feat: Add Chat endpoint for AI conversation
Browse files- src/api/agents/chat/router.py +123 -0
src/api/agents/chat/router.py
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+
"""
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Chat Agent Router - API Endpoints for Chat functionality
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"""
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel, Field
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from typing import List, Optional, Dict, Any
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from src.services.groq_service import generate_response
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from src.api.core.logger import logger
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router = APIRouter()
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class ChatMessage(BaseModel):
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"""Chat message model"""
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role: str = Field(..., description="Role: 'user' or 'assistant'")
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content: str = Field(..., description="Message content")
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class ChatRequest(BaseModel):
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"""Request model for chat"""
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message: str = Field(..., description="User message")
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context: Optional[Dict[str, Any]] = Field(default=None, description="Additional context")
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conversation_id: Optional[str] = Field(default=None, description="Conversation ID for history")
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class ChatResponse(BaseModel):
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"""Response model for chat"""
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response: str
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conversation_id: Optional[str] = None
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model: str = "llama-3.1-8b-instant"
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# Simple in-memory conversation storage
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conversations: Dict[str, List[Dict[str, str]]] = {}
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@router.post("/chat", response_model=ChatResponse)
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async def chat(request: ChatRequest) -> ChatResponse:
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"""
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Chat endpoint - AI conversation
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- **message**: User's message
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- **context**: Optional context data
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- **conversation_id**: Optional conversation ID for history
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"""
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try:
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logger.info(f"Chat request: {request.message[:50]}...")
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# Get or create conversation
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conv_id = request.conversation_id or "default"
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if conv_id not in conversations:
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conversations[conv_id] = []
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# Build messages with history
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messages = [
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{
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"role": "system",
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"content": """You are AmkyawDev AI Assistant, a helpful and friendly AI assistant.
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You can help with coding, answering questions, and various tasks.
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Always be helpful, polite, and provide accurate information."""
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}
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]
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# Add conversation history
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messages.extend(conversations[conv_id][-10:]) # Keep last 10 messages
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# Add current message
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messages.append({"role": "user", "content": request.message})
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# Generate response
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response_text = await generate_response(
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messages=messages,
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model="llama-3.1-8b-instant",
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temperature=0.7,
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max_tokens=2048
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)
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# Save to conversation history
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conversations[conv_id].append({"role": "user", "content": request.message})
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conversations[conv_id].append({"role": "assistant", "content": response_text})
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# Keep history limited
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if len(conversations[conv_id]) > 20:
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conversations[conv_id] = conversations[conv_id][-20:]
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return ChatResponse(
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response=response_text,
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conversation_id=conv_id,
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model="llama-3.1-8b-instant"
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)
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except Exception as e:
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logger.error(f"Chat error: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@router.get("/conversations")
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async def get_conversations() -> Dict[str, Any]:
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"""Get all conversation IDs"""
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return {
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"conversations": list(conversations.keys()),
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"count": len(conversations)
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}
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@router.delete("/conversations/{conversation_id}")
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async def delete_conversation(conversation_id: str) -> Dict[str, str]:
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"""Delete a conversation"""
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if conversation_id in conversations:
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del conversations[conversation_id]
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return {"status": "deleted", "conversation_id": conversation_id}
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raise HTTPException(status_code=404, detail="Conversation not found")
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@router.get("/conversations/{conversation_id}")
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async def get_conversation(conversation_id: str) -> Dict[str, Any]:
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"""Get conversation history"""
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if conversation_id in conversations:
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return {
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"conversation_id": conversation_id,
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"messages": conversations[conversation_id]
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}
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raise HTTPException(status_code=404, detail="Conversation not found")
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