backend/app/agent/builtin_tools.py

@@ -160,10 +160,11 @@ def read_attachment(arguments: AttachmentReadArguments, _: ToolExecutionContext)
     return attachment_service.read_attachment(**arguments.model_dump())
 
 
-def transcribe_audio(arguments: AudioTranscribeArguments, _: ToolExecutionContext) -> dict:
-    return transcription_service.create_transcription(
+async def transcribe_audio(arguments: AudioTranscribeArguments, _: ToolExecutionContext) -> dict:
+    job = await transcription_service.create_transcription(
         arguments.attachment_id, arguments.language
-    ).model_dump(mode="json")
+    )
+    return job.model_dump(mode="json")
 
 
 def _register(

backend/app/benchmarks/rag.py

@@ -24,6 +24,7 @@ from app.contracts import (
     SearchRequest,
 )
 from app.retrieval.engine import engine
+from app.retrieval.provenance import capture_embedding
 
 logger = logging.getLogger(__name__)
 
@@ -90,8 +91,10 @@ async def _evaluate_one(
         score_threshold=request.retrieval.score_threshold,
     )
     start = time.perf_counter()
+    embedding = {}
     try:
-        response = await engine.search(search_request)
+        with capture_embedding() as embedding:
+            response = await engine.search(search_request)
         latency_ms = (time.perf_counter() - start) * 1000.0
     except Exception as exc:  # 单个样本失败不中断整个 Benchmark
         # 详细异常只进日志，公开响应只带项目错误码与安全消息，避免泄露路径/SQL 等敏感信息
@@ -100,6 +103,7 @@ async def _evaluate_one(
             exc_info=exc,
         )
         return RAGCaseResult(
+            embedding=embedding,
             case_id=case.case_id,
             mode=mode,
             repeat=repeat,
@@ -115,6 +119,7 @@ async def _evaluate_one(
     k = request.retrieval.top_k
 
     return RAGCaseResult(
+        embedding=embedding,
         case_id=case.case_id,
         mode=mode,
         repeat=repeat,

backend/app/benchmarks/service.py

@@ -86,7 +86,8 @@ def _config_snapshot(request: RAGRunRequest, dataset: RAGDataset) -> dict:
         "modes": [m.value for m in request.modes],
         "retrieval": request.retrieval.model_dump(),
         "repeat": request.repeat,
-        "embedding": {
+        "embedding": {"policy": "per_case", "details": "cases[].embedding"},
+        "local_embedding": {
             "model_id": engine.embedding.model_id,
             "version": engine.embedding.version,
             "dim": engine.embedding.dim,

backend/app/container.py

@@ -7,6 +7,7 @@ from app.config import BACKEND_DIR, get_settings
 from app.extensions import PluginRuntime, SkillRuntime
 from app.extensions.mcp_registry import McpServerRegistry
 from app.providers import MockProvider, ProviderFactory, ProviderRegistry
+from app.providers.routing import ModelRoutingService
 from app.providers.credentials import (
     ChainedCredentialResolver,
     EncryptedCredentialStore,
@@ -18,6 +19,7 @@ from app.providers.credentials import (
 class ApplicationContainer:
     providers: ProviderRegistry
     provider_factory: ProviderFactory
+    model_routing: ModelRoutingService
     credentials: EncryptedCredentialStore
     tools: ToolRegistry
     permissions: PermissionManager
@@ -33,7 +35,7 @@ def build_container() -> ApplicationContainer:
     provider_factory = ProviderFactory(
         ChainedCredentialResolver(credentials, EnvironmentCredentialResolver())
     )
-    providers = ProviderRegistry()
+    providers = ProviderRegistry(provider_factory)
     providers.register(
         ProviderConfig(
             provider_id="mock",
@@ -86,6 +88,7 @@ def build_container() -> ApplicationContainer:
     return ApplicationContainer(
         providers=providers,
         provider_factory=provider_factory,
+        model_routing=ModelRoutingService(providers, provider_factory.credentials),
         credentials=credentials,
         tools=tools,
         permissions=permissions,

backend/app/contracts.py

@@ -236,6 +236,8 @@ class ModelCapability(str, Enum):
     streaming = "streaming"
     structured_output = "structured_output"
     embedding = "embedding"
+    transcription = "transcription"
+    speaker_matching = "speaker_matching"
 
 
 class ModelRequest(Contract):
@@ -763,7 +765,24 @@ class ProviderType(str, Enum):
     ollama = "ollama"
 
 
-class ProviderConfig(Contract):
+class ProviderConnectionFields(Contract):
+    base_url: str | None = None
+    credential_id: str | None = None
+
+    @field_validator("base_url")
+    @classmethod
+    def provider_url(cls, value: str | None) -> str | None:
+        if value is None:
+            return value
+        from urllib.parse import urlsplit
+        parsed = urlsplit(value)
+        if (parsed.scheme not in {"http", "https"} or not parsed.hostname or
+                parsed.username or parsed.password or parsed.query or parsed.fragment):
+            raise ValueError("Base URL requires HTTP(S), without credentials, query or fragment")
+        return value.rstrip("/")
+
+
+class ProviderConfig(ProviderConnectionFields):
     provider_id: str
     provider_type: ProviderType
     name: str
@@ -774,7 +793,7 @@ class ProviderConfig(Contract):
     capabilities: list[ModelCapability] = Field(default_factory=list)
 
 
-class ProviderCreateRequest(Contract):
+class ProviderCreateRequest(ProviderConnectionFields):
     provider_type: ProviderType
     name: str
     base_url: str | None = None
@@ -783,7 +802,8 @@ class ProviderCreateRequest(Contract):
     enabled: bool = True
 
 
-class ProviderUpdateRequest(Contract):
+class ProviderUpdateRequest(ProviderConnectionFields):
+    provider_type: ProviderType | None = None
     name: str | None = None
     base_url: str | None = None
     default_model: str | None = None
@@ -802,6 +822,80 @@ class ProviderPreset(Contract):
     base_url: str
     default_credential_id: str | None = None
     requires_credential: bool = True
+    logo_id: str = "custom"
+    description: str = ""
+    capabilities: list[ModelCapability] = Field(default_factory=list)
+
+
+class ModelBinding(Contract):
+    provider_id: str = Field(min_length=1, max_length=128)
+    model: str = Field(min_length=1, max_length=256)
+    endpoint: str = Field(min_length=1, max_length=256)
+    dimensions: int | None = Field(default=None, ge=1, le=16384)
+
+    @field_validator("endpoint")
+    @classmethod
+    def relative_endpoint(cls, value: str) -> str:
+        # An endpoint is a path on the selected provider, never a second origin.
+        import re
+        if not re.fullmatch(r"/[A-Za-z0-9_/-]+", value) or value.startswith("//"):
+            raise ValueError("endpoint must be an absolute API path on the provider")
+        return value
+
+    @field_validator("model", "provider_id")
+    @classmethod
+    def non_blank(cls, value: str) -> str:
+        if not value.strip():
+            raise ValueError("value must not be blank")
+        return value.strip()
+
+
+class ModelRoutingConfig(Contract):
+    version: int = Field(default=0, ge=0)
+    embedding: ModelBinding | None = None
+    transcription: ModelBinding | None = None
+    speaker_matching: ModelBinding | None = None
+
+
+class LocalBackendStatus(Contract):
+    capability: Literal["embedding", "transcription", "speaker_matching"]
+    status: Literal["placeholder", "not_installed", "ready"]
+    message: str
+
+
+class ModelRoutingResponse(Contract):
+    config: ModelRoutingConfig
+    local_backends: list[LocalBackendStatus]
+
+
+class EmbeddingRequest(Contract):
+    texts: list[str] = Field(min_length=1, max_length=256)
+
+    @field_validator("texts")
+    @classmethod
+    def bound_texts(cls, value: list[str]) -> list[str]:
+        if sum(len(text) for text in value) > 200_000:
+            raise ValueError("embedding input is too large")
+        return value
+
+
+class EmbeddingResult(Contract):
+    vectors: list[list[float]]
+    source: Literal["api", "local"]
+    model_id: str
+    dimensions: int
+    fallback_reason: str | None = None
+
+
+class SpeakerMatchRequest(Contract):
+    attachment_id: str
+    reference_attachment_id: str
+
+
+class SpeakerMatchResult(Contract):
+    score: float = Field(ge=0, le=1, allow_inf_nan=False)
+    source: Literal["api", "local"]
+    fallback_reason: str | None = None
 
 
 class ProviderPresetListResponse(Contract):
@@ -894,6 +988,8 @@ class TranscriptionJob(Contract):
     error_code: str | None = None
     error_message: str | None = None
     created_at: datetime
+    source: Literal["api", "local", "sidecar"] | None = None
+    fallback_reason: str | None = None
 
 
 class IndexStatus(Contract):
@@ -1035,6 +1131,7 @@ class BenchmarkEvent(Contract):
 
 
 class RAGCaseResult(Contract):
+    embedding: dict[str, Any] = Field(default_factory=dict)
     case_id: str
     mode: SearchMode
     repeat: int

backend/app/errors.py

@@ -36,7 +36,11 @@ async def validation_error_handler(_: Request, exc: RequestValidationError) -> J
         error=ErrorDetail(
             code="VALIDATION_ERROR",
             message="Request validation failed.",
-            details={"errors": exc.errors()},
+            # Pydantic ctx can contain exception objects; input may contain API keys.
+            details={"errors": [
+                {key: error[key] for key in ("type", "loc", "msg") if key in error}
+                for error in exc.errors()
+            ]},
         )
     )
     return JSONResponse(status_code=422, content=jsonable_encoder(body))

backend/app/providers/anthropic_messages.py

@@ -0,0 +1,163 @@
+"""Native Anthropic Messages protocol with incrementally decoded content blocks."""
+
+import json
+from contextlib import aclosing
+
+from app.contracts import MessageRole, ModelEventType, ModelRequest
+from app.providers.base import ProviderError, ProviderToolCall, ProviderTurn
+from app.providers.http_base import (
+    UsageTracker, check_error, decode_tool_arguments, invalid_response, list_value,
+    object_value, string_value, token_count, truncated_stream,
+)
+from app.providers.openai_compatible import OpenAICompatibleProvider
+from app.providers.tool_names import mapped_tool_names
+
+
+class AnthropicMessagesProvider(OpenAICompatibleProvider):
+    stream_path = "/messages"
+
+    def _headers(self) -> dict[str, str]:
+        headers = super()._headers()
+        authorization = headers.pop("Authorization", None)
+        if authorization:
+            headers["x-api-key"] = authorization.removeprefix("Bearer ")
+        headers["anthropic-version"] = "2023-06-01"
+        return headers
+
+    def _payload(self, request: ModelRequest, *, stream: bool) -> dict[str, object]:
+        systems = [request.system] if request.system else []
+        messages = []
+        for message in request.messages:
+            if message.role == MessageRole.system:
+                systems.append(message.content)
+                continue
+            if message.role == MessageRole.tool:
+                if not message.tool_call_id:
+                    raise ProviderError("PROVIDER_INVALID_REQUEST", "Tool result requires a call identifier.")
+                role = "user"
+                content = [{"type": "tool_result", "tool_use_id": message.tool_call_id, "content": message.content}]
+            else:
+                role = message.role.value
+                content = [{"type": "text", "text": message.content}] if message.content else []
+                content += [{"type": "tool_use", "id": call.tool_call_id, "name": call.name,
+                             "input": call.arguments} for call in message.tool_calls]
+            if not content:
+                continue
+            if messages and messages[-1]["role"] == role:
+                messages[-1]["content"].extend(content)
+            else:
+                messages.append({"role": role, "content": content})
+        payload: dict[str, object] = {"model": request.model, "messages": messages,
+                                     "max_tokens": request.max_tokens or 4096, "stream": stream}
+        if systems:
+            payload["system"] = "\n\n".join(systems)
+        if request.tools:
+            payload["tools"] = [{"name": tool.name, "description": tool.description,
+                                 "input_schema": tool.parameters} for tool in request.tools]
+        if request.temperature is not None:
+            payload["temperature"] = request.temperature
+        if request.response_format is not None:
+            format_ = request.response_format
+            if format_.get("type") != "json_schema":
+                raise ProviderError("PROVIDER_INVALID_REQUEST", "Messages requires a JSON schema response format.")
+            schema = object_value(format_.get("json_schema"))
+            payload["output_config"] = {"format": {"type": "json_schema", "schema": object_value(schema.get("schema"))}}
+        return payload
+
+    @mapped_tool_names
+    async def complete(self, request: ModelRequest) -> ProviderTurn:
+        data = await self._request("POST", self.stream_path, json=self._payload(request, stream=False))
+        texts = []
+        calls = []
+        for raw in list_value(data.get("content")):
+            block = object_value(raw)
+            if block.get("type") == "text":
+                texts.append(string_value(block.get("text")))
+            elif block.get("type") == "tool_use":
+                calls.append(ProviderToolCall(
+                    tool_call_id=string_value(block.get("id"), nonempty=True),
+                    name=string_value(block.get("name"), nonempty=True),
+                    arguments=decode_tool_arguments(block.get("input")),
+                ))
+        return ProviderTurn(text="".join(texts) or None, tool_calls=calls,
+                            **UsageTracker(cache_tokens=True).update(data.get("usage") or {}))
+
+    async def _events(self, request: ModelRequest):
+        blocks: dict[int, dict] = {}
+        usage = UsageTracker(cache_tokens=True)
+        started = False
+        async with aclosing(self._stream_json(self._payload(request, stream=True))) as chunks:
+            async for data in chunks:
+                kind = string_value(data.get("type"), nonempty=True)
+                if kind == "message_start":
+                    if started:
+                        raise invalid_response()
+                    started = True
+                    message = object_value(data.get("message"))
+                    check_error(message)
+                    if message.get("usage") is not None:
+                        yield ModelEventType.usage, usage.update(message["usage"])
+                elif kind == "content_block_start":
+                    index = token_count(data.get("index"))
+                    if not started or index in blocks:
+                        raise invalid_response()
+                    block = dict(object_value(data.get("content_block")))
+                    blocks[index] = block
+                    block["closed"] = False
+                    if block.get("type") == "tool_use":
+                        block["id"] = string_value(block.get("id"), nonempty=True)
+                        block["name"] = string_value(block.get("name"), nonempty=True)
+                        block["arguments"] = ""
+                        block["input"] = object_value(block.get("input", {}))
+                        yield ModelEventType.tool_call_start, {"tool_call_id": block["id"], "name": block["name"]}
+                    elif block.get("type") == "text" and block.get("text"):
+                        yield ModelEventType.text_delta, {"text": string_value(block["text"])}
+                    elif block.get("type") == "thinking" and block.get("thinking"):
+                        yield ModelEventType.thinking_delta, {"text": string_value(block["thinking"])}
+                elif kind == "content_block_delta":
+                    block = blocks.get(token_count(data.get("index")))
+                    if block is None or block["closed"]:
+                        raise invalid_response()
+                    delta = object_value(data.get("delta"))
+                    delta_type = delta.get("type")
+                    if delta_type == "text_delta":
+                        if block.get("type") != "text":
+                            raise invalid_response()
+                        yield ModelEventType.text_delta, {"text": string_value(delta.get("text"))}
+                    elif delta_type == "thinking_delta":
+                        if block.get("type") != "thinking":
+                            raise invalid_response()
+                        yield ModelEventType.thinking_delta, {"text": string_value(delta.get("thinking"))}
+                    elif delta_type == "input_json_delta" and block.get("type") == "tool_use":
+                        fragment = string_value(delta.get("partial_json"))
+                        block["arguments"] += fragment
+                        yield ModelEventType.tool_call_delta, {"tool_call_id": block["id"], "arguments_delta": fragment}
+                    # Signatures and future delta types have no representation in ModelEvent.
+                elif kind == "content_block_stop":
+                    block = blocks.get(token_count(data.get("index")))
+                    if block is None or block["closed"]:
+                        raise invalid_response()
+                    block["closed"] = True
+                    if block.get("type") == "tool_use":
+                        if block["arguments"]:
+                            decode_tool_arguments(block["arguments"])
+                        else:
+                            yield ModelEventType.tool_call_delta, {
+                                "tool_call_id": block["id"], "arguments_delta": json.dumps(block["input"]),
+                            }
+                        yield ModelEventType.tool_call_end, {"tool_call_id": block["id"]}
+                elif kind == "message_delta":
+                    if not started:
+                        raise invalid_response()
+                    object_value(data.get("delta"))
+                    if data.get("usage") is not None:
+                        yield ModelEventType.usage, usage.update(data["usage"])
+                elif kind == "message_stop":
+                    if not started:
+                        raise invalid_response()
+                    if any(not block["closed"] for block in blocks.values()):
+                        raise truncated_stream()
+                    return
+                elif kind == "[DONE]":
+                    raise truncated_stream()
+        raise truncated_stream()

backend/app/providers/factory.py

@@ -16,6 +16,18 @@ class ProviderFactory:
         self.credentials = ProviderCredentialResolver(credentials)
 
     def build(self, config: ProviderConfig) -> ModelProvider:
+        if config.provider_type == ProviderType.openai_responses:
+            from app.providers.openai_responses import OpenAIResponsesProvider
+            return OpenAIResponsesProvider(
+                base_url=config.base_url or "https://api.openai.com/v1",
+                credential_id=config.credential_id, credentials=self.credentials,
+            )
+        if config.provider_type == ProviderType.anthropic_messages:
+            from app.providers.anthropic_messages import AnthropicMessagesProvider
+            return AnthropicMessagesProvider(
+                base_url=config.base_url or "https://api.anthropic.com/v1",
+                credential_id=config.credential_id, credentials=self.credentials,
+            )
         if config.provider_type in {
             ProviderType.openai_chat,
             ProviderType.openai_compatible,
@@ -31,7 +43,7 @@ class ProviderFactory:
 
     @staticmethod
     def presets() -> list[ProviderPreset]:
-        return [
+        presets = [
             ProviderPreset(
                 preset_id="openai",
                 name="OpenAI",
@@ -54,12 +66,45 @@ class ProviderFactory:
                 requires_credential=False,
             ),
         ]
+        # General API endpoints. Coding-plan endpoints and keys are separate products.
+        domestic = [
+            ("kimi", "Kimi / 月之暗面", "https://api.moonshot.cn/v1", [], "长上下文对话；模型以账号权限为准。"),
+            ("qwen", "阿里云百炼", "https://dashscope.aliyuncs.com/compatible-mode/v1", [ModelCapability.embedding], "中国内地兼容接口；海外地域需修改地址。"),
+            ("zhipu", "智谱 GLM", "https://open.bigmodel.cn/api/paas/v4", [ModelCapability.embedding], "通用 API；Coding Plan 请使用其专用地址。"),
+            ("volcengine", "火山方舟 / 豆包", "https://ark.cn-beijing.volces.com/api/v3", [ModelCapability.embedding], "按账号填写模型 ID 或推理接入点 ID。"),
+            ("siliconflow", "硅基流动", "https://api.siliconflow.cn/v1", [ModelCapability.embedding, ModelCapability.transcription], "支持兼容 Embedding 和音频转写接口。"),
+            ("baidu", "百度千帆", "https://qianfan.baidubce.com/v2", [ModelCapability.embedding], "使用千帆 API Key；模型列表取决于账号。"),
+            ("hunyuan", "腾讯混元", "https://api.hunyuan.cloud.tencent.com/v1", [], "OpenAI 兼容对话接口。"),
+            ("minimax", "MiniMax", "https://api.minimaxi.com/v1", [], "文本对话兼容接口；其他媒体协议需独立适配。"),
+            ("stepfun", "阶跃星辰", "https://api.stepfun.com/v1", [], "通用 API；Step Plan 请使用其专用地址。"),
+        ]
+        for preset_id, name, url, extra, description in domestic:
+            presets.append(ProviderPreset(
+                preset_id=preset_id, name=name, provider_type=ProviderType.openai_compatible,
+                base_url=url, default_credential_id=preset_id, logo_id=preset_id,
+                capabilities=[ModelCapability.chat, *extra], description=description,
+            ))
+        presets.extend([
+            ProviderPreset(preset_id="openai-responses", name="OpenAI Responses", provider_type=ProviderType.openai_responses,
+                           base_url="https://api.openai.com/v1", default_credential_id="openai", logo_id="openai"),
+            ProviderPreset(preset_id="anthropic", name="Anthropic / Claude", provider_type=ProviderType.anthropic_messages,
+                           base_url="https://api.anthropic.com/v1", default_credential_id="anthropic", logo_id="anthropic"),
+        ])
+        for preset in presets:
+            if preset.logo_id == "custom":
+                preset.logo_id = preset.preset_id
+            if not preset.capabilities:
+                preset.capabilities = [ModelCapability.chat]
+        presets[0].capabilities += [ModelCapability.embedding, ModelCapability.transcription]
+        return presets
 
     @staticmethod
     def capabilities(provider_type: ProviderType) -> list[ModelCapability]:
         if provider_type in {
             ProviderType.openai_chat,
             ProviderType.openai_compatible,
+            ProviderType.openai_responses,
+            ProviderType.anthropic_messages,
         }:
             return [
                 ModelCapability.chat,

backend/app/providers/http_base.py

@@ -1,9 +1,13 @@
 import json
 from collections.abc import AsyncIterator
+from contextlib import aclosing
 from datetime import datetime, timezone
 
+import httpx
+
 from app.contracts import ModelEvent, ModelEventType, ModelRequest
 from app.providers.base import ProviderError, ProviderTurn
+from app.providers.tool_names import prepare_tool_names
 
 
 class TurnStreamingMixin:
@@ -80,3 +84,229 @@ def decode_tool_arguments(value: object) -> dict[str, object]:
     if not isinstance(decoded, dict):
         raise ProviderError("PROVIDER_INVALID_RESPONSE", "Tool arguments must be an object.")
     return decoded
+
+
+def invalid_response() -> ProviderError:
+    return ProviderError("PROVIDER_INVALID_RESPONSE", "Provider returned an invalid response.")
+
+
+def truncated_stream() -> ProviderError:
+    return ProviderError("PROVIDER_STREAM_TRUNCATED", "Provider stream ended before completion.")
+
+
+def object_value(value: object) -> dict:
+    if not isinstance(value, dict):
+        raise invalid_response()
+    return value
+
+
+def list_value(value: object) -> list:
+    if not isinstance(value, list):
+        raise invalid_response()
+    return value
+
+
+def string_value(value: object, *, nonempty: bool = False) -> str:
+    if not isinstance(value, str) or (nonempty and not value):
+        raise invalid_response()
+    return value
+
+
+def token_count(value: object) -> int:
+    if isinstance(value, bool) or not isinstance(value, int) or value < 0:
+        raise invalid_response()
+    return value
+
+
+def remote_error(value: object) -> ProviderError:
+    # Never reflect upstream messages, URLs, request bodies or credentials.
+    error = value if isinstance(value, dict) else {}
+    code = error.get("code") or error.get("type")
+    mapping = {
+        "authentication_error": "PROVIDER_AUTH_FAILED",
+        "invalid_api_key": "PROVIDER_AUTH_FAILED",
+        "permission_error": "PROVIDER_AUTH_FAILED",
+        "rate_limit_error": "PROVIDER_RATE_LIMITED",
+        "rate_limit_exceeded": "PROVIDER_RATE_LIMITED",
+        "insufficient_quota": "PROVIDER_RATE_LIMITED",
+        "not_found_error": "MODEL_NOT_FOUND",
+        "model_not_found": "MODEL_NOT_FOUND",
+        "invalid_request_error": "PROVIDER_INVALID_REQUEST",
+        "context_length_exceeded": "PROVIDER_INVALID_REQUEST",
+    }
+    mapped = mapping.get(code, "PROVIDER_UNAVAILABLE") if isinstance(code, str) else "PROVIDER_UNAVAILABLE"
+    return ProviderError(mapped, "Provider could not complete the request.")
+
+
+def check_error(data: dict) -> None:
+    if data.get("error") is not None or data.get("type") == "error":
+        raise remote_error(data.get("error") or data)
+
+
+class UsageTracker:
+    """Merge cumulative snapshots, including partial usage updates."""
+
+    def __init__(self, input_key: str = "input_tokens", output_key: str = "output_tokens",
+                 *, cache_tokens: bool = False) -> None:
+        self.input_key = input_key
+        self.output_key = output_key
+        self.cache_tokens = cache_tokens
+        self.counts: dict[str, int] = {}
+
+    def update(self, value: object) -> dict[str, int]:
+        usage = object_value(value)
+        keys = [self.input_key, self.output_key]
+        if self.cache_tokens:
+            keys += ["cache_creation_input_tokens", "cache_read_input_tokens"]
+        for key in keys:
+            if key in usage:
+                self.counts[key] = max(self.counts.get(key, 0), token_count(usage[key]))
+        inputs = self.counts.get(self.input_key, 0)
+        if self.cache_tokens:
+            inputs += sum(self.counts.get(key, 0) for key in keys[2:])
+        return {"input_tokens": inputs, "output_tokens": self.counts.get(self.output_key, 0)}
+
+
+class EventStreamingMixin:
+    async def stream(self, request: ModelRequest) -> AsyncIterator[ModelEvent]:
+        sequence = 0
+        status = "completed"
+        try:
+            request, originals = prepare_tool_names(request)
+            # Closing the public iterator must synchronously close every nested iterator.
+            async with aclosing(self._events(request)) as events:
+                async for kind, data in events:
+                    if kind == ModelEventType.tool_call_start and "name" in data:
+                        data = {**data, "name": originals.get(data["name"], data["name"])}
+                    if kind == ModelEventType.usage:
+                        data = {**data, "total_tokens": data["input_tokens"] + data["output_tokens"]}
+                    yield ModelEvent(event=kind, data=data, sequence=sequence,
+                                     timestamp=datetime.now(timezone.utc))
+                    sequence += 1
+        except ProviderError as exc:
+            status = "failed"
+            yield ModelEvent(event=ModelEventType.error, sequence=sequence,
+                             data={"code": exc.code, "message": exc.message},
+                             timestamp=datetime.now(timezone.utc))
+            sequence += 1
+        except (ValueError, TypeError, KeyError, IndexError, AttributeError, OverflowError):
+            status = "failed"
+            error = invalid_response()
+            yield ModelEvent(event=ModelEventType.error, sequence=sequence,
+                             data={"code": error.code, "message": error.message},
+                             timestamp=datetime.now(timezone.utc))
+            sequence += 1
+        # CancelledError and GeneratorExit deliberately propagate without a Done event.
+        yield ModelEvent(event=ModelEventType.done, sequence=sequence,
+                         data={"status": status},
+                         timestamp=datetime.now(timezone.utc))
+
+
+async def sse_objects(response: httpx.Response) -> AsyncIterator[dict]:
+    """Read SSE frames, accepting the adjacent data lines used by some gateways."""
+    parts: list[str] = []
+    event_name = ""
+
+    def decode() -> dict:
+        value = "\n".join(parts)
+        if value.strip() == "[DONE]":
+            return {"type": "[DONE]"}
+        try:
+            data = object_value(json.loads(value))
+        except (ValueError, TypeError) as exc:
+            raise invalid_response() from exc
+        if event_name and "type" not in data:
+            data["type"] = event_name
+        check_error(data)
+        return data
+
+    async for line in response.aiter_lines():
+        if not line:
+            if parts:
+                yield decode()
+            parts = []
+            event_name = ""
+        elif line.startswith(":"):
+            continue
+        elif line.startswith("event:"):
+            if parts:
+                yield decode()
+                parts = []
+            event_name = line[6:].strip()
+        elif line.startswith("data:"):
+            if parts:
+                # Legacy compatible endpoints sometimes omit blank separators.
+                try:
+                    json.loads("\n".join(parts))
+                except ValueError:
+                    pass
+                else:
+                    yield decode()
+                    parts = []
+                    event_name = ""
+            parts.append(line[5:].removeprefix(" "))
+    if parts:
+        yield decode()
+
+
+class HTTPProviderMixin:
+    stream_path = "/chat/completions"
+    stream_format = "sse"
+
+    def _headers(self) -> dict[str, str]:
+        return {"Content-Type": "application/json"}
+
+    @staticmethod
+    def _status_error(exc: httpx.HTTPStatusError) -> ProviderError:
+        status = exc.response.status_code
+        code = {400: "PROVIDER_INVALID_REQUEST", 401: "PROVIDER_AUTH_FAILED",
+                403: "PROVIDER_AUTH_FAILED", 404: "MODEL_NOT_FOUND",
+                408: "PROVIDER_TIMEOUT", 413: "PROVIDER_INVALID_REQUEST",
+                422: "PROVIDER_INVALID_REQUEST", 429: "PROVIDER_RATE_LIMITED"}.get(
+                    status, "PROVIDER_UNAVAILABLE")
+        return ProviderError(code, f"Provider returned HTTP {status}.")
+
+    async def _request(self, method: str, path: str, **kwargs) -> dict:
+        headers = self._headers()
+        try:
+            async with httpx.AsyncClient(timeout=self.timeout_seconds, transport=self.transport) as client:
+                response = await client.request(method, f"{self.base_url}{path}", headers=headers, **kwargs)
+                response.raise_for_status()
+                data = object_value(response.json())
+                check_error(data)
+                return data
+        except httpx.TimeoutException as exc:
+            raise ProviderError("PROVIDER_TIMEOUT", "Provider request timed out.") from exc
+        except httpx.HTTPStatusError as exc:
+            raise self._status_error(exc) from exc
+        except httpx.HTTPError as exc:
+            raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
+        except (ValueError, TypeError) as exc:
+            raise invalid_response() from exc
+
+    async def _stream_json(self, payload: dict[str, object]) -> AsyncIterator[dict]:
+        headers = self._headers()
+        headers["Accept"] = "text/event-stream" if self.stream_format == "sse" else "application/x-ndjson"
+        try:
+            async with httpx.AsyncClient(timeout=self.timeout_seconds, transport=self.transport) as client:
+                async with client.stream("POST", f"{self.base_url}{self.stream_path}",
+                                         headers=headers, json=payload) as response:
+                    response.raise_for_status()
+                    if self.stream_format == "sse":
+                        async with aclosing(sse_objects(response)) as objects:
+                            async for data in objects:
+                                yield data
+                    else:
+                        async for line in response.aiter_lines():
+                            if line.strip():
+                                data = object_value(json.loads(line))
+                                check_error(data)
+                                yield data
+        except httpx.TimeoutException as exc:
+            raise ProviderError("PROVIDER_TIMEOUT", "Provider request timed out.") from exc
+        except httpx.HTTPStatusError as exc:
+            raise self._status_error(exc) from exc
+        except httpx.HTTPError as exc:
+            raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
+        except (ValueError, TypeError) as exc:
+            raise invalid_response() from exc

backend/app/providers/ollama.py

@@ -1,16 +1,22 @@
-from uuid import uuid4
 import json
-from collections.abc import AsyncIterator
-from datetime import datetime, timezone
+from contextlib import aclosing
+from uuid import uuid4
 
 import httpx
 
-from app.contracts import ModelCapability, ModelEvent, ModelEventType, ModelInfo, ModelRequest
+from app.contracts import MessageRole, ModelCapability, ModelEventType, ModelInfo, ModelRequest
 from app.providers.base import ProviderError, ProviderToolCall, ProviderTurn
-from app.providers.http_base import TurnStreamingMixin, decode_tool_arguments
+from app.providers.tool_names import mapped_tool_names
+from app.providers.http_base import (
+    EventStreamingMixin, HTTPProviderMixin, UsageTracker, decode_tool_arguments,
+    invalid_response, list_value, object_value, string_value, truncated_stream,
+)
 
 
-class OllamaProvider(TurnStreamingMixin):
+class OllamaProvider(EventStreamingMixin, HTTPProviderMixin):
+    stream_path = "/api/chat"
+    stream_format = "jsonl"
+
     def __init__(
         self,
         base_url: str = "http://127.0.0.1:11434",
@@ -21,126 +27,55 @@ class OllamaProvider(TurnStreamingMixin):
         self.timeout_seconds = timeout_seconds
         self.transport = transport
 
+    @mapped_tool_names
     async def complete(self, request: ModelRequest) -> ProviderTurn:
-        messages = []
-        if request.system:
-            messages.append({"role": "system", "content": request.system})
-        for message in request.messages:
-            item: dict[str, object] = {
-                "role": message.role.value,
-                "content": message.content,
-            }
-            if message.tool_calls:
-                item["tool_calls"] = [
-                    {
-                        "function": {
-                            "name": call.name,
-                            "arguments": call.arguments,
-                        }
-                    }
-                    for call in message.tool_calls
-                ]
-            messages.append(item)
-        payload: dict[str, object] = {
-            "model": request.model,
-            "messages": messages,
-            "stream": False,
-        }
-        if request.tools:
-            payload["tools"] = [
-                {
-                    "type": "function",
-                    "function": {
-                        "name": tool.name,
-                        "description": tool.description,
-                        "parameters": tool.parameters,
-                    },
-                }
-                for tool in request.tools
-            ]
-        data = await self._request("POST", "/api/chat", json=payload)
-        message = data.get("message") or {}
-        tool_calls = []
-        for raw_call in message.get("tool_calls") or []:
-            function = raw_call.get("function") or {}
-            tool_calls.append(
-                ProviderToolCall(
-                    tool_call_id=raw_call.get("id") or f"call_{uuid4().hex}",
-                    name=function.get("name") or "",
-                    arguments=decode_tool_arguments(function.get("arguments", {})),
-                )
-            )
-        return ProviderTurn(
-            text=message.get("content") or None,
-            tool_calls=tool_calls,
-            input_tokens=int(data.get("prompt_eval_count") or 0),
-            output_tokens=int(data.get("eval_count") or 0),
+        data = await self._request("POST", self.stream_path, json=self._chat_payload(request, stream=False))
+        message = object_value(data.get("message"))
+        calls = [self._tool_call(raw) for raw in list_value(message.get("tool_calls", []))]
+        content = message.get("content")
+        if content is not None:
+            content = string_value(content)
+        return ProviderTurn(text=content or None, tool_calls=calls,
+                            **UsageTracker("prompt_eval_count", "eval_count").update(data))
+
+    @staticmethod
+    def _tool_call(raw: object) -> ProviderToolCall:
+        call = object_value(raw)
+        function = object_value(call.get("function"))
+        return ProviderToolCall(
+            tool_call_id=string_value(call.get("id") or f"call_{uuid4().hex}"),
+            name=string_value(function.get("name"), nonempty=True),
+            arguments=decode_tool_arguments(function.get("arguments", {})),
         )
 
-    async def list_models(self) -> list[ModelInfo]:
-        data = await self._request("GET", "/api/tags")
-        return [
-            ModelInfo(
-                model=item["name"],
-                display_name=item.get("name", ""),
-                capabilities=[ModelCapability.chat, ModelCapability.streaming],
-            )
-            for item in data.get("models", [])
-            if isinstance(item, dict) and item.get("name")
-        ]
-
-    async def stream(self, request: ModelRequest) -> AsyncIterator[ModelEvent]:
-        payload = self._chat_payload(request, stream=True)
-        sequence = 0
-
-        def event(kind: ModelEventType, data: dict | None = None) -> ModelEvent:
-            nonlocal sequence
-            item = ModelEvent(
-                event=kind, sequence=sequence, data=data or {},
-                timestamp=datetime.now(timezone.utc),
-            )
-            sequence += 1
-            return item
-
-        try:
-            async for data in self._stream_json(payload):
-                message = data.get("message") or {}
+    async def _events(self, request: ModelRequest):
+        usage = UsageTracker("prompt_eval_count", "eval_count")
+        async with aclosing(self._stream_json(self._chat_payload(request, stream=True))) as chunks:
+            async for data in chunks:
+                message = object_value(data.get("message", {}))
                 if message.get("thinking"):
-                    yield event(ModelEventType.thinking_delta, {"text": message["thinking"]})
+                    yield ModelEventType.thinking_delta, {"text": string_value(message["thinking"])}
                 if message.get("content"):
-                    yield event(ModelEventType.text_delta, {"text": message["content"]})
-                for raw_call in message.get("tool_calls") or []:
-                    function = raw_call.get("function") or {}
-                    call_id = raw_call.get("id") or f"call_{uuid4().hex}"
-                    yield event(
-                        ModelEventType.tool_call_start,
-                        {"tool_call_id": call_id, "name": function.get("name") or ""},
-                    )
-                    yield event(
-                        ModelEventType.tool_call_delta,
-                        {
-                            "tool_call_id": call_id,
-                            "arguments_delta": json.dumps(
-                                function.get("arguments") or {}, ensure_ascii=False
-                            ),
-                        },
-                    )
-                    yield event(ModelEventType.tool_call_end, {"tool_call_id": call_id})
-                if data.get("done"):
-                    yield event(
-                        ModelEventType.usage,
-                        {
-                            "input_tokens": int(data.get("prompt_eval_count") or 0),
-                            "output_tokens": int(data.get("eval_count") or 0),
-                        },
-                    )
-            yield event(ModelEventType.done)
-        except ProviderError as exc:
-            yield event(ModelEventType.error, {"code": exc.code, "message": exc.message})
-            yield event(ModelEventType.done)
+                    yield ModelEventType.text_delta, {"text": string_value(message["content"])}
+                for raw in list_value(message.get("tool_calls", [])):
+                    call = self._tool_call(raw)
+                    yield ModelEventType.tool_call_start, {"tool_call_id": call.tool_call_id, "name": call.name}
+                    yield ModelEventType.tool_call_delta, {
+                        "tool_call_id": call.tool_call_id,
+                        "arguments_delta": json.dumps(call.arguments, ensure_ascii=False),
+                    }
+                    yield ModelEventType.tool_call_end, {"tool_call_id": call.tool_call_id}
+                if "done" in data and not isinstance(data["done"], bool):
+                    raise invalid_response()
+                if "prompt_eval_count" in data or "eval_count" in data or data.get("done"):
+                    yield ModelEventType.usage, usage.update(data)
+                if data.get("done") is True:
+                    return
+        raise truncated_stream()
 
     def _chat_payload(self, request: ModelRequest, *, stream: bool) -> dict[str, object]:
         messages = []
+        names: dict[str, str] = {}
         if request.system:
             messages.append({"role": "system", "content": request.system})
         for message in request.messages:
@@ -150,53 +85,49 @@ class OllamaProvider(TurnStreamingMixin):
                     {"function": {"name": call.name, "arguments": call.arguments}}
                     for call in message.tool_calls
                 ]
+                names.update({call.tool_call_id: call.name for call in message.tool_calls})
+            if message.role == MessageRole.tool:
+                name = message.name or names.get(message.tool_call_id or "")
+                if name:
+                    item["tool_name"] = name
             messages.append(item)
         payload: dict[str, object] = {
-            "model": request.model, "messages": messages, "stream": stream
+            "model": request.model, "messages": messages, "stream": stream,
         }
         if request.tools:
             payload["tools"] = [
-                {
-                    "type": "function",
-                    "function": {
-                        "name": tool.name,
-                        "description": tool.description,
-                        "parameters": tool.parameters,
-                    },
-                }
-                for tool in request.tools
+                {"type": "function", "function": {
+                    "name": tool.name, "description": tool.description, "parameters": tool.parameters,
+                }} for tool in request.tools
             ]
+        options = {}
+        if request.temperature is not None:
+            options["temperature"] = request.temperature
+        if request.max_tokens is not None:
+            options["num_predict"] = request.max_tokens
+        if options:
+            payload["options"] = options
+        if request.response_format:
+            format_ = request.response_format
+            if format_.get("type") == "json_object":
+                payload["format"] = "json"
+            elif format_.get("type") == "json_schema":
+                payload["format"] = object_value(object_value(format_.get("json_schema")).get("schema"))
+            else:
+                payload["format"] = format_
         return payload
 
