api.py

from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from typing import Dict, List, Optional, Union, Any
from pydantic import BaseModel, Field
from datetime import datetime
import logging
import json
import os
from dotenv import load_dotenv
from dify_client_python.dify_client import models
from sse_starlette.sse import EventSourceResponse
import httpx
from json_parser import SSEParser
from logger_config import setup_logger
from fastapi.responses import StreamingResponse
from fastapi.responses import JSONResponse
from response_formatter import ResponseFormatter
import traceback

# Load environment variables
load_dotenv()

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

class AgentOutput(BaseModel):
    """Structured output from agent processing"""
    thought_content: str
    observation: Optional[str]
    tool_outputs: List[Dict]
    citations: List[Dict]
    metadata: Dict
    raw_response: str

class AgentRequest(BaseModel):
    """Enhanced request model with additional parameters"""
    query: str
    conversation_id: Optional[str] = None
    stream: bool = True
    inputs: Dict = {}
    files: List = []
    user: str = "default_user"
    response_mode: str = "streaming"

class AgentProcessor:
    def __init__(self, api_key: str):
        self.api_key = api_key
        # Update API base to use environment variable with fallback
        self.api_base = os.getenv(
            "API_BASE_URL", 
            "https://ai-engine.yamamotoqa.com/v1"
        )
        self.formatter = ResponseFormatter()
        self.client = httpx.AsyncClient(timeout=60.0)
        self.logger = setup_logger("agent_processor")


    async def log_request_details(
        self, 
        request: AgentRequest,
        start_time: datetime
    ) -> None:
        """Log detailed request information"""
        self.logger.debug(
            "Request details: \n"
            f"Query: {request.query}\n"
            f"User: {request.user}\n"
            f"Conversation ID: {request.conversation_id}\n"
            f"Stream mode: {request.stream}\n"
            f"Start time: {start_time}\n"
            f"Inputs: {request.inputs}\n"
            f"Files: {len(request.files)} files attached"
        )

    async def log_error(
        self, 
        error: Exception,
        context: Optional[Dict] = None
    ) -> None:
        """Log detailed error information"""
        error_msg = (
            f"Error type: {type(error).__name__}\n"
            f"Error message: {str(error)}\n"
            f"Stack trace:\n{traceback.format_exc()}\n"
        )
        if context:
            error_msg += f"Context:\n{json.dumps(context, indent=2)}"
        
        self.logger.error(error_msg)

    async def cleanup(self):
        """Cleanup method to properly close client"""
        await self.client.aclose()

    async def process_stream(self, request: AgentRequest):
        start_time = datetime.now()
        await self.log_request_details(request, start_time)
        
        headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json",
            "Accept": "text/event-stream"
        }
        
        chat_request = {
            "query": request.query,
            "inputs": request.inputs,
            "response_mode": "streaming" if request.stream else "blocking",
            "user": request.user,
            "conversation_id": request.conversation_id,
            "files": request.files
        }

        async def event_generator():
            parser = SSEParser()
            citations = []
            metadata = {}
            tool_outputs = []
            
            try:
                async with self.client.stream(
                    "POST",
                    f"{self.api_base}/chat-messages",
                    headers=headers,
                    json=chat_request
                ) as response:
                    self.logger.debug(
                        f"Stream connection established\n"
                        f"Status: {response.status_code}\n"
                        f"Headers: {dict(response.headers)}"
                    )
                    
                    buffer = ""
                    async for line in response.aiter_lines():
                        if not line.strip():
                            continue
                        
                        self.logger.debug(f"Raw SSE line: {line}")
                        
                        if "data:" in line:
                            try:
                                data = line.split("data:", 1)[1].strip()
                                parsed = json.loads(data)
                                
                                # Enhanced mermaid diagram handling
                                if parsed.get("observation"):
                                    try:
                                        observation = parsed["observation"]
                                        if isinstance(observation, str):
                                            if "mermaid_diagram" in observation:
                                                try:
                                                    # Clean and extract diagram content
                                                    cleaned_content = parser.clean_mermaid_content(
                                                        observation
                                                    )
                                                    
