feat(multimodal): 实现本地模型管线与请求用量配置
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@@ -16,6 +16,30 @@ class ProviderFactory:
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self.credentials = ProviderCredentialResolver(credentials)
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def build(self, config: ProviderConfig) -> ModelProvider:
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adapter = self._build(config)
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adapter.provider_config = config.model_copy(deep=True)
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from app.services.usage_service import usage_context
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from contextlib import aclosing
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from uuid import uuid4
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complete, stream = adapter.complete, adapter.stream
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async def complete_with_trace(request):
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token = usage_context.set({"request_id": uuid4().hex, "run_id": request.metadata.get("run_id")})
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try:
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return await complete(request)
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finally:
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usage_context.reset(token)
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async def stream_with_trace(request):
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token = usage_context.set({"request_id": uuid4().hex, "run_id": request.metadata.get("run_id")})
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try:
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async with aclosing(stream(request)) as events:
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async for event in events:
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yield event
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finally:
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usage_context.reset(token)
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adapter.complete, adapter.stream = complete_with_trace, stream_with_trace
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return adapter
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def _build(self, config: ProviderConfig) -> ModelProvider:
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if config.provider_type == ProviderType.openai_responses:
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from app.providers.openai_responses import OpenAIResponsesProvider
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return OpenAIResponsesProvider(
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@@ -253,6 +253,18 @@ class HTTPProviderMixin:
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stream_path = "/chat/completions"
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stream_format = "sse"
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def _custom_payload(self, payload):
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from app.request_overrides import apply_overrides
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config = getattr(self, "provider_config", None)
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return apply_overrides(payload, config.request_overrides, "chat", stream=bool(payload.get("stream"))) if config else payload
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def _usage_attempt(self, payload):
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from app.services.usage_service import UsageAttempt
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config = getattr(self, "provider_config", None)
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protocol = config.provider_type.value if config else "openai_compatible"
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return UsageAttempt(config.provider_id if config else "unregistered", str(payload.get("model", "")), protocol,
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source="local" if protocol == "ollama" else "api")
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def _headers(self) -> dict[str, str]:
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return {"Content-Type": "application/json"}
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@@ -268,11 +280,18 @@ class HTTPProviderMixin:
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async def _request(self, method: str, path: str, **kwargs) -> dict:
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headers = self._headers()
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attempt = None
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if isinstance(kwargs.get("json"), dict) and path == self.stream_path:
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kwargs["json"] = self._custom_payload(kwargs["json"])
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attempt = self._usage_attempt(kwargs["json"])
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try:
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async with httpx.AsyncClient(timeout=self.timeout_seconds, transport=self.transport) as client:
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response = await client.request(method, f"{self.base_url}{path}", headers=headers, **kwargs)
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response.raise_for_status()
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data = object_value(response.json())
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if attempt:
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attempt.observe(data)
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attempt.completed = True
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check_error(data)
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return data
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except httpx.TimeoutException as exc:
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@@ -283,8 +302,13 @@ class HTTPProviderMixin:
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raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
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except (ValueError, TypeError) as exc:
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raise invalid_response() from exc
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finally:
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if attempt:
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attempt.persist()
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async def _stream_json(self, payload: dict[str, object]) -> AsyncIterator[dict]:
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payload = self._custom_payload(payload)
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attempt = self._usage_attempt(payload)
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headers = self._headers()
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headers["Accept"] = "text/event-stream" if self.stream_format == "sse" else "application/x-ndjson"
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try:
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@@ -295,12 +319,14 @@ class HTTPProviderMixin:
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if self.stream_format == "sse":
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async with aclosing(sse_objects(response)) as objects:
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async for data in objects:
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attempt.observe(data)
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yield data
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else:
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async for line in response.aiter_lines():
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if line.strip():
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data = object_value(json.loads(line))
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check_error(data)
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attempt.observe(data)
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yield data
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except httpx.TimeoutException as exc:
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raise ProviderError("PROVIDER_TIMEOUT", "Provider request timed out.") from exc
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@@ -310,3 +336,5 @@ class HTTPProviderMixin:
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raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
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except (ValueError, TypeError) as exc:
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raise invalid_response() from exc
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finally:
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attempt.persist()
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@@ -1,14 +1,14 @@
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"""Capability routing: validated remote results, then an explicit local backend.
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Phase E supplies HTTP adapters and injectable local contracts. Hash embeddings are
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still a development placeholder; speech models are installed in phase F.
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Production injects installed CPU/CUDA backends. Deterministic embeddings remain
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available only for explicitly injected tests and protocol fixtures.