-    async def _stream_json(self, payload: dict[str, object]) -> AsyncIterator[dict]:
-        try:
-            async with httpx.AsyncClient(
-                timeout=self.timeout_seconds, transport=self.transport
-            ) as client:
-                async with client.stream(
-                    "POST", f"{self.base_url}/api/chat", json=payload
-                ) as response:
-                    response.raise_for_status()
-                    async for line in response.aiter_lines():
-                        if not line.strip():
-                            continue
-                        try:
-                            data = json.loads(line)
-                        except json.JSONDecodeError as exc:
-                            raise ProviderError(
-                                "PROVIDER_INVALID_RESPONSE", "Ollama returned invalid JSONL."
-                            ) from exc
-                        if isinstance(data, dict):
-                            yield data
-        except httpx.TimeoutException as exc:
-            raise ProviderError("PROVIDER_TIMEOUT", "Ollama request timed out.") from exc
-        except httpx.HTTPStatusError as exc:
-            raise ProviderError(
-                "MODEL_NOT_FOUND" if exc.response.status_code == 404 else "PROVIDER_UNAVAILABLE",
-                f"Ollama returned HTTP {exc.response.status_code}.",
-            ) from exc
-        except httpx.HTTPError as exc:
-            raise ProviderError("PROVIDER_UNAVAILABLE", "Ollama is unavailable.") from exc
+    async def list_models(self) -> list[ModelInfo]:
+        data = await self._request("GET", "/api/tags")
+        return [
+            ModelInfo(
+                model=string_value(item["name"]), display_name=item["name"],
+                capabilities=([ModelCapability.embedding] if "embed" in item["name"].lower()
+                              else [ModelCapability.chat, ModelCapability.streaming]),
+            )
+            for item in list_value(data.get("models"))
+            if isinstance(item, dict) and isinstance(item.get("name"), str) and item["name"]
+        ]
 
     async def test_connection(self, model: str | None = None) -> tuple[bool, str]:
         try:
@@ -206,24 +137,3 @@ class OllamaProvider(TurnStreamingMixin):
         if model and model not in {item.model for item in models}:
             return False, f"Model is not installed: {model}"
         return True, f"Connected; discovered {len(models)} local model(s)."
-
-    async def _request(self, method: str, path: str, **kwargs) -> dict:
-        try:
-            async with httpx.AsyncClient(
-                timeout=self.timeout_seconds, transport=self.transport
-            ) as client:
-                response = await client.request(method, f"{self.base_url}{path}", **kwargs)
-                response.raise_for_status()
-                data = response.json()
-        except httpx.TimeoutException as exc:
-            raise ProviderError("PROVIDER_TIMEOUT", "Ollama request timed out.") from exc
-        except httpx.HTTPStatusError as exc:
-            raise ProviderError(
-                "MODEL_NOT_FOUND" if exc.response.status_code == 404 else "PROVIDER_UNAVAILABLE",
-                f"Ollama returned HTTP {exc.response.status_code}.",
-            ) from exc
-        except (httpx.HTTPError, ValueError) as exc:
-            raise ProviderError("PROVIDER_UNAVAILABLE", "Ollama is unavailable.") from exc
-        if not isinstance(data, dict):
-            raise ProviderError("PROVIDER_INVALID_RESPONSE", "Ollama returned non-object JSON.")
-        return data

backend/app/providers/openai_compatible.py

@@ -1,24 +1,20 @@
 import json
-from collections.abc import AsyncIterator
-from datetime import datetime, timezone
+from contextlib import aclosing
 from uuid import uuid4
 
 import httpx
 
-from app.contracts import (
-    MessageRole,
-    ModelCapability,
-    ModelEvent,
-    ModelEventType,
-    ModelInfo,
-    ModelRequest,
-)
+from app.contracts import MessageRole, ModelCapability, ModelEventType, ModelInfo, ModelRequest
 from app.providers.base import ProviderError, ProviderToolCall, ProviderTurn
 from app.providers.credentials import CredentialResolver, CredentialStoreError
-from app.providers.http_base import TurnStreamingMixin, decode_tool_arguments
+from app.providers.tool_names import mapped_tool_names
+from app.providers.http_base import (
+    EventStreamingMixin, HTTPProviderMixin, UsageTracker, decode_tool_arguments,
+    invalid_response, list_value, object_value, string_value, token_count, truncated_stream,
+)
 
 
-class OpenAICompatibleProvider(TurnStreamingMixin):
+class OpenAICompatibleProvider(EventStreamingMixin, HTTPProviderMixin):
     def __init__(
         self,
         base_url: str,
@@ -33,50 +29,37 @@ class OpenAICompatibleProvider(TurnStreamingMixin):
         self.timeout_seconds = timeout_seconds
         self.transport = transport
 
+    @mapped_tool_names
     async def complete(self, request: ModelRequest) -> ProviderTurn:
-        payload = self._payload(request, stream=False)
-
-        data = await self._request("POST", "/chat/completions", json=payload)
-        try:
-            message = data["choices"][0]["message"]
-        except (KeyError, IndexError, TypeError) as exc:
-            raise ProviderError("PROVIDER_INVALID_RESPONSE", "Missing completion message.") from exc
-
-        tool_calls = []
-        for raw_call in message.get("tool_calls") or []:
-            function = raw_call.get("function") or {}
-            tool_calls.append(
-                ProviderToolCall(
-                    tool_call_id=raw_call.get("id") or f"call_{uuid4().hex}",
-                    name=function.get("name") or "",
-                    arguments=decode_tool_arguments(function.get("arguments", "{}")),
-                )
-            )
-        usage = data.get("usage") or {}
-        return ProviderTurn(
-            text=message.get("content"),
-            tool_calls=tool_calls,
-            input_tokens=int(usage.get("prompt_tokens") or 0),
-            output_tokens=int(usage.get("completion_tokens") or 0),
-        )
+        data = await self._request("POST", self.stream_path, json=self._payload(request, stream=False))
+        choices = list_value(data.get("choices"))
+        if not choices:
+            raise invalid_response()
+        message = object_value(object_value(choices[0]).get("message"))
+        calls = []
+        for raw in list_value(message.get("tool_calls", [])):
+            raw = object_value(raw)
+            function = object_value(raw.get("function"))
+            calls.append(ProviderToolCall(
+                tool_call_id=string_value(raw.get("id") or f"call_{uuid4().hex}"),
+                name=string_value(function.get("name"), nonempty=True),
+                arguments=decode_tool_arguments(function.get("arguments", "{}")),
+            ))
+        text = message.get("content")
+        if text is not None:
+            text = string_value(text)
+        usage = UsageTracker("prompt_tokens", "completion_tokens").update(data.get("usage") or {})
+        return ProviderTurn(text=text, tool_calls=calls, **usage)
 
     def _payload(self, request: ModelRequest, *, stream: bool) -> dict[str, object]:
         payload: dict[str, object] = {
-            "model": request.model,
-            "messages": self._messages(request),
-            "stream": stream,
+            "model": request.model, "messages": self._messages(request), "stream": stream,
         }
         if request.tools:
             payload["tools"] = [
-                {
-                    "type": "function",
-                    "function": {
-                        "name": tool.name,
-                        "description": tool.description,
-                        "parameters": tool.parameters,
-                    },
-                }
-                for tool in request.tools
+                {"type": "function", "function": {
+                    "name": tool.name, "description": tool.description, "parameters": tool.parameters,
+                }} for tool in request.tools
             ]
         if request.temperature is not None:
             payload["temperature"] = request.temperature
@@ -84,124 +67,78 @@ class OpenAICompatibleProvider(TurnStreamingMixin):
             payload["max_tokens"] = request.max_tokens
         if request.response_format is not None:
             payload["response_format"] = request.response_format
-
+        if stream:
+            payload["stream_options"] = {"include_usage": True}
         return payload
 
-    async def stream(self, request: ModelRequest) -> AsyncIterator[ModelEvent]:
-        sequence = 0
-        open_calls: dict[int, str] = {}
-
-        def event(kind: ModelEventType, data: dict | None = None) -> ModelEvent:
-            nonlocal sequence
-            item = ModelEvent(
-                event=kind,
-                sequence=sequence,
-                data=data or {},
-                timestamp=datetime.now(timezone.utc),
-            )
-            sequence += 1
-            return item
-
-        try:
-            async for data in self._stream_json(self._payload(request, stream=True)):
-                usage = data.get("usage") or {}
-                if usage:
-                    yield event(
-                        ModelEventType.usage,
-                        {
-                            "input_tokens": int(usage.get("prompt_tokens") or 0),
-                            "output_tokens": int(usage.get("completion_tokens") or 0),
-                        },
-                    )
-                choices = data.get("choices") or []
+    async def _events(self, request: ModelRequest):
+        calls: dict[int, dict] = {}
+        usage = UsageTracker("prompt_tokens", "completion_tokens")
+        finished = False
+        seen = False
+        async with aclosing(self._stream_json(self._payload(request, stream=True))) as chunks:
+            async for data in chunks:
+                if data.get("type") == "[DONE]":
+                    if not seen:
+                        raise invalid_response()
+                    finished = True
+                    break
+                if data.get("usage") is not None:
+                    yield ModelEventType.usage, usage.update(data["usage"])
+                choices = list_value(data.get("choices", []))
                 if not choices:
                     continue
-                choice = choices[0]
-                delta = choice.get("delta") or {}
+                seen = True
+                choice = object_value(choices[0])
+                delta = object_value(choice.get("delta") or {})
                 if delta.get("reasoning_content"):
-                    yield event(
-                        ModelEventType.thinking_delta,
-                        {"text": delta["reasoning_content"]},
-                    )
+                    yield ModelEventType.thinking_delta, {"text": string_value(delta["reasoning_content"])}
                 if delta.get("content"):
-                    yield event(ModelEventType.text_delta, {"text": delta["content"]})
-                for raw_call in delta.get("tool_calls") or []:
-                    index = int(raw_call.get("index") or 0)
-                    function = raw_call.get("function") or {}
-                    call_id = raw_call.get("id") or open_calls.get(index) or f"call_{uuid4().hex}"
-                    if index not in open_calls:
-                        open_calls[index] = call_id
-                        yield event(
-                            ModelEventType.tool_call_start,
-                            {"tool_call_id": call_id, "name": function.get("name") or ""},
-                        )
-                    if function.get("arguments"):
-                        yield event(
-                            ModelEventType.tool_call_delta,
-                            {
-                                "tool_call_id": open_calls[index],
-                                "arguments_delta": function["arguments"],
-                            },
-                        )
-                if choice.get("finish_reason") == "tool_calls":
-                    for call_id in open_calls.values():
-                        yield event(
-                            ModelEventType.tool_call_end, {"tool_call_id": call_id}
-                        )
-                    open_calls.clear()
-            for call_id in open_calls.values():
-                yield event(ModelEventType.tool_call_end, {"tool_call_id": call_id})
-            yield event(ModelEventType.done)
-        except ProviderError as exc:
-            yield event(ModelEventType.error, {"code": exc.code, "message": exc.message})
-            yield event(ModelEventType.done)
-
-    async def _stream_json(self, payload: dict[str, object]) -> AsyncIterator[dict]:
-        headers = self._headers()
-        try:
-            async with httpx.AsyncClient(
-                timeout=self.timeout_seconds, transport=self.transport
-            ) as client:
-                async with client.stream(
-                    "POST", f"{self.base_url}/chat/completions", headers=headers, json=payload
-                ) as response:
-                    response.raise_for_status()
-                    async for line in response.aiter_lines():
-                        if not line.startswith("data:"):
-                            continue
-                        value = line[5:].strip()
-                        if not value or value == "[DONE]":
-                            continue
-                        try:
-                            data = json.loads(value)
-                        except json.JSONDecodeError as exc:
-                            raise ProviderError(
-                                "PROVIDER_INVALID_RESPONSE", "Provider returned invalid SSE JSON."
-                            ) from exc
-                        if isinstance(data, dict):
-                            yield data
-        except httpx.TimeoutException as exc:
-            raise ProviderError("PROVIDER_TIMEOUT", "Provider request timed out.") from exc
-        except httpx.HTTPStatusError as exc:
-            raise self._status_error(exc) from exc
-        except httpx.HTTPError as exc:
-            raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
+                    yield ModelEventType.text_delta, {"text": string_value(delta["content"])}
+                for raw in list_value(delta.get("tool_calls", [])):
+                    raw = object_value(raw)
+                    index = token_count(raw.get("index", 0))
+                    function = object_value(raw.get("function") or {})
+                    call = calls.setdefault(index, {"id": "", "name": "", "arguments": ""})
+                    if raw.get("id"):
+                        call["id"] = string_value(raw["id"])
+                    if function.get("name"):
+                        call["name"] += string_value(function["name"])
+                    fragment = string_value(function.get("arguments", ""))
+                    call["arguments"] += fragment
+                if choice.get("finish_reason"):
+                    finished = True
+        if not finished:
+            raise truncated_stream()
+        for call in calls.values():
+            if not call["name"]:
+                raise invalid_response()
+            decode_tool_arguments(call["arguments"] or "{}")
+            # A name can span multiple chunks; publish only the complete identity.
+            call["id"] = call["id"] or f"call_{uuid4().hex}"
+            yield ModelEventType.tool_call_start, {"tool_call_id": call["id"], "name": call["name"]}
+            yield ModelEventType.tool_call_delta, {"tool_call_id": call["id"], "arguments_delta": call["arguments"] or "{}"}
+            yield ModelEventType.tool_call_end, {"tool_call_id": call["id"]}
 
     async def list_models(self) -> list[ModelInfo]:
         data = await self._request("GET", "/models")
-        return [
-            ModelInfo(
-                model=item["id"],
-                display_name=item["id"],
-                capabilities=[
-                    ModelCapability.chat,
-                    ModelCapability.tool_calling,
-                    ModelCapability.streaming,
-                ],
-            )
-            for item in data.get("data", [])
-            if isinstance(item, dict) and item.get("id")
-        ]
+        return [ModelInfo(model=string_value(item["id"]), display_name=item["id"],
+                          capabilities=self._model_capabilities(string_value(item["id"])))
+                for item in list_value(data.get("data"))
+                if isinstance(item, dict) and item.get("id")]
+
+    @staticmethod
+    def _model_capabilities(model: str) -> list[ModelCapability]:
+        # /models does not advertise capabilities. Avoid known non-chat families;
+        # these are discovery hints, not a guarantee of support by a gateway.
+        name = model.lower()
+        if "embed" in name or name.startswith(("bge-", "bge/")):
+            return [ModelCapability.embedding]
+        if any(marker in name for marker in (
+            "whisper", "tts", "transcri", "audio", "realtime", "dall-e", "image", "moderation", "rerank",
+        )):
+            return []
+        return [ModelCapability.chat]
 
     async def test_connection(self, model: str | None = None) -> tuple[bool, str]:
         try:
@@ -217,73 +154,30 @@ class OpenAICompatibleProvider(TurnStreamingMixin):
         if request.system:
             result.append({"role": "system", "content": request.system})
         for message in request.messages:
-            item: dict[str, object] = {
-                "role": message.role.value,
-                "content": message.content,
-            }
+            item: dict[str, object] = {"role": message.role.value, "content": message.content}
             if message.name:
                 item["name"] = message.name
             if message.role == MessageRole.tool and message.tool_call_id:
                 item["tool_call_id"] = message.tool_call_id
             if message.tool_calls:
                 item["tool_calls"] = [
-                    {
-                        "id": call.tool_call_id,
-                        "type": "function",
-                        "function": {
-                            "name": call.name,
-                            "arguments": json.dumps(call.arguments),
-                        },
-                    }
-                    for call in message.tool_calls
+                    {"id": call.tool_call_id, "type": "function", "function": {
+                        "name": call.name, "arguments": json.dumps(call.arguments),
+                    }} for call in message.tool_calls
                 ]
             result.append(item)
         return result
 
-    async def _request(self, method: str, path: str, **kwargs) -> dict:
-        headers = self._headers()
-        try:
-            async with httpx.AsyncClient(
-                timeout=self.timeout_seconds, transport=self.transport
-            ) as client:
-                response = await client.request(
-                    method, f"{self.base_url}{path}", headers=headers, **kwargs
-                )
-                response.raise_for_status()
-                data = response.json()
-        except httpx.TimeoutException as exc:
-            raise ProviderError("PROVIDER_TIMEOUT", "Provider request timed out.") from exc
-        except httpx.HTTPStatusError as exc:
-            raise self._status_error(exc) from exc
-        except (httpx.HTTPError, ValueError) as exc:
-            raise ProviderError("PROVIDER_UNAVAILABLE", "Provider is unavailable.") from exc
-        if not isinstance(data, dict):
-            raise ProviderError("PROVIDER_INVALID_RESPONSE", "Provider returned non-object JSON.")
-        return data
-
     def _headers(self) -> dict[str, str]:
         headers = {"Content-Type": "application/json"}
         try:
             api_key = self.credentials.resolve(self.credential_id)
         except CredentialStoreError as exc:
-            raise ProviderError(
-                "PROVIDER_CREDENTIAL_UNAVAILABLE",
-                "Credential could not be decrypted by the AI Core.",
-            ) from exc
+            raise ProviderError("PROVIDER_CREDENTIAL_UNAVAILABLE",
+                                "Credential could not be decrypted by the AI Core.") from exc
         if self.credential_id and not api_key:
-            raise ProviderError(
-                "PROVIDER_CREDENTIAL_MISSING",
-                f'Credential "{self.credential_id}" is not available in the AI Core process.',
-            )
+            raise ProviderError("PROVIDER_CREDENTIAL_MISSING",
+                                "Credential is not available in the AI Core process.")
         if api_key:
             headers["Authorization"] = f"Bearer {api_key}"
         return headers
-
-    @staticmethod
-    def _status_error(exc: httpx.HTTPStatusError) -> ProviderError:
-        code = {
-            401: "PROVIDER_AUTH_FAILED",
-            404: "MODEL_NOT_FOUND",
-            429: "PROVIDER_RATE_LIMITED",
-        }.get(exc.response.status_code, "PROVIDER_UNAVAILABLE")
-        return ProviderError(code, f"Provider returned HTTP {exc.response.status_code}.")

backend/app/providers/openai_responses.py

@@ -0,0 +1,168 @@
+"""Native /responses adapter; stateless history uses function_call/output items."""
+
+import json
+from contextlib import aclosing
+
+from app.contracts import MessageRole, ModelEventType, ModelRequest
+from app.providers.base import ProviderError, ProviderToolCall, ProviderTurn
+from app.providers.http_base import (
+    UsageTracker, check_error, decode_tool_arguments, invalid_response, list_value,
+    object_value, remote_error, string_value, token_count, truncated_stream,
+)
+from app.providers.openai_compatible import OpenAICompatibleProvider
+from app.providers.tool_names import mapped_tool_names
+
+
+class OpenAIResponsesProvider(OpenAICompatibleProvider):
+    stream_path = "/responses"
+
+    def _payload(self, request: ModelRequest, *, stream: bool) -> dict[str, object]:
+        inputs = []
+        for message in request.messages:
+            if message.role == MessageRole.tool:
+                if not message.tool_call_id:
+                    raise ProviderError("PROVIDER_INVALID_REQUEST", "Tool result requires a call identifier.")
+                inputs.append({"type": "function_call_output", "call_id": message.tool_call_id,
+                               "output": message.content})
+                continue
+            if message.content or not message.tool_calls:
+                inputs.append({"role": message.role.value, "content": message.content})
+            for call in message.tool_calls:
+                inputs.append({"type": "function_call", "call_id": call.tool_call_id,
+                               "name": call.name, "arguments": json.dumps(call.arguments)})
+        payload: dict[str, object] = {"model": request.model, "input": inputs, "stream": stream}
+        if request.system:
+            payload["instructions"] = request.system
+        if request.tools:
+            payload["tools"] = [{"type": "function", "name": tool.name,
+                                 "description": tool.description, "parameters": tool.parameters}
+                                for tool in request.tools]
+        if request.temperature is not None:
+            payload["temperature"] = request.temperature
+        if request.max_tokens is not None:
+            payload["max_output_tokens"] = request.max_tokens
+        if request.response_format is not None:
+            format_ = dict(request.response_format)
+            if format_.get("type") == "json_schema":
+                format_ = {"type": "json_schema", **object_value(format_.get("json_schema"))}
+            payload["text"] = {"format": format_}
+        return payload
+
+    @staticmethod
+    def _check_response(data: dict) -> None:
+        check_error(data)
+        status = data.get("status")
+        if status == "incomplete":
+            raise ProviderError("PROVIDER_INCOMPLETE_RESPONSE", "Provider response is incomplete.")
+        if status == "failed":
+            raise remote_error(data.get("error"))
+        if status is not None and status != "completed":
+            raise invalid_response()
+
+    @mapped_tool_names
+    async def complete(self, request: ModelRequest) -> ProviderTurn:
+        data = await self._request("POST", self.stream_path, json=self._payload(request, stream=False))
+        self._check_response(data)
+        texts = []
+        calls = []
+        for raw in list_value(data.get("output")):
+            item = object_value(raw)
+            if item.get("type") == "message":
+                for raw_part in list_value(item.get("content")):
+                    part = object_value(raw_part)
+                    if part.get("type") == "output_text":
+                        texts.append(string_value(part.get("text")))
+                    elif part.get("type") == "refusal":
+                        texts.append(string_value(part.get("refusal")))
+            elif item.get("type") == "function_call":
+                calls.append(ProviderToolCall(
+                    tool_call_id=string_value(item.get("call_id"), nonempty=True),
+                    name=string_value(item.get("name"), nonempty=True),
+                    arguments=decode_tool_arguments(item.get("arguments")),
+                ))
+        return ProviderTurn(text="".join(texts) or None, tool_calls=calls,
+                            **UsageTracker().update(data.get("usage") or {}))
+
+    async def _events(self, request: ModelRequest):
+        calls: dict[int, dict] = {}
+        usage = UsageTracker()
+
+        def finish_call(index: int, final: object = None):
+            call = calls[index]
+            if call["ended"]:
+                return []
+            events = []
+            if final is not None:
+                arguments = string_value(final)
+                if not arguments.startswith(call["arguments"]):
+                    raise invalid_response()
+                remainder = arguments[len(call["arguments"]):]
+                if remainder:
+                    events.append((ModelEventType.tool_call_delta,
+                                   {"tool_call_id": call["id"], "arguments_delta": remainder}))
+                call["arguments"] = arguments
+            decode_tool_arguments(call["arguments"])
+            call["ended"] = True
+            events.append((ModelEventType.tool_call_end, {"tool_call_id": call["id"]}))
+            return events
+
+        async with aclosing(self._stream_json(self._payload(request, stream=True))) as chunks:
+            async for data in chunks:
+                kind = string_value(data.get("type"), nonempty=True)
+                if kind in {"response.failed", "response.incomplete"}:
+                    response = object_value(data.get("response"))
+                    self._check_response({**response, "status": kind.split(".")[1]})
+                elif kind in {"response.output_text.delta", "response.refusal.delta"}:
+                    yield ModelEventType.text_delta, {"text": string_value(data.get("delta"))}
+                elif kind in {"response.reasoning_summary_text.delta", "response.reasoning_text.delta"}:
+                    yield ModelEventType.thinking_delta, {"text": string_value(data.get("delta"))}
+                elif kind in {"response.output_item.added", "response.output_item.done"}:
+                    item = object_value(data.get("item"))
+                    if item.get("type") != "function_call":
+                        continue
+                    index = token_count(data.get("output_index"))
+                    call_id = string_value(item.get("call_id"), nonempty=True)
+                    name = string_value(item.get("name"), nonempty=True)
+                    if index not in calls:
+                        calls[index] = {"id": call_id, "name": name, "arguments": "", "ended": False,
+                                        "item_id": item.get("id")}
+                        yield ModelEventType.tool_call_start, {"tool_call_id": call_id, "name": name}
+                    elif calls[index]["id"] != call_id or calls[index]["name"] != name:
+                        raise invalid_response()
+                    if kind == "response.output_item.done":
+                        for event in finish_call(index, item.get("arguments")):
+                            yield event
+                    elif item.get("arguments"):
+                        arguments = string_value(item["arguments"])
+                        calls[index]["arguments"] += arguments
+                        yield ModelEventType.tool_call_delta, {"tool_call_id": call_id, "arguments_delta": arguments}
+                elif kind in {"response.function_call_arguments.delta", "response.function_call_arguments.done"}:
+                    index = token_count(data.get("output_index"))
+                    call = calls.get(index)
+                    if call is None or (data.get("item_id") and call["item_id"] != data["item_id"]):
+                        raise invalid_response()
+                    if kind.endswith(".done"):
+                        for event in finish_call(index, data.get("arguments")):
+                            yield event
+                    else:
+                        if call["ended"]:
+                            raise invalid_response()
+                        fragment = string_value(data.get("delta"))
+                        call["arguments"] += fragment
+                        yield ModelEventType.tool_call_delta, {"tool_call_id": call["id"], "arguments_delta": fragment}
+                elif kind == "response.completed":
+                    response = object_value(data.get("response"))
+                    self._check_response(response)
+                    if any(not call["ended"] for call in calls.values()):
+                        raise truncated_stream()
+                    if response.get("usage") is not None:
+                        yield ModelEventType.usage, usage.update(response["usage"])
+                    return
+                elif kind == "[DONE]":
+                    raise truncated_stream()
+                elif kind in {"response.created", "response.in_progress"}:
+                    response = object_value(data.get("response"))
+                    check_error(response)
+                    if response.get("usage") is not None:
+                        yield ModelEventType.usage, usage.update(response["usage"])
+        raise truncated_stream()

backend/app/providers/registry.py

@@ -1,5 +1,10 @@
 from dataclasses import dataclass
 from time import perf_counter
+from pathlib import Path
+
+from app.config import get_settings
+from app.database.db import connect
+from app.errors import ApiError
 
 from app.contracts import ModelInfo, ProviderConfig, ProviderTestResponse
 from app.providers.base import ModelProvider
@@ -16,20 +21,64 @@ class RegisteredProvider:
 
 
 class ProviderRegistry:
-    def __init__(self) -> None:
+    def __init__(self, factory=None) -> None:
         self._providers: dict[str, RegisteredProvider] = {}
+        self._factory = factory
+        self._loaded_path: Path | None = None
+
+    def _restore(self) -> None:
+        if self._factory is None or self._loaded_path == get_settings().db_path:
+            return
+        conn = connect()
+        try:
+            conn.execute("CREATE TABLE IF NOT EXISTS provider_configs (provider_id TEXT PRIMARY KEY, config_json TEXT NOT NULL)")
+            restored = {}
+            for row in conn.execute("SELECT config_json FROM provider_configs"):
+                config = ProviderConfig.model_validate_json(row["config_json"])
+                if config.provider_id == "mock":
+                    raise ValueError("reserved provider")
+                restored[config.provider_id] = RegisteredProvider(config, self._factory.build(config))
+            if "mock" in self._providers:
+                restored["mock"] = self._providers["mock"]
+            self._providers = restored
+            self._loaded_path = get_settings().db_path
+        except (ValueError, TypeError) as exc:
+            raise ApiError(500, "PROVIDER_STORAGE_INVALID", "Saved provider configuration could not be loaded.") from exc
+        finally:
+            conn.close()
+
+    def _save(self, config: ProviderConfig) -> None:
+        if self._factory is None or config.provider_id == "mock":
+            return
+        conn = connect()
+        try:
+            conn.execute("INSERT OR REPLACE INTO provider_configs VALUES (?, ?)", (config.provider_id, config.model_dump_json()))
+        finally:
+            conn.close()
 
     def register(self, config: ProviderConfig, adapter: ModelProvider) -> None:
+        if config.provider_id != "mock":
+            self._restore()
         if config.provider_id in self._providers:
             raise ValueError(f"Provider already registered: {config.provider_id}")
+        self._save(config)
         self._providers[config.provider_id] = RegisteredProvider(config=config, adapter=adapter)
 
     def unregister(self, provider_id: str) -> None:
+        self._restore()
+        if self._factory is not None:
+            conn = connect()
+            try:
+                conn.execute("DELETE FROM provider_configs WHERE provider_id = ?", (provider_id,))
+            finally:
+                conn.close()
         self._providers.pop(provider_id, None)
 
     def replace(self, config: ProviderConfig, adapter: ModelProvider) -> None:
+        self._restore()
         if config.provider_id not in self._providers:
             raise ProviderNotFoundError(config.provider_id)
+        self._save(config)
         self._providers[config.provider_id] = RegisteredProvider(config=config, adapter=adapter)
 
     def get(self, provider_id: str) -> RegisteredProvider:
@@ -39,12 +88,14 @@ class ProviderRegistry:
         return provider
 
     def get_any(self, provider_id: str) -> RegisteredProvider:
+        self._restore()
         try:
             return self._providers[provider_id]
         except KeyError as exc:
             raise ProviderNotFoundError(provider_id) from exc
 
     def list_configs(self) -> list[ProviderConfig]:
+        self._restore()
         return [item.config.model_copy(deep=True) for item in self._providers.values()]
 
     async def list_models(self, provider_id: str) -> list[ModelInfo]:

