5cd46e441e
- Replace the system prompt of the prompt optimization model with a built-in prompt. - Remove system prompt entries from the database. - Remove the API endpoint for managing system prompt configuration.
139 lines
4.1 KiB
Python
139 lines
4.1 KiB
Python
import uuid
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from fastapi import APIRouter, Depends, Path
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from sqlalchemy.orm import Session
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from app.core.logging_config import get_api_logger
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from app.core.response_utils import success
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from app.dependencies import get_current_user, get_db
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from app.models.prompt_optimizer_model import RoleType
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from app.schemas.prompt_optimizer_schema import PromptOptMessage, PromptOptModelSet, CreateSessionResponse, \
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OptimizePromptResponse, SessionHistoryResponse, SessionMessage
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from app.schemas.response_schema import ApiResponse
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from app.services.prompt_optimizer_service import PromptOptimizerService
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router = APIRouter(prefix="/prompt", tags=["Prompts-Optimization"])
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logger = get_api_logger()
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@router.post(
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"/sessions",
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summary="Create a new prompt optimization session",
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response_model=ApiResponse
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)
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def create_prompt_session(
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db: Session = Depends(get_db),
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current_user=Depends(get_current_user),
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):
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"""
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Create a new prompt optimization session for the current user.
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Returns:
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ApiResponse: Contains the newly generated session ID.
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"""
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service = PromptOptimizerService(db)
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# create new session
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session = service.create_session(current_user.tenant_id, current_user.id)
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result_schema = CreateSessionResponse.model_validate(session)
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return success(data=result_schema)
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@router.get(
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"/sessions/{session_id}",
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summary="获取 prompt 优化历史对话",
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response_model=ApiResponse
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)
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def get_prompt_session(
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session_id: uuid.UUID = Path(..., description="Session ID"),
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db: Session = Depends(get_db),
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current_user=Depends(get_current_user),
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):
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"""
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Retrieve all messages from a specified prompt optimization session.
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Args:
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session_id (UUID): The ID of the session to retrieve
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db (Session): Database session
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current_user: Current logged-in user
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Returns:
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ApiResponse: Contains the session ID and the list of messages.
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"""
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service = PromptOptimizerService(db)
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history = service.get_session_message_history(
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session_id=session_id,
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user_id=current_user.id
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)
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messages = [
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SessionMessage(role=role, content=content)
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for role, content in history
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]
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result = SessionHistoryResponse(
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session_id=session_id,
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messages=messages
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)
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return success(data=result)
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@router.post(
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"/sessions/{session_id}/messages",
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summary="Get prompt optimization",
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response_model=ApiResponse
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)
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async def get_prompt_opt(
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session_id: uuid.UUID = Path(..., description="Session ID"),
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data: PromptOptMessage = ...,
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db: Session = Depends(get_db),
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current_user=Depends(get_current_user),
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):
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"""
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Send a user message in the specified session and return the optimized prompt
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along with its description and variables.
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Args:
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session_id (UUID): The session ID
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data (PromptOptMessage): Contains the user message, model ID, and current prompt
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db (Session): Database session
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current_user: Current user information
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Returns:
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ApiResponse: Contains the optimized prompt, description, and a list of variables.
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"""
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service = PromptOptimizerService(db)
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service.create_message(
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tenant_id=current_user.tenant_id,
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session_id=session_id,
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user_id=current_user.id,
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role=RoleType.USER,
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content=data.message
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)
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opt_result = await service.optimize_prompt(
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tenant_id=current_user.tenant_id,
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model_id=data.model_id,
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session_id=session_id,
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user_id=current_user.id,
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current_prompt=data.current_prompt,
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user_require=data.message
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)
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service.create_message(
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tenant_id=current_user.tenant_id,
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session_id=session_id,
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user_id=current_user.id,
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role=RoleType.ASSISTANT,
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content=opt_result.desc
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)
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variables = service.parser_prompt_variables(opt_result.prompt)
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result = {
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"prompt": opt_result.prompt,
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"desc": opt_result.desc,
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"variables": variables
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}
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result_schema = OptimizePromptResponse.model_validate(result)
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return success(data=result_schema)
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