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"""
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from __future__ import annotations
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import hashlib
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import json
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import math
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from dataclasses import dataclass
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from dataclasses import dataclass, field, replace
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from pathlib import Path
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from typing import Protocol
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@@ -55,6 +55,7 @@ class RoutedTranscript:
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text: str
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source: str
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fallback_reason: str | None = None
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segments: list = field(default_factory=list)
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def invalid_response() -> ProviderError:
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@@ -87,6 +88,19 @@ class ModelRoutingService:
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conn.execute("CREATE TABLE IF NOT EXISTS model_routing (id INTEGER PRIMARY KEY CHECK(id=1), config_json TEXT NOT NULL)")
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return conn
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def snapshot(self):
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from copy import copy
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from app.providers.registry import RegisteredProvider
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frozen = copy(self)
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config = self.configuration().model_copy(deep=True)
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providers = ProviderRegistry()
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for item in self.providers.list_configs():
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original = self.providers.get_any(item.provider_id)
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providers._providers[item.provider_id] = RegisteredProvider(item, original.adapter)
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frozen.providers = providers
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frozen.configuration = lambda: config
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return frozen
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def configuration(self) -> ModelRoutingConfig:
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conn = self._connection()
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try:
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@@ -98,11 +112,16 @@ class ModelRoutingService:
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conn.close()
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def describe(self) -> ModelRoutingResponse:
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is_hash = isinstance(self.local_embedding, HashEmbeddingProvider)
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embedding_available = getattr(self.local_embedding, "available", True)
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def speech_available(capability):
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check = getattr(self.local_speech, "available_for", None)
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return check(capability) if check else self.local_speech.available
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return ModelRoutingResponse(config=self.configuration(), local_backends=[
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LocalBackendStatus(capability="embedding", status="placeholder" if isinstance(self.local_embedding, HashEmbeddingProvider) else "ready",
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message="当前为 hash-v1 确定性占位向量,真实本地语义模型尚未集成。" if isinstance(self.local_embedding, HashEmbeddingProvider) else "本地 Embedding 模型已就绪。"),
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*[LocalBackendStatus(capability=capability, status="ready" if self.local_speech.available else "not_installed",
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message="本地模型已就绪。" if self.local_speech.available else "阶段 F 接入本地模型;当前保留回退接口。")
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LocalBackendStatus(capability="embedding", status="placeholder" if is_hash else ("ready" if embedding_available else "not_installed"),
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message="测试占位向量。" if is_hash else ("本地 Embedding 文件和运行环境已安装。" if embedding_available else "请安装本地模型运行环境并下载 Embedding 权重。")),
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*[LocalBackendStatus(capability=capability, status="ready" if speech_available(capability) else "not_installed",
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message="本地模型文件和运行环境已安装。" if speech_available(capability) else "请安装运行环境并下载对应本地模型。")
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for capability in ("transcription", "speaker_matching")],
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])
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@@ -150,8 +169,16 @@ class ModelRoutingService:
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url = (provider.base_url or "https://api.openai.com/v1").rstrip("/") + binding.endpoint
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return url, {"Authorization": f"Bearer {key}"} if key else {}
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async def _request(self, binding: ModelBinding, *, remote: tuple[str, dict[str, str]] | None = None, **kwargs) -> tuple[dict, str]:
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async def _request(self, binding: ModelBinding, *, remote: tuple[str, dict[str, str]] | None = None, provider_config=None, **kwargs) -> tuple[dict, str]:
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url, headers = remote or self._remote(binding)
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from app.request_overrides import apply_overrides
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from app.services.usage_service import UsageAttempt
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capability = "embedding" if "json" in kwargs else ("speaker_matching" if "reference_file" in kwargs.get("files", {}) else "transcription")
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provider = provider_config or self.providers.get(binding.provider_id).config
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field = "json" if capability == "embedding" else "data"
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payload = apply_overrides(kwargs.get(field, {}), provider.request_overrides, capability)
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kwargs[field] = payload if field == "json" else {key: json.dumps(value) if isinstance(value, (dict, list, bool)) or value is None else value for key, value in payload.items()}
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attempt = UsageAttempt(binding.provider_id, binding.model, provider.provider_type.value, capability)
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try:
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async with httpx.AsyncClient(timeout=30, transport=self.transport) as client:
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async with client.stream("POST", url, headers=headers, **kwargs) as response:
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@@ -162,6 +189,8 @@ class ModelRoutingService:
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if len(body) > MAX_RESPONSE_BYTES:
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raise invalid_response()
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data = json.loads(body)
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attempt.observe(data)
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attempt.completed = True
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except httpx.TimeoutException as exc:
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raise ProviderError("PROVIDER_TIMEOUT", "Model API timed out.") from exc
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except httpx.HTTPStatusError as exc:
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@@ -171,6 +200,8 @@ class ModelRoutingService:
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raise ProviderError("PROVIDER_UNAVAILABLE", "Model API is unavailable.") from exc
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except (ValueError, UnicodeError) as exc:
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raise invalid_response() from exc
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finally:
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attempt.persist()
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if not isinstance(data, dict) or data.get("error"):
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raise invalid_response()
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return data, url
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@@ -187,12 +218,13 @@ class ModelRoutingService:
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dimension = binding.dimensions
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# Freeze the origin across batches, even if the user edits the provider.