backend/app/providers/routing.py

@@ -0,0 +1,291 @@
+"""Capability routing: validated remote results, then an explicit local backend.
+
+Phase E supplies HTTP adapters and injectable local contracts. Hash embeddings are
+still a development placeholder; speech models are installed in phase F.
+"""
+from __future__ import annotations
+
+import hashlib
+import json
+import math
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Protocol
+
+import httpx
+
+from app.contracts import (
+    EmbeddingResult, LocalBackendStatus, ModelBinding, ModelRoutingConfig,
+    ModelRoutingResponse, ProviderType, SpeakerMatchResult,
+)
+from app.database.db import connect, transaction
+from app.errors import ApiError
+from app.providers.base import ProviderError
+from app.providers.credentials import CredentialResolver, CredentialStoreError
+from app.providers.registry import ProviderNotFoundError, ProviderRegistry
+from app.retrieval.embedding import EmbeddingProvider, HashEmbeddingProvider
+from app.retrieval.provenance import record_embedding
+
+CAPABILITIES = ("embedding", "transcription", "speaker_matching")
+HTTP_TYPES = {ProviderType.openai_chat, ProviderType.openai_compatible}
+MAX_MEDIA_BYTES = 25 * 1024 * 1024
+MAX_RESPONSE_BYTES = 16 * 1024 * 1024
+
+
+class LocalSpeechBackend(Protocol):
+    available: bool
+
+    async def transcribe(self, source: Path, language: str | None) -> str: ...
+
+    async def match(self, source: Path, reference: Path) -> float: ...
+
+
+class PendingSpeechBackend:
+    available = False
+
+    async def transcribe(self, source: Path, language: str | None) -> str:
+        raise ProviderError("LOCAL_MODEL_NOT_INSTALLED", "本地音频转写模型尚未安装，将在阶段 F 接入。")
+
+    async def match(self, source: Path, reference: Path) -> float:
+        raise ProviderError("LOCAL_MODEL_NOT_INSTALLED", "本地声纹模型尚未安装，将在阶段 F 接入。")
+
+
+@dataclass(frozen=True)
+class RoutedTranscript:
+    text: str
+    source: str
+    fallback_reason: str | None = None
+
+
+def invalid_response() -> ProviderError:
+    return ProviderError("PROVIDER_INVALID_RESPONSE", "Model API returned an invalid result.")
+
+
+def finite_number(value: object) -> bool:
+    if type(value) not in (int, float):
+        return False
+    try:
+        return math.isfinite(value)
+    except (OverflowError, ValueError):
+        return False
+
+
+class ModelRoutingService:
+    def __init__(self, providers: ProviderRegistry, credentials: CredentialResolver, *,
+                 local_embedding: EmbeddingProvider | None = None,
+                 local_speech: LocalSpeechBackend | None = None,
+                 transport: httpx.AsyncBaseTransport | None = None) -> None:
+        self.providers = providers
+        self.credentials = credentials
+        self.local_embedding = local_embedding or HashEmbeddingProvider()
+        self.local_speech = local_speech or PendingSpeechBackend()
+        self.transport = transport
+
+    @staticmethod
+    def _connection():
+        conn = connect()
+        conn.execute("CREATE TABLE IF NOT EXISTS model_routing (id INTEGER PRIMARY KEY CHECK(id=1), config_json TEXT NOT NULL)")
+        return conn
+
+    def configuration(self) -> ModelRoutingConfig:
+        conn = self._connection()
+        try:
+            row = conn.execute("SELECT config_json FROM model_routing WHERE id=1").fetchone()
+            return ModelRoutingConfig.model_validate_json(row[0]) if row else ModelRoutingConfig()
+        except ValueError as exc:
+            raise ApiError(500, "MODEL_ROUTING_STORAGE_INVALID", "Saved model routing could not be loaded.") from exc
+        finally:
+            conn.close()
+
+    def describe(self) -> ModelRoutingResponse:
+        return ModelRoutingResponse(config=self.configuration(), local_backends=[
+            LocalBackendStatus(capability="embedding", status="placeholder" if isinstance(self.local_embedding, HashEmbeddingProvider) else "ready",
+                               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。"),
+            *[LocalBackendStatus(capability=capability, status="ready" if self.local_speech.available else "not_installed",
+                                 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。")
+              for capability in ("transcription", "speaker_matching")],
+        ])
+
+    def update(self, config: ModelRoutingConfig) -> ModelRoutingResponse:
+        for capability in CAPABILITIES:
+            binding = getattr(config, capability)
+            if binding:
+                try:
+                    provider = self.providers.get_any(binding.provider_id).config
+                except ProviderNotFoundError as exc:
+                    raise ApiError(422, "PROVIDER_NOT_FOUND", "请选择已保存的提供商。") from exc
+                if provider.provider_type not in HTTP_TYPES:
+                    raise ApiError(422, "MODEL_ROUTING_PROTOCOL_UNSUPPORTED", "该能力当前需要 OpenAI Compatible HTTP 接口。")
+        conn = self._connection()
+        try:
+            with transaction(conn):
+                row = conn.execute("SELECT config_json FROM model_routing WHERE id=1").fetchone()
+                current = ModelRoutingConfig.model_validate_json(row[0]) if row else ModelRoutingConfig()
+                if current.version != config.version:
+                    raise ApiError(409, "MODEL_ROUTING_VERSION_CONFLICT", "配置已更新，请重新加载后再保存。")
+                saved = config.model_copy(update={"version": config.version + 1})
+                conn.execute("INSERT OR REPLACE INTO model_routing VALUES (1, ?)", (saved.model_dump_json(),))
+        finally:
+            conn.close()
+        return self.describe()
+
+    def uses_provider(self, provider_id: str) -> bool:
+        config = self.configuration()
+        return any(binding and binding.provider_id == provider_id for binding in
+                   (getattr(config, name) for name in CAPABILITIES))
+
+    def _remote(self, binding: ModelBinding) -> tuple[str, dict[str, str]]:
+        try:
+            provider = self.providers.get(binding.provider_id).config
+        except ProviderNotFoundError as exc:
+            raise ProviderError("PROVIDER_UNAVAILABLE", "Configured provider is unavailable.") from exc
+        if provider.provider_type not in HTTP_TYPES:
+            raise ProviderError("PROVIDER_CAPABILITY_UNSUPPORTED", "Provider does not support this HTTP capability.")
+        try:
+            key = self.credentials.resolve(provider.credential_id)
+        except CredentialStoreError as exc:
+            raise ProviderError("PROVIDER_CREDENTIAL_UNAVAILABLE", "Provider credential is unavailable.") from exc
+        if provider.credential_id and not key:
+            raise ProviderError("PROVIDER_CREDENTIAL_MISSING", "Provider credential is not configured.")
+        url = (provider.base_url or "https://api.openai.com/v1").rstrip("/") + binding.endpoint
+        return url, {"Authorization": f"Bearer {key}"} if key else {}
+
+    async def _request(self, binding: ModelBinding, *, remote: tuple[str, dict[str, str]] | None = None, **kwargs) -> tuple[dict, str]:
+        url, headers = remote or self._remote(binding)
+        try:
+            async with httpx.AsyncClient(timeout=30, transport=self.transport) as client:
+                async with client.stream("POST", url, headers=headers, **kwargs) as response:
+                    response.raise_for_status()
+                    body = bytearray()
+                    async for chunk in response.aiter_bytes():
+                        body.extend(chunk)
+                        if len(body) > MAX_RESPONSE_BYTES:
+                            raise invalid_response()
+                    data = json.loads(body)
+        except httpx.TimeoutException as exc:
+            raise ProviderError("PROVIDER_TIMEOUT", "Model API timed out.") from exc
+        except httpx.HTTPStatusError as exc:
+            code = {401: "PROVIDER_AUTH_FAILED", 403: "PROVIDER_AUTH_FAILED", 404: "MODEL_NOT_FOUND", 429: "PROVIDER_RATE_LIMITED"}.get(exc.response.status_code, "PROVIDER_UNAVAILABLE")
+            raise ProviderError(code, f"Model API returned HTTP {exc.response.status_code}.") from exc
+        except (httpx.HTTPError, httpx.InvalidURL) as exc:
+            raise ProviderError("PROVIDER_UNAVAILABLE", "Model API is unavailable.") from exc
+        except (ValueError, UnicodeError) as exc:
+            raise invalid_response() from exc
+        if not isinstance(data, dict) or data.get("error"):
+            raise invalid_response()
+        return data, url
+
+    async def embed(self, texts: list[str]) -> EmbeddingResult:
+        config = self.configuration()
+        binding = config.embedding
+        record_embedding(route_version=config.version,
+                         requested_route=binding.model_dump() if binding else None)
+        reason = None
+        if binding and texts:
+            try:
+                vectors = []
+                dimension = binding.dimensions
+                # Freeze the origin across batches, even if the user edits the provider.
+                remote = self._remote(binding)
+                for start in range(0, len(texts), 32):
+                    batch = texts[start:start + 32]
+                    payload = {"model": binding.model, "input": batch, "encoding_format": "float"}
+                    if binding.dimensions is not None:
+                        payload["dimensions"] = binding.dimensions
+                    data, url = await self._request(binding, remote=remote, json=payload)
+                    items = data.get("data")
+                    if not isinstance(items, list) or len(items) != len(batch):
+                        raise invalid_response()
+                    indexed = {}
+                    for item in items:
+                        if not isinstance(item, dict):
+                            raise invalid_response()
+                        index, vector = item.get("index"), item.get("embedding")
+                        if type(index) is not int or index in indexed or not 0 <= index < len(batch):
+                            raise invalid_response()
+                        if not isinstance(vector, list) or not 1 <= len(vector) <= 16384:
+                            raise invalid_response()
+                        if any(not finite_number(value) for value in vector):
+                            raise invalid_response()
+                        dimension = dimension or len(vector)
+                        norm = math.hypot(*vector)
+                        if len(vector) != dimension or not norm or not math.isfinite(norm):
+                            raise invalid_response()
+                        indexed[index] = [value / norm for value in vector]
+                    vectors.extend(indexed[index] for index in range(len(batch)))
+                identity = json.dumps([url, binding.model, dimension], separators=(",", ":"))
+                return EmbeddingResult(vectors=vectors, source="api", dimensions=dimension,
+                                       model_id="api-" + hashlib.sha256(identity.encode()).hexdigest())
+            except ProviderError as exc:
+                reason = exc.code
+        vectors = await self.local_embedding.embed_documents(texts)
+        return EmbeddingResult(vectors=vectors, source="local", model_id=self.local_embedding.model_id,
+                               dimensions=self.local_embedding.dim, fallback_reason=reason)
+
+    @staticmethod
+    def _media_file(path: Path):
+        try:
+            handle = path.open("rb")
+        except OSError as exc:
+            raise ApiError(404, "ATTACHMENT_NOT_FOUND", "Audio attachment was not found.") from exc
+        import os
+        if not 0 < os.fstat(handle.fileno()).st_size <= MAX_MEDIA_BYTES:
+            handle.close()
+            raise ApiError(413, "ATTACHMENT_TOO_LARGE", "Audio attachment must be between 1 byte and 25 MiB.")
+        return handle
+
+    async def transcribe(self, source: Path, language: str | None) -> RoutedTranscript:
+        binding = self.configuration().transcription
+        if binding is None:
+            with self._media_file(source):
+                pass
+        reason = None
+        if binding:
+            try:
+                fields = {"model": binding.model}
+                if language:
+                    fields["language"] = language
+                with self._media_file(source) as handle:
+                    data, _ = await self._request(binding, data=fields,
+                        files={"file": (source.name, handle, "application/octet-stream")})
+                text = data.get("text")
+                if not isinstance(text, str) or not text.strip():
+                    raise invalid_response()
+                return RoutedTranscript(text=text, source="api")
+            except ProviderError as exc:
+                reason = exc.code
+        try:
+            text = await self.local_speech.transcribe(source, language)
+            if not isinstance(text, str) or not text.strip():
+                raise ProviderError("LOCAL_MODEL_INVALID_RESPONSE", "Local transcription was empty.")
+            return RoutedTranscript(text=text, source="local", fallback_reason=reason)
+        except ProviderError as exc:
+            raise ApiError(503, exc.code, exc.message, {"fallback_reason": reason}) from exc
+
+    async def match_speakers(self, source: Path, reference: Path) -> SpeakerMatchResult:
+        binding = self.configuration().speaker_matching
+        if binding is None:
+            with self._media_file(source), self._media_file(reference):
+                pass
+        reason = None
+        if binding:
+            try:
+                # Explicit application contract, not an OpenAI-standard endpoint.
+                with self._media_file(source) as audio, self._media_file(reference) as sample:
+                    data, _ = await self._request(binding, data={"model": binding.model}, files={
+                        "file": (source.name, audio, "application/octet-stream"),
+                        "reference_file": (reference.name, sample, "application/octet-stream"),
+                    })
+                score = data.get("score")
+                if not finite_number(score) or not 0 <= score <= 1:
+                    raise invalid_response()
+                return SpeakerMatchResult(score=score, source="api")
+            except ProviderError as exc:
+                reason = exc.code
+        try:
+            score = await self.local_speech.match(source, reference)
+            if not finite_number(score) or not 0 <= score <= 1:
+                raise ProviderError("LOCAL_MODEL_INVALID_RESPONSE", "Local speaker matching was invalid.")
+            return SpeakerMatchResult(score=score, source="local", fallback_reason=reason)
+        except ProviderError as exc:
+            raise ApiError(503, exc.code, exc.message, {"fallback_reason": reason}) from exc

backend/app/providers/tool_names.py

@@ -0,0 +1,47 @@
+"""Keep internal namespaced tools compatible with providers' 64-character names."""
+import hashlib
+import re
+from functools import wraps
+
+from app.contracts import MessageRole, ModelRequest
+
+
+def prepare_tool_names(request: ModelRequest) -> tuple[ModelRequest, dict[str, str]]:
+    names = {tool.name for tool in request.tools}
+    for message in request.messages:
+        names.update(call.name for call in message.tool_calls)
+        if message.role == MessageRole.tool and message.name:
+            names.add(message.name)
+    mapping = {name: name for name in names if re.fullmatch(r"[A-Za-z0-9_-]{1,64}", name)}
+    used = set(mapping)
+    for name in sorted(names - mapping.keys()):
+        salt = 0
+        while True:
+            alias = "tool_" + hashlib.sha256(f"{name}:{salt}".encode()).hexdigest()[:56]
+            if alias not in used:
+                break
+            salt += 1
+        mapping[name] = alias
+        used.add(alias)
+    if all(name == alias for name, alias in mapping.items()):
+        return request, {}
+    wire = request.model_copy(deep=True)
+    for tool in wire.tools:
+        tool.name = mapping[tool.name]
+    for message in wire.messages:
+        for call in message.tool_calls:
+            call.name = mapping[call.name]
+        if message.role == MessageRole.tool and message.name:
+            message.name = mapping[message.name]
+    return wire, {alias: name for name, alias in mapping.items()}
+
+
+def mapped_tool_names(complete):
+    @wraps(complete)
+    async def wrapped(self, request: ModelRequest):
+        wire, originals = prepare_tool_names(request)
+        turn = await complete(self, wire)
+        for call in turn.tool_calls:
+            call.name = originals.get(call.name, call.name)
+        return turn
+    return wrapped

backend/app/repository.py

@@ -460,16 +460,18 @@ def get_index_meta() -> dict[str, str]:
         conn.close()
 
 
-def clear_all() -> None:
-    """清空元数据、Block 与 FTS5（重建索引用，向量由 VectorStore.clear 处理）。"""
-    conn = connect()
+def clear_all(*, conn: sqlite3.Connection | None = None) -> None:
+    """Clear rebuildable metadata using the caller's transaction when provided."""
+    owns = conn is None
+    conn = conn or connect()
     try:
-        with transaction(conn):
+        with transaction(conn) if owns else nullcontext():
             conn.execute("DELETE FROM blocks_fts")
             conn.execute("DELETE FROM blocks")
             conn.execute("DELETE FROM notes")
     finally:
-        conn.close()
+        if owns:
+            conn.close()
 
 
 def stats() -> dict[str, int]:

backend/app/retrieval/engine.py

@@ -22,6 +22,8 @@ from app.repository import BlockHit
 from app.retrieval.embedding import EmbeddingProvider, HashEmbeddingProvider
 from app.retrieval.hybrid import normalize_scores, rrf_fuse
 from app.retrieval.reranker import LexicalReranker, RankedCandidate, RerankerProvider
+from app.retrieval import routed_vectors
+from app.retrieval.provenance import record_embedding
 from app.retrieval.vectorstore import SqliteVecStore, VectorStore
 from app.textutils import make_snippet, match_query
 
@@ -39,10 +41,15 @@ class RetrievalEngine:
         embedding: EmbeddingProvider,
         reranker: RerankerProvider,
         vector_store: VectorStore,
+        *,
+        route_embeddings: bool = False,
     ) -> None:
         self.embedding = embedding
         self.reranker = reranker
         self.vector_store = vector_store
+        # Only the production instance opts in. Replaced test dependencies must
+        # remain authoritative, including monkeypatches on the singleton.
+        self._routed_defaults = (embedding, vector_store) if route_embeddings else None
 
     async def search(self, request: SearchRequest) -> SearchResponse:
         if request.mode == SearchMode.fts:
@@ -74,8 +81,19 @@ class RetrievalEngine:
                 fts_scores = {h.block_id: -h.bm25 for h in fts_hits}
 
         if request.mode in (SearchMode.vector, SearchMode.hybrid):
-            query_vec = await self.embedding.embed_query(request.query)
-            vec_hits = await self.vector_store.search(query_vec, top_k=recall)
+            record_embedding(source="unavailable")
+            vec_hits = None
+            if (
+                self._routed_defaults is not None
+                and self.embedding is self._routed_defaults[0]
+                and self.vector_store is self._routed_defaults[1]
+            ):
+                vec_hits = await routed_vectors.search_remote(request.query, top_k=recall)
+            if vec_hits is None:
+                query_vec = await self.embedding.embed_query(request.query)
+                vec_hits = await self.vector_store.search(query_vec, top_k=recall)
+                record_embedding(source="local", model_id=self.embedding.model_id,
+                                 dimensions=self.embedding.dim, version=self.embedding.version)
             vec_ranked = [v.id for v in vec_hits]
             vec_scores = {v.id: v.score for v in vec_hits}
 
@@ -268,4 +286,6 @@ def _utc(dt: datetime) -> datetime:
 
 
 # 默认引擎实例：轻量实现跑通链路，后续可替换真实模型实现
-engine = RetrievalEngine(HashEmbeddingProvider(), LexicalReranker(), SqliteVecStore())
+engine = RetrievalEngine(
+    HashEmbeddingProvider(), LexicalReranker(), SqliteVecStore(), route_embeddings=True,
+)

backend/app/retrieval/provenance.py

@@ -0,0 +1,21 @@
+"""Task-local observations of the embedding path actually used by a search."""
+from contextlib import contextmanager
+from contextvars import ContextVar
+
+_observation: ContextVar[dict | None] = ContextVar("embedding_observation", default=None)
+
+
+@contextmanager
+def capture_embedding():
+    result = {"source": "not_used"}
+    token = _observation.set(result)
+    try:
+        yield result
+    finally:
+        _observation.reset(token)
+
+
+def record_embedding(**fields) -> None:
+    result = _observation.get()
+    if result is not None:
+        result.update(fields)

backend/app/retrieval/routed_vectors.py

@@ -0,0 +1,201 @@
+"""Optional API embeddings, isolated from the stable hash/sqlite-vec index.
+
+The runtime's model_id is the authoritative space ID (including provider URL,
+endpoint, model and dimensions); equal dimensions alone never imply compatibility.
+This phase uses a lazy, rebuildable SQLite side table instead of a schema migration.
+Search scans only current blocks in one database snapshot and requires complete
+coverage. Cosine ranking costs O(blocks * dimensions) with an O(top_k) heap; this
+small-vault implementation should become a per-space ANN index at larger scale.
+"""
+
+from __future__ import annotations
+
+import heapq
+import json
+import logging
+import math
+import sqlite3
+from dataclasses import dataclass
+from typing import Protocol
+
+from app.database.db import connect, transaction
+from app.retrieval.vectorstore import VectorHit
+from app.retrieval.provenance import record_embedding
+
+logger = logging.getLogger(__name__)
+
+
+class EmbeddingResult(Protocol):
+    vectors: list[list[float]]
+    source: str
+    model_id: str
+    dimensions: int
+    fallback_reason: str | None
+
+
+class EmbeddingRuntime(Protocol):
+    async def embed(self, texts: list[str]) -> EmbeddingResult: ...
+
+
+@dataclass(frozen=True)
+class RemoteEmbeddings:
+    space_id: str
+    dimensions: int
+    vectors: list[list[float]]
+
+
+def get_model_routing() -> EmbeddingRuntime | None:
+    """Lazy integration hook; tests can inject a runtime without any network I/O."""
+    from app.container import container
+
+    return getattr(container, "model_routing", None)
+
+
+def _unit_vector(vector: list[float], dimensions: int) -> list[float]:
+    if len(vector) != dimensions:
+        raise ValueError("embedding dimension mismatch")
+    if any(isinstance(value, bool) or not isinstance(value, (int, float)) for value in vector):
+        raise ValueError("embedding must be numeric")
+    if not all(math.isfinite(value) for value in vector):
+        raise ValueError("embedding must be finite")
+    scale = max(abs(value) for value in vector)
+    if scale == 0:
+        raise ValueError("embedding must be nonzero")
+    # Scaling first avoids overflow/underflow for finite but extreme API values.
+    scaled = [value / scale for value in vector]
+    norm = math.sqrt(math.fsum(value * value for value in scaled))
+    return [value / norm for value in scaled]
+
+
+async def embed_remote(texts: list[str]) -> RemoteEmbeddings | None:
+    """Return validated API vectors, or None to use the caller's local baseline.
+
+    Do not use the runtime's local result: the caller may have injected its own
+    embedding/store pair. Exception deliberately excludes cancellation.
+    """
+    if not texts:
+        return None
+    try:
+        runtime = get_model_routing()
+        if runtime is None:
+            return None
+        result = await runtime.embed(texts)
+        if result.source != "api":
+            record_embedding(fallback_reason=result.fallback_reason)
+            return None
+        if not isinstance(result.model_id, str) or not result.model_id or result.model_id == "hash-v1":
+            raise ValueError("API embedding needs a distinct space ID")
+        if type(result.dimensions) is not int or result.dimensions <= 0:
+            raise ValueError("invalid embedding dimensions")
+        if len(result.vectors) != len(texts):
+            raise ValueError("embedding count mismatch")
+        return RemoteEmbeddings(
+            space_id=result.model_id,
+            dimensions=result.dimensions,
+            vectors=[_unit_vector(vector, result.dimensions) for vector in result.vectors],
+        )
+    except Exception as exc:
+        # Avoid logging provider exceptions containing credentials or note text.
+        record_embedding(fallback_reason="REMOTE_EMBEDDING_UNAVAILABLE")
+        logger.warning("Remote embedding unavailable (%s); using local index", type(exc).__name__)
+        return None
+
+
+def _ensure_table(conn: sqlite3.Connection) -> None:
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS routed_block_vectors (
+            space_id TEXT NOT NULL,
+            block_id TEXT NOT NULL REFERENCES blocks(block_id) ON DELETE CASCADE,
+            dimensions INTEGER NOT NULL CHECK (dimensions > 0),
+            vector TEXT NOT NULL,
+            PRIMARY KEY (space_id, block_id)
+        )
+    """)
+    conn.execute("""
+        CREATE INDEX IF NOT EXISTS routed_block_vectors_block_id
+        ON routed_block_vectors(block_id)
+    """)
+
+
+def store_remote(
+    conn: sqlite3.Connection, block_ids: list[str], batch: RemoteEmbeddings | None,
+) -> None:
+    """Best-effort side-index write inside the caller's metadata transaction.
+
+    A savepoint prevents partial remote batches and isolates storage failures from
+    note saving. Replacing/deleting blocks cascades all old spaces automatically.
+    """
+    if batch is None:
+        return
+    try:
+        conn.execute("SAVEPOINT routed_vectors_write")
+        try:
+            if len(block_ids) != len(batch.vectors):
+                raise ValueError("block/vector count mismatch")
+            _ensure_table(conn)
+            conn.executemany(
+                """INSERT INTO routed_block_vectors (space_id, block_id, dimensions, vector)
+                   VALUES (?, ?, ?, ?)
+                   ON CONFLICT (space_id, block_id) DO UPDATE SET
+                       dimensions = excluded.dimensions, vector = excluded.vector""",
+                [
+                    (batch.space_id, block_id, batch.dimensions, json.dumps(vector, allow_nan=False))
+                    for block_id, vector in zip(block_ids, batch.vectors)
+                ],
+            )
+        except BaseException:
+            conn.execute("ROLLBACK TO routed_vectors_write")
+            raise
+        finally:
+            conn.execute("RELEASE routed_vectors_write")
+    except Exception as exc:
+        logger.warning("Remote vector storage unavailable (%s); local index retained", type(exc).__name__)
+
+
+async def search_remote(query: str, *, top_k: int) -> list[VectorHit] | None:
+    """None means fallback, including any missing/invalid current-block vector.
+
+    Read coverage and vectors together so concurrent note updates cannot produce
+    an apparently complete subset. Never fill missing remote hits with local hits.
+    """
+    batch = await embed_remote([query])
+    if batch is None:
+        return None
+    record_embedding(attempted_space={"model_id": batch.space_id, "dimensions": batch.dimensions})
+    try:
+        conn = connect()
+        try:
+            with transaction(conn):
+                exists = conn.execute(
+                    "SELECT 1 FROM sqlite_master WHERE type = 'table' AND name = 'routed_block_vectors'"
+                ).fetchone()
+                if exists is None:
+                    record_embedding(fallback_reason="REMOTE_INDEX_MISSING")
+                    return None
+                rows = conn.execute(
+                    """SELECT b.block_id, r.vector
+                       FROM blocks AS b
+                       LEFT JOIN routed_block_vectors AS r
+                         ON r.block_id = b.block_id AND r.space_id = ? AND r.dimensions = ?
+                       ORDER BY b.block_id""",
+                    (batch.space_id, batch.dimensions),
+                )
+
+                def hits():
+                    for row in rows:
+                        if row["vector"] is None:
+                            raise ValueError("remote space has incomplete block coverage")
+                        vector = _unit_vector(json.loads(row["vector"]), batch.dimensions)
+                        score = math.fsum(a * b for a, b in zip(batch.vectors[0], vector))
+                        yield VectorHit(id=row["block_id"], score=max(0.0, min(1.0, score)))
+
+                result = heapq.nlargest(top_k, hits(), key=lambda hit: hit.score)
+                record_embedding(source="api", model_id=batch.space_id,
+                                 dimensions=batch.dimensions, fallback_reason=None)
+                return result
+        finally:
+            conn.close()
+    except Exception as exc:
+        record_embedding(fallback_reason="REMOTE_INDEX_UNAVAILABLE")
+        logger.debug("Remote vector search unavailable (%s); using local index", type(exc).__name__)
+        return None

backend/app/retrieval/vectorstore.py

@@ -86,13 +86,15 @@ class SqliteVecStore:
         finally:
             conn.close()
 
-    async def clear(self) -> None:
-        conn = connect()
+    async def clear(self, *, conn: sqlite3.Connection | None = None) -> None:
+        owns = conn is None
+        conn = conn or connect()
         try:
-            with transaction(conn):
+            with transaction(conn) if owns else nullcontext():
                 conn.execute("DELETE FROM vec_blocks")
         finally:
-            conn.close()
+            if owns:
+                conn.close()
 
     async def count(self) -> int:
         conn = connect()

backend/app/routes.py

@@ -1,5 +1,6 @@
 import asyncio
 from collections.abc import AsyncIterator
+from contextlib import aclosing
 from datetime import datetime, timezone
 from uuid import uuid4
 
@@ -41,6 +42,12 @@ from app.contracts import (
     McpToolSummaryListResponse,
     ModelEvent,
     ModelEventType,
+    EmbeddingRequest,
+    EmbeddingResult,
+    ModelRoutingConfig,
+    ModelRoutingResponse,
+    SpeakerMatchRequest,
+    SpeakerMatchResult,
     Note,
     NoteCreateRequest,
     NoteListResponse,
@@ -108,6 +115,7 @@ from app.services import (
     transcription_service,
     workspace_service,
 )
+from app.services.attachment_service import attachment_path
 
 router = APIRouter(prefix="/api")
 
@@ -306,17 +314,22 @@ async def chat(request: ChatRequest) -> StreamingResponse:
     provider = provider_or_404(request.provider_id)
 
     async def stream() -> AsyncIterator[str]:
+        sequence = 0
         try:
-            async for event in provider.adapter.stream(request):
-                yield as_sse(event.event.value, event.model_dump_json())
-        except Exception as exc:
+            async with aclosing(provider.adapter.stream(request)) as events:
+                async for event in events:
+                    sequence = event.sequence + 1
+                    yield as_sse(event.event.value, event.model_dump_json())
+        except Exception:
             error = ModelEvent(
                 event=ModelEventType.error,
-                data={"code": "PROVIDER_ERROR", "message": str(exc)},
+                sequence=sequence,
+                data={"code": "PROVIDER_ERROR", "message": "Provider could not complete the request."},
                 timestamp=utc_now(),
             )
             done = ModelEvent(
-                event=ModelEventType.done, sequence=1, timestamp=utc_now()
+                event=ModelEventType.done, sequence=sequence + 1,
+                data={"status": "failed"}, timestamp=utc_now()
             )
             yield as_sse(error.event.value, error.model_dump_json())
             yield as_sse(done.event.value, done.model_dump_json())
@@ -923,13 +936,13 @@ async def update_provider(
             409, "BUILTIN_PROVIDER_IMMUTABLE", "Mock provider cannot be modified."
         )
     fields = request.model_fields_set
-    if ("name" in fields and request.name is None) or (
+    if ("provider_type" in fields and request.provider_type is None) or ("name" in fields and request.name is None) or (
         "enabled" in fields and request.enabled is None
     ):
         raise ApiError(
             422,
             "VALIDATION_ERROR",
-            "name and enabled cannot be null when explicitly provided.",
+            "provider_type, name and enabled cannot be null when explicitly provided.",
         )
     updates = {name: getattr(request, name) for name in fields}
     if "credential_id" in fields:
@@ -937,7 +950,11 @@ async def update_provider(
     config = ProviderConfig.model_validate(
         {**current.model_dump(mode="python"), **updates}
     )
-    adapter = container.provider_factory.build(config)
+    config.capabilities = container.provider_factory.capabilities(config.provider_type)
+    try:
+        adapter = container.provider_factory.build(config)
+    except UnsupportedProviderError as exc:
+        raise ApiError(422, "PROVIDER_TYPE_UNSUPPORTED", "Provider adapter is not supported.") from exc
     container.providers.replace(config, adapter)
     return config
 
@@ -953,6 +970,8 @@ async def delete_provider(provider_id: str) -> OperationResponse:
         raise ApiError(
             409, "BUILTIN_PROVIDER_IMMUTABLE", "Mock provider cannot be deleted."
         )
+    if container.model_routing.uses_provider(provider_id):
+        raise ApiError(409, "PROVIDER_IN_USE", "请先在索引与模型中解除该提供商的模型绑定。")
     container.providers.unregister(provider_id)
     return OperationResponse(status="completed", resource_id=provider_id)
 
@@ -1055,6 +1074,28 @@ async def delete_task(task_id: str) -> OperationResponse:
 
 
 # Media and index
+@router.get("/model-routing", response_model=ModelRoutingResponse, tags=["Providers"])
+async def get_model_routing() -> ModelRoutingResponse:
+    return container.model_routing.describe()
+
+
+@router.put("/model-routing", response_model=ModelRoutingResponse, tags=["Providers"])
+async def update_model_routing(request: ModelRoutingConfig) -> ModelRoutingResponse:
+    return container.model_routing.update(request)
+
+
+@router.post("/models/embeddings", response_model=EmbeddingResult, tags=["Providers"])
+async def create_embeddings(request: EmbeddingRequest) -> EmbeddingResult:
+    return await container.model_routing.embed(request.texts)
+
+
+@router.post("/media/speaker-matches", response_model=SpeakerMatchResult, tags=["Media"])
+async def match_speakers(request: SpeakerMatchRequest) -> SpeakerMatchResult:
+    return await container.model_routing.match_speakers(
+        attachment_path(request.attachment_id), attachment_path(request.reference_attachment_id),
+    )
+
+
 @router.post(
     "/media/transcriptions",
     response_model=TranscriptionJob,
@@ -1062,8 +1103,8 @@ async def delete_task(task_id: str) -> OperationResponse:
     tags=["Media"],
 )
 async def create_transcription(request: TranscriptionRequest) -> TranscriptionJob:
-    return transcription_service.create_transcription(
-        request.attachment_id, request.language
+    return await transcription_service.create_transcription(
+        request.attachment_id, request.language, diarization=request.diarization
     )
 
 

backend/app/services/index_service.py

@@ -6,7 +6,6 @@ MVP 阶段重建是同步的（数据量小），完成后直接返回 completed
 
 from __future__ import annotations
 
-import shutil
 from datetime import datetime, timezone
 from pathlib import Path
 from uuid import uuid4
@@ -16,8 +15,8 @@ from app.config import get_settings
 from app.contracts import IndexJob, IndexRebuildRequest, IndexStatus
 from app.errors import ApiError
 from app.knowledge.parser import parse_note
-from app.services.note_service import index_note
-from app.services import task_service
+from app.services.note_service import index_note, prepare_note_index
+from app.database.db import connect, transaction
 from app.services.coordination import serialized_vault_mutation
 from app.retrieval.vectorstore import SqliteVecStore
 
@@ -74,18 +73,7 @@ async def rebuild(request: IndexRebuildRequest) -> IndexJob:
             {"scope": request.scope, "note_ids": request.note_ids},
         )
 
-    # 先扫描到内存（失败不会清旧索引），再快照旧库用于失败回滚
     docs = _scan_vault()
-    settings = get_settings()
-    database_existed = settings.db_path.exists()
-    task_note_links = task_service.note_links() if database_existed else {}
-    backup_path = (
-        settings.db_path.with_name(f"{settings.db_path.name}.{job_id}.bak")
-        if database_existed
-        else None
-    )
-    if backup_path is not None:
-        shutil.copy2(settings.db_path, backup_path)
 
     _active_job_id = job_id
     _last_error = None
@@ -94,21 +82,34 @@ async def rebuild(request: IndexRebuildRequest) -> IndexJob:
         created_at=datetime.now(timezone.utc),
     ))
     try:
-        repository.clear_all()
-        await vector_store.clear()
+        prepared_notes = []
         for rel, folder, markdown, created, updated in docs:
             parsed = parse_note(
                 markdown=markdown, file_path=rel, folder=folder, tags=None,
                 created_at=created, updated_at=updated,
             )
-            await index_note(parsed)
-        task_service.restore_note_links(task_note_links)
+            prepared_notes.append((parsed, await prepare_note_index(parsed)))
+        # All network/model awaits precede the transaction. The concrete SQLite
+        # methods below complete synchronously despite their async interfaces.
+        conn = connect()
+        try:
+            with transaction(conn):
+                task_note_links = dict(conn.execute(
+                    "SELECT task_id, note_id FROM tasks WHERE note_id IS NOT NULL"
+                ).fetchall())
+                repository.clear_all(conn=conn)
+                await vector_store.clear(conn=conn)
+                for parsed, prepared in prepared_notes:
+                    await index_note(parsed, prepared=prepared, conn=conn)
+                for task_id, note_id in task_note_links.items():
+                    conn.execute(
+                        "UPDATE tasks SET note_id = ? WHERE task_id = ? "
+                        "AND EXISTS (SELECT 1 FROM notes WHERE note_id = ?)",
+                        (note_id, task_id, note_id),
+                    )
+        finally:
+            conn.close()
     except BaseException as exc:
-        # 重建失败：恢复旧索引，避免留下半成品；记录 failed 任务后向上抛
-        if backup_path is not None and backup_path.exists():
-            shutil.copy2(backup_path, settings.db_path)
-        elif not database_existed:
-            settings.db_path.unlink(missing_ok=True)
         _remember_job(IndexJob(
             job_id=job_id, status="failed", scope=request.scope,
             created_at=datetime.now(timezone.utc),
@@ -117,8 +118,6 @@ async def rebuild(request: IndexRebuildRequest) -> IndexJob:
         raise
     finally:
         _active_job_id = None
-        if backup_path is not None:
-            backup_path.unlink(missing_ok=True)
 
     job = IndexJob(job_id=job_id, status="completed", scope=request.scope, created_at=datetime.now(timezone.utc))
     _remember_job(job)

backend/app/services/note_service.py

@@ -6,6 +6,8 @@ Markdown 文件是笔记正文的持久化载体（Vault），SQLite/FTS5/向量
 
 from __future__ import annotations
 
+import sqlite3
+from contextlib import nullcontext
 from datetime import datetime, timezone
 from pathlib import Path
 from uuid import uuid4
@@ -16,6 +18,7 @@ from app.database.db import connect, transaction
 from app.errors import ApiError
 from app.knowledge.parser import ParsedNote, parse_note
 from app.retrieval.embedding import HashEmbeddingProvider
+from app.retrieval import routed_vectors
 from app.retrieval.vectorstore import SqliteVecStore, VectorRecord
 from app.services.coordination import serialized_vault_mutation
 from app.services.vault_paths import (
@@ -71,17 +74,34 @@ def _delete_markdown(rel_path: str) -> None:
         path.unlink()
 
 
-async def index_note(parsed: ParsedNote) -> None:
+PreparedIndex = tuple[list[list[float]], routed_vectors.RemoteEmbeddings | None]
+
+
+async def prepare_note_index(parsed: ParsedNote) -> PreparedIndex:
+    """Compute vectors before opening a write transaction (including API I/O)."""
+    texts = [block.content for block in parsed.blocks]
+    vectors = await embedding.embed_documents(texts)
+    remote = await routed_vectors.embed_remote(texts)
+    return vectors, remote
+
+
+async def index_note(
+    parsed: ParsedNote, *, prepared: PreparedIndex | None = None,
+    conn: sqlite3.Connection | None = None,
+) -> None:
     """把解析结果写入元数据 + FTS5 + 向量（三层可重建索引），单事务保证原子性。
 
     元数据与向量在同一连接、同一事务内提交，避免「新元数据已提交、向量写入失败」的
     半提交状态。替换元数据时拿到旧 block_id：清理已删除/内容变化的旧向量，只为新增
     block 写向量（内容未变的 block 其向量仍有效，无需重复写入）。
     """
-    vectors = await embedding.embed_documents([block.content for block in parsed.blocks])
-    conn = connect()
+    if conn is not None and prepared is None:
+        raise ValueError("Prepare embeddings before supplying a write connection")
+    vectors, remote = prepared if prepared is not None else await prepare_note_index(parsed)
+    owns = conn is None
+    conn = conn or connect()
     try:
-        with transaction(conn):
+        with transaction(conn) if owns else nullcontext():
             old_block_ids = repository.replace_note_metadata(
                 conn=conn,
                 note_id=parsed.note_id,
@@ -105,12 +125,14 @@ async def index_note(parsed: ParsedNote) -> None:
                 if block.block_id in missing_ids
             ]
             await vector_store.upsert(records, conn=conn)
+            routed_vectors.store_remote(conn, [block.block_id for block in parsed.blocks], remote)
             repository.set_index_meta(
                 {"embedding_model": embedding.model_id, "embedding_dim": str(embedding.dim)},
                 conn=conn,
             )
     finally:
-        conn.close()
+        if owns:
+            conn.close()
 
 
 @serialized_vault_mutation

backend/app/services/transcription_service.py

@@ -1,37 +1,59 @@
-"""转写适配层；第一阶段消费文本附件或桌面 Host 预生成的旁路文本。"""
+"""转写作业：API 优先，本地模型回退；保留已有 Host 文本入口。"""
 
 from __future__ import annotations
 
 from collections import OrderedDict
 from datetime import datetime, timezone
-from pathlib import Path
 from uuid import uuid4
 
 from app.contracts import TranscriptionJob
+from app.errors import ApiError
 from app.services.attachment_service import attachment_path
 
