Add backend api and engine

api/app/schemas.py

@@ -0,0 +1,271 @@
+from datetime import datetime
+from typing import List, Optional
+from pydantic import BaseModel
+
+
+# ============ Voice ============
+class VoiceBase(BaseModel):
+    name: str
+    vendor: str
+    gender: str
+    language: str
+    description: str
+
+
+class VoiceOut(VoiceBase):
+    id: str
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Assistant ============
+class AssistantBase(BaseModel):
+    name: str
+    opener: str = ""
+    prompt: str = ""
+    knowledgeBaseId: Optional[str] = None
+    language: str = "zh"
+    voice: Optional[str] = None
+    speed: float = 1.0
+    hotwords: List[str] = []
+    tools: List[str] = []
+    interruptionSensitivity: int = 500
+    configMode: str = "platform"
+    apiUrl: Optional[str] = None
+    apiKey: Optional[str] = None
+
+
+class AssistantCreate(AssistantBase):
+    pass
+
+
+class AssistantUpdate(AssistantBase):
+    name: Optional[str] = None
+
+
+class AssistantOut(AssistantBase):
+    id: str
+    callCount: int = 0
+    created_at: Optional[datetime] = None
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Knowledge Base ============
+class KnowledgeDocument(BaseModel):
+    id: str
+    name: str
+    size: str
+    fileType: str = "txt"
+    storageUrl: Optional[str] = None
+    status: str = "pending"
+    chunkCount: int = 0
+    uploadDate: str
+
+
+class KnowledgeDocumentCreate(BaseModel):
+    name: str
+    size: str
+    fileType: str = "txt"
+    storageUrl: Optional[str] = None
+
+
+class KnowledgeDocumentUpdate(BaseModel):
+    status: Optional[str] = None
+    chunkCount: Optional[int] = None
+    errorMessage: Optional[str] = None
+
+
+class KnowledgeBaseBase(BaseModel):
+    name: str
+    description: str = ""
+    embeddingModel: str = "text-embedding-3-small"
+    chunkSize: int = 500
+    chunkOverlap: int = 50
+
+
+class KnowledgeBaseCreate(KnowledgeBaseBase):
+    pass
+
+
+class KnowledgeBaseUpdate(BaseModel):
+    name: Optional[str] = None
+    description: Optional[str] = None
+    embeddingModel: Optional[str] = None
+    chunkSize: Optional[int] = None
+    chunkOverlap: Optional[int] = None
+    status: Optional[str] = None
+
+
+class KnowledgeBaseOut(KnowledgeBaseBase):
+    id: str
+    docCount: int = 0
+    chunkCount: int = 0
+    status: str = "active"
+    createdAt: Optional[datetime] = None
+    updatedAt: Optional[datetime] = None
+    documents: List[KnowledgeDocument] = []
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Knowledge Search ============
+class KnowledgeSearchQuery(BaseModel):
+    query: str
+    kb_id: str
+    nResults: int = 5
+
+
+class KnowledgeSearchResult(BaseModel):
+    query: str
+    results: List[dict]
+
+
+class DocumentIndexRequest(BaseModel):
+    document_id: str
+    content: str
+
+
+class KnowledgeStats(BaseModel):
+    kb_id: str
+    docCount: int
+    chunkCount: int
+
+
+# ============ Workflow ============
+class WorkflowNode(BaseModel):
+    name: str
+    type: str
+    isStart: Optional[bool] = None
+    metadata: dict
+    prompt: Optional[str] = None
+    messagePlan: Optional[dict] = None
+    variableExtractionPlan: Optional[dict] = None
+    tool: Optional[dict] = None
+    globalNodePlan: Optional[dict] = None
+
+
+class WorkflowEdge(BaseModel):
+    from_: str
+    to: str
+    label: Optional[str] = None
+
+    class Config:
+        populate_by_name = True
+
+
+class WorkflowBase(BaseModel):
+    name: str
+    nodeCount: int = 0
+    createdAt: str = ""
+    updatedAt: str = ""
+    globalPrompt: Optional[str] = None
+    nodes: List[dict] = []
+    edges: List[dict] = []
+
+
+class WorkflowCreate(WorkflowBase):
+    pass
+
+
+class WorkflowUpdate(BaseModel):
+    name: Optional[str] = None
+    nodeCount: Optional[int] = None
+    nodes: Optional[List[dict]] = None
+    edges: Optional[List[dict]] = None
+    globalPrompt: Optional[str] = None
+
+
+class WorkflowOut(WorkflowBase):
+    id: str
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Call Record ============
+class TranscriptSegment(BaseModel):
+    turnIndex: int
+    speaker: str  # human/ai
+    content: str
+    confidence: Optional[float] = None
+    startMs: int
+    endMs: int
+    durationMs: Optional[int] = None
+    audioUrl: Optional[str] = None
+
+
+class CallRecordCreate(BaseModel):
+    user_id: int
+    assistant_id: Optional[str] = None
+    source: str = "debug"
+
+
+class CallRecordUpdate(BaseModel):
+    status: Optional[str] = None
+    summary: Optional[str] = None
+    duration_seconds: Optional[int] = None
+
+
+class CallRecordOut(BaseModel):
+    id: str
+    user_id: int
+    assistant_id: Optional[str] = None
+    source: str
+    status: str
+    started_at: str
+    ended_at: Optional[str] = None
+    duration_seconds: Optional[int] = None
+    summary: Optional[str] = None
+    transcripts: List[TranscriptSegment] = []
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Call Transcript ============
+class TranscriptCreate(BaseModel):
+    turn_index: int
+    speaker: str
+    content: str
+    confidence: Optional[float] = None
+    start_ms: int
+    end_ms: int
+    duration_ms: Optional[int] = None
+    emotion: Optional[str] = None
+
+
+class TranscriptOut(TranscriptCreate):
+    id: int
+    audio_url: Optional[str] = None
+
+    class Config:
+        from_attributes = True
+
+
+# ============ Dashboard ============
+class DashboardStats(BaseModel):
+    totalCalls: int
+    answerRate: int
+    avgDuration: str
+    humanTransferCount: int
+    trend: List[dict]
+
+
+# ============ API Response ============
+class Message(BaseModel):
+    message: str
+
+
+class DocumentIndexRequest(BaseModel):
+    content: str
+
+
+class ListResponse(BaseModel):
+    total: int
+    page: int
+    limit: int
+    list: List