init. project

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

@@ -0,0 +1,12 @@
+from .api_key import APIKey, APIKeyCreate, APIKeyUpdate, APIKeyInDB
+from .user import UserBase, UserCreate, UserUpdate, UserResponse
+from .token import Token, TokenPayload
+from .knowledge import KnowledgeBaseBase, KnowledgeBaseCreate, KnowledgeBaseUpdate, KnowledgeBaseResponse
+from .testing import (
+	ExpectedResultEntry,
+	StepLogEntry,
+	TestCaseEntry,
+	TestItemEntry,
+	TestingPipelineRequest,
+	TestingPipelineResponse,
+)

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

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+from typing import Optional
+from datetime import datetime
+from pydantic import BaseModel
+
+class APIKeyBase(BaseModel):
+    name: str
+    is_active: bool = True
+
+class APIKeyCreate(APIKeyBase):
+    pass
+
+class APIKeyUpdate(BaseModel):
+    name: Optional[str] = None
+    is_active: Optional[bool] = None
+
+class APIKey(APIKeyBase):
+    id: int
+    key: str
+    user_id: int
+    last_used_at: Optional[datetime] = None
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+class APIKeyInDB(APIKey):
+    pass 

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

@@ -0,0 +1,39 @@
+from pydantic import BaseModel
+from typing import List, Optional
+from datetime import datetime
+
+class MessageBase(BaseModel):
+    content: str
+    role: str
+
+class MessageCreate(MessageBase):
+    chat_id: int
+
+class MessageResponse(MessageBase):
+    id: int
+    chat_id: int
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+class ChatBase(BaseModel):
+    title: str
+
+class ChatCreate(ChatBase):
+    knowledge_base_ids: List[int]
+
+class ChatUpdate(ChatBase):
+    knowledge_base_ids: Optional[List[int]] = None
+
+class ChatResponse(ChatBase):
+    id: int
+    user_id: int
+    created_at: datetime
+    updated_at: datetime
+    messages: List[MessageResponse] = []
+    knowledge_base_ids: List[int] = []
+
+    class Config:
+        from_attributes = True 

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

@@ -0,0 +1,85 @@
+from typing import Optional, List
+from datetime import datetime
+from pydantic import BaseModel
+
+class KnowledgeBaseBase(BaseModel):
+    name: str
+    description: Optional[str] = None
+
+class KnowledgeBaseCreate(KnowledgeBaseBase):
+    pass
+
+class KnowledgeBaseUpdate(KnowledgeBaseBase):
+    pass
+
+class DocumentBase(BaseModel):
+    file_name: str
+    file_path: str
+    file_hash: str
+    file_size: int
+    content_type: str
+
+class DocumentCreate(DocumentBase):
+    knowledge_base_id: int
+
+class DocumentUploadBase(BaseModel):
+    file_name: str
+    file_hash: str
+    file_size: int
+    content_type: str
+    temp_path: str
+    status: str = "pending"
+    error_message: Optional[str] = None
+
+class DocumentUploadCreate(DocumentUploadBase):
+    knowledge_base_id: int
+
+class DocumentUploadResponse(DocumentUploadBase):
+    id: int
+    created_at: datetime
+    
+    class Config:
+        from_attributes = True
+
+class ProcessingTaskBase(BaseModel):
+    status: str
+    error_message: Optional[str] = None
+
+class ProcessingTaskCreate(ProcessingTaskBase):
+    document_id: int
+    knowledge_base_id: int
+
+class ProcessingTask(ProcessingTaskBase):
+    id: int
+    document_id: int
+    knowledge_base_id: int
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+class DocumentResponse(DocumentBase):
+    id: int
+    knowledge_base_id: int
+    created_at: datetime
+    updated_at: datetime
+    processing_tasks: List[ProcessingTask] = []
+
+    class Config:
+        from_attributes = True
+
+class KnowledgeBaseResponse(KnowledgeBaseBase):
+    id: int
+    user_id: int
+    created_at: datetime
+    updated_at: datetime
+    documents: List[DocumentResponse] = []
+
+    class Config:
+        from_attributes = True
+
+class PreviewRequest(BaseModel):
+    document_ids: List[int]
+    chunk_size: int = 1000
+    chunk_overlap: int = 200 