 _jobs: OrderedDict[str, TranscriptionJob] = OrderedDict()
 MAX_JOBS = 100
 
 
-def create_transcription(attachment_id: str, language: str | None = None) -> TranscriptionJob:
-    # TODO(ai-core): 第二阶段接入本地 ASR 队列后，保留相同 Job 契约替换此同步降级实现。
-    del language  # 预生成 transcript 暂不需要语言识别。
+async def create_transcription(attachment_id: str, language: str | None = None, *, diarization: bool = False) -> TranscriptionJob:
+    from app.container import container
+
     source = attachment_path(attachment_id)
-    transcript = source if source.suffix.lower() in {".txt", ".md"} else Path(f"{source}.txt")
     job = TranscriptionJob(
         job_id=f"transcription_{uuid4().hex}",
         attachment_id=attachment_id,
-        status="completed" if transcript.is_file() else "failed",
-        text=transcript.read_text(encoding="utf-8") if transcript.is_file() else None,
-        error_code=None if transcript.is_file() else "TRANSCRIPTION_BACKEND_UNAVAILABLE",
-        error_message=(
-            None
-            if transcript.is_file()
-            else "No host-generated transcript is available; local speech models are phase two."
-        ),
+        status="processing",
         created_at=datetime.now(timezone.utc),
     )
+    try:
+        if diarization:
+            # Speaker verification and diarization are different capabilities.
+            raise ApiError(501, "DIARIZATION_NOT_IMPLEMENTED", "说话人分离将在阶段 F 接入，当前不能忽略 diarization 请求。")
+        transcript = source if source.suffix.lower() in {".txt", ".md"} else attachment_path(f"{attachment_id}.txt")
+        # A saved transcript remains an explicit import path, never faked ASR.
+        if transcript.is_file() and (source == transcript or container.model_routing.configuration().transcription is None):
+            with transcript.open("rb") as handle:
+                content = handle.read(1024 * 1024 + 1)
+            if len(content) > 1024 * 1024:
+                raise ApiError(413, "TRANSCRIPT_TOO_LARGE", "Transcript exceeds 1 MiB.")
+            job.text = content.decode("utf-8")
+            if not job.text.strip():
+                raise ApiError(422, "TRANSCRIPT_EMPTY", "Transcript is empty.")
+            job.source = "sidecar"
+        else:
+            result = await container.model_routing.transcribe(source, language)
+            job.text = result.text
+            job.source = result.source
+            job.fallback_reason = result.fallback_reason
+        job.status = "completed"
+    except ApiError as exc:
+        job.status = "failed"
+        job.error_code = exc.code
+        job.error_message = exc.message
+        job.fallback_reason = exc.details.get("fallback_reason")
+    except (OSError, UnicodeError):
+        job.status = "failed"
+        job.error_code = "TRANSCRIPT_UNREADABLE"
+        job.error_message = "Transcript could not be read."
     _jobs[job.job_id] = job
     while len(_jobs) > MAX_JOBS:
         _jobs.popitem(last=False)

backend/tests/test_benchmark.py

@@ -221,8 +221,9 @@ def test_config_snapshot_records_index_and_models() -> None:
 
     snapshot = run.config_snapshot
     assert snapshot["index_meta"] is not None
-    assert snapshot["embedding"]["version"]
-    assert snapshot["embedding"]["dim"]
+    assert snapshot["embedding"]["policy"] == "per_case"
+    assert snapshot["local_embedding"]["version"]
+    assert snapshot["local_embedding"]["dim"]
     assert snapshot["reranker"]["version"]
     assert snapshot["retrieval"]["rrf_k"] == 60
 

backend/tests/test_model_routing.py

@@ -0,0 +1,663 @@
+"""Offline model-routing contracts, HTTP validation, media lifetimes and persistence.
+
+All HTTP uses MockTransport (or the in-process API). Credentials, models and
+attachments are fakes, and conftest redirects all storage to temporary paths.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import hashlib
+import json
+from email import policy
+from email.parser import BytesParser
+from types import SimpleNamespace
+
+import httpx
+import pytest
+from fastapi.testclient import TestClient
+
+from app.contracts import ModelBinding, ModelRoutingConfig, ProviderConfig, ProviderType
+from app.errors import ApiError
+from app.providers import MockProvider
+from app.providers.credentials import CredentialStoreError
+from app.providers.registry import ProviderRegistry
+from app.providers.routing import ModelRoutingService, PendingSpeechBackend
+from app.retrieval.embedding import HashEmbeddingProvider
+
+
+def run(awaitable):
+    return asyncio.run(awaitable)
+
+
+def response(data, status=200):
+    # Raw JSON intentionally permits NaN/Infinity to exercise hostile API output.
+    return httpx.Response(status, content=json.dumps(data).encode(), headers={"content-type": "application/json"})
+
+
+class FakeCredentials:
+    def __init__(self):
+        self.value = "unit-test-placeholder"
+        self.error = None
+        self.calls = []
+
+    def resolve(self, credential_id):
+        self.calls.append(credential_id)
+        if self.error:
+            raise self.error
+        return self.value if credential_id else None
+
+
+class FakeEmbedding:
+    model_id = "fake-local-model"
+    dim = 3
+
+    def __init__(self):
+        self.calls = []
+        self.error = None
+
+    async def embed_documents(self, texts):
+        self.calls.append(list(texts))
+        if self.error:
+            raise self.error
+        return [[0.6, 0.8, 0.0] for _ in texts]
+
+
+class FakeSpeech:
+    available = True
+
+    def __init__(self):
+        self.calls = []
+        self.text = "local transcript"
+        self.score = 0.25
+        self.error = None
+
+    async def transcribe(self, source, language):
+        self.calls.append(("transcribe", source, language))
+        if self.error:
+            raise self.error
+        return self.text
+
+    async def match(self, source, reference):
+        self.calls.append(("match", source, reference))
+        if self.error:
+            raise self.error
+        return self.score
+
+
+@pytest.fixture(autouse=True)
+def no_real_http(monkeypatch):
+    async def reject_async(*args, **kwargs):
+        pytest.fail("Real HTTP transport is forbidden in model-routing tests")
+
+    def reject_sync(*args, **kwargs):
+        pytest.fail("Real HTTP transport is forbidden in model-routing tests")
+
+    monkeypatch.setattr(httpx.AsyncHTTPTransport, "handle_async_request", reject_async)
+    monkeypatch.setattr(httpx.HTTPTransport, "handle_request", reject_sync)
+
+
+@pytest.fixture
+def rig():
+    requests = []
+
+    def unexpected(request):
+        pytest.fail(f"Unexpected model HTTP request: {request.url}")
+
+    state = SimpleNamespace(handler=unexpected)
+
+    async def dispatch(request):
+        requests.append(request)
+        result = state.handler(request)
+        return await result if hasattr(result, "__await__") else result
+
+    providers = ProviderRegistry()
+    config = ProviderConfig(
+        provider_id="test-provider", provider_type=ProviderType.openai_compatible,
+        name="Fake provider", base_url="https://models.invalid/v1/", credential_id="test-credential",
+    )
+    providers.register(config, MockProvider())
+    credentials, embedding, speech = FakeCredentials(), FakeEmbedding(), FakeSpeech()
+    service = ModelRoutingService(
+        providers, credentials, local_embedding=embedding, local_speech=speech,
+        transport=httpx.MockTransport(dispatch),
+    )
+    return SimpleNamespace(
+        service=service, providers=providers, credentials=credentials,
+        embedding=embedding, speech=speech, requests=requests, http=state,
+    )
+
+
+def bind(rig, capability="embedding", **overrides):
+    endpoints = {
+        "embedding": "/embeddings", "transcription": "/audio/transcriptions",
+        "speaker_matching": "/audio/speaker-matches",
+    }
+    binding = ModelBinding(**{
+        "provider_id": "test-provider", "model": "test-model",
+        "endpoint": endpoints[capability], **overrides,
+    })
+    current = rig.service.configuration()
+    return rig.service.update(current.model_copy(update={capability: binding}))
+
+
+def assert_local(rig, result, texts, reason):
+    assert result.source == "local"
+    assert result.model_id == rig.embedding.model_id
+    assert result.dimensions == 3
+    assert result.vectors == [[0.6, 0.8, 0.0] for _ in texts]
+    assert result.fallback_reason == reason
+    assert rig.embedding.calls == [texts]
+
+
+def test_embedding_observation_keeps_request_binding_when_config_changes(rig):
+    from app.retrieval.provenance import capture_embedding
+    initial = bind(rig, model="original-model")
+
+    def handler(request):
+        assert json.loads(request.content)["model"] == "original-model"
+        bind(rig, model="next-model")
+        return response({"data": [{"index": 0, "embedding": [1, 0, 0]}]})
+
+    rig.http.handler = handler
+    with capture_embedding() as observation:
+        result = run(rig.service.embed(["query"]))
+    assert result.source == "api"
+    assert observation["route_version"] == initial.config.version
+    assert observation["requested_route"]["model"] == "original-model"
+    assert observation["requested_route"]["provider_id"] == "test-provider"
+    assert rig.service.configuration().embedding.model == "next-model"
+    assert rig.credentials.value not in json.dumps(observation)
+    assert "credential_id" not in json.dumps(observation)
+
+
+@pytest.fixture
+def audio(tmp_path):
+    source, reference = tmp_path / "audio.wav", tmp_path / "reference.wav"
+    source.write_bytes(b"fake-audio-content")
+    reference.write_bytes(b"fake-reference-content")
+    return source, reference
+
+
+def media_call(rig, capability, audio):
+    if capability == "transcription":
+        return rig.service.transcribe(audio[0], "zh")
+    return rig.service.match_speakers(*audio)
+
+
+def track_media_handles(rig, monkeypatch):
+    handles = []
+    original = rig.service._media_file
+
+    def tracked(path):
+        handle = original(path)
+        handles.append(handle)
+        return handle
+
+    monkeypatch.setattr(rig.service, "_media_file", tracked)
+    return handles
+
+
+def test_absent_binding_uses_hash_without_network(rig):
+    rig.service.local_embedding = HashEmbeddingProvider()
+    texts = ["hello retrieval", "向量检索"]
+    result = run(rig.service.embed(texts))
+    assert result.source == "local"
+    assert result.model_id == "hash-v1"
+    assert result.dimensions == 128
+    assert result.vectors == run(HashEmbeddingProvider().embed_documents(texts))
+    assert result.fallback_reason is None
+    assert rig.requests == rig.credentials.calls == []
+    statuses = {item.capability: item.status for item in rig.service.describe().local_backends}
+    assert statuses == {"embedding": "placeholder", "transcription": "ready", "speaker_matching": "ready"}
+
+
+def test_empty_embedding_input_does_not_call_remote(rig):
+    bind(rig)
+    result = run(rig.service.embed([]))
+    assert result.vectors == [] and result.source == "local"
+    assert rig.requests == []
+
+
+def test_remote_embedding_restores_batch_order_normalizes_and_sends_auth(rig):
+    bind(rig, dimensions=2)
+    texts = [str(index) for index in range(35)]
+
+    def handler(request):
+        assert request.method == "POST"
+        assert str(request.url) == "https://models.invalid/v1/embeddings"
+        assert request.headers["authorization"] == "Bearer unit-test-placeholder"
+        payload = json.loads(request.content)
+        assert payload["model"] == "test-model"
+        assert payload["dimensions"] == 2
+        assert payload["encoding_format"] == "float"
+        return response({"data": [
+            {"index": index, "embedding": [float(int(text) + 1), 1.0]}
+            for index, text in reversed(list(enumerate(payload["input"])))
+        ]})
+
+    rig.http.handler = handler
+    result = run(rig.service.embed(texts))
+    assert result.source == "api" and result.fallback_reason is None
+    assert result.dimensions == 2 and len(result.vectors) == 35
+    for index, vector in enumerate(result.vectors):
+        assert sum(value * value for value in vector) == pytest.approx(1.0)
+        assert vector[0] / vector[1] == pytest.approx(index + 1)
+    assert [json.loads(req.content)["input"] for req in rig.requests] == [texts[:32], texts[32:]]
+    assert rig.embedding.calls == []
+
+
+def test_space_id_is_stable_and_includes_full_url_model_and_inferred_dimensions(rig):
+    dimensions = 2
+
+    def handler(request):
+        assert "dimensions" not in json.loads(request.content)
+        return response({"data": [{"index": 0, "embedding": [1.0] * dimensions}]})
+
+    rig.http.handler = handler
+    bind(rig, model="  trimmed-model  ")
+
+    def check(url, model, dimension):
+        result = run(rig.service.embed(["hello"]))
+        digest = hashlib.sha256(json.dumps([url, model, dimension], separators=(",", ":")).encode()).hexdigest()
+        assert result.model_id == "api-" + digest
+        assert result.source == "api"
+        return result.model_id
+
+    first = check("https://models.invalid/v1/embeddings", "trimmed-model", 2)
+    assert first == check("https://models.invalid/v1/embeddings", "trimmed-model", 2)
+    config = rig.providers.get_any("test-provider").config.model_copy(update={"base_url": "https://models.invalid/v1"})
+    rig.providers.replace(config, MockProvider())
+    assert first == check("https://models.invalid/v1/embeddings", "trimmed-model", 2)
+    bind(rig, model="trimmed-model", endpoint="/custom/embeddings")
+    endpoint_id = check("https://models.invalid/v1/custom/embeddings", "trimmed-model", 2)
+    bind(rig, model="another-model", endpoint="/custom/embeddings")
+    model_id = check("https://models.invalid/v1/custom/embeddings", "another-model", 2)
+    dimensions = 3
+    dim_id = check("https://models.invalid/v1/custom/embeddings", "another-model", 3)
+    config = config.model_copy(update={"base_url": "https://other.invalid/v1"})
+    rig.providers.replace(config, MockProvider())
+    provider_id = check("https://other.invalid/v1/custom/embeddings", "another-model", 3)
+    assert len({first, endpoint_id, model_id, dim_id, provider_id}) == 5
+
+
+@pytest.mark.parametrize("data", [
+    {"data": []},
+    {"data": [{"index": 0, "embedding": [1, 0]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 0, "embedding": [0, 1]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 2, "embedding": [0, 1]}]},
+    {"data": [{"index": False, "embedding": [1, 0]}, {"index": 1, "embedding": [0, 1]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": [0, 1, 0]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": [float("nan"), 1]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": [float("inf"), 1]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": [True, 1]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": [0, 0]}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": []}]},
+    {"data": [{"index": 0, "embedding": [1, 0]}, {"index": 1, "embedding": ["1", 0]}]},
+    {"data": [None, None]},
+    {"error": {"message": "in-band failure"}, "data": []},
+    [],
+], ids=["empty", "count", "duplicate-index", "out-of-range-index", "bool-index", "dimensions", "nan", "infinity", "bool", "zero", "empty-vector", "string", "invalid-items", "in-band-error", "non-object"])
+def test_invalid_remote_embeddings_fall_back_as_a_whole(rig, data):
+    bind(rig)
+    rig.http.handler = lambda request: response(data)
+    texts = ["first", "second"]
+    assert_local(rig, run(rig.service.embed(texts)), texts, "PROVIDER_INVALID_RESPONSE")
+
+
+def test_explicit_embedding_dimension_mismatch_falls_back(rig):
+    bind(rig, dimensions=3)
+    rig.http.handler = lambda request: response({"data": [{"index": 0, "embedding": [1, 0]}]})
+    assert_local(rig, run(rig.service.embed(["text"])), ["text"], "PROVIDER_INVALID_RESPONSE")
+
+
+def test_later_batch_dimension_mismatch_discards_earlier_remote_vectors(rig):
+    bind(rig)
+
+    def handler(request):
+        batch = json.loads(request.content)["input"]
+        dimension = 2 if len(rig.requests) == 1 else 3
+        return response({"data": [{"index": i, "embedding": [1] * dimension} for i in range(len(batch))]})
+
+    rig.http.handler = handler
+    texts = [str(i) for i in range(33)]
+    assert_local(rig, run(rig.service.embed(texts)), texts, "PROVIDER_INVALID_RESPONSE")
+    assert len(rig.requests) == 2
+
+
+@pytest.mark.parametrize("failure, reason", [
+    (401, "PROVIDER_AUTH_FAILED"), (403, "PROVIDER_AUTH_FAILED"),
+    (404, "MODEL_NOT_FOUND"), (429, "PROVIDER_RATE_LIMITED"), (500, "PROVIDER_UNAVAILABLE"),
+    ("timeout", "PROVIDER_TIMEOUT"), ("connect", "PROVIDER_UNAVAILABLE"),
+    ("json", "PROVIDER_INVALID_RESPONSE"),
+])
+def test_embedding_http_failures_use_injected_local(rig, failure, reason):
+    bind(rig)
+
+    def handler(request):
+        if failure == "timeout":
+            raise httpx.ReadTimeout("simulated timeout", request=request)
+        if failure == "connect":
+            raise httpx.ConnectError("simulated connection failure", request=request)
+        if failure == "json":
+            return httpx.Response(200, content=b"not JSON")
+        return response({"error": "failed"}, failure)
+
+    rig.http.handler = handler
+    assert_local(rig, run(rig.service.embed(["text"])), ["text"], reason)
+
+
+@pytest.mark.parametrize("failure, reason", [
+    ("missing-key", "PROVIDER_CREDENTIAL_MISSING"),
+    ("unreadable-key", "PROVIDER_CREDENTIAL_UNAVAILABLE"),
+    ("disabled-provider", "PROVIDER_UNAVAILABLE"),
+])
+def test_unavailable_remote_configuration_falls_back_without_http(rig, failure, reason):
+    bind(rig)
+    if failure == "missing-key":
+        rig.credentials.value = None
+    elif failure == "unreadable-key":
+        rig.credentials.error = CredentialStoreError("fake unavailable store")
+    else:
+        config = rig.providers.get_any("test-provider").config.model_copy(update={"enabled": False})
+        rig.providers.replace(config, MockProvider())
+    assert_local(rig, run(rig.service.embed(["text"])), ["text"], reason)
+    assert rig.requests == []
+
+
+@pytest.mark.parametrize("capability", ["transcription", "speaker_matching"])
+def test_media_success_sends_expected_multipart_and_closes_files(rig, audio, monkeypatch, capability):
+    bind(rig, capability)
+    handles = track_media_handles(rig, monkeypatch)
+
+    def handler(request):
+        assert request.headers["authorization"] == "Bearer unit-test-placeholder"
+        assert str(request.url).endswith("/audio/transcriptions" if capability == "transcription" else "/audio/speaker-matches")
+        message = BytesParser(policy=policy.default).parsebytes(
+            b"Content-Type: " + request.headers["content-type"].encode() + b"\r\nMIME-Version: 1.0\r\n\r\n" + request.content,
+        )
+        parts = {part.get_param("name", header="content-disposition"): part for part in message.iter_parts()}
+        assert parts["model"].get_payload(decode=True) == b"test-model"
+        assert parts["file"].get_filename() == audio[0].name
+        assert parts["file"].get_payload(decode=True) == audio[0].read_bytes()
+        if capability == "transcription":
+            assert set(parts) == {"model", "language", "file"}
+            assert parts["language"].get_payload(decode=True) == b"zh"
+            return response({"text": "remote transcript"})
+        assert set(parts) == {"model", "file", "reference_file"}
+        assert parts["reference_file"].get_filename() == audio[1].name
+        assert parts["reference_file"].get_payload(decode=True) == audio[1].read_bytes()
+        return response({"score": 0.875})
+
+    rig.http.handler = handler
+    result = run(media_call(rig, capability, audio))
+    assert result.source == "api" and result.fallback_reason is None
+    assert result.text == "remote transcript" if capability == "transcription" else result.score == 0.875
+    assert len(handles) == (1 if capability == "transcription" else 2)
+    assert all(handle.closed for handle in handles)
+    assert rig.speech.calls == []
+
+
+@pytest.mark.parametrize("capability, data", [
+    ("transcription", {}), ("transcription", {"text": "  "}), ("transcription", {"text": False}),
+    ("transcription", {"error": "in-band", "text": "must not use"}),
+    ("speaker_matching", {}), ("speaker_matching", {"score": -0.1}),
+    ("speaker_matching", {"score": 1.1}), ("speaker_matching", {"score": True}),
+    ("speaker_matching", {"score": float("nan")}), ("speaker_matching", {"score": "0.5"}),
+    ("speaker_matching", {"error": "in-band", "score": 0.9}),
+])
+def test_invalid_remote_media_falls_back_to_injected_local(rig, audio, monkeypatch, capability, data):
+    bind(rig, capability)
+    handles = track_media_handles(rig, monkeypatch)
+    rig.http.handler = lambda request: response(data)
+    result = run(media_call(rig, capability, audio))
+    assert result.source == "local" and result.fallback_reason == "PROVIDER_INVALID_RESPONSE"
+    assert result.text == "local transcript" if capability == "transcription" else result.score == 0.25
+    assert rig.speech.calls == [
+        ("transcribe", audio[0], "zh") if capability == "transcription" else ("match", *audio)
+    ]
+    assert handles and all(handle.closed for handle in handles)
+
+
+@pytest.mark.parametrize("capability", ["transcription", "speaker_matching"])
+@pytest.mark.parametrize("configured", [False, True])
+def test_pending_local_backend_has_explicit_503_and_fallback_details(rig, audio, capability, configured):
+    rig.service.local_speech = PendingSpeechBackend()
+    if configured:
+        bind(rig, capability)
+        rig.http.handler = lambda request: response({"error": "unauthorized"}, 401)
+    with pytest.raises(ApiError) as caught:
+        run(media_call(rig, capability, audio))
+    assert caught.value.status_code == 503
+    assert caught.value.code == "LOCAL_MODEL_NOT_INSTALLED"
+    assert caught.value.details == {"fallback_reason": "PROVIDER_AUTH_FAILED" if configured else None}
+    statuses = {item.capability: item.status for item in rig.service.describe().local_backends}
+    assert statuses["transcription"] == statuses["speaker_matching"] == "not_installed"
+    assert len(rig.requests) == int(configured)
+
+
+@pytest.mark.parametrize("capability", ["transcription", "speaker_matching"])
+def test_invalid_local_speech_returns_explicit_503(rig, audio, capability):
+    rig.speech.text = ""
+    rig.speech.score = True
+    with pytest.raises(ApiError) as caught:
+        run(media_call(rig, capability, audio))
+    assert (caught.value.status_code, caught.value.code) == (503, "LOCAL_MODEL_INVALID_RESPONSE")
+    assert caught.value.details == {"fallback_reason": None}
+
+
+@pytest.mark.parametrize("capability", ["embedding", "transcription", "speaker_matching"])
+@pytest.mark.parametrize("stage", ["remote", "local"])
+def test_cancellation_propagates_and_upload_handles_close(rig, audio, monkeypatch, capability, stage):
+    bind(rig, capability)
+    handles = track_media_handles(rig, monkeypatch)
+
+    async def cancelled(request):
+        raise asyncio.CancelledError()
+
+    if stage == "remote":
+        rig.http.handler = cancelled
+    else:
+        rig.http.handler = lambda request: response({"error": "fallback"}, 500)
+        rig.embedding.error = rig.speech.error = asyncio.CancelledError()
+    operation = rig.service.embed(["text"]) if capability == "embedding" else media_call(rig, capability, audio)
+    with pytest.raises(asyncio.CancelledError):
+        run(operation)
+    assert len(handles) == {"embedding": 0, "transcription": 1, "speaker_matching": 2}[capability]
+    assert all(handle.closed for handle in handles)
+    if stage == "remote":
+        assert rig.embedding.calls == rig.speech.calls == []
+
+
+def test_missing_reference_closes_already_open_source(rig, audio, monkeypatch):
+    bind(rig, "speaker_matching")
+    handles = track_media_handles(rig, monkeypatch)
+    audio[1].unlink()
+    with pytest.raises(ApiError) as caught:
+        run(rig.service.match_speakers(*audio))
+    assert caught.value.status_code == 404
+    assert len(handles) == 1 and handles[0].closed
+    assert rig.requests == []
+
+
+def test_config_optimistic_conflict_preserves_saved_bindings(rig):
+    assert rig.service.configuration().version == 0
+    saved = bind(rig).config
+    assert saved.version == 1
+    with pytest.raises(ApiError) as caught:
+        rig.service.update(ModelRoutingConfig(version=0))
+    assert (caught.value.status_code, caught.value.code) == (409, "MODEL_ROUTING_VERSION_CONFLICT")
+    assert rig.service.configuration() == saved
+    assert rig.service.uses_provider("test-provider")
+    assert not rig.service.uses_provider("not-a-provider")
+    cleared = rig.service.update(ModelRoutingConfig(version=1)).config
+    assert cleared.version == 2 and cleared.embedding is None
+    assert not rig.service.uses_provider("test-provider")
+
+
+@pytest.mark.parametrize("capability", ["embedding", "transcription", "speaker_matching"])
+@pytest.mark.parametrize("provider_id, code", [
+    ("missing", "PROVIDER_NOT_FOUND"), ("unsupported", "MODEL_ROUTING_PROTOCOL_UNSUPPORTED"),
+])
+def test_config_references_require_existing_supported_providers(rig, capability, provider_id, code):
+    rig.providers.register(
+        ProviderConfig(provider_id="unsupported", provider_type=ProviderType.ollama, name="unsupported"), MockProvider(),
+    )
+    with pytest.raises(ApiError) as caught:
+        bind(rig, capability, provider_id=provider_id)
+    assert (caught.value.status_code, caught.value.code) == (422, code)
+    assert rig.service.configuration() == ModelRoutingConfig()
+    assert rig.requests == []
+
+
+@pytest.fixture
+def api(monkeypatch, no_real_http, _isolate_data_dir):
+    # Import the production container only after temporary storage is configured.
+    from app import container as container_module, routes
+    from app.main import app
+
+    containers = []
+
+    def restart():
+        container = container_module.build_container()
+        container.model_routing.credentials = FakeCredentials()
+
+        def unexpected(request):
+            pytest.fail(f"Unexpected API-side provider HTTP: {request.url}")
+
+        container.model_routing.transport = httpx.MockTransport(unexpected)
+        monkeypatch.setattr(container_module, "container", container)
+        monkeypatch.setattr(routes, "container", container)
+        containers.append(container)
+        return container
+
+    container = restart()
+    client = TestClient(app)
+    yield SimpleNamespace(client=client, container=container, restart=restart)
+    client.close()
+    for container in containers:
+        container.plugins.shutdown()
+        container.mcp_servers.shutdown()
+
+
+def create_api_provider(api):
+    result = api.client.post("/api/providers", json={
+        "provider_type": "openai_compatible", "name": "Persisted fake",
+        "base_url": "https://persist.invalid/v1", "default_model": "fake-model",
+    })
+    assert result.status_code == 200, result.text
+    return result.json()
+
+
+def test_api_config_conflict_reference_delete_and_restart_persistence(api):
+    provider = create_api_provider(api)
+    provider_id = provider["provider_id"]
+    assert api.client.get("/api/model-routing").json()["config"]["version"] == 0
+    config = {"version": 0, "embedding": {"provider_id": provider_id, "model": "embed-model", "endpoint": "/embeddings"}}
+    saved = api.client.put("/api/model-routing", json=config)
+    assert saved.status_code == 200
+    assert saved.json()["config"]["version"] == 1
+    conflict = api.client.put("/api/model-routing", json=config)
+    assert conflict.status_code == 409
+    assert conflict.json()["error"]["code"] == "MODEL_ROUTING_VERSION_CONFLICT"
+    blocked = api.client.delete(f"/api/providers/{provider_id}")
+    assert blocked.status_code == 409 and blocked.json()["error"]["code"] == "PROVIDER_IN_USE"
+    restarted = api.restart()
+    assert restarted.providers.get_any(provider_id).config.model_dump(mode="json") == provider
+    assert api.client.get("/api/model-routing").json()["config"] == saved.json()["config"]
+    assert {item["provider_id"] for item in api.client.get("/api/providers").json()["items"]} == {"mock", provider_id}
+    cleared = api.client.put("/api/model-routing", json={"version": 1})
+    assert cleared.status_code == 200
+    assert api.client.delete(f"/api/providers/{provider_id}").status_code == 200
+    api.restart()
+    assert api.client.get(f"/api/providers/{provider_id}").status_code == 404
+    assert api.client.get("/api/model-routing").json()["config"]["version"] == 2
+
+
+def test_api_provider_type_patch_rebuilds_adapter_and_persists(api):
+    from app.providers.anthropic_messages import AnthropicMessagesProvider
+
+    provider = create_api_provider(api)
+    provider_id = provider["provider_id"]
+    changed = api.client.patch(f"/api/providers/{provider_id}", json={
+        "provider_type": "anthropic_messages", "base_url": "https://anthropic.invalid/v1",
+    })
+    assert changed.status_code == 200, changed.text
+    assert changed.json()["provider_type"] == "anthropic_messages"
+    assert changed.json()["name"] == provider["name"]
+    assert isinstance(api.container.providers.get_any(provider_id).adapter, AnthropicMessagesProvider)
+    restarted = api.restart()
+    assert isinstance(restarted.providers.get_any(provider_id).adapter, AnthropicMessagesProvider)
+    assert api.client.get(f"/api/providers/{provider_id}").json() == changed.json()
+    for invalid_type in (None, "mock", "nonexistent-type"):
+        rejected = api.client.patch(f"/api/providers/{provider_id}", json={"provider_type": invalid_type})
+        assert rejected.status_code == 422
+        assert api.client.get(f"/api/providers/{provider_id}").json() == changed.json()
+
+
+@pytest.mark.parametrize("endpoint", ["https://elsewhere.invalid/embed", "//elsewhere.invalid/embed", "relative", "/../embed", "/embed?key=test"])
+def test_api_config_rejects_non_provider_endpoint_paths(api, endpoint):
+    provider = create_api_provider(api)
+    result = api.client.put("/api/model-routing", json={
+        "embedding": {"provider_id": provider["provider_id"], "model": "embed", "endpoint": endpoint},
+    })
+    assert result.status_code == 422
+    assert api.client.get("/api/model-routing").json()["config"]["version"] == 0
+
+
+def test_api_embedding_reports_remote_and_fallback_sources(api):
+    provider = create_api_provider(api)
+    assert api.client.put("/api/model-routing", json={
+        "embedding": {"provider_id": provider["provider_id"], "model": "embed", "endpoint": "/embeddings"},
+    }).status_code == 200
+    api.container.model_routing.transport = httpx.MockTransport(
+        lambda request: response({"data": [{"index": 0, "embedding": [3, 4]}]}),
+    )
+    result = api.client.post("/api/models/embeddings", json={"texts": ["hello"]})
+    assert result.status_code == 200
+    assert result.json()["source"] == "api" and result.json()["vectors"][0] == pytest.approx([0.6, 0.8])
+    api.container.model_routing.transport = httpx.MockTransport(lambda request: response({"error": "denied"}, 401))
+    result = api.client.post("/api/models/embeddings", json={"texts": ["hello"]})
+    assert result.status_code == 200
+    assert result.json()["source"] == "local" and result.json()["model_id"] == "hash-v1"
+    assert result.json()["fallback_reason"] == "PROVIDER_AUTH_FAILED"
+    assert api.client.post("/api/models/embeddings", json={"texts": []}).status_code == 422
+
+
+def test_api_speech_failure_reports_reason_in_503_and_transcription_job(api):
+    from app.services.attachment_service import attachment_path
+
+    source, reference = attachment_path("audio.wav"), attachment_path("reference.wav")
+    source.parent.mkdir(parents=True, exist_ok=True)
+    source.write_bytes(b"test audio")
+    reference.write_bytes(b"test reference")
+    provider = create_api_provider(api)
+    assert api.client.put("/api/model-routing", json={
+        "transcription": {"provider_id": provider["provider_id"], "model": "asr", "endpoint": "/audio/transcriptions"},
+        "speaker_matching": {"provider_id": provider["provider_id"], "model": "voice", "endpoint": "/audio/speaker-matches"},
+    }).status_code == 200
+    api.container.model_routing.transport = httpx.MockTransport(lambda request: response({"error": "offline"}, 500))
+    match = api.client.post("/api/media/speaker-matches", json={"attachment_id": source.name, "reference_attachment_id": reference.name})
+    assert match.status_code == 503
+    assert match.json()["error"]["code"] == "LOCAL_MODEL_NOT_INSTALLED"
+    assert match.json()["error"]["details"] == {"fallback_reason": "PROVIDER_UNAVAILABLE"}
+    transcript = api.client.post("/api/media/transcriptions", json={"attachment_id": source.name, "language": "zh"})
+    assert transcript.status_code == 202
+    job = transcript.json()
+    assert job["status"] == "failed" and job["error_code"] == "LOCAL_MODEL_NOT_INSTALLED"
+    assert job["fallback_reason"] == "PROVIDER_UNAVAILABLE"
+    assert api.client.get(f"/api/media/transcriptions/{job['job_id']}").json() == job
+
+
+@pytest.mark.parametrize("capability", ["embedding", "speaker_matching"])
+def test_out_of_float_range_json_number_is_invalid_remote_and_falls_back(rig, audio, capability):
+    """JSON integers may be finite but too large to convert to a Python float."""
+    bind(rig, capability)
+    data = {"data": [{"index": 0, "embedding": [10 ** 400, 1]}]} if capability == "embedding" else {"score": 10 ** 400}
+    rig.http.handler = lambda request: response(data)
+    if capability == "embedding":
+        assert_local(rig, run(rig.service.embed(["text"])), ["text"], "PROVIDER_INVALID_RESPONSE")
+    else:
+        result = run(media_call(rig, capability, audio))
+        assert result.source == "local" and result.score == rig.speech.score
+        assert result.fallback_reason == "PROVIDER_INVALID_RESPONSE"

backend/tests/test_provider_adapters.py

@@ -84,7 +84,7 @@ def test_openai_compatible_maps_tool_call_and_credentials() -> None:
         )
     )
 
-    assert captured["tools"][0]["function"]["name"] == "math.add"
+    assert captured["tools"][0]["function"]["name"].startswith("tool_")
     assert turn.tool_calls[0].name == "math.add"
     assert turn.tool_calls[0].arguments == {"left": 1, "right": 2}
     assert turn.input_tokens == 8

