عبارت تأیید نهایی است (مثل «ثبت کن»، «همینه، ثبتش کن») → intent="commit_draft".
- اگر لغو است («بی‌خیال»، «لغو») → intent="discard_draft".
@@ -113,12 +120,28 @@ def _extract_json(raw: str) -> dict | None:
return None
async def understand(settings: Settings, text: str, draft_summary: str | None = None) -> dict:
"""Return {"intent": ..., "patch": {...}, "confidence": ...}; never raises."""
fallback = {"intent": "unknown", "patch": {}, "confidence": 0.0}
async def understand(settings: Settings, text: str | list[dict], draft_summary: str | None = None) -> dict:
"""Return {"consensus_text": ..., "intent": ..., "patch": {...}, "confidence": ...}; never raises."""
fallback = {"consensus_text": "", "intent": "unknown", "patch": {}, "confidence": 0.0}
if not settings.AI_BASE_URL or not settings.AI_API_KEY:
logger.warning("AI provider not configured; cannot understand message")
return fallback
if isinstance(text, list):
first_text = text[0].get("text") if text else ""
lines = ["پیام صوتی کاربر توسط چند مدل تبدیل گفتار به متن (STT) به صورت زیر پیاده‌سازی شده است:"]
for idx, item in enumerate(text, start=1):
name = item.get("name") or f"مدل {idx}"
t = normalize_digits(item.get("text") or "")
lines.append(f"- نسخه {idx} ({name}): «{t}»")
lines.append("\nبا تلفیق این نسخه‌ها و تصحیح خطاهای شنیداری، پیام را تحلیل کن و consensus_text را به همراه intent و patch بساز.")
user_content = "\n".join(lines)
else:
user_content = normalize_digits(str(text))
first_text = str(text)
fallback["consensus_text"] = first_text
try:
async with httpx.AsyncClient(timeout=settings.LLM_TIMEOUT_SECONDS) as client:
resp = await client.post(
@@ -128,7 +151,7 @@ async def understand(settings: Settings, text: str, draft_summary: str | None =
"model": settings.LLM_MODEL,
"messages": [
{"role": "system", "content": _build_system_prompt(draft_summary)},
{"role": "user", "content": normalize_digits(text)},
{"role": "user", "content": user_content},
],
"temperature": 0.1,
"response_format": {"type": "json_object"},
@@ -143,6 +166,8 @@ async def understand(settings: Settings, text: str, draft_summary: str | None =
logger.warning("unparseable LLM output: %r", content[:200])
return fallback
parsed.setdefault("patch", {})
if not parsed.get("consensus_text"):
parsed["consensus_text"] = first_text
return parsed
except (httpx.HTTPError, json.JSONDecodeError, KeyError, TypeError):
logger.exception("NLU failure")
+55 -15
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@@ -37,11 +37,45 @@ def _to_mp3(raw: bytes, suffix: str) -> bytes:
return dst.read_bytes()
async def transcribe(settings: Settings, audio: bytes, mime_type: str | None = None,
filename: str | None = None) -> str:
"""Return the Persian transcript for a voice note (empty string on silence)."""
if not settings.stt_base_url or not settings.stt_api_key:
raise RuntimeError("STT provider is not configured (PROCUREMENT_BOT_STT_BASE_URL / _AI_BASE_URL)")
async def _call_single_stt(client: httpx.AsyncClient, provider: dict, converted_mp3: bytes) -> dict | None:
name = provider.get("name") or "stt"
base_url = (provider.get("base_url") or "").rstrip("/")
api_key = provider.get("api_key") or ""
model = provider.get("model") or "whisper-1"
language = provider.get("language") or "fa"
timeout = float(provider.get("timeout") or _STT_TIMEOUT)
url = f"{base_url}/audio/transcriptions"
try:
resp = await client.post(
url,
headers={"Authorization": f"Bearer {api_key}"},
files={"file": ("voice.mp3", converted_mp3, "audio/mpeg")},
data={"model": model, "language": language},
timeout=timeout,
)
if resp.status_code == 200:
txt = str((resp.json() or {}).get("text") or "").strip()
if txt:
logger.info("STT provider %s succeeded: %r", name, txt[:60])
return {"name": name, "text": txt, "model": model}
else:
logger.warning("STT provider %s returned HTTP %s: %s", name, resp.status_code, resp.text[:200])
except Exception as exc:
logger.warning("STT provider %s failed: %s", name, exc)
return None
async def transcribe_multi(settings: Settings, audio: bytes, mime_type: str | None = None,
filename: str | None = None) -> list[dict]:
"""Transcribe audio with all configured STT providers in parallel.
Returns a list of candidate dicts: [{"name": str, "text": str, "model": str}, ...]
Empty list if all failed or silence.
"""
providers = settings.stt_providers
if not providers:
raise RuntimeError("No STT providers are configured (PROCUREMENT_BOT_STT_*)")
suffix = Path(filename or "").suffix
if not suffix and mime_type:
@@ -49,14 +83,20 @@ async def transcribe(settings: Settings, audio: bytes, mime_type: str | None = N
"audio/mp4": ".m4a", "audio/wav": ".wav"}.get(mime_type.split(";")[0].strip(), ".ogg")
converted = await asyncio.to_thread(_to_mp3, audio, suffix)
url = f"{settings.stt_base_url.rstrip('/')}/audio/transcriptions"
async with httpx.AsyncClient(timeout=_STT_TIMEOUT) as client:
resp = await client.post(
url,
headers={"Authorization": f"Bearer {settings.stt_api_key}"},
files={"file": ("voice.mp3", converted, "audio/mpeg")},
data={"model": settings.STT_MODEL, "language": settings.STT_LANGUAGE},
)
if resp.status_code != 200:
raise RuntimeError(f"STT provider returned HTTP {resp.status_code}: {resp.text[:300]}")
return str((resp.json() or {}).get("text") or "").strip()
tasks = [_call_single_stt(client, p, converted) for p in providers]
results = await asyncio.gather(*tasks, return_exceptions=True)
valid_transcripts: list[dict] = []
for r in results:
if isinstance(r, dict) and r.get("text"):
valid_transcripts.append(r)
return valid_transcripts
async def transcribe(settings: Settings, audio: bytes, mime_type: str | None = None,
filename: str | None = None) -> str:
"""Return the Persian transcript for a voice note (empty string on silence)."""
transcripts = await transcribe_multi(settings, audio, mime_type=mime_type, filename=filename)
return transcripts[0]["text"] if transcripts else ""