import anthropic, json
from fastapi import APIRouter, HTTPException
from fastapi.responses import StreamingResponse
from dotenv import load_dotenv
from os import getenv

router = APIRouter()

load_dotenv(".env_file")
client = anthropic.Anthropic(api_key=getenv('CLAUDE_KEY'))

with open('/home/rodo/Documents/py/LittleAPI/list.json', 'r') as f:
    config = json.load(f)
    pdf_file_ids = config.get("files", [])

@router.post("/using_docs", tags=["AI"])
async def send_message_using_docs(message:str):
    """
    Envía un mensaje usando documentos PDF almacenados.
    
    - **message**: El mensaje de texto a procesar
    - **Retorna**: Stream de texto con la respuesta de Claude
    """
    try:
        content = [
            {
                "type": "text",
                "text": message
            }
        ]

        for file_id in pdf_file_ids:
            content.append(
                {
                    "type": "document",
                    "source" : {
                        "type" : "file",
                        "file_id": file_id
                    }
                }
            )

        def event_generator():
            with client.beta.messages.stream(
                model="claude-haiku-4-5",
                max_tokens=2048,
                messages=[{
                    "role": "user",
                    "content": content
                }],
                betas=["files-api-2025-04-14"],
            ) as stream:
                for text in stream.text_stream:
                    yield text
        return StreamingResponse(event_generator(), media_type="text/plain")
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@router.post("/", tags=["AI"])
async def send_message(message:str):
    """
    Envía un mensaje normal a Claude.
    
    - **message**: El mensaje de texto a procesar
    - **Retorna**: Stream de texto con la respuesta de Claude
    """
    try:
        content = [
            {
                "type": "text",
                "text": message
            }
        ]

        def event_generator():
            with client.beta.messages.stream(
                model="claude-haiku-4-5",
                max_tokens=512,
                messages=[{
                    "role": "user",
                    "content": content
                }],
            ) as stream:
                for text in stream.text_stream:
                    yield text

        return StreamingResponse(event_generator(), media_type="text/plain")
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))