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

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+from typing import Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class TestItemEntry(BaseModel):
+    id: str
+    content: str
+
+
+class TestCaseEntry(BaseModel):
+    id: str
+    item_id: str
+    operation_steps: List[str]
+    test_content: str
+    expected_result_placeholder: str
+
+
+class ExpectedResultEntry(BaseModel):
+    id: str
+    case_id: str
+    result: str
+
+
+class StepLogEntry(BaseModel):
+    step_name: str
+    input_summary: str
+    output_summary: str
+    success: bool
+    fallback_used: bool
+    duration_ms: float
+
+
+class TestingPipelineRequest(BaseModel):
+    requirement_text: str = Field(..., min_length=1)
+    requirement_type: Optional[str] = None
+    knowledge_base_ids: List[int] = []
+    retrieval_top_k: int = Field(default=8, ge=1, le=20)
+    knowledge_context: Optional[str] = None
+    use_model_generation: bool = True
+    max_items_per_group: int = Field(default=12, ge=4, le=30)
+    cases_per_item: int = Field(default=2, ge=1, le=5)
+    max_focus_points: int = Field(default=6, ge=3, le=12)
+    max_llm_calls: int = Field(default=10, ge=0, le=100)
+    debug: bool = False
+
+
+class TestingPipelineResponse(BaseModel):
+    trace_id: str
+    requirement_type: str
+    reason: str
+    candidates: List[str]
+    test_items: Dict[str, List[TestItemEntry]]
+    test_cases: Dict[str, List[TestCaseEntry]]
+    expected_results: Dict[str, List[ExpectedResultEntry]]
+    formatted_output: str
+    pipeline_summary: str
+    knowledge_used: bool = False
+    step_logs: List[StepLogEntry] = []

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

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+from pydantic import BaseModel
+from typing import Optional
+
+class Token(BaseModel):
+    access_token: str
+    token_type: str
+
+class TokenPayload(BaseModel):
+    sub: Optional[int] = None 

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

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+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel
+
+
+class ToolDefinitionResponse(BaseModel):
+    name: str
+    version: str
+    description: str
+    input_schema: Dict[str, Any]
+    output_schema: Dict[str, Any]
+
+
+class SRSToolCreateJobResponse(BaseModel):
+    job_id: int
+    status: str
+
+
+class SRSToolJobStatusResponse(BaseModel):
+    job_id: int
+    tool_name: str
+    status: str
+    error_message: Optional[str] = None
+    extraction_id: Optional[int] = None
+    started_at: Optional[datetime] = None
+    completed_at: Optional[datetime] = None
+
+
+class SRSToolRequirementItem(BaseModel):
+    id: str
+    title: str
+    description: str
+    priority: str
+    acceptanceCriteria: List[str]
+    sourceField: str
+    sectionNumber: Optional[str] = None
+    sectionTitle: Optional[str] = None
+    requirementType: Optional[str] = None
+    sortOrder: int
+
+
+class SRSToolResultResponse(BaseModel):
+    jobId: int
+    documentName: str
+    generatedAt: str
+    statistics: Dict[str, Any]
+    requirements: List[SRSToolRequirementItem]
+
+
+class SRSToolRequirementsSaveRequest(BaseModel):
+    requirements: List[SRSToolRequirementItem]

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

@@ -0,0 +1,23 @@
+from pydantic import BaseModel, EmailStr
+from typing import Optional
+from datetime import datetime
+
+class UserBase(BaseModel):
+    email: EmailStr
+    username: str
+    is_active: bool = True
+    is_superuser: bool = False
+
+class UserCreate(UserBase):
+    password: str
+
+class UserUpdate(UserBase):
+    password: Optional[str] = None
+
+class UserResponse(UserBase):
+    id: int
+    created_at: datetime
+    updated_at: datetime
+
+    class Config:
+        from_attributes = True