                                                    # Create tool output without extra wrapping
                                                    tool_output = {
                                                        "type": "mermaid_diagram",
                                                        "content": cleaned_content
                                                    }
                                                    tool_outputs.append(tool_output)
                                                    
                                                    # Send clean event
                                                    yield (
                                                        "event: tool_output\n"
                                                        f"data: {json.dumps(tool_output)}\n\n"
                                                    )
                                                except Exception as e:
                                                    self.logger.error(
                                                        f"Failed to process mermaid diagram: {e}"
                                                    )
                                    except Exception as e:
                                        self.logger.error(
                                            f"Error processing observation: {e}"
                                        )
                                
                                if parsed.get("event") == "message_end":
                                    citations = parsed.get("retriever_resources", [])
                                    metadata = parsed.get("metadata", {})
                                    metadata["tool_outputs"] = tool_outputs
                                    self.logger.debug(
                                        f"Message end event:\n"
                                        f"Citations: {citations}\n"
                                        f"Metadata: {metadata}\n"
                                        f"Tool outputs: {tool_outputs}"
                                    )
                                
                                formatted = self.format_terminal_output(
                                    parsed,
                                    citations=citations,
                                    metadata=metadata,
                                    tool_outputs=tool_outputs
                                )
                                if formatted:
                                    self.logger.info(formatted)
                                    yield f"data: {formatted}\n\n"
                                
                            except Exception as e:
                                await self.log_error(
                                    e, 
                                    {"line": line, "event": "parse_data"}
                                )
                    
                    buffer += line + "\n"
                    
                    if line.startswith("data:") or buffer.strip().endswith("}"):
                        try:
                            processed_response = parser.parse_sse_event(buffer)
                            if processed_response and isinstance(processed_response, dict):
                                cleaned_response = self.clean_response(processed_response)
                                if cleaned_response:
                                    xml_content = cleaned_response.get("content", "")
                                    yield f"data: {xml_content}\n\n"
                        except Exception as parse_error:
                            await self.log_error(
                                parse_error,
                                {"buffer": buffer, "event": "process_buffer"}
                            )
                            error_xml = (
                                f"<agent_response>"
                                f"<error>{str(parse_error)}</error>"
                                f"</agent_response>"
                            )
                            yield f"data: {error_xml}\n\n"
                        finally:
                            buffer = ""
                            
            except Exception as e:
                self.logger.error(f"Stream processing error: {str(e)}")
                yield f"data: {{'error': '{str(e)}'}}\n\n"

        return StreamingResponse(
            event_generator(),
            media_type="text/event-stream",
            headers={
                "Cache-Control": "no-cache",
                "Connection": "keep-alive",
                "X-Accel-Buffering": "no",
                "Access-Control-Allow-Origin": "*"
            }
        )

    def format_terminal_output(
        self, 
        response: Dict, 
        citations: List[Dict] = None,
        metadata: Dict = None,
        tool_outputs: List[Dict] = None
    ) -> Optional[str]:
        """Format response for terminal output"""
        event_type = response.get("event")
        
        if event_type == "agent_thought":
            thought = response.get("thought", "")
            observation = response.get("observation", "")
            terminal_output, _ = self.formatter.format_thought(
                thought, 
                observation,
                citations=citations,
                metadata=metadata,
                tool_outputs=tool_outputs
            )
            return terminal_output
            
        elif event_type == "agent_message":
            message = response.get("answer", "")
            terminal_output, _ = self.formatter.format_message(message)
            return terminal_output
            
        elif event_type == "error":
            error = response.get("error", "Unknown error")
            terminal_output, _ = self.formatter.format_error(error)
            return terminal_output
            
        return None

    def clean_response(self, response: Dict) -> Optional[Dict]:
        """Clean and transform the response for frontend consumption"""
        try:
            event_type = response.get("event")
            if not event_type:
                return None