backend/tests/test_provider_protocols.py

@@ -0,0 +1,610 @@
+"""Wire-level provider tests: no credentials, SDKs, clocks, or network services."""
+
+import asyncio
+import json
+
+import httpx
+import pytest
+
+from app.contracts import Message, MessageRole, ModelCapability, ModelEventType as E, ModelRequest, ToolCall, ToolDefinition
+from app.providers.anthropic_messages import AnthropicMessagesProvider
+from app.providers.base import ProviderError
+from app.providers.ollama import OllamaProvider
+from app.providers.openai_compatible import OpenAICompatibleProvider
+from app.providers.openai_responses import OpenAIResponsesProvider
+
+
+NATIVE = ["responses", "anthropic"]
+PROTOCOLS = [*NATIVE, "compatible", "ollama"]
+SECRET = "test-only-sensitive-upstream-body"
+
+
+class Credentials:
+    def resolve(self, credential_id):
+        return SECRET if credential_id else None
+
+
+class Bytes(httpx.AsyncByteStream):
+    def __init__(self, body: bytes, *, fragment: int = 17):
+        self.body = body
+        self.fragment = fragment
+        self.closed = False
+
+    async def __aiter__(self):
+        for offset in range(0, len(self.body), self.fragment):
+            yield self.body[offset:offset + self.fragment]
+
+    async def aclose(self):
+        self.closed = True
+
+
+class GatedBytes(Bytes):
+    def __init__(self, body):
+        super().__init__(body)
+        self.waiting = asyncio.Event()
+        self.release = asyncio.Event()
+
+    async def __aiter__(self):
+        yield self.body
+        self.waiting.set()
+        await self.release.wait()
+
+
+def provider(protocol, handler, *, credential_id="test"):
+    transport = httpx.MockTransport(handler)
+    if protocol == "ollama":
+        return OllamaProvider("https://provider.test", transport=transport)
+    cls = {"responses": OpenAIResponsesProvider, "anthropic": AnthropicMessagesProvider,
+           "compatible": OpenAICompatibleProvider}[protocol]
+    return cls("https://provider.test/v1/", credential_id, Credentials(), transport=transport)
+
+
+def request(*, history=False):
+    messages = [Message(role=MessageRole.user, content="查笔记")]
+    if history:
+        messages += [
+            Message(role=MessageRole.system, content="Additional rules"),
+            Message(role=MessageRole.assistant, content="Checking", tool_calls=[
+                ToolCall(tool_call_id="old_1", name="lookup", arguments={"query": "a"}),
+                ToolCall(tool_call_id="old_2", name="lookup", arguments={"query": "b"}),
+            ]),
+            Message(role=MessageRole.tool, tool_call_id="old_1", content='{"found":1}'),
+            Message(role=MessageRole.tool, tool_call_id="old_2", content='{"found":2}'),
+        ]
+    return ModelRequest(
+        provider_id="test", model="model", system="System rules", messages=messages,
+        tools=[ToolDefinition(name="lookup", description="Find notes", parameters={"type": "object"})],
+        max_tokens=512, temperature=0,
+    )
+
+
+async def collect(iterator):
+    return [event async for event in iterator]
+
+
+@pytest.mark.parametrize("name", ["lookup", "notes.search"])
+def test_compatible_split_tool_name_preserves_identity(name):
+    from app.providers.tool_names import prepare_tool_names
+    req = request()
+    req.tools[0].name = name
+    wire, _ = prepare_tool_names(req)
+    alias = wire.tools[0].name
+
+    def handler(_):
+        return httpx.Response(200, content=sse(
+            {"choices": [{"delta": {"tool_calls": [{"index": 0, "id": "call_1",
+                "function": {"name": alias[:3], "arguments": ""}}]}}]},
+            {"choices": [{"delta": {"tool_calls": [{"index": 0,
+                "function": {"name": alias[3:], "arguments": '{"query":"x"}'}}]},
+                "finish_reason": "tool_calls"}]},
+            {"type": "[DONE]"},
+        ))
+
+    events = asyncio.run(collect(provider("compatible", handler).stream(req)))
+    assert [e.data["name"] for e in events if e.event == E.tool_call_start] == [name]
+    assert json.loads("".join(e.data["arguments_delta"] for e in events
+                             if e.event == E.tool_call_delta)) == {"query": "x"}
+    assert events[-1].data["status"] == "completed"
+
+
+def sse(*events):
+    return "".join(
+        f"event: {event.get('type', 'message')}\r\ndata: {json.dumps(event, ensure_ascii=False)}\r\n\r\n"
+        for event in events
+    ).encode()
+
+
+def wire(protocol, *events):
+    if protocol == "ollama":
+        return ("\n".join(json.dumps(event, ensure_ascii=False) for event in events) + "\n").encode()
+    return sse(*events)
+
+
+def start(protocol):
+    if protocol == "responses":
+        return [{"type": "response.output_text.delta", "delta": "你好"}]
+    if protocol == "anthropic":
+        return [{"type": "message_start", "message": {"usage": {"input_tokens": 7, "output_tokens": 0}}},
+                {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}},
+                {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "你好"}}]
+    if protocol == "compatible":
+        return [{"choices": [{"delta": {"content": "你好"}}]}]
+    return [{"message": {"content": "你好"}, "done": False}]
+
+
+def terminal(protocol):
+    if protocol == "responses":
+        return [{"type": "response.completed", "response": {"status": "completed", "usage": {"input_tokens": 7, "output_tokens": 2}}}]
+    if protocol == "anthropic":
+        return [{"type": "content_block_stop", "index": 0},
+                {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 2}},
+                {"type": "message_stop"}]
+    if protocol == "compatible":
+        return [{"choices": [{"delta": {}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 7, "completion_tokens": 2}}]
+    return [{"message": {}, "done": True, "prompt_eval_count": 7, "eval_count": 2}]
+
+
+def assert_events(events):
+    assert events[-1].event == E.done
+    assert events[-1].data["status"] == ("failed" if any(event.event == E.error for event in events) else "completed")
+    assert sum(event.event == E.done for event in events) == 1
+    assert [event.sequence for event in events] == list(range(len(events)))
+    assert all(event.timestamp.tzinfo is not None for event in events)
+
+
+def assert_error(events, code):
+    assert_events(events)
+    assert events[-2].event == E.error
+    assert events[-2].data["code"] == code
+    assert SECRET not in str(events[-2].data)
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_native_completion_and_history(protocol):
+    captured = {}
+
+    def handler(req):
+        captured.update(json.loads(req.content))
+        assert req.url.path == ("/v1/responses" if protocol == "responses" else "/v1/messages")
+        if protocol == "responses":
+            assert req.headers["authorization"] == f"Bearer {SECRET}"
+            body = {"status": "completed", "output": [
+                {"type": "reasoning", "summary": [{"type": "summary_text", "text": "thinking"}]},
+                {"type": "message", "content": [{"type": "output_text", "text": "完成"}]},
+                {"type": "function_call", "call_id": "next", "name": "lookup", "arguments": '{"query":"c"}'},
+            ], "usage": {"input_tokens": 10, "output_tokens": 3}}
+        else:
+            assert "authorization" not in req.headers
+            assert req.headers["x-api-key"] == SECRET
+            assert req.headers["anthropic-version"] == "2023-06-01"
+            body = {"type": "message", "content": [
+                {"type": "thinking", "thinking": "thinking", "signature": "sig"},
+                {"type": "text", "text": "完成"},
+                {"type": "tool_use", "id": "next", "name": "lookup", "input": {"query": "c"}},
+            ], "usage": {"input_tokens": 5, "cache_creation_input_tokens": 2, "cache_read_input_tokens": 3, "output_tokens": 3}}
+        return httpx.Response(200, json=body)
+
+    turn = asyncio.run(provider(protocol, handler).complete(request(history=True)))
+    assert turn.text == "完成"
+    assert (turn.input_tokens, turn.output_tokens) == (10, 3)
+    assert turn.tool_calls[0].tool_call_id == "next"
+    assert turn.tool_calls[0].arguments == {"query": "c"}
+    assert captured["stream"] is False
+    assert captured["temperature"] == 0
+    if protocol == "responses":
+        assert captured["instructions"] == "System rules"
+        assert captured["max_output_tokens"] == 512
+        assert captured["tools"][0]["parameters"] == {"type": "object"}
+        calls = [item for item in captured["input"] if item.get("type") == "function_call"]
+        outputs = [item for item in captured["input"] if item.get("type") == "function_call_output"]
+        assert [call["call_id"] for call in calls] == ["old_1", "old_2"]
+        assert json.loads(calls[1]["arguments"]) == {"query": "b"}
+        assert outputs == [{"type": "function_call_output", "call_id": "old_1", "output": '{"found":1}'},
+                           {"type": "function_call_output", "call_id": "old_2", "output": '{"found":2}'}]
+        assert {"role": "system", "content": "Additional rules"} in captured["input"]
+    else:
+        assert captured["system"] == "System rules\n\nAdditional rules"
+        assert captured["max_tokens"] == 512
+        assert captured["tools"][0]["input_schema"] == {"type": "object"}
+        assert captured["messages"][1]["content"][2] == {
+            "type": "tool_use", "id": "old_2", "name": "lookup", "input": {"query": "b"},
+        }
+        assert captured["messages"][-1] == {"role": "user", "content": [
+            {"type": "tool_result", "tool_use_id": "old_1", "content": '{"found":1}'},
+            {"type": "tool_result", "tool_use_id": "old_2", "content": '{"found":2}'},
+        ]}
+
+
+def responses_tool_events():
+    events = [
+        {"type": "response.created", "response": {"usage": {"input_tokens": 10, "output_tokens": 0}}},
+        {"type": "response.reasoning_summary_text.delta", "delta": "计划"},
+        {"type": "response.output_text.delta", "delta": "查"},
+        {"type": "response.output_text.delta", "delta": "找"},
+    ]
+    for index in (2, 3):
+        events.append({"type": "response.output_item.added", "output_index": index, "item": {
+            "id": f"item_{index}", "type": "function_call", "call_id": f"call_{index}", "name": "lookup", "arguments": "",
+        }})
+    for index, fragment in [(2, '{"query":'), (3, '{}'), (2, '"笔记"}')]:
+        events.append({"type": "response.function_call_arguments.delta", "output_index": index,
+                       "item_id": f"item_{index}", "delta": fragment})
+    for index, arguments in [(3, '{}'), (2, '{"query":"笔记"}')]:
+        events += [
+            {"type": "response.function_call_arguments.done", "output_index": index, "item_id": f"item_{index}", "arguments": arguments},
+            {"type": "response.output_item.done", "output_index": index, "item": {
+                "id": f"item_{index}", "type": "function_call", "call_id": f"call_{index}", "name": "lookup", "arguments": arguments,
+            }},
+        ]
+    events += [{"type": "future.event"}, {"type": "response.completed", "response": {
+        "status": "completed", "usage": {"input_tokens": 10, "output_tokens": 9},
+    }}]
+    return events
+
+
+def anthropic_tool_events():
+    events = [
+        {"type": "message_start", "message": {"usage": {
+            "input_tokens": 5, "cache_read_input_tokens": 3, "cache_creation_input_tokens": 2, "output_tokens": 1,
+        }}},
+        {"type": "ping"},
+        {"type": "content_block_start", "index": 0, "content_block": {"type": "thinking", "thinking": ""}},
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "计划"}},
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "signature_delta", "signature": "sig"}},
+        {"type": "content_block_stop", "index": 0},
+        {"type": "content_block_start", "index": 1, "content_block": {"type": "text", "text": "查"}},
+        {"type": "content_block_delta", "index": 1, "delta": {"type": "text_delta", "text": "找"}},
+        {"type": "content_block_stop", "index": 1},
+    ]
+    for index, fragments in [(2, ['{"query":', '"笔记"}']), (3, [])]:
+        events.append({"type": "content_block_start", "index": index, "content_block": {
+            "type": "tool_use", "id": f"call_{index}", "name": "lookup", "input": {},
+        }})
+        for fragment in fragments:
+            events.append({"type": "content_block_delta", "index": index,
+                           "delta": {"type": "input_json_delta", "partial_json": fragment}})
+        events.append({"type": "content_block_stop", "index": index})
+    events += [
+        {"type": "message_delta", "delta": {"stop_reason": "tool_use"}, "usage": {"output_tokens": 4}},
+        {"type": "future.event"},
+        {"type": "message_delta", "delta": {}, "usage": {"output_tokens": 9}},
+        {"type": "message_stop"},
+    ]
+    return events
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_native_stream_tools_reasoning_usage_and_fragmented_utf8(protocol):
+    frames = responses_tool_events() if protocol == "responses" else anthropic_tool_events()
+    body = Bytes(b": comment\r\n\r\n" + sse(*frames) + b"data: malformed after completion\n\n", fragment=1)
+
+    def handler(req):
+        payload = json.loads(req.content)
+        assert payload["stream"] is True
+        assert payload["tools"]
+        assert (payload.get("input") or payload.get("messages"))
+        return httpx.Response(200, stream=body)
+
+    events = asyncio.run(collect(provider(protocol, handler).stream(request(history=True))))
+    assert_events(events)
+    assert not any(event.event == E.error for event in events)
+    assert [event.data["text"] for event in events if event.event == E.text_delta] == ["查", "找"]
+    assert [event.data["text"] for event in events if event.event == E.thinking_delta] == ["计划"]
+    assert [event.data["tool_call_id"] for event in events if event.event == E.tool_call_start] == ["call_2", "call_3"]
+    assert sorted(event.data["tool_call_id"] for event in events if event.event == E.tool_call_end) == ["call_2", "call_3"]
+    for call_id, expected in [("call_2", {"query": "笔记"}), ("call_3", {})]:
+        arguments = "".join(event.data["arguments_delta"] for event in events
+                            if event.event == E.tool_call_delta and event.data["tool_call_id"] == call_id)
+        assert json.loads(arguments) == expected
+    usages = [event.data for event in events if event.event == E.usage]
+    assert usages[-1] == {"input_tokens": 10, "output_tokens": 9, "total_tokens": 19}
+    assert all(usage["input_tokens"] == 10 for usage in usages)
+    if protocol == "anthropic":
+        assert [usage["output_tokens"] for usage in usages] == [1, 4, 9]
+    assert body.closed
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+def test_stream_terminal_usage_and_closure(protocol):
+    body = Bytes(wire(protocol, *start(protocol), *terminal(protocol)))
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, stream=body)).stream(request())))
+    assert_events(events)
+    assert not any(event.event == E.error for event in events)
+    assert [event.data["text"] for event in events if event.event == E.text_delta] == ["你好"]
+    assert [event.data for event in events if event.event == E.usage][-1] == {"input_tokens": 7, "output_tokens": 2, "total_tokens": 9}
+    assert body.closed
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("empty", [False, True])
+def test_truncated_stream(protocol, empty):
+    body = Bytes(b"" if empty else wire(protocol, *start(protocol)))
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, stream=body)).stream(request())))
+    assert_error(events, "PROVIDER_STREAM_TRUNCATED")
+    assert body.closed
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("bad", [b"not-json", b"[]", b"null", b'{"usage":'])
+def test_malformed_stream_is_sanitized(protocol, bad):
+    suffix = bad + b"\n" if protocol == "ollama" else b"data: " + bad + b"\n\n"
+    body = Bytes(wire(protocol, *start(protocol)) + suffix)
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, stream=body)).stream(request())))
+    assert_error(events, "PROVIDER_INVALID_RESPONSE")
+    assert body.closed
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("error_type,code", [("rate_limit_error", "PROVIDER_RATE_LIMITED"),
+                                           ("authentication_error", "PROVIDER_AUTH_FAILED"),
+                                           ("overloaded_error", "PROVIDER_UNAVAILABLE")])
+def test_in_band_error_after_partial_output(protocol, error_type, code):
+    body = Bytes(wire(protocol, *start(protocol), {"type": "error", "error": {"type": error_type, "message": SECRET}}))
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, stream=body)).stream(request())))
+    assert any(event.event == E.text_delta for event in events)
+    assert_error(events, code)
+    assert body.closed
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("status,code", [(400, "PROVIDER_INVALID_REQUEST"), (401, "PROVIDER_AUTH_FAILED"),
+                                       (403, "PROVIDER_AUTH_FAILED"), (404, "MODEL_NOT_FOUND"),
+                                       (429, "PROVIDER_RATE_LIMITED"), (500, "PROVIDER_UNAVAILABLE")])
+def test_http_errors_completion_and_stream(protocol, status, code):
+    adapter = provider(protocol, lambda _: httpx.Response(status, text=SECRET))
+    with pytest.raises(ProviderError) as exc:
+        asyncio.run(adapter.complete(request()))
+    assert exc.value.code == code
+    assert SECRET not in str(exc.value)
+    assert_error(asyncio.run(collect(adapter.stream(request()))), code)
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("body,code", [(b"broken", "PROVIDER_INVALID_RESPONSE"),
+                                     (b"[]", "PROVIDER_INVALID_RESPONSE"),
+                                     (b"{}", "PROVIDER_INVALID_RESPONSE"),
+                                     (json.dumps({"error": {"code": "invalid_api_key", "message": SECRET}}).encode(), "PROVIDER_AUTH_FAILED")])
+def test_bad_completion(protocol, body, code):
+    adapter = provider(protocol, lambda _: httpx.Response(200, content=body))
+    with pytest.raises(ProviderError) as exc:
+        asyncio.run(adapter.complete(request()))
+    assert exc.value.code == code
+    assert SECRET not in str(exc.value)
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("error,code", [(httpx.ReadTimeout, "PROVIDER_TIMEOUT"),
+                                      (httpx.ConnectError, "PROVIDER_UNAVAILABLE")])
+def test_transport_error_mapping(protocol, error, code):
+    def handler(req):
+        raise error(SECRET, request=req)
+
+    adapter = provider(protocol, handler)
+    with pytest.raises(ProviderError) as exc:
+        asyncio.run(adapter.complete(request()))
+    assert exc.value.code == code
+    assert SECRET not in str(exc.value)
+    assert_error(asyncio.run(collect(adapter.stream(request()))), code)
+
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("cancel", [True, False])
+def test_incremental_delivery_cancellation_and_explicit_close(protocol, cancel):
+    async def scenario():
+        body = GatedBytes(wire(protocol, *start(protocol)))
+        adapter = provider(protocol, lambda _: httpx.Response(200, stream=body))
+        iterator = adapter.stream(request())
+        seen = []
+        while True:
+            event = await asyncio.wait_for(anext(iterator), timeout=1)
+            seen.append(event)
+            if event.event == E.text_delta:
+                break
+        # The first token arrives while the response is still open and blocked.
+        assert seen[-1].data["text"] == "你好"
+        assert not body.closed
+        if cancel:
+            pending = asyncio.create_task(anext(iterator))
+            await asyncio.wait_for(body.waiting.wait(), timeout=1)
+            pending.cancel()
+            with pytest.raises(asyncio.CancelledError):
+                await pending
+        else:
+            await iterator.aclose()
+        assert body.closed
+        assert not any(event.event in {E.error, E.done} for event in seen)
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_cancellation_before_response_headers(protocol):
+    async def scenario():
+        entered = asyncio.Event()
+        closed = asyncio.Event()
+
+        async def handler(req):
+            entered.set()
+            try:
+                await asyncio.Event().wait()
+            finally:
+                closed.set()
+
+        adapter = provider(protocol, handler)
+        pending = asyncio.create_task(adapter.complete(request()))
+        await asyncio.wait_for(entered.wait(), timeout=1)
+        pending.cancel()
+        with pytest.raises(asyncio.CancelledError):
+            await pending
+        assert closed.is_set()
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_native_discovery_does_not_claim_non_chat_capabilities(protocol):
+    def handler(req):
+        assert req.url.path == "/v1/models"
+        return httpx.Response(200, json={"data": [{"id": name} for name in ["chat-model", "text-embedding-3-small", "whisper-1", "gpt-audio"]]})
+
+    models = asyncio.run(provider(protocol, handler).list_models())
+    assert ModelCapability.chat in models[0].capabilities
+    assert models[1].capabilities == [ModelCapability.embedding]
+    assert all(ModelCapability.chat not in model.capabilities for model in models[1:])
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_native_structured_format_mapping(protocol):
+    adapter = provider(protocol, lambda _: pytest.fail("No network expected"))
+    req = request()
+    req.response_format = {"type": "json_schema", "json_schema": {
+        "name": "answer", "strict": True, "schema": {"type": "object", "properties": {}},
+    }}
+    payload = adapter._payload(req, stream=False)
+    format_ = payload["text"]["format"] if protocol == "responses" else payload["output_config"]["format"]
+    assert format_["type"] == "json_schema"
+    assert format_["schema"] == {"type": "object", "properties": {}}
+    if protocol == "responses":
+        assert format_["name"] == "answer"
+        assert format_["strict"] is True
+
+
+@pytest.mark.parametrize("protocol", NATIVE)
+def test_invalid_tool_arguments_and_unclosed_tool(protocol):
+    frames = responses_tool_events() if protocol == "responses" else anthropic_tool_events()
+    # A syntactically valid terminal cannot rescue an unfinished tool block.
+    index = next(i for i, frame in enumerate(frames)
+                 if frame["type"] in {"response.function_call_arguments.delta", "content_block_delta"}
+                 and (frame.get("output_index") == 2 or frame.get("index") == 2))
+    partial = frames[:index + 1]
+    final = frames[-1]
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, content=sse(*partial, final))).stream(request())))
+    assert_error(events, "PROVIDER_STREAM_TRUNCATED")
+    assert not any(event.event == E.tool_call_end for event in events)
+
+    for frame in frames:
+        if frame["type"] == "response.function_call_arguments.done":
+            frame["arguments"] = "[]"
+            break
+        if frame["type"] == "content_block_delta" and frame.get("index") == 2:
+            frame["delta"]["partial_json"] = "malformed"
+            break
+    events = asyncio.run(collect(provider(protocol, lambda _: httpx.Response(200, content=sse(*frames))).stream(request())))
+    assert_error(events, "PROVIDER_INVALID_RESPONSE")
+
+
+@pytest.mark.parametrize("kind,code", [("response.failed", "PROVIDER_UNAVAILABLE"),
+                                     ("response.incomplete", "PROVIDER_INCOMPLETE_RESPONSE")])
+def test_responses_failed_and_incomplete(kind, code):
+    frame = {"type": kind, "response": {"status": kind.split(".")[1], "incomplete_details": {"reason": SECRET}}}
+    events = asyncio.run(collect(provider("responses", lambda _: httpx.Response(200, content=sse(*start("responses"), frame))).stream(request())))
+    assert_error(events, code)
+
+
+def test_sse_multiline_data_and_event_name_without_json_type():
+    body = (b': keepalive\n\nevent: response.output_text.delta\ndata: {\ndata: "delta": "hello"\ndata: }\n\n'
+            + sse({"type": "response.completed", "response": {"status": "completed"}}))
+    events = asyncio.run(collect(provider("responses", lambda _: httpx.Response(200, content=body)).stream(request())))
+    assert_events(events)
+    assert [event.data["text"] for event in events if event.event == E.text_delta] == ["hello"]
+    assert not any(event.event == E.error for event in events)
+
+
+def test_ollama_history_options_and_in_band_string_error():
+    captured = {}
+
+    def handler(req):
+        captured.update(json.loads(req.content))
+        return httpx.Response(200, json={"error": SECRET})
+
+    with pytest.raises(ProviderError) as exc:
+        asyncio.run(provider("ollama", handler).complete(request(history=True)))
+    assert exc.value.code == "PROVIDER_UNAVAILABLE"
+    assert SECRET not in str(exc.value)
+    assert captured["messages"][-1]["tool_name"] == "lookup"
+    assert captured["options"] == {"temperature": 0.0, "num_predict": 512}
+
+@pytest.mark.parametrize("protocol", PROTOCOLS)
+@pytest.mark.parametrize("streaming", [False, True])
+def test_namespaced_tools_roundtrip_without_changing_internal_request(protocol, streaming):
+    import re
+    model_request = request(history=True)
+    original_name = "mcp.my-server.search.notes"
+    model_request.tools[0].name = original_name
+    for message in model_request.messages:
+        for call in message.tool_calls:
+            call.name = original_name
+    before = model_request.model_dump()
+
+    def handler(req):
+        payload = json.loads(req.content)
+        definition = payload["tools"][0]
+        name = (definition.get("function") or definition)["name"]
+        assert name != original_name and re.fullmatch(r"[a-zA-Z0-9_-]{1,64}", name)
+        assert original_name not in req.content.decode()
+        if protocol == "responses":
+            item = {"type": "function_call", "id": "item1", "call_id": "call1", "name": name, "arguments": "{}"}
+            body = {"status": "completed", "output": [item]}
+            events = [
+                {"type": "response.output_item.done", "output_index": 0, "item": item},
+                {"type": "response.completed", "response": {"status": "completed"}},
+            ]
+        elif protocol == "anthropic":
+            item = {"type": "tool_use", "id": "call1", "name": name, "input": {}}
+            body = {"content": [item]}
+            events = [
+                {"type": "message_start", "message": {}},
+                {"type": "content_block_start", "index": 0, "content_block": item},
+                {"type": "content_block_stop", "index": 0},
+                {"type": "message_stop"},
+            ]
+        elif protocol == "compatible":
+            item = {"id": "call1", "function": {"name": name, "arguments": "{}"}}
+            body = {"choices": [{"message": {"tool_calls": [item]}}]}
+            events = [{"choices": [{"delta": {"tool_calls": [{"index": 0, **item}]}, "finish_reason": "tool_calls"}]}]
+        else:
+            item = {"function": {"name": name, "arguments": {}}}
+            body = {"message": {"tool_calls": [item]}, "done": True}
+            events = [body]
+        return httpx.Response(200, content=wire(protocol, *events)) if streaming else httpx.Response(200, json=body)
+
+    adapter = provider(protocol, handler)
+    if streaming:
+        events = asyncio.run(collect(adapter.stream(model_request)))
+        assert_events(events)
+        assert [event.data["name"] for event in events if event.event == E.tool_call_start] == [original_name]
+    else:
+        assert asyncio.run(adapter.complete(model_request)).tool_calls[0].name == original_name
+    assert model_request.model_dump() == before
+
+def test_chat_route_closes_upstream_and_sanitizes_unexpected_errors(monkeypatch):
+    from types import SimpleNamespace
+    from datetime import datetime, timezone
+    from app import routes
+    from app.contracts import ChatRequest, ModelEvent
+    closed = []
+
+    class Adapter:
+        async def stream(self, request):
+            try:
+                yield ModelEvent(event=E.text_delta, sequence=0, data={"text": "first"}, timestamp=datetime.now(timezone.utc))
+                raise RuntimeError(SECRET)
+            finally:
+                closed.append(True)
+
+    monkeypatch.setattr(routes, "provider_or_404", lambda _: SimpleNamespace(adapter=Adapter()))
+
+    async def scenario():
+        response = await routes.chat(ChatRequest(provider_id="test", model="test", messages=[]))
+        iterator = response.body_iterator
+        await anext(iterator)
+        await iterator.aclose()
+        assert len(closed) == 1
+        response = await routes.chat(ChatRequest(provider_id="test", model="test", messages=[]))
+        items = [json.loads(chunk.split("data: ")[1].strip()) async for chunk in response.body_iterator]
+        assert [item["sequence"] for item in items] == [0, 1, 2]
+        assert items[-1]["data"]["status"] == "failed"
+        assert SECRET not in str(items)
+        assert len(closed) == 2
+
+    asyncio.run(scenario())

backend/tests/test_retrieval.py

@@ -640,9 +640,10 @@ def test_rebuild_failure_restores_old_index(vault, monkeypatch) -> None:
     assert repository.stats() == before  # 旧索引已恢复，无半成品
 
 
-def test_first_rebuild_failure_removes_partial_database(vault, monkeypatch) -> None:
+def test_first_rebuild_failure_leaves_no_partial_index(vault, monkeypatch) -> None:
     """首次启动没有旧库时，失败也不能留下已经写入的部分索引。"""
     from app.services import index_service
+    from app import repository
 
     _write_vault(
         vault,
@@ -651,17 +652,17 @@ def test_first_rebuild_failure_removes_partial_database(vault, monkeypatch) -> N
     real_index = index_service.index_note
     calls = {"count": 0}
 
-    async def fail_on_second(parsed):
+    async def fail_on_second(parsed, **kwargs):
         calls["count"] += 1
         if calls["count"] == 2:
             raise RuntimeError("injected first-rebuild failure")
-        await real_index(parsed)
+        await real_index(parsed, **kwargs)
 
     monkeypatch.setattr(index_service, "index_note", fail_on_second)
     with pytest.raises(RuntimeError):
         asyncio.run(index_service.rebuild(IndexRebuildRequest(scope="all")))
 
-    assert not get_settings().db_path.exists()
+    assert repository.stats() == {"notes": 0, "blocks": 0}
 
 
 def test_rebuild_preserves_task_note_links(vault) -> None:

backend/tests/test_routed_retrieval.py

@@ -0,0 +1,466 @@
+"""Phase E route integration: deterministic runtimes, isolated DBs, no network."""
+
+from __future__ import annotations
+
+import asyncio
+import json
+from dataclasses import dataclass, field
+from types import SimpleNamespace
+
+import pytest
+
+from app import repository
+from app.config import get_settings
+from app.contracts import IndexRebuildRequest, SearchMode, SearchRequest
+from app.database.db import connect, transaction
+from app.retrieval import routed_vectors
+from app.retrieval.embedding import HashEmbeddingProvider
+from app.retrieval.engine import RetrievalEngine, engine
+from app.retrieval.reranker import LexicalReranker
+from app.retrieval.vectorstore import SqliteVecStore, VectorHit
+from app.services import index_service, note_service
+
+
+@dataclass
+class FakeRuntime:
+    model_id: str = "space-a"
+    dimensions: int = 3  # Deliberately differs from sqlite-vec's fixed 128.
+    source: str = "api"
+    error: BaseException | None = None
+    calls: list[list[str]] = field(default_factory=list)
+    result_override: object | None = None
+
+    async def embed(self, texts):
+        self.calls.append(list(texts))
+        if self.error is not None:
+            raise self.error
+        if self.result_override is not None:
+            return self.result_override
+        vectors = []
+        for text in texts:
+            # The API associates "apple" with banana; hash retrieval picks apple.
+            first = text == "apple orchard"
+            if self.model_id == "space-b":
+                first = not first
+            vectors.append(([1.0, 0.0] if first else [0.0, 1.0]) + [0.0] * (self.dimensions - 2))
+        return SimpleNamespace(
+            vectors=vectors, source=self.source, model_id=self.model_id,
+            dimensions=self.dimensions, fallback_reason=None,
+        )
+
+
+@pytest.fixture
+def runtime(monkeypatch):
+    runtime = FakeRuntime()
+    monkeypatch.setattr(routed_vectors, "get_model_routing", lambda: runtime)
+    return runtime
+
+
+async def seed():
+    apple = await note_service.create_note(
+        title="Apple", markdown="apple orchard", folder=None, tags=[],
+    )
+    banana = await note_service.create_note(
+        title="Banana", markdown="banana grove", folder=None, tags=[],
+    )
+    return apple, banana
+
+
+@pytest.mark.parametrize("outcome", ["api", "api_failure", "missing_space"])
+def test_benchmark_reports_actual_embedding_and_fallback(runtime, outcome):
+    from app.benchmarks import service
+    from app.contracts import RAGRunRequest
+
+    async def scenario():
+        apple, banana = await seed()
+        if outcome == "api_failure":
+            runtime.result_override = SimpleNamespace(source="local", fallback_reason="PROVIDER_TIMEOUT")
+        elif outcome == "missing_space":
+            runtime.model_id = "space-without-index"
+        directory = get_settings().benchmark_datasets_path
+        directory.mkdir(parents=True, exist_ok=True)
+        (directory / "routing.json").write_text(json.dumps({
+            "dataset_id": "routing", "kind": "rag", "version": "1",
+            "cases": [{"case_id": "query", "query": "apple", "expected_note_ids": [banana.note_id]}],
+        }), encoding="utf-8")
+        run = await service.create_rag_run(RAGRunRequest(
+            dataset_id="routing", modes=[SearchMode.fts, SearchMode.vector],
+        ))
+        await service.wait_for_run(run.run_id)
+        report = service.get_report(run.run_id)
+        assert report.config_snapshot["embedding"]["policy"] == "per_case"
+        fts, vector = report.cases
+        assert fts.embedding == {"source": "not_used"}
+        if outcome == "api":
+            assert vector.embedding["source"] == "api"
+            assert vector.embedding["model_id"] == "space-a"
+            assert vector.embedding["dimensions"] == 3
+            assert vector.retrieved_note_ids[0] == banana.note_id
+        else:
+            assert vector.embedding["source"] == "local"
+            assert vector.embedding["model_id"] == "hash-v1"
+            assert vector.embedding["dimensions"] == 128
+            assert vector.retrieved_note_ids[0] == apple.note_id
+            if outcome == "api_failure":
+                assert vector.embedding["fallback_reason"] == "PROVIDER_TIMEOUT"
+            if outcome == "missing_space":
+                assert vector.embedding["fallback_reason"] == "REMOTE_INDEX_UNAVAILABLE"
+                assert vector.embedding["attempted_space"]["model_id"] == "space-without-index"
+        events = service.get_events(run.run_id)
+        case_events = [e for e in events if e.event.value == "CaseCompleted"]
+        assert case_events[-1].data["embedding"] == vector.embedding
+
+    asyncio.run(scenario())
+
+
+def test_embedding_observations_are_isolated_between_concurrent_searches(runtime, monkeypatch):
+    from app.retrieval.provenance import capture_embedding
+
+    async def scenario():
+        await seed()
+        original = runtime.embed
+
+        async def embed(texts):
+            await asyncio.sleep(0)
+            if texts == ["offline"]:
+                raise RuntimeError("private upstream details")
+            return await original(texts)
+
+        monkeypatch.setattr(runtime, "embed", embed)
+
+        async def query(text):
+            with capture_embedding() as observation:
+                await engine.search(SearchRequest(query=text, mode=SearchMode.vector))
+            return observation
+
+        remote, local, another = await asyncio.gather(query("apple"), query("offline"), query("apple"))
+        assert remote["source"] == another["source"] == "api"
+        assert local["source"] == "local"
+        assert local["fallback_reason"] == "REMOTE_EMBEDDING_UNAVAILABLE"
+        assert "fallback_reason" not in remote or remote["fallback_reason"] is None
+        assert "private upstream" not in json.dumps(local)
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("failure", ["cancel", "write"])
+def test_rebuild_failure_preserves_concurrent_configuration_and_all_indexes(runtime, monkeypatch, failure):
+    from app.container import container
+    from app.contracts import ModelRoutingConfig, ProviderConfig, ProviderType
+    from app.services import task_service
+
+    async def scenario():
+        apple, _ = await seed()
+        task = task_service.create_task(title="before", note_id=apple.note_id)
+        before = {table: [tuple(row) for row in rows(f"SELECT * FROM {table}")]
+                  for table in ("notes", "blocks", "blocks_fts", "vec_blocks", "index_meta", "routed_block_vectors")}
+        container.model_routing.update(ModelRoutingConfig())
+        entered, release = asyncio.Event(), asyncio.Event()
+        original_embed = runtime.embed
+
+        async def pending_embed(texts):
+            entered.set()
+            await release.wait()
+            return await original_embed(texts)
+
+        monkeypatch.setattr(runtime, "embed", pending_embed)
+        original_index = index_service.index_note
+        writes = 0
+
+        async def fail_write(parsed, **kwargs):
+            nonlocal writes
+            await original_index(parsed, **kwargs)
+            writes += 1
+            if writes == 2:
+                raise RuntimeError("injected write failure")
+
+        if failure == "write":
+            monkeypatch.setattr(index_service, "index_note", fail_write)
+        rebuilding = asyncio.create_task(index_service.rebuild(IndexRebuildRequest()))
+        await asyncio.wait_for(entered.wait(), timeout=5)
+        saved = container.model_routing.update(container.model_routing.configuration())
+        config = ProviderConfig(provider_id="concurrent", provider_type=ProviderType.openai_compatible,
+                                name="saved during rebuild", base_url="https://unused.invalid/v1")
+        container.providers.register(config, container.provider_factory.build(config))
+        task_service.update_task(task.task_id, {"title": "saved during rebuild"})
+        # Preparation keeps the old searchable index intact while API I/O is pending.
+        assert repository.stats()["notes"] == 2
+        if failure == "cancel":
+            rebuilding.cancel()
+            expected = asyncio.CancelledError
+        else:
+            release.set()
+            expected = RuntimeError
+        with pytest.raises(expected):
+            await rebuilding
+        assert container.model_routing.configuration().version == saved.config.version
+        assert rows("SELECT provider_id FROM provider_configs")[-1][0] == "concurrent"
+        restored = task_service.get_task(task.task_id)
+        assert restored.title == "saved during rebuild"
+        assert restored.note_id == apple.note_id
+        for table, values in before.items():
+            assert [tuple(row) for row in rows(f"SELECT * FROM {table}")] == values
+
+    asyncio.run(scenario())
+
+
+def local_engine():
+    return RetrievalEngine(HashEmbeddingProvider(), LexicalReranker(), SqliteVecStore())
+
+
+def request(mode=SearchMode.vector):
+    return SearchRequest(query="apple", mode=mode, limit=10)
+
+
+def rows(sql, parameters=()):
+    conn = connect()
+    try:
+        return conn.execute(sql, parameters).fetchall()
+    finally:
+        conn.close()
+
+
+def test_api_index_and_query_use_matching_space_and_keep_local_metadata(runtime):
+    async def scenario():
+        apple, banana = await seed()
+        result = await engine.search(request())
+        assert result.items[0].note_id == banana.note_id
+        baseline = await local_engine().search(request())
+        assert baseline.items[0].note_id == apple.note_id
+        assert rows("SELECT DISTINCT space_id, dimensions FROM routed_block_vectors")[0][:] == ("space-a", 3)
+        assert rows("SELECT COUNT(*) FROM routed_block_vectors")[0][0] == len(apple.blocks) + len(banana.blocks)
+        meta = repository.get_index_meta()
+        assert meta["embedding_model"] == "hash-v1"
+        assert meta["embedding_dim"] == "128"
+        assert len(runtime.calls) == 3
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("failure", ["exception", "local", "missing", "dimension", "corrupt"])
+def test_query_falls_back_to_exact_local_results(runtime, failure):
+    async def scenario():
+        await seed()
+        if failure == "exception":
+            runtime.error = RuntimeError("offline")
+        elif failure == "local":
+            runtime.source = "local"
+        elif failure == "missing":
+            rows("DELETE FROM routed_block_vectors WHERE block_id = (SELECT MIN(block_id) FROM blocks)")
+        elif failure == "dimension":
+            runtime.dimensions = 4
+        else:
+            rows("UPDATE routed_block_vectors SET vector = ?", ("[0, 0, 0]",))
+        actual = await engine.search(request())
+        baseline = await local_engine().search(request())
+        assert actual == baseline
+
+    asyncio.run(scenario())
+
+
+def test_same_dimension_model_switch_never_combines_partial_spaces(runtime):
+    async def scenario():
+        apple, banana = await seed()
+        baseline = await local_engine().search(request())
+        runtime.model_id = "space-b"
+        assert await engine.search(request()) == baseline
+        await note_service.update_note(apple.note_id, markdown="apple orchard")
+        assert {row[0] for row in rows("SELECT DISTINCT space_id FROM routed_block_vectors")} == {"space-a", "space-b"}
+        assert await routed_vectors.search_remote("apple", top_k=10) is None
+        assert await engine.search(request()) == baseline
+        runtime.model_id = "space-a"
+        assert await engine.search(request()) == baseline
+        runtime.model_id = "space-b"
+        await note_service.update_note(banana.note_id, markdown="banana grove")
+        hits = await routed_vectors.search_remote("apple", top_k=10)
+        assert hits is not None and hits[0].id == banana.blocks[0].block_id
+        assert (await engine.search(request())).items[0].note_id == banana.note_id
+
+    asyncio.run(scenario())
+
+
+def test_complete_spaces_coexist_but_only_requested_space_is_ranked(runtime):
+    async def scenario():
+        apple, banana = await seed()
+        conn = connect()
+        try:
+            with transaction(conn):
+                routed_vectors.store_remote(
+                    conn, [apple.blocks[0].block_id, banana.blocks[0].block_id],
+                    routed_vectors.RemoteEmbeddings("space-b", 3, [[1, 0, 0], [0, 1, 0]]),
+                )
+        finally:
+            conn.close()
+        assert (await engine.search(request())).items[0].note_id == banana.note_id
+        runtime.model_id = "space-b"
+        result = await engine.search(request())
+        assert len(result.items) == 2
+        assert result.items[0].note_id == apple.note_id
+
+    asyncio.run(scenario())
+
+
+def test_failed_note_embedding_preserves_save_and_forces_coverage_fallback(runtime):
+    async def scenario():
+        apple, banana = await seed()
+        runtime.error = RuntimeError("offline")
+        await note_service.update_note(banana.note_id, markdown="banana changed")
+        assert (await note_service.get_note(banana.note_id)).markdown == "banana changed"
+        assert rows("SELECT COUNT(*) FROM routed_block_vectors")[0][0] == len(apple.blocks)
+        runtime.error = None
+        assert await engine.search(request()) == await local_engine().search(request())
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("vectors, dimensions, space", [
+    ([], 3, "space-a"),
+    ([[1, 0]], 3, "space-a"),
+    ([[0, 0, 0]], 3, "space-a"),
+    ([[float("nan"), 0, 0]], 3, "space-a"),
+    ([[float("inf"), 0, 0]], 3, "space-a"),
+    ([[True, 0, 0]], 3, "space-a"),
+    ([[1, 0, 0]], 0, "space-a"),
+    ([[1, 0, 0]], 3, "hash-v1"),
+])
+def test_invalid_remote_batch_does_not_break_note_saving(runtime, vectors, dimensions, space):
+    runtime.result_override = SimpleNamespace(
+        source="api", vectors=vectors, dimensions=dimensions, model_id=space,
+    )
+
+    async def scenario():
+        note = await note_service.create_note(title="Apple", markdown="apple orchard", folder=None, tags=[])
+        assert (await local_engine().search(request())).items[0].note_id == note.note_id
+        assert await routed_vectors.search_remote("apple", top_k=10) is None
+
+    asyncio.run(scenario())
+
+
+def test_remote_storage_failure_rolls_back_batch_but_keeps_local_index(runtime):
+    async def scenario():
+        await seed()
+        rows("""CREATE TRIGGER reject_remote_vector BEFORE INSERT ON routed_block_vectors
+                WHEN (SELECT content FROM blocks WHERE block_id = NEW.block_id) = 'second'
+                BEGIN SELECT RAISE(ABORT, 'simulated storage failure'); END""")
+        note = await note_service.create_note(
+            title="Multi", markdown="first\n\nsecond", folder=None, tags=[],
+        )
+        assert len(note.blocks) == 2
+        assert rows(
+            "SELECT COUNT(*) FROM routed_block_vectors r JOIN blocks b USING(block_id) WHERE b.note_id = ?",
+            (note.note_id,),
+        )[0][0] == 0
+        assert rows("SELECT COUNT(*) FROM vec_blocks")[0][0] == rows("SELECT COUNT(*) FROM blocks")[0][0]
+        assert (get_settings().vault_path / note.file_path).exists()
+
+    asyncio.run(scenario())
+
+
+def test_rebuild_and_delete_clear_old_remote_rows_through_foreign_keys(runtime):
+    async def scenario():
+        apple, _ = await seed()
+        await note_service.delete_note(apple.note_id)
+        assert rows("SELECT COUNT(*) FROM routed_block_vectors")[0][0] == 1
+        runtime.source = "local"
+        job = await index_service.rebuild(IndexRebuildRequest())
+        assert job.status == "completed"
+        assert rows("SELECT COUNT(*) FROM routed_block_vectors")[0][0] == 0
+        assert rows("SELECT COUNT(*) FROM vec_blocks")[0][0] == 1
+        runtime.source = "api"
+        runtime.model_id = "space-b"
+        await index_service.rebuild(IndexRebuildRequest())
+        assert [row[0] for row in rows("SELECT space_id FROM routed_block_vectors")] == ["space-b"]
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("operation", ["save", "query", "rebuild"])
+def test_cancellation_propagates_and_mutations_roll_back(runtime, operation):
+    async def scenario():
+        apple, _ = await seed()
+        before = [tuple(row) for row in rows("SELECT * FROM routed_block_vectors ORDER BY block_id")]
+        runtime.error = asyncio.CancelledError()
+        with pytest.raises(asyncio.CancelledError):
+            if operation == "query":
+                await engine.search(request())
+            elif operation == "rebuild":
+                await index_service.rebuild(IndexRebuildRequest())
+            else:
+                await note_service.update_note(apple.note_id, markdown="changed")
+        assert (await note_service.get_note(apple.note_id)).markdown == "apple orchard"
+        assert [tuple(row) for row in rows("SELECT * FROM routed_block_vectors ORDER BY block_id")] == before
+
+    asyncio.run(scenario())
+
+
+@pytest.mark.parametrize("injected", ["embedding", "vector_store", "constructor"])
+def test_injected_engine_dependencies_are_respected(runtime, monkeypatch, injected):
+    async def scenario():
+        apple, _ = await seed()
+        target = engine
+        if injected == "constructor":
+            target = local_engine()
+        elif injected == "embedding":
+            monkeypatch.setattr(engine, "embedding", HashEmbeddingProvider())
+        else:
+            class FakeStore:
+                async def search(self, vector, *, top_k):
+                    assert len(vector) == 128
+                    return [VectorHit(id=apple.blocks[0].block_id, score=1.0)]
+
+            monkeypatch.setattr(engine, "vector_store", FakeStore())
+        runtime.calls.clear()
+        assert (await target.search(request())).items[0].note_id == apple.note_id
+        assert runtime.calls == []
+
+    asyncio.run(scenario())
+
+
+def test_fts_skips_routing_and_hybrid_uses_routed_vector_channel(runtime, monkeypatch):
+    async def scenario():
+        _, banana = await seed()
+        runtime.calls.clear()
+        await engine.search(request(SearchMode.fts))
+        assert runtime.calls == []
+        # Empty lexical channel isolates the vector contribution to hybrid fusion.
+        monkeypatch.setattr(repository, "fts_search", lambda *_: [])
+
+        class PreserveOrder:
+            async def rerank(self, query, candidates):
+                return sorted(candidates, key=lambda candidate: -candidate.score)
+
+        monkeypatch.setattr(engine, "reranker", PreserveOrder())
+        result = await engine.search(request(SearchMode.hybrid))
+        assert result.items[0].note_id == banana.note_id
+        assert runtime.calls == [["apple"]]
+
+    asyncio.run(scenario())
+
+
+def test_arbitrary_dimensions_and_extreme_finite_values(runtime):
+    dimensions = 257
+    runtime.result_override = SimpleNamespace(
+        source="api", model_id="space-wide", dimensions=dimensions,
+        vectors=[[1e308, 1e308] + [0.0] * (dimensions - 2)],
+    )
+
+    async def scenario():
+        note = await note_service.create_note(title="Apple", markdown="apple orchard", folder=None, tags=[])
+        hits = await routed_vectors.search_remote("apple", top_k=1)
+        assert hits is not None and hits[0].id == note.blocks[0].block_id
+        assert hits[0].score == pytest.approx(1.0)
+        vector = json.loads(rows("SELECT vector FROM routed_block_vectors")[0][0])
+        assert len(vector) == dimensions
+
+    asyncio.run(scenario())
+
+
+def test_missing_runtime_uses_unchanged_local_retrieval(runtime, monkeypatch):
+    monkeypatch.setattr(routed_vectors, "get_model_routing", lambda: None)
+
+    async def scenario():
+        await seed()
+        assert await engine.search(request()) == await local_engine().search(request())
+        assert runtime.calls == []
+
+    asyncio.run(scenario())

docs/architecture/AI笔记软件技术栈说明-团队版-v2.3.md

@@ -5,7 +5,7 @@
 > 适用范围：桌面客户端、本地知识库、RAG、Agent、Skill、多模型接入、多模态处理与可选云同步  
 > 目标读者：前端、Rust 桌面端、Python AI Core、算法、测试与后续接手项目的开发成员
 
