112 lines
3.5 KiB
Python
112 lines
3.5 KiB
Python
import os
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from typing import Optional
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from fastapi import FastAPI, HTTPException, Security, Depends
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from fastapi.security import APIKeyHeader
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import JSONResponse
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from dotenv import load_dotenv
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import json
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from pydantic import BaseModel
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from langchain_openai import ChatOpenAI
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import requests
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import tempfile
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from typing import Dict, Any
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from fastapi.responses import Response
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from datetime import datetime
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from fastapi import HTTPException
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from pydantic import BaseModel
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from typing import Optional, Union, Dict, Any
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import os
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import requests
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import os
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from PyPDF2 import PdfReader
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from scripts.transcriber import transcribe_media,group_words_into_sentences # Import the transcribe_media function
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# Load environment variables
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load_dotenv()
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API_KEY = os.getenv("API_KEY_ACCESS")
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# Initialize FastAPI app
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app = FastAPI(
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title="Microdot AI API",
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description="API For fire fighter",
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version="1.0.0"
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)
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# Add CORS middleware
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# Setup API key authentication
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api_key_header = APIKeyHeader(name="Authorization", auto_error=False)
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async def get_api_key(api_key_header: str = Security(api_key_header)) -> str:
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"""Validate API key from header"""
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if not api_key_header or not api_key_header.startswith('Bearer '):
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raise HTTPException(
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status_code=401,
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detail={"error": "Unauthorized", "message": "API key is missing or invalid."}
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)
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token = api_key_header.split(' ')[1]
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if token != API_KEY:
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raise HTTPException(
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status_code=401,
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detail={"error": "Unauthorized", "message": "API key does not match."}
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)
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return token
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class TranscribeRequest(BaseModel):
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media_url: Optional[str] = None
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media_type: Optional[str] # Corrected type hint for media_type
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class ChatResp(BaseModel): # Added BaseModel inheritance
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error: Optional[str] = None
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class TranscriptResponse(BaseModel):
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transcript: dict # Changed type hint for transcript to a dictionary
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@app.post("/microdot-ai/transcribe")
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async def chat_endpoint(
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request: TranscribeRequest,
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api_key: str = Depends(get_api_key)
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):
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try:
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# Use the transcribe_media function to transcribe the media
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if request.media_url:
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transcription_response = transcribe_media(request.media_url, media_type=request.media_type)
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if transcription_response is None:
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raise HTTPException(status_code=500, detail="Transcription failed.")
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print(f"Transcription response: {transcription_response}") # Debugging print
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# Parse response
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words = transcription_response["results"]["channels"][0]["alternatives"][0]["words"]
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transcript = group_words_into_sentences(words=words)
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return TranscriptResponse(
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transcript=transcript, # Corrected to return the transcript
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error=None
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)
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except Exception as e:
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print(f"Error processing chat request: {str(e)}") # Print statement added
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raise HTTPException(
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status_code=500,
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detail=f"Error processing chat request: {str(e)}"
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)
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@app.on_event("startup")
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async def startup_event():
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"""Initialize required components on startup"""
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pass
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run("app:app", host="0.0.0.0", port=3000, reload=True) |