Removed final.wav to comply with Hugging Face restrictions

app.py

@@ -1,7 +1,94 @@
+# Import necessary libraries
+import os
 import gradio as gr
+from pydub import AudioSegment
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Importing AI processing functions
+from brain_of_the_doctor import encode_image, analyze_image_with_query
+from voice_of_the_patient import transcribe_with_groq
+from voice_of_the_doctor import text_to_speech_with_elevenlabs
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# System prompt for the AI doctor
+system_prompt = """You have to act as a professional doctor, I know you are not but this is for learning purposes. 
+With what I see, I think you have .... Do you find anything wrong with it medically? 
+If you make a differential, suggest some remedies for them. Do not add any numbers or special characters in 
+your response. Your response should be in one long paragraph. Always answer as if you are answering a real person.
+Do not respond as an AI model in markdown. Keep your answer concise (max 2 sentences). No preamble, start your answer right away please."""
+
+
+# Function to process inputs
+def process_inputs(audio_filepath, image_filepath):
+    """Handles audio transcription, image analysis, and text-to-speech generation."""
+
+    print(f"DEBUG: Received audio file path: {audio_filepath}")
+
+    # Ensure audio file exists before processing
+    if not audio_filepath or not os.path.exists(audio_filepath):
+        return "Error: No valid audio file provided.", "No response generated.", None
+
+    try:
+        # Convert speech to text using Groq API
+        speech_to_text_output = transcribe_with_groq(
+            GROQ_API_KEY=os.getenv("GROQ_API_KEY"),
+            audio_filepath=audio_filepath,
+            stt_model="whisper-large-v3",
+        )
+    except Exception as e:
+        return f"Error transcribing audio: {e}", "No response generated.", None
+
+    # Handle image analysis
+    if image_filepath and os.path.exists(image_filepath):
+        try:
+            encoded_img = encode_image(image_filepath)
+            doctor_response = analyze_image_with_query(
+                query=system_prompt + speech_to_text_output,
+                encoded_image=encoded_img,
+                model="llama-3.2-11b-vision-preview",
+            )
+        except Exception as e:
+            doctor_response = f"Error analyzing image: {e}"
+    else:
+        doctor_response = "No image provided for analysis."
+
+    # Convert doctor's response to speech using ElevenLabs
+    output_wav = "final.wav"
+    try:
+        text_to_speech_with_elevenlabs(
+            input_text=doctor_response,
+            output_filepath="final.mp3",  # Generate MP3 first
+        )
+
+        # Convert MP3 to WAV
+        if os.path.exists("final.mp3"):
+            audio = AudioSegment.from_mp3("final.mp3")
+            audio.export(output_wav, format="wav")
+        else:
+            return (
+                speech_to_text_output,
+                doctor_response,
+                "Error: Failed to generate audio.",
+            )
+    except Exception as e:
+        return speech_to_text_output, doctor_response, f"Error generating speech: {e}"
+
+    return speech_to_text_output, doctor_response, output_wav
+
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=process_inputs,
+    inputs=[
+        gr.Audio(sources=["microphone"], type="filepath"),
+        gr.Image(type="filepath"),
+    ],
+    outputs=[
+        gr.Textbox(label="Speech to Text"),
+        gr.Textbox(label="Doctor's Response"),
+        gr.Audio(label="Doctor's Voice Response"),
+    ],
+    title="AI Doctor with Vision and Voice",
+    description="Upload an image and speak into the microphone. The AI doctor will analyze the image, transcribe your speech, and respond in both text and voice.",
+)
+
+# Launch
+iface.launch()