Update main.py

main.py

@@ -144,102 +144,7 @@ async def root():
     return {
         "message": "Welcome to the Audio Similarity API!"
 
-
-# Load GROQ API key from environment variable
-API_KEY = os.getenv("GROQ_API_KEY")
-if not API_KEY:
-    raise RuntimeError("GROQ_API_KEY environment variable not set")
-client = Groq(api_key=API_KEY)
-
-
-def transcribe_audio(file_tuple: tuple) -> str:
-    """
-    Transcribes speech from an audio file using the GROQ Whisper model.
-    Args:
-        file_tuple (tuple): (filename, file_bytes)
-    Returns:
-        str: The transcription text or error message.
-    """
-    try:
-        transcription = client.audio.transcriptions.create(
-            file=file_tuple,
-            model="whisper-large-v3",
-            response_format="text"
-        )
-        return transcription
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Transcription error: {e}")
-
-
-def levenshtein_similarity(text1: str, text2: str) -> float:
-    """
-    Calculate normalized Levenshtein similarity between two texts.
-    Returns a score between 0 and 1.
-    """
-    distance = Levenshtein.distance(text1, text2)
-    max_len = max(len(text1), len(text2))
-    return 1 - distance / max_len if max_len > 0 else 1.0
-
-
-def find_differences(text_original: str, text_user: str) -> str:
-    """
-    Identify differences between original and user transcriptions using GROQ chat.
-    """
-    messages = [
-        {"role": "system", "content": 
-            "You are a helpful assistant that finds mistakes between two texts. "
-            "Provide only the mistakes, no extra explanation."},
-        {"role": "user", "content": (
-            f"Original transcription: '{text_original}'\n"
-            f"User transcription: '{text_user}'\n"
-            "Explain the differences between these texts."
-        )}
-    ]
-    try:
-        completion = client.chat.completions.create(
-            model="mistral-saba-24b",
-            messages=messages,
-            temperature=1,
-            max_tokens=1024,
-            top_p=1,
-            stream=False
-        )
-        return completion.choices[0].message.content
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error generating explanation: {e}")
-
-
-@app.post("/compare")
-async def compare_audio(
-    original_audio: UploadFile = File(...),
-    user_audio: UploadFile = File(...)
-):
-    """
-    Endpoint to upload two audio files, transcribe, compare, and return similarity and differences.
-    """
-    # Read uploaded files
-    original_bytes = await original_audio.read()
-    user_bytes = await user_audio.read()
-
-    # Transcribe
-    transcription_original = transcribe_audio((original_audio.filename, original_bytes))
-    transcription_user = transcribe_audio((user_audio.filename, user_bytes))
-
-    # Compute similarity
-    similarity_score = levenshtein_similarity(transcription_original, transcription_user)
-
-    # Find differences
-    explanation = find_differences(transcription_original, transcription_user)
-
-    # Build response
-    result = {
-        "original_transcription": transcription_original,
-        "user_transcription": transcription_user,
-        "levenshtein_similarity": round(similarity_score, 2),
-        "explanation_of_differences": explanation
-    }
-    return JSONResponse(content=result)
-
+        
 @app.post("/compare-dtw")
 async def compare_dtw(
     audio1: UploadFile = File(...),