            # Handle different event types
            if event_type == "agent_thought":
                thought = response.get("thought", "")
                observation = response.get("observation", "")
                tool = response.get("tool", "")
                
                # Handle mermaid diagram observations
                if tool == "mermaid_diagram" and observation:
                    try:
                        # First check if observation is error message
                        if isinstance(observation, str):
                            obs_data = json.loads(observation)
                            if "mermaid_diagram" in obs_data:
                                if obs_data["mermaid_diagram"].startswith("tool invoke error"):
                                    self.logger.warning(
                                        f"Mermaid diagram tool error: {obs_data['mermaid_diagram']}"
                                    )
                                    return None
                        
                        # Handle successful mermaid diagram
                        if isinstance(observation, dict):
                            mermaid_data = observation.get("mermaid_diagram", "")
                        else:
                            obs_data = json.loads(observation)
                            mermaid_data = obs_data.get("mermaid_diagram", "")

                        if mermaid_data:
                            # Handle nested JSON structure
                            if isinstance(mermaid_data, str):
                                mermaid_data = json.loads(mermaid_data)
                            
                            # Extract diagram from either format
                            if isinstance(mermaid_data, dict):
                                diagram = mermaid_data.get("mermaid_diagram", "")
                            else:
                                diagram = mermaid_data

                            # Clean up the diagram code
                            if isinstance(diagram, str):
                                if "tool response:" in diagram:
                                    diagram = diagram.split("tool response:")[0]
                                if diagram.startswith('{"mermaid_diagram": "'):
                                    diagram = json.loads(diagram)["mermaid_diagram"]
                                if diagram.startswith("```mermaid\n"):
                                    diagram = diagram[10:]
                                if diagram.endswith("\n```"):
                                    diagram = diagram[:-4]
                                
                                return {
                                    "type": "mermaid_diagram",
                                    "content": diagram.strip()
                                }
                    except (json.JSONDecodeError, KeyError) as e:
                        self.logger.error(f"Failed to parse mermaid diagram data: {str(e)}")
                        self.logger.debug(f"Raw observation: {observation}")
                        return None
                
                # Handle regular thought
                _, xml_output = self.formatter.format_thought(thought, observation)
                return {
                    "type": "thought",
                    "content": xml_output
                }
            
            elif event_type == "agent_message":
                message = response.get("answer", "")
                _, xml_output = self.formatter.format_message(message)
                return {
                    "type": "message",
                    "content": xml_output
                }
            
            elif event_type == "error":
                error = response.get("error", "Unknown error")
                _, xml_output = self.formatter.format_error(error)
                return {
                    "type": "error",
                    "content": xml_output
                }
            
            return None
        except Exception as e:
            logger.error(f"Error cleaning response: {str(e)}")
            return None

# Initialize FastAPI app
app = FastAPI()
agent_processor = None

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.on_event("startup")
async def startup_event():
    global agent_processor
    api_key = os.getenv("DIFY_API_KEY")
    agent_processor = AgentProcessor(api_key=api_key)

@app.on_event("shutdown")
async def shutdown_event():
    global agent_processor
    if agent_processor:
        await agent_processor.cleanup()

@app.post("/v1/agent")
async def process_agent_request(request: AgentRequest):
    try:
        logger.info(f"Processing agent request: {request.query}")
        return await agent_processor.process_stream(request)
        
    except Exception as e:
        logger.error(f"Error in agent request processing: {e}", exc_info=True)
        raise HTTPException(status_code=500, detail=str(e))

@app.middleware("http")
async def error_handling_middleware(request: Request, call_next):
    try:
        response = await call_next(request)
        return response
    except Exception as e:
        logger.error(f"Unhandled error: {str(e)}", exc_info=True)
        return JSONResponse(
            status_code=500,
            content={"error": "Internal server error occurred"}
        )

# Add host and port parameters to the launch
if __name__ == "__main__":
    import uvicorn
    port = int(os.getenv("PORT", 7860))
    uvicorn.run(
        "api:app",
        host="0.0.0.0",
        port=port,
        reload=True
    )