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remote = self._remote(binding)
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provider_config = self.providers.get(binding.provider_id).config.model_copy(deep=True)
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for start in range(0, len(texts), 32):
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batch = texts[start:start + 32]
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payload = {"model": binding.model, "input": batch, "encoding_format": "float"}
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if binding.dimensions is not None:
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payload["dimensions"] = binding.dimensions
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data, url = await self._request(binding, remote=remote, json=payload)
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data, url = await self._request(binding, remote=remote, provider_config=provider_config, json=payload)
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items = data.get("data")
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if not isinstance(items, list) or len(items) != len(batch):
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raise invalid_response()
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@@ -213,12 +245,20 @@ class ModelRoutingService:
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raise invalid_response()
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indexed[index] = [value / norm for value in vector]
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vectors.extend(indexed[index] for index in range(len(batch)))
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identity = json.dumps([url, binding.model, dimension], separators=(",", ":"))
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identity_parts = [url, binding.model, dimension]
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extensions = [rule.model_dump() for rule in provider_config.request_overrides
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if rule.capability == "embedding" and rule.model in (None, binding.model)]
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if extensions:
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identity_parts.append(extensions)
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identity = json.dumps(identity_parts, separators=(",", ":"))
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return EmbeddingResult(vectors=vectors, source="api", dimensions=dimension,
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model_id="api-" + hashlib.sha256(identity.encode()).hexdigest())
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except ProviderError as exc:
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reason = exc.code
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vectors = await self.local_embedding.embed_documents(texts)
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try:
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vectors = await self.local_embedding.embed_documents(texts)
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except ProviderError as exc:
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raise ApiError(503, exc.code, exc.message, {"fallback_reason": reason}) from exc
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return EmbeddingResult(vectors=vectors, source="local", model_id=self.local_embedding.model_id,
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dimensions=self.local_embedding.dim, fallback_reason=reason)
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@@ -234,8 +274,8 @@ class ModelRoutingService:
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raise ApiError(413, "ATTACHMENT_TOO_LARGE", "Audio attachment must be between 1 byte and 25 MiB.")
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return handle
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async def transcribe(self, source: Path, language: str | None) -> RoutedTranscript:
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binding = self.configuration().transcription
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async def transcribe(self, source: Path, language: str | None, *, local_only: bool = False) -> RoutedTranscript:
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binding = None if local_only else self.configuration().transcription
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if binding is None:
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with self._media_file(source):
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pass
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@@ -251,19 +291,41 @@ class ModelRoutingService:
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text = data.get("text")
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if not isinstance(text, str) or not text.strip():
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raise invalid_response()
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return RoutedTranscript(text=text, source="api")
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segments = []
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raw_segments = data.get("segments", [])
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if not isinstance(raw_segments, list) or len(raw_segments) > 10000:
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raise invalid_response()
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from app.contracts import TranscriptSegment
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for index, raw in enumerate(raw_segments):
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if not isinstance(raw, dict):
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raise invalid_response()
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start, end = raw.get("start", raw.get("start_time")), raw.get("end", raw.get("end_time"))
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if not finite_number(start) or not finite_number(end) or not isinstance(raw.get("text"), str):
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raise invalid_response()
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try:
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segments.append(TranscriptSegment(segment_id=f"segment_{index + 1}", start_time=start,
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end_time=end, text=raw["text"], speaker=raw.get("speaker")))
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except ValueError as exc:
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raise invalid_response() from exc
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if segments != sorted(segments, key=lambda segment: segment.start_time):
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raise invalid_response()
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return RoutedTranscript(text=text, source="api", segments=segments)
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except ProviderError as exc:
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reason = exc.code
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try:
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text = await self.local_speech.transcribe(source, language)
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if isinstance(text, RoutedTranscript):
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if not text.text.strip():
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raise ProviderError("LOCAL_MODEL_INVALID_RESPONSE", "Local transcription was empty.")
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return replace(text, source="local", fallback_reason=reason)
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if not isinstance(text, str) or not text.strip():
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raise ProviderError("LOCAL_MODEL_INVALID_RESPONSE", "Local transcription was empty.")
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return RoutedTranscript(text=text, source="local", fallback_reason=reason)
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except ProviderError as exc:
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raise ApiError(503, exc.code, exc.message, {"fallback_reason": reason}) from exc
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async def match_speakers(self, source: Path, reference: Path) -> SpeakerMatchResult:
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binding = self.configuration().speaker_matching
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async def match_speakers(self, source: Path, reference: Path, *, local_only: bool = False) -> SpeakerMatchResult:
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binding = None if local_only else self.configuration().speaker_matching
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if binding is None:
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with self._media_file(source), self._media_file(reference):
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pass
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