-> 实施状态更新：2026-09-03。本文同时包含目标架构、当前实现和第二阶段接口基线。第一阶段已完成 Vue Web 联调前端、FastAPI、Knowledge/Retrieval、Agent/Tool/Permission、Skill/Plugin 声明式运行时、Mock/OpenAI-Compatible/Ollama Provider、DeepSeek/OpenAI 预设、模型发现及开发阶段 Fernet 凭据存储。Web Workspace 已通过 FastAPI 接入后端配置的真实单 Vault；第二阶段 Agent Trace 持久化、分页快照、可恢复 SSE、stdio MCP Bridge、隔离 Plugin Host、Plugin Command 与 Plugin Settings/Secret Contract 已完成；RAG Benchmark 检索评测（Dataset 加载、异步运行、SSE 进度、指标聚合与报告）已完成，Agent Benchmark 暂缓。后续继续接入真实音频处理、Provider 协议增强、文档导出、主题包、Trace 可视化、Mermaid 和函数图像。Tauri/Rust Host、Stronghold、原生多 Vault 文件系统和 Sync Server 仍未实现。
+> 实施状态更新：2026-09-04。本文同时包含目标架构、当前实现和第二阶段接口基线。第一阶段已完成 Vue Web 联调前端、FastAPI、Knowledge/Retrieval、Agent/Tool/Permission、Skill/Plugin 声明式运行时、Mock/OpenAI-Compatible/Ollama Provider、DeepSeek/OpenAI 预设、模型发现及开发阶段 Fernet 凭据存储。Web Workspace 已通过 FastAPI 接入后端配置的真实单 Vault；第二阶段 Agent Trace 持久化、分页快照、可恢复 SSE、stdio MCP Bridge、隔离 Plugin Host、Plugin Command 与 Plugin Settings/Secret Contract 已完成。阶段 E 已完成 Responses/Anthropic 协议、国内 logo 预设、Provider 配置恢复和 Embedding/转写/声纹 API 路由；本地语音模型仍为阶段 F 接口预留。RAG Benchmark 检索评测（Dataset 加载、异步运行、SSE 进度、指标聚合与报告）已完成，Agent Benchmark 暂缓。后续继续接入真实音频处理、文档导出、主题包、Trace 可视化、Mermaid 和函数图像。Tauri/Rust Host、Stronghold、原生多 Vault 文件系统和 Sync Server 仍未实现。
 
 ---
 

docs/contracts/后端接口契约-开发版.md

@@ -180,7 +180,7 @@ RunCancelled
 
 - Chat、Agent Run、Agent Events、Tool 列表、Provider 配置生命周期、模型列表和连接测试已经接入 AI Core。
 - Agent Run/Event 已持久化到 SQLite；SSE 帧携带 sequence `id`，断线后可以回放缺失事件。Trace API 与 Benchmark 共用同一事件事实，并在入库前执行 Secret 脱敏和结果限长。
-- Provider Adapter 当前包含 Mock、真正增量 SSE 的 OpenAI-Compatible Chat Completions，以及 Ollama JSONL Streaming。
+- Provider Adapter 当前包含 Mock、增量 SSE 的 OpenAI-Compatible Chat Completions、OpenAI Responses、Anthropic Messages，以及 Ollama JSONL Streaming。阶段 E 增加 `/api/model-routing`、`/api/models/embeddings`、`/api/media/speaker-matches`；具体请求和阶段边界见第二阶段契约 §8.5。
 - Notes、Search、Index、Skills、Plugins、Tasks 和 Provider 生命周期均已接入业务服务。
 - Workspace 已接入后端配置的真实 Vault；文件树、笔记读写、文件/目录新建、重命名和删除不再使用前端 Mock Fallback。
 - Note Move 保留 `note_id`；Citation 的字符偏移统一使用 UTF-16 code unit，供浏览器编辑器直接定位。

docs/contracts/第二阶段接口契约-开发版.md

@@ -718,6 +718,8 @@ stdio 命令始终以 executable 与 args 数组通过 `shell=False` 启动；
 
 ## 8. Provider Adapter 扩展
 
+> 阶段 E 实施更新（2026-09-04）：OpenAI Responses、Anthropic Messages、Chat Completions 与 Ollama Adapter 已接入；国内提供商 logo 预设、独立凭据输入、配置恢复、Embedding / 转写 / 声纹 API 路由已实现。真实本地语音模型仍属于阶段 F。实现细节见 [模型提供商与模型发现开发说明](../development/模型提供商与模型发现开发说明.md)。
+
 第二阶段不新增平行 Provider CRUD，继续使用第一阶段接口：
 
 ```text
@@ -734,7 +736,7 @@ POST   /api/chat
 
 ### 8.1 ModelInfo 扩展
 
-`GET /api/providers/{provider_id}/models` 的 item 增加可选字段：
+以下为后续计划的可选字段；阶段 E 的 `GET /api/providers/{provider_id}/models` 实际 item 仍只包含 `model`、`display_name`、`capabilities`：
 
 ```json
 {
@@ -774,6 +776,8 @@ Done
 - 浏览器取消 Fetch 或 SSE 后，服务端必须取消上游 Provider 请求。
 - 不支持 reasoning 的 Provider 不发送伪造 ThinkingDelta。
 
+阶段 E 补充：取消或关闭迭代器直接关闭上游连接并传播取消，不向已断开的客户端继续发送 Done。内部带点号、长名称的工具映射为合法的 64 字符以内名称，响应恢复原命名空间，映射在请求内隔离。实际流中断错误码为 `PROVIDER_STREAM_TRUNCATED`；`PROVIDER_INVALID_RESPONSE` 用于无效结构/参数。上面的 `Done.data.status` 适用于真实 HTTP Adapter；开发 Mock 保留原有测试事件。
+
 ### 8.3 Provider 一致性测试 Contract
 
 每个 Adapter 使用相同 Case 描述：
@@ -811,6 +815,25 @@ MODEL_CONTEXT_LENGTH_EXCEEDED
 
 ---
 
+### 8.5 阶段 E 模型路由接口（已实现）
+
+| 方法 | 路径 | 契约 |
+| --- | --- | --- |
+| GET | `/api/model-routing` | `{config, local_backends}` |
+| PUT | `/api/model-routing` | 提交 ModelRoutingConfig，返回递增版本配置 |
+| POST | `/api/models/embeddings` | `{texts: string[]}` → `{vectors, source, model_id, dimensions, fallback_reason}` |
+| POST | `/api/media/speaker-matches` | `{attachment_id, reference_attachment_id}` → `{score, source, fallback_reason}` |
+
+`ModelRoutingConfig` 包含 `version`、`embedding`、`transcription`、`speaker_matching`。每个能力为 null 或 `{provider_id, model, endpoint, dimensions?}`。dimensions 仅 Embedding 使用，范围 1–16384；endpoint 是选定 Provider 下不带查询的路径，不能传第二个 URL。PUT 不提交 GET 返回的 local_backends；版本冲突返回 409 `MODEL_ROUTING_VERSION_CONFLICT`。删除仍被引用的 Provider 返回 409 `PROVIDER_IN_USE`。
+
+本阶段远程能力仅接受 OpenAI Chat / Compatible HTTP 配置，默认路径分别是 `/embeddings`、`/audio/transcriptions`、`/audio/speaker-matches`。最后一个是本项目自定义 multipart 接口，**不是公共 OpenAI 标准协议**：请求 model、file、reference_file，响应有限 0–1 的 score。转写采用 multipart model、file、可选 language，必须返回非空 text。文件来自受控附件目录，限制 25 MiB。
+
+`TranscriptionJob` 新增可选 `source: api|local|sidecar` 和 `fallback_reason`。保留已有转写 Job 路径；`diarization=true` 返回失败 Job，错误为 `DIARIZATION_NOT_IMPLEMENTED`，不能静默忽略。
+
+无配置时调用本地接口；有配置时 API 优先，网络/鉴权/限流/结果无效时回退。本地 Embedding 当前为 hash 占位；本地 ASR / 声纹后端尚未安装时返回 `LOCAL_MODEL_NOT_INSTALLED`，而非伪成功。远程 Embedding 独立索引并检查完整覆盖，模型变化后需重建；不与本地向量混算。
+
+Provider PATCH 支持 provider_type；普通配置持久化到 SQLite，凭据继续独立加密。预设新增 logo_id、description、capabilities，前端图标随应用打包。
+
 ## 9. RAG / Agent Benchmark
 
 Benchmark Service 同时提供 Python 调用接口和本地 HTTP 接口。CLI、测试和前端报告页调用同一 Service，不各自实现指标。
@@ -1544,3 +1567,7 @@ frontend/src/
 ```
 
 目录调整应按实际代码规模渐进进行。Router 只做参数接收和错误映射，状态机、第三方 SDK 与文件处理继续放在 Service/Adapter 层。
+
+### Benchmark Embedding 运行归属（阶段 E 集成修复）
+
+`config_snapshot.local_embedding` 仅表示本地基线；`config_snapshot.embedding` 为 `{ "policy": "per_case", "details": "cases[].embedding" }`。报告与 CaseCompleted 事件的逐样本 `embedding` 包含实际 source（api/local/not_used/unavailable）、model_id、dimensions，以及可选 version、fallback_reason、requested_route、route_version、attempted_space。requested_route 仅含提供商引用、模型、相对端点和维度，不包含 API Key 或凭据引用。FTS 不使用 Embedding，标记 not_used；远程失败或索引不完整回退时记录实际本地模型及原因。

docs/development/AI-Core与Agent-Core开发说明.md

@@ -342,7 +342,7 @@ Skill Manifest
 
 前端智能体页面已经完成中文联调：运行状态、Agent Event、内置 Tool、Permission 和常用事件详情字段均通过集中标签映射展示中文；`notes.search` 等技术 ID 继续保留，便于与后端 Trace、日志和接口契约对应。
 
-- 已实现 Mock、OpenAI-Compatible Chat Completions 与 Ollama Adapter；OpenAI Responses 和 Anthropic Messages 尚未实现。
+- 已实现 Mock、OpenAI-Compatible Chat Completions、Ollama、OpenAI Responses 和 Anthropic Messages Adapter；阶段 E 同时完成国内预设、持久化配置和能力模型路由，详见 [模型提供商与模型发现开发说明](模型提供商与模型发现开发说明.md)。
 - Provider 配置暂存内存，后续通过 Repository 接入 SQLite；PATCH 已支持用显式 `null` 清空 base URL、默认模型和凭据引用。
 - Run/Trace 已通过 Repository 接入 SQLite；后续增加按保留策略归档和 Benchmark 引用保护。
 - Permission 已有核心等待/恢复机制，前端确认 UI 已完成联调和中文展示。

docs/development/Benchmark开发说明.md

@@ -64,7 +64,9 @@ BENCHMARK_CASE_EVALUATION_FAILED
 
 ## 配置快照
 
-报告与运行记录保存 `config_snapshot`：dataset hash/version、modes、retrieval 参数、Embedding model/version/dim、Reranker、索引元数据、App 版本与环境、Python 版本，保证不同实验结果可复现。
+报告与运行记录保存 `config_snapshot`：dataset hash/version、modes、retrieval 参数、Reranker、索引元数据、App 版本与环境、Python 版本。`local_embedding` 记录本地基线 model/version/dim；`embedding.policy = per_case` 表示实际来源以逐样本结果为准，不能把本地基线当作本次使用的模型。
+
+每个 `RAGCaseResult.embedding`（同时出现在报告 cases 和 CaseCompleted SSE 中）记录 `source`（api/local/not_used/unavailable）、实际 `model_id` 空间标识、`dimensions`、本地 `version`、`fallback_reason`。远程路由还记录请求时的 `route_version` 和 `requested_route`（provider_id/model/endpoint/dimensions，不含凭据）、成功生成查询向量后的 `attempted_space`。FTS 标记 not_used；调用失败而未完成向量检索时标记 unavailable。API 不可用或远程索引缺失时，实际模型仍记录最终使用的本地基线。配置允许在样本间改变，逐样本记录对应实际调用；汇总指标可能包含多种空间，比较实验时需检查 cases。记录使用任务局部上下文隔离，并发评测不会相互覆盖。
 
 ## 测试
 

docs/development/模型提供商与模型发现开发说明.md

@@ -1,107 +1,107 @@
-# 模型提供商与模型发现开发说明
+# 模型提供商、协议适配与模型路由开发说明
 
-> 更新日期：2026-09-02。OpenAI、DeepSeek、Ollama 预设、模型自动发现、默认模型选择和开发阶段加密凭据存储均已实现并接入设置页。
+> 更新日期：2026-09-04。阶段 E 实现记录。本地小模型的实际安装与多模态队列属于阶段 F；本阶段保留并测试可注入的本地后端接口。
 
-## 1. 本次目标
+## 1. 设置与凭据
 
-本次完善设置页的模型提供商配置，不改变 Agent、Chat 和 Skill 对统一 Model Core 接口的依赖：
+设置 → 模型提供商 → 新增 Provider 提供可搜索的 logo 预设网格，包含 DeepSeek、Kimi、阿里云百炼、智谱 GLM、火山方舟、硅基流动、百度千帆、腾讯混元、MiniMax、阶跃星辰，以及 OpenAI Chat / Responses、Anthropic 和 Ollama。图标打包到前端，使用时不请求第三方图片服务；来源和许可见前端 assets/providers 目录。
 
-- 提供 OpenAI、DeepSeek 和 Ollama 配置预设；
-- 保存 Provider 后自动获取该账号或服务当前可用的模型列表；
-- 支持手动刷新模型列表和选择默认模型；
-- 保留自定义 OpenAI-Compatible 服务入口；
-- 不在 Vue、FastAPI 配置或仓库文件中保存、回显 API Key 明文。
+预设返回 `preset_id`、`logo_id`、`name`、`provider_type`、`base_url`、`requires_credential`、`description` 和 `capabilities`。能力标签表示预设接入范围，不保证该账号的每个模型支持全部能力。厂商专用媒体协议、Coding Plan 和海外地域需要使用对应地址，不能仅凭厂商名称推断协议兼容。
 
-## 2. 接口与实现
+预设和自定义服务都可以直接输入 API Key。每个新配置分配独立 Credential ID，避免同厂商多账号相互覆盖。明文只留在密码输入框和专用请求中，提交、失败、切换预设及关闭时清空；密钥不进入 Pinia、localStorage、Provider 配置响应或模型路由。
 
-### 2.1 Provider 预设
+凭据继续使用独立的 `PUT /api/credentials/{credential_id}` 和 Fernet 开发存储。`plugin.*`、`mcp.*` 是保留命名空间。桌面端阶段仍需要把主密钥管理迁移到 Stronghold。保存密钥与保存 Provider 是两个请求，Provider 保存失败时可能留下未引用的加密凭据，可通过凭据删除接口清理。
 
-新增接口：
+Provider 配置和 Credential ID 写入 SQLite `provider_configs`，重启后恢复。Mock 为内置 Provider，不能编辑或删除。PATCH 已支持变更 `provider_type` 并重新创建 Adapter；Base URL 限制为不带用户信息、查询或 fragment 的 HTTP(S) 地址。
 
-```http
-GET /api/providers/presets
+## 2. 协议适配
+
+支持的协议是 OpenAI Chat Completions、OpenAI-Compatible、OpenAI Responses、Anthropic Messages 和 Ollama。Agent、Chat、Skill 仍只依赖内部 `ModelRequest` / `ModelEvent` / `ProviderTurn`，不直接解释厂商协议。
+
+Adapter 负责消息及 Tool 历史转换、增量文本、可用的 reasoning delta、工具参数片段、usage、终止与统一错误。外部错误正文不原样返回；HTTP 鉴权、限流、超时、无效数据、流中断分别映射为内部错误。取消继续传播并关闭上游连接，不触发第二次本地推理。
+
+`GET /api/providers/{provider_id}/models` 用于发现模型。模型列表不等于每个模型的能力承诺；部分厂商或代理不提供 `/models` 时，允许直接手动输入模型 ID。连接测试验证模型发现接口，不代表每一种媒体模型已完成真实推理验收。
+
+## 3. 三类模型路由
+
+接口：
+
+| 方法 | 路径 | 用途 |
+| --- | --- | --- |
+| GET | `/api/model-routing` | 读取配置和本地后端状态 |
+| PUT | `/api/model-routing` | 带版本更新三类模型绑定 |
+| POST | `/api/models/embeddings` | 文本向量，返回来源和回退原因 |
+| POST | `/api/media/transcriptions` | 附件转写作业 |
+| GET | `/api/media/transcriptions/{job_id}` | 获取转写作业 |
+| POST | `/api/media/speaker-matches` | 两个音频附件的声纹相似度 |
+
+设置 → 索引与模型分别选择 Embedding、音频转文本和声纹匹配。三种绑定互相独立，可使用不同提供商、模型、密钥和 API 路径。
+
+GET / PUT 响应：
+
+```json
+{
+  "config": {
+    "version": 1,
+    "embedding": {
+      "provider_id": "provider_example",
+      "model": "your-embedding-model",
+      "endpoint": "/embeddings",
+      "dimensions": null
+    },
+    "transcription": null,
+    "speaker_matching": null
+  },
+  "local_backends": [
+    {"capability": "embedding", "status": "placeholder", "message": "当前为 hash-v1 占位向量"},
+    {"capability": "transcription", "status": "not_installed", "message": "阶段 F 接入"},
+    {"capability": "speaker_matching", "status": "not_installed", "message": "阶段 F 接入"}
+  ]
+}
 ```
 
-预设由后端 `ProviderFactory` 提供，前端只消费名称、协议类型、Base URL 和是否需要凭据等配置元数据，不直接实现厂商协议。
+PUT body 只提交 `config` 的内容。`version` 为读取时的版本，成功递增；并发更新返回 `MODEL_ROUTING_VERSION_CONFLICT`。绑定为空表示使用本地后端。删除仍被路由引用的 Provider 返回 `PROVIDER_IN_USE`，须先解除绑定。
 
-当前预设：
+本阶段三类远程路由使用 `openai_chat` / `openai_compatible` 的 Bearer HTTP 配置，endpoint 只能是该提供商下的路径。Responses、Anthropic 和 Ollama 原生协议不冒充上述媒体协议；Ollama 用户需要另建兼容 HTTP 配置才能用于当前远程 Embedding 接口。
 
-| 提供商 | Provider Type | Base URL | 默认 Credential ID |
-| --- | --- | --- | --- |
-| OpenAI | `openai_chat` | `https://api.openai.com/v1` | `openai` |
-| DeepSeek | `openai_compatible` | `https://api.deepseek.com` | `deepseek` |
-| Ollama | `ollama` | `http://127.0.0.1:11434` | 无 |
+调用规则：无绑定 → 本地接口；有绑定 → API → 校验结果 → 失败或无效时调用本地接口。Provider 停用、密钥缺失、鉴权失败、限流、网络超时及无效结果均可回退；用户取消不会回退。附件不存在、大小非法等输入错误直接返回，不把用户输入错误当成模型故障。
 
-OpenAI 和 DeepSeek 都通过项目已有的 `OpenAICompatibleProvider` 访问。模型发现分别请求 Base URL 下的 `/models`，不引入厂商 SDK。
+## 4. Embedding 与索引一致性
 
-### 2.2 自动获取模型
+请求使用 `model`、`input`、`encoding_format: float`；只有明确配置维度时才发送 `dimensions`。按最多 32 条分批请求，全部批次有效才使用 API 结果。校验返回数量、连续唯一 index、维度一致性、有限数值、非零范数，并 L2 归一化。维度可为 1–16384，不截断、补零或混用不同模型的向量。
 
-模型列表继续使用既有接口：
+返回 `vectors`、`source`、`model_id`、`dimensions`、`fallback_reason`。远程空间 ID 由完整 API URL、模型和实际维度生成；即使维度相同，不同模型的空间也不同。
 
-```http
-GET /api/providers/{provider_id}/models
-```
+笔记索引始终保留现有 hash/sqlite-vec 本地基线，远程向量写入独立 `routed_block_vectors` 表。远程查询只搜索对应空间，并要求覆盖全部当前 Block。API 失败、索引缺失、不完整或损坏时使用完整本地索引。切换模型、URL、维度后应在设置中重建全部索引。旧空间与当前文本不会混合打分，删除笔记或重建索引会通过外键清理远程向量。
 
-设置页在以下时机调用该接口：
+当前远程侧索引采用 SQLite JSON 向量和精确余弦扫描，复杂度 O(Block 数量 × 维度)，适用于当前小型 Vault；后续大规模索引需替换为按空间隔离的 ANN。网络等待发生在数据库写事务之前，当前仍会增加保存或重建延迟，异步索引队列尚未接入。全量重建先在内存中准备全部向量，再使用一个 SQLite 事务更新元数据、FTS、本地与远程向量及任务关联；取消或失败只回滚索引事务，不再覆盖整库文件。准备阶段保留旧索引可查询，代价是内存同时容纳本次重建的向量。
 
-- Provider 列表加载完成后，为所有已启用 Provider 自动刷新；
-- 新增或编辑 Provider 保存成功后自动刷新；
-- 用户点击“刷新模型”时手动刷新；
-- 打开已有 Provider 的编辑窗口时刷新可选模型。
+OpenAI Compatible 流中，工具名称可能分片返回。适配器在本轮输出结束后发送完整工具名及已缓冲参数，避免把名称片段当作工具 ID；文本与推理内容仍逐片发送。
 
-前端按模型名称排序并按 `model_id` 去重。获取结果保存在 `providerStore.modelsByProvider`，加载状态和错误按 Provider 隔离，单个外部服务失败不会阻止其他服务展示。
+无 API 时使用的 `HashEmbeddingProvider` 是确定性特征哈希占位实现，**不是已集成的小型语义模型**。真实本地 Embedding 可实现既有 `EmbeddingProvider` 接口注入。
 
-获取成功后，Provider 卡片展示模型数量和默认模型下拉框。更换默认模型会调用 Provider PATCH 接口写回配置；编辑窗口仍允许手动输入模型 ID，以兼容未出现在列表中的代理模型或部署别名。
+## 5. 音频与声纹边界
 
-### 2.3 错误处理
+转写默认请求 `/audio/transcriptions`，multipart 字段 `model`、可选 `language` 和 `file`，响应必须包含非空字符串 `text`。已有纯文本附件和 Host 旁路 `.txt` 导入保留，来源标记 `sidecar`，不伪称 ASR。转写作业新增 `source`、`fallback_reason`；回退失败的作业记录 `LOCAL_MODEL_NOT_INSTALLED` 等明确错误。作业目前同步执行、限量保存在内存中，不是持久化异步队列。
 
-Provider Adapter 的错误在 FastAPI 路由转换为统一 API Error：
+声纹匹配使用**本项目自定义 HTTP 契约**，默认 `/audio/speaker-matches`，multipart 字段 `model`、`file`、`reference_file`；响应为 `{"score": 0.85}`，score 必须为有限的 0–1 数值。公共入口只接受 `attachment_id` 和 `reference_attachment_id`，不接收任意文件路径。此接口用于一对一声纹比对，不等同于 pyannote 说话人分离，也不声称任意国内厂商原生支持该路径。
 
-| Provider Error | HTTP 状态 |
-| --- | --- |
-| `PROVIDER_AUTH_FAILED` | 401 |
-| `MODEL_NOT_FOUND` | 404 |
-| `PROVIDER_RATE_LIMITED` | 429 |
-| `PROVIDER_TIMEOUT` | 504 |
-| 其他 Provider 可用性错误 | 502 |
+媒体文件限制 1 字节至 25 MiB，API 响应限制 16 MiB，单次请求超时 30 秒。文件从后端受控附件目录读取，使用结束或取消时关闭句柄。
 
-前端在对应 Provider 卡片内展示失败原因，并允许用户修正 Credential ID、Base URL 后重新获取。
+`LocalSpeechBackend` 提供 `transcribe` 和 `match` 接口。阶段 E 默认 `PendingSpeechBackend` 明确报告未安装；阶段 F 接入 faster-whisper、pyannote.audio 及模型资源后替换。当前 `diarization=true` 明确返回失败作业 `DIARIZATION_NOT_IMPLEMENTED`，不会静默忽略。视频解码、TTS、视频生成及厂商专用异步媒体协议不在本次交付内。
 
-## 3. 凭据边界
+## 6. 官方协议依据与验证
 
-设置页选择 OpenAI 或 DeepSeek 预设后展示密码类型的 API Key 输入框，不再要求用户理解 Credential ID。输入值只存在于表单的临时 `ref`，不会写入 Pinia 或 localStorage；请求完成、取消表单或失败后都会清空。
+国内通用地址核对依据：[阿里云百炼兼容接口](https://help.aliyun.com/zh/model-studio/compatibility-of-openai-with-dashscope)、[百度千帆兼容接口](https://cloud.baidu.com/doc/qianfan/s/Hmh4suq26)、[腾讯混元兼容接口](https://cloud.tencent.com/document/product/1729/111007)、[MiniMax 文本接口](https://platform.minimaxi.com/docs/guides/text-generation)、[阶跃星辰通用与套餐地址区别](https://platform.stepfun.com/docs/zh/step-plan/overview)、[火山方舟 API](https://www.volcengine.com/docs/82379/1795150)、[智谱开放接口](https://docs.bigmodel.cn/api-reference/文件-api/文件列表)。模型 ID 以账号实际开通列表为准，不写死“最新模型”。
 
-API Key 通过独立接口写入：
+流式事件依据：[OpenAI Responses streaming](https://platform.openai.com/docs/api-reference/responses-streaming)、[Anthropic streaming](https://platform.claude.com/docs/en/build-with-claude/streaming)。音频请求依据：[SiliconFlow transcription](https://docs.siliconflow.com/en/api-reference/audio/create-audio-transcriptions)。
 
-```http
-GET    /api/credentials/{credential_id}
-PUT    /api/credentials/{credential_id}
-DELETE /api/credentials/{credential_id}
-```
+自动化验证使用虚构凭据、本地附件、httpx.MockTransport 和可注入本地模型，覆盖流式 Tool/Usage/取消、错误映射、回退、索引空间隔离、版本冲突、重启恢复和界面凭据行为。没有使用真实 API Key 或向厂商发送推理请求。审阅修复并同步主分支后验证：后端全量 447 项、前端 76 项测试通过，Vue/TypeScript 类型检查和生产构建通过，浅色/深色预设页面与路由保存经过浏览器检查，git diff --check 通过。后端仅保留既有 Starlette 测试客户端弃用提示，前端保留既有大 bundle 提示。
 
