app.py

import gradio as gr
import os
from dotenv import load_dotenv
from ai_core import analyze_image_with_query
from audio_utils import transcribe_with_groq, text_to_speech_with_gtts
from image_utils import encode_image

load_dotenv()

# --- Configuration ---
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
STT_MODEL = "whisper-large-v3"
VISION_MODEL = "meta-llama/llama-4-scout-17b-16e-instruct"
SYSTEM_PROMPT = """You are SymptoScan MD, an AI medical assistant. Your role is to act as a professional, empathetic, and knowledgeable doctor.

When analyzing the user's symptoms and any provided medical images, please follow these guidelines:

1.  **Analyze Symptoms:** Carefully consider the user's described symptoms from the transcript.
2.  **Analyze Image:** If an image is provided, analyze it in detail for any visible signs related to the symptoms.
3.  **Provide a Possible Diagnosis:** Based on the text and image, provide a potential diagnosis or a few possible explanations for the symptoms.
4.  **Suggest Next Steps:** Recommend clear and safe next steps for the user. This could include seeing a specialist, trying over-the-counter remedies, or making lifestyle changes.
5.  **Maintain a Professional Tone:** Your response should be clear, concise, and easy for a non-medical person to understand.
6.  **Include a Disclaimer:** ALWAYS end your response with the following disclaimer: 'Disclaimer: I am an AI assistant and not a real doctor. This is not a real medical diagnosis. Please consult a qualified healthcare professional for any medical concerns.'

Your primary goal is to be helpful and safe. Do not provide any information that could be dangerous or misleading.
"""

# --- Main Processing Function ---
def process_inputs(audio_filepath, image_filepath):
    transcript = "No audio was provided."
    if audio_filepath:
        try:
            transcript = transcribe_with_groq(
                stt_model=STT_MODEL,
                audio_filepath=audio_filepath,
                groq_api_key=GROQ_API_KEY
            )
        except Exception as e:
            return f"Error in transcription: {e}", "", None

    if image_filepath:
        try:
            encoded_image = encode_image(image_filepath)
            query = f"{SYSTEM_PROMPT}\n\nUser symptoms: {transcript}"
            doctor_response = analyze_image_with_query(
                query=query,
                model=VISION_MODEL,
                encoded_image=encoded_image,
                groq_api_key=GROQ_API_KEY
            )
        except Exception as e:
            return transcript, f"Error in AI analysis: {e}", None
    else:
        doctor_response = "No image provided. Please upload an image for analysis."

    try:
        voice_path = text_to_speech_with_gtts(
            input_text=doctor_response,
            output_filepath="symptoscan_md_response.mp3"
        )
    except Exception as e:
        return transcript, doctor_response, f"Error in generating audio: {e}"

    return transcript, doctor_response, voice_path

# --- Gradio UI ---
professional_theme = gr.themes.Soft(
    primary_hue="teal",
    secondary_hue="blue",
    neutral_hue="slate",
).set(
    body_background_fill="#F0F4F8",
)

with gr.Blocks(title="SymptoScan MD", theme=professional_theme, css=".gradio-container { max-width: 900px !important; margin: auto !important; }") as demo:
    gr.Markdown(
        """
        # 🩺 SymptoScan MD
        ### Your AI-Powered Visual Health Assistant
        Upload a medical image (e.g., a skin condition) and describe your symptoms. Our AI will provide a preliminary analysis and suggest next steps.
        """
    )

    with gr.Row(equal_height=True):
        with gr.Column(scale=1):
            audio_input = gr.Audio(sources=["microphone"], type="filepath", label="🎤 Record Your Symptoms")
            image_input = gr.Image(type="filepath", label="🖼️ Upload Medical Image")
            submit_btn = gr.Button("Analyze Symptoms", variant="primary")

        with gr.Column(scale=2):
            transcript_output = gr.Textbox(label="📝 Your Symptoms (Transcribed)", lines=4, interactive=False)
            response_output = gr.Textbox(label="👩‍⚕️ AI Doctor's Analysis", lines=8, interactive=False)
            audio_output = gr.Audio(label="🔊 AI Voice Response", interactive=False)

    # --- Logic ---
    submit_btn.click(
        fn=process_inputs,
        inputs=[audio_input, image_input],
        outputs=[transcript_output, response_output, audio_output],
        api_name="analyze"
    )

if __name__ == "__main__":
    demo.launch(debug=True)