Files
ai-video-fullstack/backend/services/config_resolver.py
Xin Wang 90e3e8a0c0 Refactor backend to support interface-definition driven model resources
- Introduce a new model structure for managing interface definitions and model resources, enhancing the backend's capability to handle various service integrations.
- Update the Makefile to reflect changes in database seeding and resource management commands.
- Remove the deprecated credentials management routes and replace them with a unified model registry API.
- Modify existing routes and schemas to align with the new model structure, ensuring seamless integration with the frontend.
- Enhance database seeding scripts to populate new model resources and their configurations.
- Update README documentation to reflect the new architecture and usage instructions for model resources and interface definitions.
2026-06-14 19:36:12 +08:00

94 lines
4.3 KiB
Python

"""assistant_id → 运行时配置(把真 key 在服务端组装好)。
浏览器只传 assistant_id;真 key 在这里从 model_resources 取出注入。
助手按 capability binding 引用资源;取不到则回退该能力默认资源,再回退 .env。
"""
import config
from db.models import Assistant, AssistantModelBinding, ModelResource
from models import AssistantConfig
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
async def _resource_for(
session: AsyncSession,
assistant_id: str,
capability: str,
) -> ModelResource | None:
binding = await session.get(AssistantModelBinding, (assistant_id, capability))
resource_id = binding.model_resource_id if binding else None
resource = await session.get(ModelResource, resource_id) if resource_id else None
if resource and resource.capability != capability:
resource = None
if resource is None:
resource = (
await session.execute(
select(ModelResource)
.where(ModelResource.capability == capability, ModelResource.enabled.is_(True))
.order_by(ModelResource.is_default.desc(), ModelResource.id.asc())
.limit(1)
)
).scalar_one_or_none()
return resource
def _value(resource: ModelResource | None, key: str, default):
if not resource:
return default
value = (resource.values or {}).get(key, default)
return default if value is None else value
def _secret(resource: ModelResource | None, key: str, default: str) -> str:
if not resource:
return default
return str((resource.secrets or {}).get(key) or default)
async def resolve_runtime_config(
session: AsyncSession, assistant_id: str
) -> AssistantConfig:
"""加载助手 + 解析模型资源,产出可直接交给管线的运行时配置(含真 key)。"""
assistant = await session.get(Assistant, assistant_id)
if assistant is None:
raise ValueError(f"助手不存在: {assistant_id}")
llm_resource = await _resource_for(session, assistant.id, "LLM")
stt_resource = await _resource_for(session, assistant.id, "ASR")
tts_resource = await _resource_for(session, assistant.id, "TTS")
realtime_resource = await _resource_for(session, assistant.id, "Realtime")
return AssistantConfig(
name=assistant.name,
greeting=assistant.greeting,
# prompt 现在是真列;外部类型由其平台编排,这里给个兜底
prompt=assistant.prompt or "你是一个有帮助的助手。",
runtimeMode=assistant.runtime_mode, # type: ignore[arg-type]
enableInterrupt=assistant.enable_interrupt,
# 模型/音色:模型资源中的配置优先
model=str(_value(llm_resource, "modelId", "")),
asr=str(_value(stt_resource, "modelId", "")),
tts_model=str(_value(tts_resource, "modelId", "")),
voice=str(_value(tts_resource, "voice", "")),
stt_language=str(_value(stt_resource, "language", "")),
tts_speed=float(_value(tts_resource, "speed", 1.0)),
llm_interface_type=(llm_resource.interface_type if llm_resource else "openai-llm"),
stt_interface_type=(stt_resource.interface_type if stt_resource else "openai-asr"),
tts_interface_type=(tts_resource.interface_type if tts_resource else "openai-tts"),
realtimeModel=str(_value(realtime_resource, "modelId", "")),
llm_values=(llm_resource.values or {}) if llm_resource else {},
llm_secrets=(llm_resource.secrets or {}) if llm_resource else {},
stt_values=(stt_resource.values or {}) if stt_resource else {},
stt_secrets=(stt_resource.secrets or {}) if stt_resource else {},
tts_values=(tts_resource.values or {}) if tts_resource else {},
tts_secrets=(tts_resource.secrets or {}) if tts_resource else {},
# 运行时连接信息(真 key + url):模型资源优先,否则 .env 兜底
llm_api_key=_secret(llm_resource, "apiKey", config.LLM_API_KEY),
llm_base_url=str(_value(llm_resource, "apiUrl", config.LLM_BASE_URL)),
stt_api_key=_secret(stt_resource, "apiKey", config.STT_API_KEY),
stt_base_url=str(_value(stt_resource, "apiUrl", config.STT_BASE_URL)),
tts_api_key=_secret(tts_resource, "apiKey", config.TTS_API_KEY),
tts_base_url=str(_value(tts_resource, "apiUrl", config.TTS_BASE_URL)),
)