-PUT 请求使用 Pydantic `SecretStr` 接收密钥，响应仅包含 Credential ID 和 `configured` 状态。后端使用 Fernet 认证加密，将密文保存到 `data/credentials/credentials.json`，主密钥保存到 `data/credentials/master.key`；目录和文件尽可能设置为仅当前用户可访问并整体排除版本控制。写入采用临时文件替换，避免进程中断留下半写文件。Provider 发起请求时按 Credential ID 解密，解密失败转换为统一 Provider Error，任何读取接口均不返回明文。
-
-本地开发存储的主密钥与密文仍位于同一用户数据目录，因此它解决的是仓库泄漏、普通配置误提交和静态明文暴露，不等同于操作系统安全硬件或 Stronghold。Tauri 集成后应以 Stronghold 实现替换 `EncryptedCredentialStore`。无界面环境仍兼容 `OPENAI_API_KEY`、`DEEPSEEK_API_KEY` 和 Host 注入的 `AINOTE_CREDENTIAL_<ID>`；设置页保存的本地密钥优先，环境变量仅作为回退。
-
-自动化测试仅使用虚构测试值，验证磁盘文件不包含明文、加解密往返、API 响应不泄密，以及 Provider 能用解密后的值构造 Authorization Header。本次没有使用真实 OpenAI 或 DeepSeek Key，也没有向厂商发起真实请求。
-
-## 4. 验证
-
-后端：
-
-```bash
+```powershell
 cd backend
 uv run pytest -q -p no:cacheprovider
-```
-
-前端：
-
-```bash
-cd frontend
+cd ../frontend
 pnpm test
 pnpm build
 ```
-
-自动化验证覆盖 Provider 预设、OpenAI-Compatible `/models` 请求与鉴权头、模型映射、前端自动刷新、排序去重及按 Provider 隔离错误。生产构建同时执行 Vue 和 TypeScript 类型检查。
-
-当前完整回归基线：后端 136 项测试、前端 29 项测试通过，前端类型检查和生产构建通过。Provider 配置目前仍保存在内存 Registry，AI Core 重启后需要重新创建；凭据密文会保留。`plugin.*` 为 Plugin Secret 保留命名空间，Provider 配置、临时测试凭据和通用凭据 API 均拒绝该前缀。OpenAI Responses 与 Anthropic Messages Adapter 尚未实现，设置页正式预设不会使用这两种协议。

frontend/public/provider-icons-LICENSE.txt

@@ -0,0 +1,40 @@
+Lobe Icons — Copyright (c) 2023 LobeHub. MIT license; see LICENSE.
+Source: https://github.com/lobehub/lobe-icons
+Revision: 4aaf4ee1fb2678a7f989ea570f0f6ce14a9abf75
+Source directory: packages/static-svg/icons/
+Assets are bundled locally. Brand trademarks belong to their respective owners.
+File mapping (local: upstream):
+anthropic.svg: anthropic.svg
+baidu.svg: baidu-color.svg
+deepseek.svg: deepseek-color.svg
+hunyuan.svg: hunyuan-color.svg
+kimi.svg: kimi-color.svg
+minimax.svg: minimax-color.svg
+ollama.svg: ollama.svg
+openai.svg: openai.svg
+qwen.svg: qwen-color.svg
+siliconflow.svg: siliconcloud-color.svg
+stepfun.svg: stepfun-color.svg
+volcengine.svg: volcengine-color.svg
+zhipu.svg: zhipu-color.svg
+MIT License
+
+Copyright (c) 2023 LobeHub
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

frontend/src/assets/providers/ATTRIBUTION.txt

@@ -0,0 +1,19 @@
+Lobe Icons — Copyright (c) 2023 LobeHub. MIT license; see LICENSE.
+Source: https://github.com/lobehub/lobe-icons
+Revision: 4aaf4ee1fb2678a7f989ea570f0f6ce14a9abf75
+Source directory: packages/static-svg/icons/
+Assets are bundled locally. Brand trademarks belong to their respective owners.
+File mapping (local: upstream):
+anthropic.svg: anthropic.svg
+baidu.svg: baidu-color.svg
+deepseek.svg: deepseek-color.svg
+hunyuan.svg: hunyuan-color.svg
+kimi.svg: kimi-color.svg
+minimax.svg: minimax-color.svg
+ollama.svg: ollama.svg
+openai.svg: openai.svg
+qwen.svg: qwen-color.svg
+siliconflow.svg: siliconcloud-color.svg
+stepfun.svg: stepfun-color.svg
+volcengine.svg: volcengine-color.svg
+zhipu.svg: zhipu-color.svg

frontend/src/assets/providers/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 LobeHub
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

frontend/src/assets/providers/anthropic.svg

@@ -0,0 +1 @@
+<svg fill="currentColor" fill-rule="evenodd" height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Anthropic</title><path d="M13.827 3.52h3.603L24 20h-3.603l-6.57-16.48zm-7.258 0h3.767L16.906 20h-3.674l-1.343-3.461H5.017l-1.344 3.46H0L6.57 3.522zm4.132 9.959L8.453 7.687 6.205 13.48H10.7z"></path></svg>

frontend/src/assets/providers/baidu.svg

@@ -0,0 +1 @@
+<svg height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Baidu</title><path d="M8.859 11.735c1.017-1.71 4.059-3.083 6.202.286 1.579 2.284 4.284 4.397 4.284 4.397s2.027 1.601.73 4.684c-1.24 2.956-5.64 1.607-6.005 1.49l-.024-.009s-1.746-.568-3.776-.112c-2.026.458-3.773.286-3.773.286l-.045-.001c-.328-.01-2.38-.187-3.001-2.968-.675-3.028 2.365-4.687 2.592-4.968.226-.288 1.802-1.37 2.816-3.085zm.986 1.738v2.032h-1.64s-1.64.138-2.213 2.014c-.2 1.252.177 1.99.242 2.148.067.157.596 1.073 1.927 1.342h3.078v-7.514l-1.394-.022zm3.588 2.191l-1.44.024v3.956s.064.985 1.44 1.344h3.541v-5.3h-1.528v3.979h-1.46s-.466-.068-.553-.447v-3.556zM9.82 16.715v3.06H8.58s-.863-.045-1.126-1.049c-.136-.445.02-.959.088-1.16.063-.203.353-.671.951-.85H9.82zm9.525-9.036c2.086 0 2.646 2.06 2.646 2.742 0 .688.284 3.597-2.309 3.655-2.595.057-2.704-1.77-2.704-3.08 0-1.374.277-3.317 2.367-3.317zM4.24 6.08c1.523-.135 2.645 1.55 2.762 2.513.07.625.393 3.486-1.975 4-2.364.515-3.244-2.249-2.984-3.544 0 0 .28-2.797 2.197-2.969zm8.847-1.483c.14-1.31 1.69-3.316 2.931-3.028 1.236.285 2.367 1.944 2.137 3.37-.224 1.428-1.345 3.313-3.095 3.082-1.748-.226-2.143-1.823-1.973-3.424zM9.425 1c1.307 0 2.364 1.519 2.364 3.398 0 1.879-1.057 3.4-2.364 3.4s-2.367-1.521-2.367-3.4C7.058 2.518 8.118 1 9.425 1z" fill="#2932E1" fill-rule="nonzero"></path></svg>

frontend/src/assets/providers/deepseek.svg

@@ -0,0 +1 @@
+<svg height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>DeepSeek</title><path d="M23.748 4.482c-.254-.124-.364.113-.512.234-.051.039-.094.09-.137.136-.372.397-.806.657-1.373.626-.829-.046-1.537.214-2.163.848-.133-.782-.575-1.248-1.247-1.548-.352-.156-.708-.311-.955-.65-.172-.241-.219-.51-.305-.774-.055-.16-.11-.323-.293-.35-.2-.031-.278.136-.356.276-.313.572-.434 1.202-.422 1.84.027 1.436.633 2.58 1.838 3.393.137.093.172.187.129.323-.082.28-.18.552-.266.833-.055.179-.137.217-.329.14a5.526 5.526 0 01-1.736-1.18c-.857-.828-1.631-1.742-2.597-2.458a11.365 11.365 0 00-.689-.471c-.985-.957.13-1.743.388-1.836.27-.098.093-.432-.779-.428-.872.004-1.67.295-2.687.684a3.055 3.055 0 01-.465.137 9.597 9.597 0 00-2.883-.102c-1.885.21-3.39 1.102-4.497 2.623C.082 8.606-.231 10.684.152 12.85c.403 2.284 1.569 4.175 3.36 5.653 1.858 1.533 3.997 2.284 6.438 2.14 1.482-.085 3.133-.284 4.994-1.86.47.234.962.327 1.78.397.63.059 1.236-.03 1.705-.128.735-.156.684-.837.419-.961-2.155-1.004-1.682-.595-2.113-.926 1.096-1.296 2.746-2.642 3.392-7.003.05-.347.007-.565 0-.845-.004-.17.035-.237.23-.256a4.173 4.173 0 001.545-.475c1.396-.763 1.96-2.015 2.093-3.517.02-.23-.004-.467-.247-.588zM11.581 18c-2.089-1.642-3.102-2.183-3.52-2.16-.392.024-.321.471-.235.763.09.288.207.486.371.739.114.167.192.416-.113.603-.673.416-1.842-.14-1.897-.167-1.361-.802-2.5-1.86-3.301-3.307-.774-1.393-1.224-2.887-1.298-4.482-.02-.386.093-.522.477-.592a4.696 4.696 0 011.529-.039c2.132.312 3.946 1.265 5.468 2.774.868.86 1.525 1.887 2.202 2.891.72 1.066 1.494 2.082 2.48 2.914.348.292.625.514.891.677-.802.09-2.14.11-3.054-.614zm1-6.44a.306.306 0 01.415-.287.302.302 0 01.2.288.306.306 0 01-.31.307.303.303 0 01-.304-.308zm3.11 1.596c-.2.081-.399.151-.59.16a1.245 1.245 0 01-.798-.254c-.274-.23-.47-.358-.552-.758a1.73 1.73 0 01.016-.588c.07-.327-.008-.537-.239-.727-.187-.156-.426-.199-.688-.199a.559.559 0 01-.254-.078c-.11-.054-.2-.19-.114-.358.028-.054.16-.186.192-.21.356-.202.767-.136 1.146.016.352.144.618.408 1.001.782.391.451.462.576.685.914.176.265.336.537.445.848.067.195-.019.354-.25.452z" fill="#4D6BFE"></path></svg>

frontend/src/assets/providers/hunyuan.svg

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frontend/src/assets/providers/kimi.svg

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frontend/src/assets/providers/minimax.svg

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frontend/src/assets/providers/ollama.svg

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frontend/src/assets/providers/openai.svg

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frontend/src/assets/providers/qwen.svg

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frontend/src/assets/providers/siliconflow.svg

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frontend/src/assets/providers/stepfun.svg

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frontend/src/assets/providers/volcengine.svg

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frontend/src/assets/providers/zhipu.svg

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+<svg height="1em" style="flex:none;line-height:1" viewBox="0 0 24 24" width="1em" xmlns="http://www.w3.org/2000/svg"><title>Zhipu</title><path d="M11.991 23.503a.24.24 0 00-.244.248.24.24 0 00.244.249.24.24 0 00.245-.249.24.24 0 00-.22-.247l-.025-.001zM9.671 5.365a1.697 1.697 0 011.099 2.132l-.071.172-.016.04-.018.054c-.07.16-.104.32-.104.498-.035.71.47 1.279 1.186 1.314h.366c1.309.053 2.338 1.173 2.286 2.523-.052 1.332-1.152 2.38-2.478 2.327h-.174c-.715.018-1.274.64-1.239 1.368 0 .124.018.23.053.337.209.373.54.658.96.8.75.23 1.517-.125 1.9-.782l.018-.035c.402-.64 1.17-.96 1.92-.711.854.284 1.378 1.226 1.099 2.167a1.661 1.661 0 01-2.077 1.102 1.711 1.711 0 01-.907-.711l-.017-.035c-.2-.323-.463-.58-.851-.711l-.056-.018a1.646 1.646 0 00-1.954.746 1.66 1.66 0 01-1.065.764 1.677 1.677 0 01-1.989-1.279c-.209-.906.332-1.83 1.257-2.043a1.51 1.51 0 01.296-.035h.018c.68-.071 1.151-.622 1.116-1.333a1.307 1.307 0 00-.227-.693 2.515 2.515 0 01-.366-1.403 2.39 2.39 0 01.366-1.208c.14-.195.21-.444.227-.693.018-.71-.506-1.261-1.186-1.332l-.07-.018a1.43 1.43 0 01-.299-.07l-.05-.019a1.7 1.7 0 01-1.047-2.114 1.68 1.68 0 012.094-1.101zm-5.575 10.11c.26-.264.639-.367.994-.27.355.096.633.379.728.74.095.362-.007.748-.267 1.013-.402.41-1.053.41-1.455 0a1.062 1.062 0 010-1.482zm14.845-.294c.359-.09.738.024.992.297.254.274.344.665.237 1.025-.107.36-.396.634-.756.718-.551.128-1.1-.22-1.23-.781a1.05 1.05 0 01.757-1.26zm-.064-4.39c.314.32.49.753.49 1.206 0 .452-.176.886-.49 1.206-.315.32-.74.5-1.185.5-.444 0-.87-.18-1.184-.5a1.727 1.727 0 010-2.412 1.654 1.654 0 012.369 0zm-11.243.163c.364.484.447 1.128.218 1.691a1.665 1.665 0 01-2.188.923c-.855-.36-1.26-1.358-.907-2.228a1.68 1.68 0 011.33-1.038c.593-.08 1.183.169 1.547.652zm11.545-4.221c.368 0 .708.2.892.524.184.324.184.724 0 1.048a1.026 1.026 0 01-.892.524c-.568 0-1.03-.47-1.03-1.048 0-.579.462-1.048 1.03-1.048zm-14.358 0c.368 0 .707.2.891.524.184.324.184.724 0 1.048a1.026 1.026 0 01-.891.524c-.569 0-1.03-.47-1.03-1.048 0-.579.461-1.048 1.03-1.048zm10.031-1.475c.925 0 1.675.764 1.675 1.706s-.75 1.705-1.675 1.705-1.674-.763-1.674-1.705c0-.942.75-1.706 1.674-1.706zm-2.626-.684c.362-.082.653-.356.761-.718a1.062 1.062 0 00-.238-1.028 1.017 1.017 0 00-.996-.294c-.547.14-.881.7-.752 1.257.13.558.675.907 1.225.783zm0 16.876c.359-.087.644-.36.75-.72a1.062 1.062 0 00-.237-1.019 1.018 1.018 0 00-.985-.301 1.037 1.037 0 00-.762.717c-.108.361-.017.754.239 1.028.245.263.606.377.953.305l.043-.01zM17.19 3.5a.631.631 0 00.628-.64c0-.355-.279-.64-.628-.64a.631.631 0 00-.628.64c0 .355.28.64.628.64zm-10.38 0a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64a.631.631 0 00-.628.64c0 .355.279.64.628.64zm-5.182 7.852a.631.631 0 00-.628.64c0 .354.28.639.628.639a.63.63 0 00.627-.606l.001-.034a.62.62 0 00-.628-.64zm5.182 9.13a.631.631 0 00-.628.64c0 .355.279.64.628.64a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64zm10.38.018a.631.631 0 00-.628.64c0 .355.28.64.628.64a.631.631 0 00.628-.64c0-.355-.279-.64-.628-.64zm5.182-9.148a.631.631 0 00-.628.64c0 .354.279.639.628.639a.631.631 0 00.628-.64c0-.355-.28-.64-.628-.64zm-.384-4.992a.24.24 0 00.244-.249.24.24 0 00-.244-.249.24.24 0 00-.244.249c0 .142.122.249.244.249zM11.991.497a.24.24 0 00.245-.248A.24.24 0 0011.99 0a.24.24 0 00-.244.249c0 .133.108.236.223.247l.021.001zM2.011 6.36a.24.24 0 00.245-.249.24.24 0 00-.244-.249.24.24 0 00-.244.249.24.24 0 00.244.249zm0 11.263a.24.24 0 00-.243.248.24.24 0 00.244.249.24.24 0 00.244-.249.252.252 0 00-.244-.248zm19.995-.018a.24.24 0 00-.245.248.24.24 0 00.245.25.24.24 0 00.244-.25.252.252 0 00-.244-.248z" fill="#3859FF" fill-rule="nonzero"></path></svg>

frontend/src/contracts/index.ts

@@ -416,6 +416,39 @@ export interface ProviderPreset {
   base_url: string
   default_credential_id?: string | null
   requires_credential: boolean
+  logo_id?: string
+  description?: string
+  capabilities?: string[]
+}
+
+export type ProviderUpdateRequest = Partial<Omit<ProviderConfig, 'provider_id' | 'credential_id' | 'base_url'>> & {
+  credential_id?: string | null
+  base_url?: string | null
+}
+
+export type RoutingCapability = 'embedding' | 'transcription' | 'speaker_matching'
+
+export interface ModelBinding {
+  provider_id: string
+  model: string
+  endpoint: string
+  dimensions?: number | null
+}
+
+export interface ModelRoutingConfig {
+  version: number
+  embedding: ModelBinding | null
+  transcription: ModelBinding | null
+  speaker_matching: ModelBinding | null
+}
+
+export interface ModelRoutingResponse {
+  config: ModelRoutingConfig
+  local_backends: Array<{
+    capability: RoutingCapability
+    status: 'placeholder' | 'not_installed' | 'ready'
+    message: string
+  }>
 }
 
 // ============ Tasks ============
@@ -721,6 +754,9 @@ export interface ApiProviderPreset {
   base_url: string
   default_credential_id?: string | null
   requires_credential: boolean
+  logo_id?: string
+  description?: string
+  capabilities?: string[]
 }
 
 export interface ApiModelInfo {

frontend/src/features/settings/ModelRoutingSettings.spec.ts

@@ -0,0 +1,170 @@
+// @vitest-environment happy-dom
+import { flushPromises, mount } from '@vue/test-utils'
+import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest'
+import type { ModelRoutingResponse, ProviderConfig } from '@/contracts'
+import { ApiErrorClass } from '@/services/apiClient'
+import * as service from '@/services/modelRoutingService'
+import { listProviders } from '@/services/providerService'
+import ModelRoutingSettings from './ModelRoutingSettings.vue'
+
+vi.mock('@/services/modelRoutingService', () => ({ getModelRouting: vi.fn(), saveModelRouting: vi.fn() }))
+vi.mock('@/services/providerService', () => ({ listProviders: vi.fn() }))
+const providers: ProviderConfig[] = [
+  { provider_id: 'p1', provider_type: 'openai_compatible', name: 'Custom API', enabled: true, default_model: 'chat-model', capabilities: {}, has_credential: true },
+  { provider_id: 'p2', provider_type: 'openai_chat', name: 'OpenAI', enabled: true, default_model: '', capabilities: {}, has_credential: true },
+  { provider_id: 'responses', provider_type: 'openai_responses', name: 'Responses', enabled: true, default_model: '', capabilities: {}, has_credential: true },
+  { provider_id: 'anthropic', provider_type: 'anthropic_messages', name: 'Anthropic', enabled: true, default_model: '', capabilities: {}, has_credential: true },
+  { provider_id: 'ollama', provider_type: 'ollama', name: 'Ollama', enabled: true, default_model: '', capabilities: {}, has_credential: false },
+  { provider_id: 'disabled', provider_type: 'openai_chat', name: 'Disabled', enabled: false, default_model: '', capabilities: {}, has_credential: true },
+]
+const initial: ModelRoutingResponse = { config: { version: 3, embedding: null, transcription: null, speaker_matching: null }, local_backends: [
+  { capability: 'embedding', status: 'placeholder', message: 'hash fallback' },
+  { capability: 'transcription', status: 'not_installed', message: 'ASR not installed' },
+  { capability: 'speaker_matching', status: 'not_installed', message: 'speaker not installed' },
+] }
+const wrappers: ReturnType<typeof mount>[] = []
+async function render() {
+  const wrapper = mount(ModelRoutingSettings)
+  wrappers.push(wrapper)
+  await flushPromises()
+  return wrapper
+}
+beforeEach(() => {
+  vi.resetAllMocks()
+  vi.mocked(service.getModelRouting).mockResolvedValue(structuredClone(initial))
+  vi.mocked(listProviders).mockResolvedValue(providers)
+  vi.mocked(service.saveModelRouting).mockImplementation(async config => ({ ...initial, config: { ...config, version: config.version + 1 } }))
+})
+afterEach(() => { wrappers.splice(0).forEach(wrapper => wrapper.unmount()) })
+
+describe('ModelRoutingSettings', () => {
+  it('loads local selections honestly, explains index rebuilds, and disables incompatible providers', async () => {
+    const wrapper = await render()
+    expect(wrapper.findAll('select').map(select => (select.element as HTMLSelectElement).value)).toEqual(['', '', ''])
+    expect(wrapper.text()).toContain('当前为占位实现')
+    expect(wrapper.text()).toContain('真实本地 ASR 尚未接入')
+    expect(wrapper.text()).toContain('真实本地说话人匹配尚未接入')
+    expect(wrapper.text()).toContain('重建全部')
+    expect(wrapper.text()).toContain('重建完成前继续使用本地检索')
+    expect(wrapper.text()).toContain('不是 OpenAI 标准接口')
+    for (const id of ['responses', 'anthropic', 'ollama', 'disabled']) expect(wrapper.get(`option[value="${id}"]`).attributes()).toHaveProperty('disabled')
+    expect(wrapper.get('option[value="p1"]').attributes()).not.toHaveProperty('disabled')
+  })
+
+  it('saves all three independent bindings with expected version and remote dimensions', async () => {
+    const wrapper = await render()
+    for (const capability of ['embedding', 'transcription', 'speaker_matching']) {
+      const card = wrapper.get(`[data-capability="${capability}"]`)
+      await card.get('select').setValue('p1')
+      await card.get('[data-field="model"]').setValue(`${capability}-model`)
+    }
+    await wrapper.get('[data-field="dimensions"]').setValue('3072')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.saveModelRouting).toHaveBeenCalledWith({ version: 3,
+      embedding: { provider_id: 'p1', model: 'embedding-model', endpoint: '/embeddings', dimensions: 3072 },
+      transcription: { provider_id: 'p1', model: 'transcription-model', endpoint: '/audio/transcriptions' },
+      speaker_matching: { provider_id: 'p1', model: 'speaker_matching-model', endpoint: '/audio/speaker-matches' },
+    })
+    expect(wrapper.text()).toContain('配置版本 4')
+    expect(wrapper.text()).toContain('模型路由已保存')
+    await wrapper.get('[data-capability="embedding"] select').setValue('')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.saveModelRouting).toHaveBeenLastCalledWith(expect.objectContaining({ version: 4, embedding: null }))
+  })
+
+  it('supports omitted dimensions and clears stale models/endpoints when switching providers', async () => {
+    const wrapper = await render()
+    const card = wrapper.get('[data-capability="embedding"]')
+    await card.get('select').setValue('p1')
+    await card.get('[data-field="model"]').setValue('custom-embedding')
+    await card.get('[data-field="endpoint"]').setValue('/custom/embeddings')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.saveModelRouting).toHaveBeenCalledWith(expect.objectContaining({ embedding: { provider_id: 'p1', model: 'custom-embedding', endpoint: '/custom/embeddings', dimensions: null } }))
+    await card.get('select').setValue('p2')
+    expect((card.get('[data-field="model"]').element as HTMLInputElement).value).toBe('')
+    expect((card.get('[data-field="endpoint"]').element as HTMLInputElement).value).toBe('/embeddings')
+  })
+
+  it('shows a loading state and does not offer a default local configuration after load failure', async () => {
+    let fail!: (error: Error) => void
+    vi.mocked(service.getModelRouting).mockReturnValueOnce(new Promise((_, reject) => { fail = reject }))
+    const wrapper = await render()
+    expect(wrapper.text()).toContain('正在加载模型路由')
+    expect(wrapper.find('form').exists()).toBe(false)
+    fail(new Error('offline'))
+    await flushPromises()
+    expect(wrapper.text()).toContain('加载失败：offline')
+    expect(wrapper.find('form').exists()).toBe(false)
+    await wrapper.get('button').trigger('click')
+    await flushPromises()
+    expect(wrapper.find('form').exists()).toBe(true)
+  })
+
+  it('keeps unsaved input on save failure and retries without inventing a new version', async () => {
+    const wrapper = await render()
+    const card = wrapper.get('[data-capability="transcription"]')
+    await card.get('select').setValue('p1')
+    await card.get('[data-field="model"]').setValue('asr-model')
+    vi.mocked(service.saveModelRouting).mockRejectedValueOnce(new Error('disk full'))
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(wrapper.text()).toContain('保存失败：disk full')
+    expect((card.get('[data-field="model"]').element as HTMLInputElement).value).toBe('asr-model')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.saveModelRouting).toHaveBeenLastCalledWith(expect.objectContaining({ version: 3 }))
+  })
+
+  it('blocks overwrite after a conflict until explicitly reloading the latest configuration', async () => {
+    const wrapper = await render()
+    vi.mocked(service.saveModelRouting).mockRejectedValueOnce(new ApiErrorClass('MODEL_ROUTING_VERSION_CONFLICT', 'stale'))
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(wrapper.text()).toContain('配置版本冲突')
+    expect(wrapper.get('button[type="submit"]').attributes()).toHaveProperty('disabled')
+    await wrapper.get('form').trigger('submit')
+    expect(service.saveModelRouting).toHaveBeenCalledTimes(1)
+    vi.mocked(service.getModelRouting).mockResolvedValueOnce({ ...initial, config: { ...initial.config, version: 8 } })
+    await wrapper.findAll('button').find(button => button.text().includes('放弃当前输入'))!.trigger('click')
+    await flushPromises()
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.saveModelRouting).toHaveBeenLastCalledWith(expect.objectContaining({ version: 8 }))
+  })
+
+  it('prevents invalid dimensions, endpoints, and missing provider bindings from being saved', async () => {
+    vi.mocked(service.getModelRouting).mockResolvedValueOnce({ ...initial, config: { ...initial.config, embedding: { provider_id: 'missing', model: 'old-model', endpoint: '/embeddings' } } })
+    const wrapper = await render()
+    expect(wrapper.text()).toContain('原提供商已不可用')
+    await wrapper.get('form').trigger('submit')
+    expect(service.saveModelRouting).not.toHaveBeenCalled()
+    const card = wrapper.get('[data-capability="embedding"]')
+    await card.get('select').setValue('p1')
+    await card.get('[data-field="model"]').setValue('embedding-model')
+    await card.get('[data-field="dimensions"]').setValue('1.5')
+    await wrapper.get('form').trigger('submit')
+    expect(wrapper.text()).toContain('嵌入维度必须为 1–16384 的整数')
+    await card.get('[data-field="dimensions"]').setValue('16385')
+    await wrapper.get('form').trigger('submit')
+    expect(service.saveModelRouting).not.toHaveBeenCalled()
+    expect(card.get('[data-field="dimensions"]').attributes('max')).toBe('16384')
+    await card.get('[data-field="dimensions"]').setValue('')
+    await card.get('[data-field="endpoint"]').setValue('https://example.test/embeddings')
+    await wrapper.get('form').trigger('submit')
+    expect(wrapper.text()).toContain('Endpoint 必须是以 / 开头的相对路径')
+    expect(service.saveModelRouting).not.toHaveBeenCalled()
+  })
+
+  it('labels injected ready local backends accurately', async () => {
+    vi.mocked(service.getModelRouting).mockResolvedValueOnce({ ...initial, local_backends: [{ capability: 'transcription', status: 'ready', message: 'Local ASR ready' }] })
+    const wrapper = await render()
+    const card = wrapper.get('[data-capability="transcription"]')
+    expect(card.get('option[value=""]').text()).toBe('本地 · 已就绪')
+    expect(card.text()).toContain('本地后端已就绪')
+    expect(card.text()).toContain('Local ASR ready')
+    expect(card.text()).not.toContain('真实本地 ASR 尚未接入')
+  })
+})

frontend/src/features/settings/ModelRoutingSettings.vue

@@ -0,0 +1,160 @@
+<script setup lang="ts">
+import { computed, onBeforeUnmount, onMounted, reactive, ref } from 'vue'
+import type { ModelBinding, ModelRoutingConfig, ModelRoutingResponse, ProviderConfig, RoutingCapability } from '@/contracts'
+import { getModelRouting, saveModelRouting } from '@/services/modelRoutingService'
+import { listProviders } from '@/services/providerService'
+import { ApiErrorClass } from '@/services/apiClient'
+
+const capabilities: Array<{ id: RoutingCapability; name: string; endpoint: string; placeholder: string; local: string }> = [
+  { id: 'embedding', name: '向量嵌入 · Embedding', endpoint: '/embeddings', placeholder: '例如 text-embedding-3-small', local: '当前为占位实现，尚未接入真实本地嵌入模型。' },
+  { id: 'transcription', name: '语音转写 · Transcription', endpoint: '/audio/transcriptions', placeholder: '输入转写模型 ID', local: '真实本地 ASR 尚未接入，等待阶段 F；当前无法进行本地语音识别。' },
+  { id: 'speaker_matching', name: '说话人匹配 · Speaker matching', endpoint: '/audio/speaker-matches', placeholder: '输入说话人匹配模型 ID', local: '真实本地说话人匹配尚未接入，等待阶段 F；当前无法进行本地声纹匹配。' },
+]
+type Draft = { provider_id: string; model: string; endpoint: string; dimensions: string | number }
+const drafts = reactive(Object.fromEntries(capabilities.map(item => [item.id, { provider_id: '', model: '', endpoint: item.endpoint, dimensions: '' }])) as Record<RoutingCapability, Draft>)
+const providers = ref<ProviderConfig[]>([])
+const response = ref<ModelRoutingResponse | null>(null)
+const loading = ref(false)
+const saving = ref(false)
+const error = ref('')
+const saved = ref(false)
+const conflict = ref(false)
+let active = true
+const eligible = (provider: ProviderConfig) => provider.enabled && ['openai_chat', 'openai_compatible'].includes(provider.provider_type)
+const available = computed(() => providers.value.filter(eligible))
+const unavailable = computed(() => providers.value.filter(provider => !eligible(provider)))
+const localBackend = (capability: RoutingCapability) => response.value?.local_backends.find(item => item.capability === capability)
+const localLabel = (capability: RoutingCapability) => {
+  const status = localBackend(capability)?.status
+  return status === 'ready' ? '已就绪' : status === 'placeholder' ? '占位实现' : '尚未接入'
+}
+const protocols = [
+  { id: 'openai_chat', label: 'OpenAI Chat' }, { id: 'openai_compatible', label: 'OpenAI Compatible' },
+  { id: 'openai_responses', label: 'Responses' }, { id: 'anthropic_messages', label: 'Anthropic' }, { id: 'ollama', label: 'Ollama' },
+]
+
+function applyResponse(result: ModelRoutingResponse) {
+  response.value = result
+  for (const item of capabilities) {
+    const binding = result.config[item.id]
+    Object.assign(drafts[item.id], { provider_id: binding?.provider_id ?? '', model: binding?.model ?? '', endpoint: binding?.endpoint ?? item.endpoint, dimensions: binding?.dimensions?.toString() ?? '' })
+  }
+}
+
+async function load() {
+  if (loading.value || saving.value) return
+  loading.value = true
+  error.value = ''
+  saved.value = false
+  try {
+    const [routing, items] = await Promise.all([getModelRouting(), listProviders()])
+    if (!active) return
+    providers.value = items
+    applyResponse(routing)
+    conflict.value = false
+  } catch (reason) {
+    if (active) error.value = `加载失败：${reason instanceof Error ? reason.message : '无法读取模型路由或提供商'}`
+  } finally { loading.value = false }
+}
+
+onMounted(load)
+onBeforeUnmount(() => { active = false })
+
+function changeProvider(capability: RoutingCapability) {
+  const draft = drafts[capability]
+  draft.model = ''
+  draft.dimensions = ''
+  draft.endpoint = capabilities.find(item => item.id === capability)!.endpoint
+  saved.value = false
+}
+
+function bindingFor(capability: RoutingCapability): ModelBinding | null {
+  const draft = drafts[capability]
+  if (!draft.provider_id) return null
+  if (!available.value.some(provider => provider.provider_id === draft.provider_id)) throw new Error('请选择已启用且协议可用的提供商，或切换到本地。')
+  if (!draft.model.trim()) throw new Error('请填写所选 API 的模型 ID。')
+  if (!/^\/[A-Za-z0-9_/-]+$/.test(draft.endpoint) || draft.endpoint.startsWith('//')) throw new Error('Endpoint 必须是以 / 开头的相对路径，只能包含字母、数字、下划线、连字符和 /。')
+  const binding: ModelBinding = { provider_id: draft.provider_id, model: draft.model.trim(), endpoint: draft.endpoint }
+  if (capability === 'embedding') {
+    const dimension = String(draft.dimensions).trim()
+    if (dimension && (!/^\d+$/.test(dimension) || !Number.isSafeInteger(Number(dimension)) || Number(dimension) < 1 || Number(dimension) > 16384)) throw new Error('嵌入维度必须为 1–16384 的整数，或留空使用 API 默认值。')
+    binding.dimensions = dimension ? Number(dimension) : null
+  }
+  return binding
+}
+
+async function save() {
+  if (!response.value || loading.value || saving.value || conflict.value) return
+  saving.value = true
+  error.value = ''
+  saved.value = false
+  try {
+    const config: ModelRoutingConfig = {
+      version: response.value.config.version,
+      embedding: bindingFor('embedding'), transcription: bindingFor('transcription'), speaker_matching: bindingFor('speaker_matching'),
+    }
+    const result = await saveModelRouting(config)
+    if (active) { applyResponse(result); saved.value = true }
+  } catch (reason) {
+    if (!active) return
+    conflict.value = reason instanceof ApiErrorClass && /CONFLICT|VERSION|HTTP_409/i.test(reason.code)
+    error.value = conflict.value
+      ? '配置版本冲突：其他窗口已修改路由。当前输入尚未保存，请重新加载最新配置后再编辑。'
+      : `保存失败：${reason instanceof Error ? reason.message : '请重试'}`
+  } finally { saving.value = false }
+}
+</script>
+
+<template>
+  <section class="routing-settings" aria-labelledby="routing-title" :aria-busy="loading || saving">
+    <div><h2 id="routing-title">能力模型路由</h2><p class="subtle">向量嵌入、语音转写和说话人匹配分别选择提供商与模型，独立于默认聊天模型。API Key 在「模型提供商」中管理。</p></div>
+    <p class="subtle">未选择提供商即使用本地路径。API 请求失败、配置不可用或响应无效时，服务端会回退到当前本地处理；本地占位不代表真实模型已接入。</p>
+    <p v-if="loading" role="status">正在加载模型路由…</p>
+    <div v-if="error" class="error-banner" role="alert">{{ error }}</div>
+    <div class="inline-actions"><button type="button" class="button-secondary" :disabled="loading || saving" @click="load">{{ conflict ? '放弃当前输入并加载最新配置' : response ? '重新加载（放弃未保存更改）' : '重试加载' }}</button><span v-if="response" class="subtle">配置版本 {{ response.config.version }}</span></div>
+    <form v-if="response" @submit.prevent="save" @input="saved = false" @change="saved = false">
+      <fieldset :disabled="loading || saving || conflict">
+        <article v-for="capability in capabilities" :key="capability.id" class="routing-card" :data-capability="capability.id">
+          <h3>{{ capability.name }}</h3>
+          <p v-if="capability.id === 'embedding'" class="embedding-notice">更换模型或接口后，请重建全部索引。重建完成前继续使用本地检索。</p>
+          <div class="protocols" aria-label="协议可用性">
+            <span v-for="protocol in protocols" :key="protocol.id" class="badge" :class="{ 'protocol-unavailable': !['openai_chat', 'openai_compatible'].includes(protocol.id) }">{{ protocol.label }}{{ ['openai_chat', 'openai_compatible'].includes(protocol.id) ? ' · 可用' : ' · 不可用' }}</span>
+          </div>
+          <label class="field"><span>处理方式 / 提供商</span><select v-model="drafts[capability.id].provider_id" class="select" data-field="provider" @change="changeProvider(capability.id)">
+            <option value="">本地 · {{ localLabel(capability.id) }}</option>
+            <option v-for="provider in available" :key="provider.provider_id" :value="provider.provider_id">{{ provider.name }} · {{ provider.provider_type }}</option>
+            <option v-for="provider in unavailable" :key="provider.provider_id" :value="provider.provider_id" disabled>{{ provider.name }} · {{ provider.enabled ? '协议不可用' : '未启用' }}</option>
+            <option v-if="drafts[capability.id].provider_id && !providers.some(provider => provider.provider_id === drafts[capability.id].provider_id)" :value="drafts[capability.id].provider_id" disabled>原提供商已不可用 · {{ drafts[capability.id].provider_id }}</option>
+          </select></label>
+          <div v-if="drafts[capability.id].provider_id" class="routing-fields">
+            <label class="field"><span>模型 ID</span><input v-model="drafts[capability.id].model" class="input" data-field="model" :placeholder="capability.placeholder" maxlength="256" required /></label>
+            <label class="field"><span>Endpoint（相对 Base URL）</span><input v-model="drafts[capability.id].endpoint" class="input" data-field="endpoint" :placeholder="capability.endpoint" maxlength="256" required /></label>
+            <label v-if="capability.id === 'embedding'" class="field"><span>向量维度（可选）</span><input v-model="drafts.embedding.dimensions" class="input" data-field="dimensions" type="number" min="1" max="16384" step="1" placeholder="留空使用 API 默认维度" /><small class="subtle">填写模型支持的 1–16384 整数维度，或留空使用 API 默认值。</small></label>
+          </div>
+          <p v-if="capability.id === 'speaker_matching'" class="subtle">说话人匹配使用本应用自定义 HTTP multipart 契约。该端点不是 OpenAI 标准接口；服务需实现对应的说话人匹配请求和响应。</p>
+          <div class="local-status" :class="{ selected: !drafts[capability.id].provider_id }">
+            <strong>{{ drafts[capability.id].provider_id ? '本地回退状态' : '当前本地状态' }}</strong>
+            <p>{{ localBackend(capability.id)?.status === 'ready' ? '本地后端已就绪。' : capability.local }}</p>
+            <p v-for="backend in response.local_backends.filter(item => item.capability === capability.id)" :key="backend.capability" class="subtle"><span class="badge">{{ backend.status === 'ready' ? '已就绪' : backend.status === 'placeholder' ? '占位实现' : '未安装 / 未接入' }}</span> {{ backend.message }}</p>
+          </div>
+        </article>
+      </fieldset>
+      <div class="inline-actions"><button type="submit" class="button-primary" :disabled="loading || saving || conflict">{{ saving ? '保存中…' : '保存模型路由' }}</button><span v-if="saved" role="status">模型路由已保存。</span></div>
+    </form>
+  </section>
+</template>
+
+<style scoped>
+.routing-settings, form, fieldset { display: grid; gap: var(--space-lg); }
+.routing-settings { border-top: 1px solid var(--color-border-default); padding-top: var(--space-xl); margin-top: var(--space-md); }
+fieldset { min-width: 0; padding: 0; margin: 0; border: 0; }
+.routing-card { display: grid; gap: var(--space-md); padding: var(--space-lg); border: 1px solid var(--color-border-default); border-radius: var(--radius-lg); background: var(--color-surface-primary); }
+.routing-card h3 { margin: 0; }
+.protocols { display: flex; flex-wrap: wrap; gap: var(--space-xs); }
+.protocol-unavailable { opacity: .65; }
+.embedding-notice { padding: var(--space-md); border-radius: var(--radius-md); background: var(--color-accent-soft); color: var(--color-text-primary); }
+.routing-fields { display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: var(--space-md); }
+.local-status { display: grid; gap: var(--space-xs); padding: var(--space-md); background: var(--color-background-secondary); border-radius: var(--radius-md); }
+.local-status.selected { border-left: 3px solid var(--color-accent-primary); }
+@media (max-width: 700px) { .routing-fields { grid-template-columns: 1fr; } }
+</style>

frontend/src/features/settings/ProviderForm.spec.ts

@@ -0,0 +1,157 @@
+// @vitest-environment happy-dom
+import { flushPromises, mount } from '@vue/test-utils'
+import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest'
+import type { ProviderConfig, ProviderPreset } from '@/contracts'
+import * as service from '@/services/providerService'
+import ProviderForm from './ProviderForm.vue'
+import ProviderPresetSelector from './ProviderPresetSelector.vue'
+
+vi.mock('@/services/providerService', () => ({ listProviderPresets: vi.fn(), getCredentialStatus: vi.fn(), putCredential: vi.fn(), createProvider: vi.fn(), updateProvider: vi.fn() }))
+const presets: ProviderPreset[] = [
+  { preset_id: 'deepseek', name: 'DeepSeek', provider_type: 'openai_compatible', base_url: 'https://deepseek.example.test', default_credential_id: 'shared-deepseek', requires_credential: true, logo_id: 'deepseek' },
+  { preset_id: 'qwen', name: '通义千问', provider_type: 'openai_compatible', base_url: 'https://qwen.example.test', default_credential_id: 'shared-qwen', requires_credential: true, logo_id: 'qwen' },
+]
+const existing: ProviderConfig = { provider_id: 'p1', provider_type: 'openai_compatible', name: 'DeepSeek', base_url: presets[0].base_url, default_model: 'old-model', enabled: true, credential_id: 'old-shared-key', has_credential: true, capabilities: {} }
+const wrappers: ReturnType<typeof mount>[] = []
+async function render(provider?: ProviderConfig) {
+  const wrapper = mount(ProviderForm, { props: { provider, models: [{ model_id: 'old-model', name: 'Old', capabilities: {} }] } })
+  wrappers.push(wrapper)
+  await flushPromises()
+  return wrapper
+}
+beforeEach(() => {
+  vi.resetAllMocks()
+  vi.mocked(service.listProviderPresets).mockResolvedValue(presets)
+  vi.mocked(service.getCredentialStatus).mockResolvedValue(true)
+  vi.mocked(service.putCredential).mockResolvedValue()
+  vi.mocked(service.createProvider).mockResolvedValue(existing)
+  vi.mocked(service.updateProvider).mockResolvedValue(existing)
+})
+afterEach(() => { wrappers.splice(0).forEach(wrapper => wrapper.unmount()) })
+
+describe('ProviderForm', () => {
+  it('filters compact preset chips and resolves bundled logos', async () => {
+    const wrapper = await render()
+    await wrapper.get('#provider-search').setValue('通义')
+    expect(wrapper.find('[data-preset="deepseek"]').exists()).toBe(false)
+    expect(wrapper.find('[data-preset="qwen"]').exists()).toBe(true)
+    expect(wrapper.get('[data-preset="qwen"] img').attributes('src')).not.toMatch(/^https?:/)
+  })
+
+  it('clears the secret, old model and credential on preset and custom selection', async () => {
+    const wrapper = await render(existing)
+    await wrapper.get('input[type="password"]').setValue('draft-secret')
+    await wrapper.get('[data-preset="qwen"]').trigger('click')
+    expect((wrapper.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+    expect((wrapper.get('[data-field="model"]').element as HTMLInputElement).value).toBe('')
+    expect(wrapper.findAll('datalist option')).toHaveLength(0)
+    await wrapper.get('form').trigger('submit')
+    expect(service.updateProvider).not.toHaveBeenCalled()
+    expect(wrapper.text()).toContain('请输入 API Key')
+    await wrapper.get('input[type="password"]').setValue('new-secret')
+    wrapper.getComponent(ProviderPresetSelector).vm.$emit('update:modelValue', '')
+    await flushPromises()
+    expect((wrapper.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+  })
+
+  it('allocates different credential IDs for two new providers using the same preset', async () => {
+    for (let i = 0; i < 2; i++) {
+      const wrapper = await render()
+      await wrapper.get('[data-preset="deepseek"]').trigger('click')
+      await wrapper.get('input[type="password"]').setValue(`test-key-${i}`)
+      await wrapper.get('form').trigger('submit')
+      await flushPromises()
+    }
+    const ids = vi.mocked(service.putCredential).mock.calls.map(call => call[0])
+    expect(ids).toHaveLength(2)
+    expect(new Set(ids).size).toBe(2)
+    ids.forEach(id => expect(id).toMatch(/^provider-key-[0-9a-f-]{36}$/))
