app.py

import gradio as gr
import pandas as pd
import json
from together import Together

# Load CSV data
prescription_meds_df = pd.read_csv('data/prescription_meds.csv')
psychedelics_df = pd.read_csv('data/psychedelics.csv')
interactions_df = pd.read_csv('data/interactions.csv')

# Initialize Together client
with open('configs.json', 'r') as f:    
    config = json.load(f)

TOGETHER_API_KEY = config["together"]
client = Together(api_key=TOGETHER_API_KEY)

def get_ai_safety_info(prescription, psychedelic, interaction_text):
    prompt = f"""
As a harm reduction expert, please analyze this drug interaction and provide additional safety information:

{interaction_text}

Please include:
1. Additional information on drug interactions
2. Emergency warning signs to watch for

Keep the response factual and focused on harm reduction.
"""
    
    response = client.chat.completions.create(
        model="meta-llama/Meta-Llama-3-8B-Instruct-Lite",
        messages=[{"role": "user", "content": prompt}],
    )
    return response.choices[0].message.content

def analyze_interaction(prescriptions, psychedelic):
    if not prescriptions or not psychedelic:
        return "Please select both prescription medication(s) and a psychedelic.", ""
    
    result_text = ""
    
    # Analyze each prescription
    for prescription in prescriptions:
        # Get drug information from DataFrames
        med_info = prescription_meds_df[prescription_meds_df['name'] == prescription].iloc[0]
        psych_info = psychedelics_df[psychedelics_df['name'] == psychedelic].iloc[0]
        interaction = interactions_df[
            (interactions_df['medication'] == prescription) & 
            (interactions_df['psychedelic'] == psychedelic)
        ].iloc[0]
        
        # Format the results
        result_text += f"""
PRESCRIPTION MEDICATION: {prescription}
Type: {med_info['type']}
Description: {med_info['description']}
Half-life: {med_info['half_life']}

INTERACTION ANALYSIS:
Risk Level: {interaction['risk_level']}
Description: {interaction['description']}

RECOMMENDATION:
{interaction['recommendation']}
-------------------
"""
    
    # Add psychedelic information once
    psych_info = psychedelics_df[psychedelics_df['name'] == psychedelic].iloc[0]
    result_text += f"""
PSYCHEDELIC: {psychedelic}
Description: {psych_info['description']}
Duration: {psych_info['duration']}
Mechanisms: {psych_info['mechanisms']}
"""
    
    return result_text

def get_safety_analysis(interaction_text):
    if not interaction_text or interaction_text.startswith("Please select both"):
        return "Please analyze drug interactions first before requesting AI safety information."
    
    return get_ai_safety_info(None, None, interaction_text)

def create_interface():
    # Get drug lists from DataFrames
    prescription_meds = prescription_meds_df['name'].tolist()
    psychedelics = psychedelics_df['name'].tolist()
    
    with gr.Blocks(title="TripSafely - Drug Interaction Analyzer", theme=gr.themes.Soft()) as interface:
        gr.Markdown("# TripSafely - Drug Interaction Analyzer")
        gr.Markdown("Psychedelic & Prescription Drug Interaction Analyzer with AI Safety Information")
        
        with gr.Row():
            prescriptions = gr.CheckboxGroup(
                choices=prescription_meds,
                label="Select Prescription Medication(s)",
                info="Select one or more medications"
            )
            psychedelic = gr.Radio(
                choices=psychedelics,
                label="Select Psychedelic",
            )
        
        analyze_btn = gr.Button("Analyze Interactions")
        interaction_output = gr.Textbox(
            label="Interaction Analysis",
            lines=15,
        )
        
        safety_btn = gr.Button("Get AI Safety Analysis")
        safety_output = gr.Textbox(
            label="AI Safety Analysis",
            lines=15,
        )
        
        gr.Markdown("*Disclaimer: This information is for educational purposes only and should not replace medical advice. AI-generated content should be verified with medical professionals.*")
        
        analyze_btn.click(
            fn=analyze_interaction,
            inputs=[prescriptions, psychedelic],
            outputs=interaction_output
        )
        
        safety_btn.click(
            fn=get_safety_analysis,
            inputs=[interaction_output],
            outputs=safety_output
        )
    
    return interface

if __name__ == "__main__":
    interface = create_interface()
    interface.launch()