310491a557
- Updated python_coding_microproject.csv to use NVIDIA NIM Kimi K2 - Updated kali_linux_shell_simulator.csv to use NVIDIA NIM Kimi K2 - Made more general-purpose (flexible targets, expanded tools) - Added nemotron-mini-agent.csv for fast local inference via Ollama - Added nemotron-agent.csv for advanced reasoning via Ollama - Added wiki page: Projects for NVIDIA NIMs and Nemotron
137 lines
4.5 KiB
Python
137 lines
4.5 KiB
Python
"""
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Message API endpoints for GT 2.0 Tenant Backend
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Handles message management within conversations.
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"""
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from fastapi import APIRouter, HTTPException, Depends
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from fastapi.responses import JSONResponse, StreamingResponse
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from typing import Dict, Any
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from pydantic import BaseModel, Field
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import json
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import logging
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from app.services.conversation_service import ConversationService
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from app.core.security import get_current_user
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from app.core.user_resolver import resolve_user_uuid
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router = APIRouter(tags=["messages"])
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class SendMessageRequest(BaseModel):
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"""Request model for sending a message"""
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content: str = Field(..., description="Message content")
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stream: bool = Field(default=False, description="Stream the response")
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logger = logging.getLogger(__name__)
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async def get_conversation_service(
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current_user: Dict[str, Any] = Depends(get_current_user)
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) -> ConversationService:
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"""Get properly initialized conversation service"""
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tenant_domain, user_email, user_id = await resolve_user_uuid(current_user)
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return ConversationService(tenant_domain=tenant_domain, user_id=user_id)
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@router.get("/conversations/{conversation_id}/messages")
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async def list_messages(
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conversation_id: str,
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current_user: Dict[str, Any] = Depends(get_current_user)
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) -> JSONResponse:
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"""List messages in conversation"""
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try:
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# Get properly initialized service
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service = await get_conversation_service(current_user)
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# Get conversation with messages
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result = await service.get_conversation(
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conversation_id=conversation_id,
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user_identifier=service.user_id,
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include_messages=True
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)
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return JSONResponse(
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status_code=200,
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content={"messages": result.get("messages", [])}
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)
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except ValueError as e:
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raise HTTPException(status_code=404, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@router.post("/conversations/{conversation_id}/messages")
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async def send_message(
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conversation_id: str,
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role: str,
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content: str,
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stream: bool = False,
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current_user: Dict[str, Any] = Depends(get_current_user)
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) -> JSONResponse:
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"""Send a message and get AI response"""
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try:
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# Get properly initialized service
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service = await get_conversation_service(current_user)
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# Send message
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result = await service.send_message(
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conversation_id=conversation_id,
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content=content,
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stream=stream
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)
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# Generate title after first message
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if result.get("is_first_message", False):
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try:
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await service.auto_generate_conversation_title(
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conversation_id=conversation_id,
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user_identifier=service.user_id
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)
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logger.info(f"✅ Title generated for conversation {conversation_id}")
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except Exception as e:
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logger.warning(f"Failed to generate title: {e}")
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# Don't fail the request if title generation fails
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return JSONResponse(status_code=201, content=result)
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except ValueError as e:
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raise HTTPException(status_code=404, detail=str(e))
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/conversations/{conversation_id}/messages/stream")
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async def stream_message(
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conversation_id: int,
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content: str,
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service: ConversationService = Depends(get_conversation_service),
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current_user: str = Depends(get_current_user)
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):
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"""Stream AI response for a message"""
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async def generate():
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"""Generate SSE stream"""
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try:
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async for chunk in service.stream_message_response(
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conversation_id=conversation_id,
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message_content=content,
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user_identifier=current_user
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):
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# Format as Server-Sent Event
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yield f"data: {json.dumps({'content': chunk})}\n\n"
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# Send completion signal
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yield "data: [DONE]\n\n"
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except Exception as e:
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logger.error(f"Message streaming failed: {e}", exc_info=True)
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yield f"data: {json.dumps({'error': 'An internal error occurred. Please try again.'})}\n\n"
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return StreamingResponse(
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generate(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no"
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}
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) |