+    vi.mocked(service.createProvider).mock.calls.forEach(([data], index) => {
+      expect(data.credential_id).toBe(ids[index])
+      expect(JSON.stringify(data)).not.toContain('test-key')
+      expect(JSON.stringify(data)).not.toContain('shared-deepseek')
+    })
+  })
+
+  it('accepts a custom API key and clears it after a failed credential save', async () => {
+    const wrapper = await render()
+    await wrapper.get('[data-field="name"]').setValue('Custom')
+    await wrapper.get('[data-field="base-url"]').setValue('https://custom.example.test/v1')
+    await wrapper.get('input[type="password"]').setValue('custom-test-key')
+    vi.mocked(service.putCredential).mockRejectedValueOnce(new Error('credential store unavailable'))
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect((wrapper.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+    expect(wrapper.text()).toContain('credential store unavailable')
+    expect(service.createProvider).not.toHaveBeenCalled()
+    await wrapper.get('input[type="password"]').setValue('custom-test-key')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.createProvider).toHaveBeenCalledWith(expect.objectContaining({ name: 'Custom', credential_id: expect.stringMatching(/^provider-key-/) }))
+  })
+
+  it('preserves its own existing key when untouched and rotates shared legacy references when replacing a key', async () => {
+    const untouched = await render(existing)
+    await untouched.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.updateProvider).toHaveBeenLastCalledWith('p1', expect.objectContaining({ credential_id: 'old-shared-key', default_model: 'old-model' }))
+    const rotated = await render(existing)
+    await rotated.get('input[type="password"]').setValue('replacement-test-key')
+    await rotated.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.putCredential).toHaveBeenCalledWith(expect.stringMatching(/^provider-key-/), 'replacement-test-key')
+    expect(service.updateProvider).toHaveBeenLastCalledWith('p1', expect.objectContaining({ credential_id: vi.mocked(service.putCredential).mock.calls[0][0] }))
+  })
+
+  it('persists edited protocols and unlinks the previous credential and model', async () => {
+    const wrapper = await render(existing)
+    await wrapper.get('[data-field="protocol"]').setValue('openai_responses')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.updateProvider).toHaveBeenCalledWith('p1', expect.objectContaining({ provider_type: 'openai_responses', default_model: '', credential_id: null }))
+  })
+
+  it('does not let a late credential status reuse a key after switching presets', async () => {
+    let resolveStatus!: (configured: boolean) => void
+    vi.mocked(service.getCredentialStatus).mockReturnValue(new Promise(resolve => { resolveStatus = resolve }))
+    const wrapper = await render(existing)
+    await wrapper.get('[data-preset="qwen"]').trigger('click')
+    resolveStatus(true)
+    await flushPromises()
+    await wrapper.get('form').trigger('submit')
+    expect(service.updateProvider).not.toHaveBeenCalled()
+    expect(wrapper.text()).toContain('请输入 API Key')
+  })
+
+  it('clears secrets on close and unmount, and stops a pending credential save from creating a provider', async () => {
+    let finish!: () => void
+    vi.mocked(service.putCredential).mockReturnValue(new Promise(resolve => { finish = resolve }))
+    const wrapper = await render()
+    await wrapper.get('[data-preset="deepseek"]').trigger('click')
+    await wrapper.get('input[type="password"]').setValue('pending-test-key')
+    await wrapper.get('form').trigger('submit')
+    await wrapper.get('[aria-label="关闭提供商表单"]').trigger('click')
+    expect((wrapper.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+    wrapper.unmount()
+    finish()
+    await flushPromises()
+    expect(service.createProvider).not.toHaveBeenCalled()
+    const reopened = await render()
+    expect((reopened.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+  })
+
+  it('clears a secret after provider save failure and keeps only the successfully saved reference for retry', async () => {
+    const wrapper = await render()
+    await wrapper.get('[data-preset="deepseek"]').trigger('click')
+    await wrapper.get('input[type="password"]').setValue('retry-test-key')
+    vi.mocked(service.createProvider).mockRejectedValueOnce(new Error('provider save failed'))
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(wrapper.text()).toContain('provider save failed')
+    expect((wrapper.get('input[type="password"]').element as HTMLInputElement).value).toBe('')
+    await wrapper.get('form').trigger('submit')
+    await flushPromises()
+    expect(service.putCredential).toHaveBeenCalledTimes(1)
+    expect(service.createProvider).toHaveBeenCalledTimes(2)
+  })
+})

frontend/src/features/settings/ProviderForm.vue

@@ -0,0 +1,177 @@
+<script setup lang="ts">
+import { computed, nextTick, onBeforeUnmount, onMounted, reactive, ref } from 'vue'
+import type { ModelInfo, ProviderConfig, ProviderPreset, ProviderType } from '@/contracts'
+import * as service from '@/services/providerService'
+import ProviderPresetSelector from './ProviderPresetSelector.vue'
+
+const props = defineProps<{ provider?: ProviderConfig; models?: ModelInfo[] }>()
+const emit = defineEmits<{ close: []; saved: [provider: ProviderConfig] }>()
+const newCredentialId = () => `provider-key-${crypto.randomUUID()}`
+const form = reactive({
+  preset_id: '', provider_type: props.provider?.provider_type ?? 'openai_compatible' as ProviderType,
+  name: props.provider?.name ?? '', base_url: props.provider?.base_url ?? '',
+  default_model: props.provider?.default_model ?? '', enabled: props.provider?.enabled ?? true,
+})
+const credentialId = ref(props.provider?.credential_id || newCredentialId())
+const apiKey = ref('')
+const configured = ref(false)
+const credentialLoading = ref(false)
+const credentialError = ref('')
+const presets = ref<ProviderPreset[]>([])
+const presetsLoading = ref(false)
+const presetsError = ref('')
+const saving = ref(false)
+const error = ref('')
+const contextChanged = ref(false)
+const dialog = ref<HTMLElement>()
+const previousFocus = document.activeElement as HTMLElement | null
+let active = true
+let credentialGeneration = 0
+const selectedPreset = computed(() => presets.value.find(preset => preset.preset_id === form.preset_id))
+const modelOptions = computed(() => contextChanged.value ? [] : props.models ?? [])
+
+async function loadPresets() {
+  presetsLoading.value = true
+  presetsError.value = ''
+  try {
+    presets.value = await service.listProviderPresets()
+    if (!contextChanged.value) form.preset_id = presets.value.find(preset => preset.provider_type === props.provider?.provider_type && preset.base_url === props.provider?.base_url)?.preset_id ?? ''
+  } catch { presetsError.value = '预设加载失败，请重试，或填写自定义服务。' }
+  finally { presetsLoading.value = false }
+}
+
+onMounted(async () => {
+  void loadPresets()
+  if (props.provider?.credential_id) {
+    const generation = credentialGeneration
+    credentialLoading.value = true
+    try {
+      const result = await service.getCredentialStatus(credentialId.value)
+      if (active && generation === credentialGeneration) configured.value = result
+    } catch {
+      if (active && generation === credentialGeneration) credentialError.value = '无法检查已保存的凭据。可输入新密钥，或关闭后重试。'
+    } finally {
+      if (generation === credentialGeneration) credentialLoading.value = false
+    }
+  }
+  await nextTick()
+  if (active) dialog.value?.querySelector<HTMLInputElement>('input')?.focus()
+})
+
+function detachCredential() {
+  credentialGeneration++
+  apiKey.value = ''
+  credentialId.value = newCredentialId()
+  configured.value = false
+  credentialLoading.value = false
+  credentialError.value = ''
+  form.default_model = ''
+  contextChanged.value = true
+  error.value = ''
+}
+
+function applyPreset(id: string) {
+  if (form.preset_id === id) return
+  detachCredential()
+  form.preset_id = id
+  const preset = presets.value.find(item => item.preset_id === id)
+  Object.assign(form, { provider_type: preset?.provider_type ?? 'openai_compatible', name: preset?.name ?? '', base_url: preset?.base_url ?? '' })
+}
+
+function changeConnection() {
+  form.preset_id = ''
+  detachCredential()
+}
+
+function close() {
+  active = false
+  apiKey.value = ''
+  emit('close')
+}
+
+onBeforeUnmount(() => {
+  active = false
+  apiKey.value = ''
+  previousFocus?.focus()
+})
+
+function handleKeydown(event: KeyboardEvent) {
+  if (event.key === 'Escape') { event.preventDefault(); close() }
+  if (event.key !== 'Tab') return
+  const elements = Array.from(dialog.value?.querySelectorAll<HTMLElement>('button, input, select, [tabindex="0"]') ?? []).filter(element => !element.matches(':disabled'))
+  const first = elements[0], last = elements[elements.length - 1]
+  if (event.shiftKey && document.activeElement === first) { event.preventDefault(); last?.focus() }
+  else if (!event.shiftKey && document.activeElement === last) { event.preventDefault(); first?.focus() }
+}
+
+async function save() {
+  if (saving.value || credentialLoading.value || !active) return
+  error.value = ''
+  saving.value = true
+  try {
+    if (!form.name.trim() || (form.provider_type !== 'mock' && !form.base_url.trim())) throw new Error('请填写名称和 Base URL。')
+    if (selectedPreset.value?.requires_credential && !apiKey.value.trim() && !configured.value) throw new Error('请输入 API Key。密钥将由后端加密保存。')
+    // Snapshot before awaiting: closing/unmounting must never create a provider with a changed draft.
+    const data = { provider_type: form.provider_type, name: form.name.trim(), base_url: form.base_url.trim() || undefined, default_model: form.default_model.trim(), enabled: form.enabled, capabilities: {}, has_credential: false }
+    if (apiKey.value.trim()) {
+      // Rotate even an existing reference: older installations may share preset credential IDs.
+      const nextId = newCredentialId()
+      const request = service.putCredential(nextId, apiKey.value.trim())
+      apiKey.value = ''
+      await request
+      if (!active) return
+      credentialId.value = nextId
+      configured.value = true
+    }
+    const reference = configured.value ? credentialId.value : undefined
+    // A failed status check must not silently unlink the provider's existing credential.
+    if (credentialError.value && !reference) throw new Error(credentialError.value)
+    const saved = props.provider
+      ? await service.updateProvider(props.provider.provider_id, { ...data, credential_id: reference ?? null })
+      : await service.createProvider({ ...data, credential_id: reference })
+    if (active) { emit('saved', saved); close() }
+  } catch (reason) {
+    if (active) error.value = reason instanceof Error ? reason.message : 'Provider 保存失败，请重试。'
+  } finally { apiKey.value = ''; saving.value = false }
+}
+</script>
+
+<template>
+  <div class="modal-backdrop provider-backdrop" @click.self="close" @keydown="handleKeydown">
+    <div ref="dialog" class="modal provider-modal" role="dialog" aria-modal="true" aria-labelledby="provider-form-title" :aria-busy="saving">
+      <div class="form-heading"><h2 id="provider-form-title">{{ provider ? '编辑 Provider' : '新增 Provider' }}</h2><button type="button" class="button-secondary" aria-label="关闭提供商表单" @click="close">关闭</button></div>
+      <p v-if="presetsLoading" class="subtle" role="status">正在加载提供商预设…</p>
+      <div v-if="presetsError" class="error-banner" role="alert">{{ presetsError }} <button type="button" class="button-secondary" :disabled="presetsLoading || saving" @click="loadPresets">重试</button></div>
+      <form @submit.prevent="save">
+        <fieldset :disabled="saving">
+          <ProviderPresetSelector :presets="presets" :model-value="form.preset_id" @update:model-value="applyPreset" />
+          <p v-if="selectedPreset?.description" class="subtle">{{ selectedPreset.description }}</p>
+          <div class="form-grid">
+            <label class="field"><span>接入协议</span><select v-model="form.provider_type" class="select" data-field="protocol" @change="changeConnection"><option value="openai_compatible">OpenAI Compatible</option><option value="openai_chat">OpenAI Chat</option><option value="openai_responses">OpenAI Responses</option><option value="anthropic_messages">Anthropic Messages</option><option value="ollama">Ollama</option><option v-if="provider?.provider_type === 'mock'" value="mock">Mock</option></select></label>
+            <label class="field"><span>名称</span><input v-model="form.name" class="input" data-field="name" required /></label>
+            <label class="field wide"><span>Base URL</span><input v-model="form.base_url" class="input" data-field="base-url" placeholder="https://api.example.com/v1" :required="form.provider_type !== 'mock'" @change="changeConnection" /></label>
+            <label class="field wide"><span>API Key</span><input v-model="apiKey" class="input" type="password" autocomplete="new-password" spellcheck="false" :placeholder="configured ? '已配置，留空表示不修改' : '请输入 API Key（无鉴权服务可留空）'" /><small class="subtle">密钥由本地 AI Core 加密保存；提供商配置仅保存独立的凭据引用。</small></label>
+            <p v-if="credentialLoading" class="subtle wide" role="status">正在检查凭据状态…</p>
+            <p v-if="credentialError" class="error-text wide" role="alert">{{ credentialError }}</p>
+            <label class="field wide"><span>默认聊天模型</span><input v-model="form.default_model" class="input" data-field="model" list="provider-model-options" placeholder="输入模型 ID，或保存后获取模型列表" /><datalist id="provider-model-options"><option v-for="model in modelOptions" :key="model.model_id" :value="model.model_id">{{ model.name }}</option></datalist></label>
+          </div>
+          <label class="inline-actions"><input v-model="form.enabled" type="checkbox" /> 启用</label>
+        </fieldset>
+        <div v-if="error" class="error-banner" role="alert">{{ error }}</div>
+        <div class="inline-actions form-footer"><button class="button-primary" type="submit" :disabled="saving || credentialLoading">{{ saving ? '保存中…' : '保存提供商' }}</button><button type="button" class="button-secondary" @click="close">取消</button></div>
+      </form>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.provider-modal { width: min(820px, 100%); max-height: 90dvh; }
+.form-heading { display: flex; align-items: center; justify-content: space-between; gap: var(--space-md); margin-bottom: var(--space-md); }
+.form-heading h2 { margin: 0; }
+fieldset { display: grid; gap: var(--space-md); border: 0; padding: 0; margin: 0; min-width: 0; }
+.form-grid { display: grid; grid-template-columns: 1fr 1fr; gap: var(--space-md); }
+.wide { grid-column: 1 / -1; }
+.error-text { color: var(--color-error); }
+.form-footer { padding-top: var(--space-sm); }
+@media (max-width: 600px) { .provider-backdrop { padding: 12px; }.provider-modal { padding: var(--space-lg); max-height: 94dvh; }.form-grid { grid-template-columns: 1fr; } }
+</style>

frontend/src/features/settings/ProviderLogo.vue

@@ -0,0 +1,24 @@
+<script setup lang="ts">
+import { computed } from 'vue'
+
+const props = defineProps<{ logoId?: string }>()
+const assets = import.meta.glob<string>('../../assets/providers/*.svg', { eager: true, query: '?url', import: 'default' })
+const source = computed(() => {
+  const id = props.logoId === 'openai-responses' ? 'openai' : props.logoId
+  return assets[`../../assets/providers/${id}.svg`]
+})
+</script>
+
+<template>
+  <span class="provider-logo" :class="{ 'dark-logo': logoId === 'kimi' }" aria-hidden="true">
+    <img v-if="source" :src="source" alt="" width="22" height="22" />
+    <span v-else class="custom-logo">+</span>
+  </span>
+</template>
+
+<style scoped>
+.provider-logo { display: inline-flex; flex: 0 0 28px; align-items: center; justify-content: center; width: 28px; height: 28px; border-radius: 7px; background: #fff; color: #252b36; }
+img { display: block; object-fit: contain; }
+.dark-logo { background: #111; }
+.custom-logo { font-size: 23px; line-height: 1; }
+</style>

frontend/src/features/settings/ProviderPresetSelector.vue

@@ -0,0 +1,36 @@
+<script setup lang="ts">
+import { computed, ref } from 'vue'
+import type { ProviderPreset } from '@/contracts'
+import ProviderLogo from './ProviderLogo.vue'
+
+const props = defineProps<{ presets: ProviderPreset[]; modelValue: string }>()
+const emit = defineEmits<{ 'update:modelValue': [value: string] }>()
+const search = ref('')
+const filtered = computed(() => {
+  const query = search.value.trim().toLocaleLowerCase()
+  return props.presets.filter(preset => [preset.name, preset.preset_id, preset.description, preset.base_url]
+    .some(value => value?.toLocaleLowerCase().includes(query)))
+})
+</script>
+
+<template>
+  <div class="preset-selector">
+    <label class="field" for="provider-search"><span>提供商预设</span><input id="provider-search" v-model="search" class="input" type="search" placeholder="搜索提供商，例如 通义千问 / DeepSeek" /></label>
+    <div class="preset-grid" role="group" aria-label="提供商预设">
+      <button type="button" class="preset-chip" :class="{ selected: !modelValue }" :aria-pressed="!modelValue" @click="emit('update:modelValue', '')"><ProviderLogo /><span>自定义</span></button>
+      <button v-for="preset in filtered" :key="preset.preset_id" type="button" class="preset-chip" :class="{ selected: modelValue === preset.preset_id }" :aria-pressed="modelValue === preset.preset_id" :title="preset.description || preset.name" :data-preset="preset.preset_id" @click="emit('update:modelValue', preset.preset_id)">
+        <ProviderLogo :logo-id="preset.logo_id || preset.preset_id" /><span>{{ preset.name }}</span>
+      </button>
+    </div>
+    <p v-if="search && !filtered.length" class="subtle" role="status">没有匹配的预设，可以使用自定义服务。</p>
+  </div>
+</template>
+
+<style scoped>
+.preset-selector { display: grid; gap: var(--space-sm); }
+.preset-grid { display: flex; flex-wrap: wrap; gap: 8px; max-height: 220px; overflow-y: auto; padding: 3px; }
+.preset-chip { display: inline-flex; align-items: center; gap: 7px; padding: 6px 10px; border: 1px solid var(--color-border-default); border-radius: 11px; background: var(--color-surface-primary); color: var(--color-text-primary); cursor: pointer; font: inherit; font-size: 13px; }
+.preset-chip:hover { background: var(--color-background-hover); }
+.preset-chip.selected { border-color: #377cf6; background: color-mix(in srgb, #377cf6 12%, var(--color-surface-primary)); color: #377cf6; box-shadow: 0 0 0 1px #377cf6; }
+.preset-chip:focus-visible { outline: 2px solid var(--color-border-focus); outline-offset: 2px; }
+</style>

frontend/src/features/settings/SettingsView.vue

@@ -1,6 +1,9 @@
 <script setup lang="ts">
-import { computed, onMounted, reactive, ref } from 'vue'
-import type { ProviderConfig, ProviderType } from '@/contracts'
+import { onMounted, ref } from 'vue'
+import type { ProviderConfig } from '@/contracts'
+import ProviderForm from './ProviderForm.vue'
+import ProviderLogo from './ProviderLogo.vue'
+import ModelRoutingSettings from './ModelRoutingSettings.vue'
 import { useProviderStore } from '@/stores/provider'
 import { useSettingsStore } from '@/stores/settings'
 import { useThemeStore } from '@/stores/theme'
@@ -15,14 +18,9 @@ const settingsStore = useSettingsStore()
 const providerStore = useProviderStore()
 const themeStore = useThemeStore()
 const showProviderForm = ref(false)
-const editingProviderId = ref<string | null>(null)
+const editingProvider = ref<ProviderConfig>()
 const providerAction = ref('')
 const testResults = ref<Record<string, string>>({})
-const providerApiKey = ref('')
-const providerForm = reactive({ preset_id: '', provider_type: 'openai_compatible' as ProviderType, name: '', base_url: '', default_model: '', credential_id: '', enabled: true })
-const formModels = computed(() => editingProviderId.value ? providerStore.modelsByProvider[editingProviderId.value] ?? [] : [])
-const selectedPreset = computed(() => providerStore.presets.find((item) => item.preset_id === providerForm.preset_id) ?? null)
-
 onMounted(async () => {
   await Promise.all([providerStore.loadProviders(), providerStore.loadPresets(), settingsStore.loadDiagnostics()])
   await providerStore.refreshEnabledModels()
@@ -36,54 +34,15 @@ function presetIdFor(provider?: ProviderConfig) {
 }
 
 function openProvider(provider?: ProviderConfig) {
-  editingProviderId.value = provider?.provider_id ?? null
-  const presetId = presetIdFor(provider)
-  const preset = providerStore.presets.find((item) => item.preset_id === presetId)
-  Object.assign(providerForm, { preset_id: presetId, provider_type: provider?.provider_type ?? 'openai_compatible', name: provider?.name ?? '', base_url: provider?.base_url ?? '', default_model: provider?.default_model ?? '', credential_id: provider?.credential_id ?? preset?.default_credential_id ?? '', enabled: provider?.enabled ?? true })
-  providerApiKey.value = ''
+  editingProvider.value = provider
+  providerAction.value = ''
   showProviderForm.value = true
-  if (providerForm.credential_id) void providerStore.loadCredentialStatus(providerForm.credential_id).catch(() => undefined)
   if (provider) void providerStore.loadModels(provider.provider_id).catch(() => undefined)
 }
 
-function applyProviderPreset() {
-  const preset = providerStore.presets.find((item) => item.preset_id === providerForm.preset_id)
-  if (!preset) return
-  Object.assign(providerForm, {
-    provider_type: preset.provider_type,
-    name: preset.name,
-    base_url: preset.base_url,
-    credential_id: preset.default_credential_id ?? '',
-  })
-  providerApiKey.value = ''
-  if (providerForm.credential_id) void providerStore.loadCredentialStatus(providerForm.credential_id).catch(() => undefined)
-}
-
-function closeProvider() {
-  providerApiKey.value = ''
-  showProviderForm.value = false
-}
-
-async function saveProvider() {
-  providerAction.value = ''
-  const credentialId = providerForm.credential_id.trim()
-  const requiresApiKey = Boolean(selectedPreset.value?.requires_credential)
-  if (requiresApiKey && !providerApiKey.value && !providerStore.credentialConfiguredById[credentialId]) {
-    providerAction.value = '请输入 API Key。密钥将由后端加密保存。'
-    return
-  }
-  const data = { ...providerForm, base_url: providerForm.base_url || undefined, credential_id: providerForm.credential_id || undefined, capabilities: {}, has_credential: Boolean(providerForm.credential_id) }
-  try {
-    if (providerApiKey.value) await providerStore.saveCredential(credentialId, providerApiKey.value)
-    const saved = editingProviderId.value
-      ? await providerStore.updateProvider(editingProviderId.value, data)
-      : await providerStore.addProvider(data)
-    closeProvider()
-    if (saved.enabled) void providerStore.loadModels(saved.provider_id).catch(() => undefined)
-  } catch (error) {
-    providerApiKey.value = ''
-    providerAction.value = error instanceof Error ? error.message : 'Provider 保存失败'
-  }
+async function providerSaved(provider: ProviderConfig) {
+  await providerStore.loadProviders()
+  if (provider.enabled) void providerStore.loadModels(provider.provider_id).catch(() => undefined)
 }
 
 async function removeProvider(provider: ProviderConfig) { if (!confirm(`确定删除 Provider“${provider.name}”吗？`)) return; try { await providerStore.deleteProvider(provider.provider_id) } catch (error) { providerAction.value = error instanceof Error ? error.message : '删除失败' } }
@@ -107,14 +66,14 @@ async function chooseDefaultModel(provider: ProviderConfig, event: Event) {
 
     <div v-else-if="activeSection === 'providers'" class="settings-section">
       <div class="section-head">
-        <div><h2>模型提供商</h2><p class="subtle">支持 OpenAI、DeepSeek、Ollama 和自定义兼容服务。</p></div>
+        <div><h2>模型提供商</h2><p class="subtle">选择国内外提供商预设，或配置自定义 API 与独立密钥。</p></div>
         <button class="button-primary" @click="openProvider()">新增 Provider</button>
       </div>
       <div v-if="providerStore.error || providerAction" class="error-banner">{{ providerStore.error || providerAction }}</div>
       <div class="provider-list">
         <article v-for="provider in providerStore.providers" :key="provider.provider_id" class="item-card provider-card">
           <div class="provider-main">
-            <div class="inline-actions"><strong>{{ provider.name }}</strong><span class="badge" :class="{ success: provider.enabled }">{{ provider.provider_type }}</span></div>
+            <div class="inline-actions"><ProviderLogo :logo-id="providerStore.presets.find(preset => preset.preset_id === presetIdFor(provider))?.logo_id || presetIdFor(provider)" /><strong>{{ provider.name }}</strong><span class="badge" :class="{ success: provider.enabled }">{{ provider.provider_type }}</span></div>
             <p class="subtle">{{ provider.base_url || '本地内置' }} · 默认模型 {{ provider.default_model || '未设置' }}</p>
             <div class="tag-list"><span v-for="(_, capability) in provider.capabilities" :key="capability" class="badge">{{ capability }}</span></div>
             <div v-if="providerStore.modelsByProvider[provider.provider_id]?.length" class="model-picker">
@@ -138,42 +97,13 @@ async function chooseDefaultModel(provider: ProviderConfig, event: Event) {
       </div>
     </div>
 
-    <div v-else-if="activeSection === 'index'" class="panel settings-section"><h2>索引与模型</h2><div class="index-summary"><div><span class="badge" :class="{ success: settingsStore.indexStatus.status === 'idle', error: settingsStore.indexStatus.status === 'error' }">{{ settingsStore.indexStatus.status }}</span><p>待处理任务 {{ settingsStore.indexStatus.pending_jobs }}</p></div><div><strong>{{ settingsStore.indexStatus.total_notes }}</strong><small>笔记</small></div><div><strong>{{ settingsStore.indexStatus.total_blocks }}</strong><small>Block</small></div></div><div v-if="settingsStore.indexStatus.error" class="error-banner">{{ settingsStore.indexStatus.error }}</div><div class="inline-actions"><button class="button-primary" @click="settingsStore.rebuildIndex('full')">重建全部</button><button class="button-secondary" @click="settingsStore.rebuildIndex('fts')">重建文本索引</button><button class="button-secondary" @click="settingsStore.rebuildIndex('vector')">重建向量索引</button></div></div>
+    <div v-else-if="activeSection === 'index'" class="panel settings-section"><h2>索引与模型</h2><div class="index-summary"><div><span class="badge" :class="{ success: settingsStore.indexStatus.status === 'idle', error: settingsStore.indexStatus.status === 'error' }">{{ settingsStore.indexStatus.status }}</span><p>待处理任务 {{ settingsStore.indexStatus.pending_jobs }}</p></div><div><strong>{{ settingsStore.indexStatus.total_notes }}</strong><small>笔记</small></div><div><strong>{{ settingsStore.indexStatus.total_blocks }}</strong><small>Block</small></div></div><div v-if="settingsStore.indexStatus.error" class="error-banner">{{ settingsStore.indexStatus.error }}</div><div class="inline-actions"><button class="button-primary" @click="settingsStore.rebuildIndex('full')">重建全部</button><button class="button-secondary" @click="settingsStore.rebuildIndex('fts')">重建文本索引</button><button class="button-secondary" @click="settingsStore.rebuildIndex('vector')">重建向量索引</button></div><ModelRoutingSettings /></div>
 
     <div v-else-if="activeSection === 'permissions'" class="panel settings-section"><h2>权限策略</h2><p class="muted section-description">高影响能力默认需要确认。未知权限由后端拒绝。</p><div class="permission-list"><div v-for="(policy, permission) in settingsStore.permissionPolicy" :key="permission" class="setting-row"><span><strong>{{ permission }}</strong></span><select :value="policy" class="select short" @change="settingsStore.setPermission(String(permission), ($event.target as HTMLSelectElement).value as 'allow' | 'confirm' | 'deny')"><option value="allow">允许</option><option value="confirm">每次确认</option><option value="deny">拒绝</option></select></div></div></div>
 
     <div v-else class="panel settings-section"><h2>AI Core 诊断</h2><div v-if="settingsStore.diagnosticsError" class="error-banner">{{ settingsStore.diagnosticsError }}</div><div class="diagnostic-grid"><div class="item-card"><span class="badge" :class="{ success: settingsStore.aiCoreStatus === 'running', error: settingsStore.aiCoreStatus === 'error' }">{{ settingsStore.aiCoreStatus }}</span><h3>Sidecar 状态</h3><p class="subtle">AI Core 不可用时，Markdown 编辑仍可继续使用。</p></div><div class="item-card"><strong>{{ settingsStore.aiCoreAddress }}</strong><h3>开发 API 地址</h3><p class="subtle">正式桌面环境由 Sidecar Manager 动态提供。</p></div></div><div class="inline-actions diagnostic-actions"><button class="button-primary" @click="settingsStore.loadDiagnostics">重新检测</button><button class="button-secondary" @click="settingsStore.restartAiCore">重启 AI Core</button></div></div>
 
-    <div v-if="showProviderForm" class="modal-backdrop" @click.self="closeProvider">
-      <div class="modal">
-        <h2>{{ editingProviderId ? '编辑 Provider' : '新增 Provider' }}</h2>
-        <form @submit.prevent="saveProvider">
-          <div class="field">
-            <label>提供商预设</label>
-            <select v-model="providerForm.preset_id" class="select" @change="applyProviderPreset">
-              <option value="">自定义</option>
-              <option v-for="preset in providerStore.presets" :key="preset.preset_id" :value="preset.preset_id">{{ preset.name }}</option>
-            </select>
-          </div>
-          <div class="field"><label>接入协议</label><select v-model="providerForm.provider_type" class="select"><option value="openai_compatible">OpenAI Compatible</option><option value="openai_chat">OpenAI Chat</option><option value="openai_responses">OpenAI Responses</option><option value="anthropic_messages">Anthropic Messages</option><option value="ollama">Ollama</option></select></div>
-          <div class="field"><label>名称</label><input v-model="providerForm.name" class="input" required /></div>
-          <div class="field"><label>Base URL</label><input v-model="providerForm.base_url" class="input" placeholder="https://api.example.com/v1" required /></div>
-          <div class="field">
-            <label>默认模型</label>
-            <input v-model="providerForm.default_model" class="input" :list="editingProviderId ? 'provider-model-options' : undefined" placeholder="保存后自动获取，也可以手动输入" />
-            <datalist id="provider-model-options"><option v-for="model in formModels" :key="model.model_id" :value="model.model_id">{{ model.name }}</option></datalist>
-          </div>
-          <div v-if="selectedPreset?.requires_credential" class="field">
-            <label>API Key</label>
-            <input v-model="providerApiKey" class="input" type="password" autocomplete="new-password" spellcheck="false" :placeholder="providerStore.credentialConfiguredById[providerForm.credential_id] ? '已配置，留空表示不修改' : '请输入 API Key'" />
-            <small class="subtle">提交后由本地 AI Core 加密保存，页面不会回显已保存的密钥。</small>
-          </div>
-          <div v-else-if="!selectedPreset" class="field"><label>Credential ID</label><input v-model="providerForm.credential_id" class="input" placeholder="自定义凭据标识" /><small class="subtle">自定义服务可以引用 Host 注入或后端已保存的凭据。</small></div>
-          <label class="inline-actions"><input v-model="providerForm.enabled" type="checkbox" /> 启用</label>
-          <div class="inline-actions"><button class="button-primary">保存并获取模型</button><button type="button" class="button-secondary" @click="closeProvider">取消</button></div>
-        </form>
-      </div>
-    </div>
+    <ProviderForm v-if="showProviderForm" :provider="editingProvider" :models="editingProvider ? providerStore.modelsByProvider[editingProvider.provider_id] : []" @close="showProviderForm = false" @saved="providerSaved" />
   </section>
 </template>
 

frontend/src/services/index.ts

@@ -10,6 +10,7 @@ export * as skillService from './skillService'
 export * as pluginService from './pluginService'
 export * as mcpServerService from './mcpServerService'
 export * as providerService from './providerService'
+export * as modelRoutingService from './modelRoutingService'
 export * as taskService from './taskService'
 export * as indexService from './indexService'
 export * as systemService from './systemService'

frontend/src/services/modelRoutingService.spec.ts

@@ -0,0 +1,28 @@
+// @vitest-environment happy-dom
+import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest'
+import { getModelRouting, saveModelRouting } from './modelRoutingService'
+
+const config = { version: 7, embedding: { provider_id: 'p1', model: 'embedding', endpoint: '/embeddings', dimensions: 1024 }, transcription: null, speaker_matching: null }
+const result = { config, local_backends: [{ capability: 'embedding', status: 'placeholder', message: 'hash' }] }
+const json = (body: unknown, status = 200) => new Response(JSON.stringify(body), { status, headers: { 'Content-Type': 'application/json' } })
+beforeEach(() => { vi.stubGlobal('fetch', vi.fn()) })
+afterEach(() => { vi.unstubAllGlobals() })
+
+describe('model routing service', () => {
+  it('round-trips versioned routing without an extra config wrapper', async () => {
+    vi.mocked(fetch).mockImplementation(async () => json(result))
+    expect(await getModelRouting()).toEqual(result)
+    expect(await saveModelRouting(config)).toEqual(result)
+    expect(fetch).toHaveBeenNthCalledWith(1, '/api/model-routing', expect.objectContaining({ method: 'GET' }))
+    expect(fetch).toHaveBeenNthCalledWith(2, '/api/model-routing', expect.objectContaining({ method: 'PUT', body: JSON.stringify(config) }))
+  })
+
+  it('surfaces load, save and version conflict errors instead of returning local defaults', async () => {
+    vi.mocked(fetch).mockRejectedValueOnce(new Error('offline'))
+      .mockResolvedValueOnce(json({ error: { code: 'MODEL_ROUTING_VERSION_CONFLICT', message: 'conflict' } }, 409))
+      .mockResolvedValueOnce(json({ error: { code: 'SAVE_FAILED', message: 'disk full' } }, 500))
+    await expect(getModelRouting()).rejects.toMatchObject({ code: 'NETWORK_ERROR' })
+    await expect(saveModelRouting(config)).rejects.toMatchObject({ code: 'MODEL_ROUTING_VERSION_CONFLICT' })
+    await expect(saveModelRouting(config)).rejects.toMatchObject({ code: 'SAVE_FAILED' })
+  })
+})

frontend/src/services/modelRoutingService.ts

@@ -0,0 +1,11 @@
+import type { ModelRoutingConfig, ModelRoutingResponse } from '@/contracts'
+import apiClient from './apiClient'
+
+export function getModelRouting(): Promise<ModelRoutingResponse> {
+  return apiClient.get('/api/model-routing')
+}
+
+// version is the last version read from the server (optimistic concurrency).
+export function saveModelRouting(config: ModelRoutingConfig): Promise<ModelRoutingResponse> {
+  return apiClient.put('/api/model-routing', config)
+}

frontend/src/services/providerService.spec.ts

@@ -0,0 +1,35 @@
+// @vitest-environment happy-dom
+import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest'
+import { createProvider, listProviderPresets, putCredential, updateProvider } from './providerService'
+
+const provider = { provider_id: 'provider-1', provider_type: 'openai_chat', name: 'Custom', capabilities: [], enabled: true }
+const json = (body: unknown) => new Response(JSON.stringify(body), { headers: { 'Content-Type': 'application/json' } })
+beforeEach(() => { vi.stubGlobal('fetch', vi.fn()) })
+afterEach(() => { vi.unstubAllGlobals() })
+
+describe('provider wire contracts', () => {
+  it('retains preset logos, descriptions and capabilities', async () => {
+    const preset = { preset_id: 'qwen', logo_id: 'qwen', description: '通义千问', capabilities: ['chat', 'embedding'] }
+    vi.mocked(fetch).mockResolvedValue(json({ items: [preset] }))
+    expect(await listProviderPresets()).toEqual([preset])
+  })
+
+  it('persists protocol edits and explicit credential unlinking', async () => {
+    vi.mocked(fetch).mockResolvedValue(json(provider))
+    await updateProvider('provider-1', { provider_type: 'openai_responses', default_model: '', credential_id: null })
+    expect(fetch).toHaveBeenCalledWith('/api/providers/provider-1', expect.objectContaining({ method: 'PATCH' }))
+    expect(JSON.parse(String(vi.mocked(fetch).mock.calls[0][1]?.body))).toEqual({ provider_type: 'openai_responses', default_model: '', credential_id: null })
+  })
+
+  it('sends secrets only to credentials and a reference to provider configuration', async () => {
+    vi.mocked(fetch).mockResolvedValueOnce(json({ configured: true })).mockResolvedValueOnce(json(provider))
+    await putCredential('provider-key-test', 'test-only-key')
+    await createProvider({ name: 'Custom', provider_type: 'openai_compatible', default_model: '', enabled: true, credential_id: 'provider-key-test', has_credential: true, capabilities: {} })
+    const calls = vi.mocked(fetch).mock.calls
+    expect(calls[0][0]).toBe('/api/credentials/provider-key-test')
+    expect(JSON.parse(String(calls[0][1]?.body))).toEqual({ api_key: 'test-only-key' })
+    expect(JSON.parse(String(calls[1][1]?.body))).toMatchObject({ credential_id: 'provider-key-test' })
+    expect(calls[1][1]?.body).not.toContain('test-only-key')
+    expect(calls[1][1]?.body).not.toContain('has_credential')
+  })
+})

frontend/src/services/providerService.ts

@@ -1,5 +1,5 @@
 import apiClient from './apiClient'
-import type { ApiModelInfo, ApiProviderConfig, ApiProviderPreset, ModelCapability, ModelInfo, OperationResponse, ProviderConfig, ProviderPreset } from '@/contracts'
+import type { ApiModelInfo, ApiProviderConfig, ApiProviderPreset, ModelCapability, ModelInfo, OperationResponse, ProviderConfig, ProviderPreset, ProviderUpdateRequest } from '@/contracts'
 
 function capabilityMap(capabilities: string[]): Partial<ModelCapability> {
   return Object.fromEntries(capabilities.map((capability) => [capability, true])) as Partial<ModelCapability>
@@ -61,8 +61,9 @@ export async function putCredential(credentialId: string, apiKey: string): Promi
   )
 }
 
-export async function updateProvider(providerId: string, data: Partial<ProviderConfig>): Promise<ProviderConfig> {
+export async function updateProvider(providerId: string, data: ProviderUpdateRequest): Promise<ProviderConfig> {
   const response = await apiClient.patch<ApiProviderConfig>(`/api/providers/${providerId}`, {
+    provider_type: data.provider_type,
     name: data.name,
     base_url: data.base_url,
     default_model: data.default_model,