Enhance credential management and testing functionality

- Introduce new fields for voice, speed, and language in the AssistantConfig and ProviderCredential models to support TTS and ASR configurations.
- Update the database schema and seeding script to accommodate the new fields, ensuring backward compatibility.
- Implement credential testing endpoints and logic to validate OpenAI-compatible credentials, enhancing user experience and reliability.
- Modify frontend components to include new fields in the credential forms and improve connection testing feedback.
- Refactor related services and API interactions to support the new credential testing feature.
This commit is contained in:
Xin Wang
2026-06-09 14:42:25 +08:00
parent 3661dab81c
commit c64b7dcf99
12 changed files with 443 additions and 28 deletions

View File

@@ -58,7 +58,9 @@ async def resolve_runtime_config(
# 模型/音色:凭证的模型ID优先
model=(llm.model_id if llm else ""),
asr=(stt.model_id if stt else ""),
voice="", # 音色无独立列,留空 → service_factory 回退 .env TTS_VOICE
voice=(tts.voice if tts else ""),
stt_language=(stt.language if stt else ""),
tts_speed=(tts.speed if tts else 1.0),
realtimeModel=(realtime.model_id if realtime else ""),
# 运行时连接信息(真 key + url):凭证优先,否则 .env 兜底
llm_api_key=(llm.api_key if llm else config.LLM_API_KEY),

View File

@@ -0,0 +1,124 @@
"""OpenAI 兼容模型凭证的最小连通测试。"""
from __future__ import annotations
import io
import time
import wave
import httpx
from schemas import CredentialTestRequest, CredentialTestResult
TEST_TIMEOUT_SECONDS = 10.0
def _endpoint(base_url: str, path: str) -> str:
return f"{base_url.rstrip('/')}/{path.lstrip('/')}"
def _silent_wav() -> bytes:
buffer = io.BytesIO()
with wave.open(buffer, "wb") as wav:
wav.setnchannels(1)
wav.setsampwidth(2)
wav.setframerate(16_000)
wav.writeframes(b"\x00\x00" * 1_600)
return buffer.getvalue()
def _error_detail(response: httpx.Response, api_key: str) -> str:
try:
body = response.json()
detail = (
body.get("error", {}).get("message")
if isinstance(body, dict) and isinstance(body.get("error"), dict)
else body.get("detail") if isinstance(body, dict) else None
)
except ValueError:
detail = None
text = str(detail or response.text or response.reason_phrase).strip()
return text.replace(api_key, "***")[:300]
async def test_openai_credential(
config: CredentialTestRequest,
) -> CredentialTestResult:
started = time.perf_counter()
headers = {"Authorization": f"Bearer {config.api_key}"}
try:
async with httpx.AsyncClient(timeout=TEST_TIMEOUT_SECONDS) as client:
if config.type == "LLM":
response = await client.post(
_endpoint(config.api_url, "chat/completions"),
headers=headers,
json={
"model": config.model_id,
"messages": [{"role": "user", "content": "Reply with OK."}],
"max_tokens": 1,
"stream": False,
},
)
elif config.type == "Embedding":
response = await client.post(
_endpoint(config.api_url, "embeddings"),
headers=headers,
json={"model": config.model_id, "input": "ping"},
)
elif config.type == "ASR":
response = await client.post(
_endpoint(config.api_url, "audio/transcriptions"),
headers=headers,
data={
"model": config.model_id,
**({"language": config.language} if config.language else {}),
},
files={"file": ("test.wav", _silent_wav(), "audio/wav")},
)
elif config.type == "TTS":
response = await client.post(
_endpoint(config.api_url, "audio/speech"),
headers=headers,
json={
"model": config.model_id,
"input": "测试",
"voice": config.voice,
"speed": config.speed,
},
)
else:
return CredentialTestResult(
ok=False,
message="暂不支持该资源类型的连通测试",
detail=f"当前仅支持 LLM、Embedding、ASR、TTS收到 {config.type}",
)
latency_ms = round((time.perf_counter() - started) * 1000)
if response.is_success:
return CredentialTestResult(
ok=True,
latency_ms=latency_ms,
message="连接成功",
detail=f"OpenAI 兼容接口响应正常HTTP {response.status_code}",
)
return CredentialTestResult(
ok=False,
latency_ms=latency_ms,
message=f"连接失败HTTP {response.status_code}",
detail=_error_detail(response, config.api_key),
)
except httpx.TimeoutException:
return CredentialTestResult(
ok=False,
latency_ms=round((time.perf_counter() - started) * 1000),
message="连接超时",
detail=f"服务未在 {TEST_TIMEOUT_SECONDS:g} 秒内响应",
)
except httpx.RequestError as exc:
return CredentialTestResult(
ok=False,
latency_ms=round((time.perf_counter() - started) * 1000),
message="无法连接到模型服务",
detail=str(exc)[:300],
)

View File

@@ -11,6 +11,17 @@ from models import AssistantConfig
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.services.openai.stt import OpenAISTTService
from pipecat.services.openai.tts import OpenAITTSService
from pipecat.transcriptions.language import Language
def _language(value: str) -> Language | None:
if not value:
return None
try:
return Language(value)
except ValueError:
logger.warning(f"忽略不支持的 ASR language: {value}")
return None
def create_stt(cfg: AssistantConfig):
@@ -22,6 +33,7 @@ def create_stt(cfg: AssistantConfig):
api_key=cfg.stt_api_key or config.STT_API_KEY,
base_url=cfg.stt_base_url or config.STT_BASE_URL,
model=cfg.asr or config.STT_MODEL,
language=_language(cfg.stt_language),
)
@@ -41,6 +53,7 @@ def create_tts(cfg: AssistantConfig):
base_url=cfg.tts_base_url or config.TTS_BASE_URL,
model=config.TTS_MODEL,
voice=cfg.voice or config.TTS_VOICE,
speed=cfg.tts_speed,
)