feat(prompt-optimizer): add prompt optimization APIs and database tables

- Added API endpoints for prompt optimization:
  * POST /prompt/sessions: Create a new prompt optimization session
  * GET /prompt/sessions/{session_id}: Retrieve session message history
  * POST /prompt/sessions/{session_id}/messages: Send message and get optimized prompt
  * PUT /prompt/model: Create or update system prompt model configuration

- Added database models for prompt optimization:
  * prompt_opt_session: Stores session metadata
  * prompt_opt_session_history: Stores session message history
  * prompt_opt_message: Stores user and assistant messages
  * prompt_opt_model_config: Stores system prompt model configurations

- Updated service layer to handle message creation, prompt optimization, and variable parsing
- Added corresponding Pydantic schemas for request and response validation

api/app/controllers/__init__.py

@@ -28,6 +28,7 @@ from . import (
     public_share_controller,
     multi_agent_controller,
     workflow_controller,
+    prompt_optimizer_controller
 )
 
 # 创建管理端 API 路由器
@@ -58,5 +59,6 @@ manager_router.include_router(public_share_controller.router)  # 公开路由（
 manager_router.include_router(memory_dashboard_controller.router)
 manager_router.include_router(multi_agent_controller.router)
 manager_router.include_router(workflow_controller.router)
+manager_router.include_router(prompt_optimizer_controller.router)
 
 __all__ = ["manager_router"]

api/app/controllers/prompt_optimizer_controller.py

@@ -0,0 +1,170 @@
+import uuid
+
+from fastapi import APIRouter, Depends, Path
+from sqlalchemy.orm import Session
+
+from app.core.logging_config import get_api_logger
+from app.core.response_utils import success
+from app.dependencies import get_current_user, get_db
+from app.models.prompt_optimizer_model import RoleType
+from app.schemas.prompt_optimizer_schema import PromptOptMessage, PromptOptModelSet, CreateSessionResponse, \
+    OptimizePromptResponse, SessionHistoryResponse, SessionMessage
+from app.schemas.response_schema import ApiResponse
+from app.services.prompt_optimizer_service import PromptOptimizerService
+
+router = APIRouter(prefix="/prompt", tags=["Prompts-Optimization"])
+logger = get_api_logger()
+
+
+@router.post(
+    "/sessions",
+    summary="Create a new prompt optimization session",
+    response_model=ApiResponse
+)
+def create_prompt_session(
+        db: Session = Depends(get_db),
+        current_user=Depends(get_current_user),
+):
+    """
+    Create a new prompt optimization session for the current user.
+
+    Returns:
+        ApiResponse: Contains the newly generated session ID.
+    """
+    service = PromptOptimizerService(db)
+    # create new session
+    session = service.create_session(current_user.tenant_id, current_user.id)
+    result_schema = CreateSessionResponse.model_validate(session)
+    return success(data=result_schema)
+
+
+@router.get(
+    "/sessions/{session_id}",
+    summary="获取 prompt 优化历史对话",
+    response_model=ApiResponse
+)
+def get_prompt_session(
+        session_id: uuid.UUID = Path(..., description="Session ID"),
+        db: Session = Depends(get_db),
+        current_user=Depends(get_current_user),
+):
+    """
+    Retrieve all messages from a specified prompt optimization session.
+
+    Args:
+        session_id (UUID): The ID of the session to retrieve
+        db (Session): Database session
+        current_user: Current logged-in user
+
+    Returns:
+        ApiResponse: Contains the session ID and the list of messages.
+    """
+    service = PromptOptimizerService(db)
+
+    history = service.get_session_message_history(
+        session_id=session_id,
+        user_id=current_user.id
+    )
+
+    messages = [
+        SessionMessage(role=role, content=content)
+        for role, content in history
+    ]
+    
+    result = SessionHistoryResponse(
+        session_id=session_id,
+        messages=messages
+    )
+    
+    return success(data=result)
+
+
+@router.post(
+    "/sessions/{session_id}/messages",
+    summary="Get prompt optimization",
+    response_model=ApiResponse
+)
+async def get_prompt_opt(
+        session_id: uuid.UUID = Path(..., description="Session ID"),
+        data: PromptOptMessage = ...,
+        db: Session = Depends(get_db),
+        current_user=Depends(get_current_user),
+):
+    """
+    Send a user message in the specified session and return the optimized prompt
+    along with its description and variables.
+
+    Args:
+        session_id (UUID): The session ID
+        data (PromptOptMessage): Contains the user message, model ID, and current prompt
+        db (Session): Database session
+        current_user: Current user information
+
+    Returns:
+        ApiResponse: Contains the optimized prompt, description, and a list of variables.
+    """
+    service = PromptOptimizerService(db)
+    service.create_message(
+        tenant_id=current_user.tenant_id,
+        session_id=session_id,
+        user_id=current_user.id,
+        role=RoleType.USER,
+        content=data.message
+    )
+    opt_result = await service.optimize_prompt(
+        tenant_id=current_user.tenant_id,
+        model_id=data.model_id,
+        session_id=session_id,
+        user_id=current_user.id,
+        current_prompt=data.current_prompt,
+        message=data.message
+    )
+    service.create_message(
+        tenant_id=current_user.tenant_id,
+        session_id=session_id,
+        user_id=current_user.id,
+        role=RoleType.ASSISTANT,
+        content=opt_result.desc
+    )
+    variables = service.parser_prompt_variables(opt_result.prompt)
+    result = {
+        "prompt": opt_result.prompt,
+        "desc": opt_result.desc,
+        "variables": variables
+    }
+    result_schema = OptimizePromptResponse.model_validate(result)
+    return success(data=result_schema)
+
+
+@router.put(
+    "/model",
+    summary="Create or update prompt model config",
+    response_model=ApiResponse
+)
+def set_system_prompt(
+        data: PromptOptModelSet = ...,
+        db: Session = Depends(get_db),
+        current_user=Depends(get_current_user),
+):
+    """
+    Create or update a system prompt model configuration for the tenant.
+
+    Args:
+        data (PromptOptModelSet): Model configuration data including model ID,
+                                   system prompt, and optional configuration ID
+        db (Session): Database session
+        current_user: Current user information
+
+    Returns:
+        UUID: The ID of the created or updated model configuration.
+    """
+    if data.id is None:
+        data.id = uuid.uuid4()
+
+    model_config = PromptOptimizerService(db).create_update_model_config(
+        current_user.tenant_id,
+        data.id, data.model_id,
+        data.system_prompt
+    )
+    return success(data=model_config.id)
+