import gradio as gr
import pandas as pd
import logging
import sys
import os

# Set up logging to capture errors
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logger = logging.getLogger(__name__)

# Verify that required files exist
try:
    if not os.path.exists("dataset.csv"):
        logger.error("dataset.csv not found!")
        raise FileNotFoundError("dataset.csv not found!")
    if not os.path.exists("style.css"):
        logger.error("style.css not found!")
        raise FileNotFoundError("style.css not found!")
except Exception as e:
    logger.error(f"Error checking files: {str(e)}")
    raise

# Load the dataset
try:
    logger.info("Loading dataset.csv...")
    df = pd.read_csv("dataset.csv")
    logger.info("Dataset loaded successfully.")
except Exception as e:
    logger.error(f"Error loading dataset: {str(e)}")
    raise

# Function to suggest treatment and medicines based on symptoms
def suggest_treatment(symptoms_input):
    try:
        logger.info(f"Processing symptoms: {symptoms_input}")
        symptoms_input = symptoms_input.lower().strip()
        if not symptoms_input:
            return "Please enter symptoms."
        # Search for matching symptoms in the dataset
        for index, row in df.iterrows():
            dataset_symptoms = row['symptoms'].lower().strip()
            input_symptom_list = [s.strip() for s in symptoms_input.split(",")]
            dataset_symptom_list = [s.strip() for s in dataset_symptoms.split(",")]
            if all(symptom in dataset_symptom_list for symptom in input_symptom_list):
                result = (
                    f"**Possible Disease**: {row['disease']}\n"
                    f"**Suggested Treatment**: {row['treatment']}\n"
                    f"**Medicines**: {row['medicines']}"
                )
                logger.info(f"Suggestion generated: {result}")
                return result
        return "Sorry, no matching disease found for the given symptoms. Please consult a doctor."
    except Exception as e:
        logger.error(f"Error in suggest_treatment: {str(e)}")
        return f"Error processing symptoms: {str(e)}"

# Create Gradio interface using Blocks
with gr.Blocks(css="style.css") as app:
    gr.Markdown("# Medical Suggestion AI")
    gr.Markdown("Enter your symptoms to get treatment and medicine suggestions.")
    
    symptoms_input = gr.Textbox(
        label="Symptoms (e.g., fever, headache)",
        placeholder="Enter symptoms separated by commas",
        elem_classes="symptoms-input"
    )
    submit_btn = gr.Button("Submit", elem_classes="submit-btn")
    output = gr.Markdown(label="Suggestions", elem_classes="output")
    
    submit_btn.click(
        fn=suggest_treatment,
        inputs=symptoms_input,
        outputs=output
    )

# Launch the app
try:
    logger.info("Launching Gradio app...")
    app.launch(server_name="0.0.0.0", server_port=7860, share=False)
    logger.info("Gradio app launched successfully.")
except Exception as e:
    logger.error(f"Error launching Gradio app: {str(e)}")
    raise