Create app.py

app.py

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+# Required Libraries
+import whisper
+from groq import Groq
+from gtts import gTTS
+import gradio as gr
+import os
+import tempfile
+from pydub import AudioSegment
+
+# ---------------------------
+# 🔑 API Key Configuration
+# ---------------------------
+GROQ_API_KEY= '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'
+
+client=Groq(api_key=GROQ_API_KEY)
+
+# Initialize Whisper model
+whisper_model = whisper.load_model("base")
+
+# ---------------------------
+# 🎙️ Audio Processing
+# ---------------------------
+
+def validate_audio_file(audio_file):
+    """Validate if the audio file exists and is not empty."""
+    if not audio_file or not os.path.exists(audio_file) or os.path.getsize(audio_file) == 0:
+        print(f"[ERROR] Invalid or empty audio file: {audio_file}")
+        return False
+    return True
+
+
+def convert_to_wav(audio_file):
+    """Convert audio file to WAV format if needed."""
+    try:
+        audio = AudioSegment.from_file(audio_file)
+        wav_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name
+        audio.export(wav_path, format="wav")
+        print(f"[INFO] Audio converted to WAV: {wav_path}")
+        return wav_path
+    except Exception as e:
+        print(f"[ERROR] Audio Conversion Error: {e}")
+        return None
+
+
+def transcribe_audio(audio_file):
+    """Transcribe audio using Whisper."""
+    try:
+        print(f"[INFO] Transcribing audio file: {audio_file}")
+        if not validate_audio_file(audio_file):
+            raise FileNotFoundError("Audio file not found or invalid path.")
+        
+        audio_file = convert_to_wav(audio_file)
+        if not audio_file:
+            raise Exception("Failed to convert audio to WAV format.")
+        
+        result = whisper_model.transcribe(audio_file)
+        print(f"[INFO] Transcription result: {result['text']}")
+        return result['text']
+    except Exception as e:
+        print(f"[ERROR] Transcription Error: {e}")
+        return f"Transcription Error: {e}"
+
+
+# ---------------------------
+# 🤖 LLM Interaction
+# ---------------------------
+
+def get_groq_response(user_input):
+    """Get chatbot response from Groq's API."""
+    try:
+        print(f"[INFO] Sending input to Groq: {user_input}")
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {"role": "user", "content": user_input}
+            ],
+            model="llama-3.3-70b-versatile",
+            stream=False,
+        )
+        response = chat_completion.choices[0].message.content
+        print(f"[INFO] Groq response: {response}")
+        return response
+    except Exception as e:
+        print(f"[ERROR] Groq API Error: {e}")
+        return f"Groq API Error: {e}"
+
+
+# ---------------------------
+# 🗣️ Text-to-Speech
+# ---------------------------
+
+def text_to_speech(text):
+    """Convert text to speech using gTTS."""
+    try:
+        print(f"[INFO] Converting text to speech: {text}")
+        tts = gTTS(text)
+        audio_path = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False).name
+        tts.save(audio_path)
+        print(f"[INFO] Audio file saved: {audio_path}")
+        return audio_path
+    except Exception as e:
+        print(f"[ERROR] TTS Error: {e}")
+        return f"TTS Error: {e}"
+
+
+# ---------------------------
+# 🛠️ Main Interaction Logic
+# ---------------------------
+
+def chatbot(audio_input):
+    """Handle full chatbot interaction."""
+    try:
+        print(f"[INFO] Audio Input Path: {audio_input}")
+        
+        # Validate Audio File
+        if not validate_audio_file(audio_input):
+            return "Error: Audio file not found or invalid path", None
+
+        # Step 1: Transcribe Audio
+        text_input = transcribe_audio(audio_input)
+        if "Error" in text_input:
+            return text_input, None
+
+        # Step 2: Get Response from Groq
+        llm_response = get_groq_response(text_input)
+        if "Error" in llm_response:
+            return llm_response, None
+
+        # Step 3: Convert Response to Audio
+        audio_output = text_to_speech(llm_response)
+        if "Error" in audio_output:
+            return audio_output, None
+
+        return llm_response, audio_output
+    except Exception as e:
+        print(f"[ERROR] General Error: {e}")
+        return f"General Error: {e}", None
+
+
+# ---------------------------
+# 🌐 Gradio Interface
+# ---------------------------
+
+interface = gr.Interface(
+    fn=chatbot,
+    inputs=gr.Audio(type="filepath"),
+    outputs=[
+        gr.Textbox(label="LLM Response"),
+        gr.Audio(label="Audio Response")
+    ],
+    title="Real-Time Voice-to-Voice Chatbot",
+    description="Speak into the microphone, and the chatbot will respond with audio.",
+    live=True  # Ensures real-time interaction
+)
+
+# Launch Gradio App
+if __name__ == "__main__":
+    interface.launch(share=True)