增加代码知识库；修复文档处理内容；增加API设置

rag-web-ui/backend/app/schemas/__init__.py

@@ -1,4 +1,10 @@
 from .api_key import APIKey, APIKeyCreate, APIKeyUpdate, APIKeyInDB
+from .model_config import (
+    ModelConfigCreate,
+    ModelConfigResponse,
+    ModelConfigUpdate,
+    ModelProviderOptionsResponse,
+)
 from .user import UserBase, UserCreate, UserUpdate, UserResponse
 from .token import Token, TokenPayload
 from .knowledge import KnowledgeBaseBase, KnowledgeBaseCreate, KnowledgeBaseUpdate, KnowledgeBaseResponse

rag-web-ui/backend/app/schemas/consistency.py

@@ -0,0 +1,119 @@
+from __future__ import annotations
+
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class CodeKnowledgeBaseCreate(BaseModel):
+    name: str = Field(..., min_length=1)
+    project_path: Optional[str] = None
+    vector_path: str = Field(..., min_length=1)
+    metadata_path: str = Field(..., min_length=1)
+    graph_path: str = Field(..., min_length=1)
+
+
+class CodeKnowledgeBaseUploadResponse(BaseModel):
+    id: int
+    status: str
+
+
+class CodeKnowledgeBaseResponse(BaseModel):
+    id: int
+    name: str
+    project_path: Optional[str] = None
+    vector_path: str
+    metadata_path: str
+    graph_path: str
+    status: str
+    metadata_summary: Optional[Dict[str, Any]] = None
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+
+class CodeQuestionRequest(BaseModel):
+    question: str = Field(..., min_length=1)
+    top_k: int = Field(default=6, ge=1, le=20)
+    min_similarity: float = Field(default=0.0, ge=0.0, le=1.0)
+    use_llm: bool = True
+
+
+class CodeQuestionResponse(BaseModel):
+    answer: str
+    evidence: List[Dict[str, Any]]
+    raw_response: Optional[str] = None
+
+
+class ConsistencyJobCreate(BaseModel):
+    srs_extraction_id: int
+    code_kb_id: int
+    requirement_uids: Optional[List[str]] = None
+    top_k: int = Field(default=8, ge=1, le=30)
+    max_call_hops: int = Field(default=2, ge=0, le=4)
+    min_similarity: float = Field(default=0.55, ge=0.0, le=1.0)
+    use_llm: bool = True
+
+
+class ConsistencyJobCreateResponse(BaseModel):
+    job_id: int
+    status: str
+
+
+class AutoConsistencyJobCreateResponse(BaseModel):
+    job_id: int
+    status: str
+
+
+class AutoConsistencyJobStatusResponse(BaseModel):
+    job_id: int
+    status: str
+    error_message: Optional[str] = None
+    current_step: Optional[str] = None
+    srs_extraction_id: Optional[int] = None
+    code_kb_id: Optional[int] = None
+    consistency_job_id: Optional[int] = None
+    created_at: datetime
+    updated_at: datetime
+
+
+class ConsistencyJobResponse(BaseModel):
+    id: int
+    srs_extraction_id: int
+    code_kb_id: int
+    status: str
+    total_requirements: int
+    completed_requirements: int
+    output_summary: Optional[Dict[str, Any]] = None
+    error_message: Optional[str] = None
+    started_at: Optional[datetime] = None
+    completed_at: Optional[datetime] = None
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+
+class ConsistencyResultResponse(BaseModel):
+    id: int
+    job_id: int
+    requirement_uid: str
+    verdict: str
+    coverage_score: float
+    confidence: float
+    matched_functions: List[Dict[str, Any]]
+    covered_points: List[str]
+    missing_points: List[str]
+    conflict_points: List[str]
+    call_chain_evidence: List[str]
+    suggestion: Optional[str] = None
+    raw_judgment: Optional[Dict[str, Any]] = None
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True

rag-web-ui/backend/app/schemas/model_config.py

@@ -0,0 +1,57 @@
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class ModelConfigBase(BaseModel):
+    name: str
+    provider: str = "dashscope"
+    api_base: Optional[str] = None
+    chat_model: str = "qwen3-max"
+    embedding_model: str = "text-embedding-v4"
+    is_active: bool = True
+
+
+class ModelConfigCreate(ModelConfigBase):
+    api_key: str = Field(default="")
+
+
+class ModelConfigUpdate(BaseModel):
+    name: Optional[str] = None
+    provider: Optional[str] = None
+    api_key: Optional[str] = None
+    api_base: Optional[str] = None
+    chat_model: Optional[str] = None
+    embedding_model: Optional[str] = None
+    is_active: Optional[bool] = None
+
+
+class ModelConfigResponse(ModelConfigBase):
+    id: int
+    user_id: int
+    has_api_key: bool
+    api_key_masked: str
+    last_used_at: Optional[datetime] = None
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+
+class ModelProviderOption(BaseModel):
+    provider: str
+    label: str
+    default_api_base: str
+    default_chat_model: str
+    default_embedding_model: str
+    chat_models: List[str]
+    embedding_models: List[str]
+    requires_api_key: bool = True
+    supports_custom_api_base: bool = True
+
+
+class ModelProviderOptionsResponse(BaseModel):
+    providers: List[ModelProviderOption]
+    defaults: Dict[str, Any]