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from fastapi import FastAPI, Header, HTTPException
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from pydantic import BaseModel
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import base64
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import numpy as np
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import pydub
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import tempfile
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import os
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from dotenv import load_dotenv
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load_dotenv()
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from models import detect_audio
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app = FastAPI(title="AI-Generated Voice Detection API - GUVI Hackathon")
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API_KEY = os.getenv("API_KEY")
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class AudioInput(BaseModel):
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language: str
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audioFormat: str
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audioBase64: str
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@app.post("/api/voice-detection")
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def detect_voice(
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input_data: AudioInput,
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x_api_key: str = Header(None, alias="x-api-key")
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):
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if x_api_key != API_KEY:
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raise HTTPException(status_code=401, detail="Invalid API key")
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if input_data.audioFormat.lower() != "mp3":
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raise HTTPException(status_code=400, detail="Only mp3 supported")
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try:
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audio_bytes = base64.b64decode(input_data.audioBase64)
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with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
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tmp.write(audio_bytes)
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tmp_path = tmp.name
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try:
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segment = pydub.AudioSegment.from_file(tmp_path, format="mp3")
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finally:
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os.remove(tmp_path)
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segment = segment.set_channels(1).set_frame_rate(16000)
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samples = segment.get_array_of_samples()
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y = np.array(samples, dtype=np.float32) / 32768.0
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classification, confidence, explanation = detect_audio(y)
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return {
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"status": "success",
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"languageProvided": input_data.language,
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"classification": classification,
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"confidenceScore": confidence,
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"explanation": explanation
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}
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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@app.get("/health")
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def health():
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return {"status": "healthy"}
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@app.get("/")
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def root():
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return {"message": "AI Voice Detection API - Ready"}
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