app.py

import os
import time
import gradio as gr
from groq import Groq
from dotenv import load_dotenv

load_dotenv()
api_key = os.getenv("GROQ_API_KEY")

if not api_key:
    api_key = "gsk_..." 

client = Groq(api_key=api_key)

APP_NAME = "MindEase: Your AI Therapist 🌿"
SYSTEM_INSTRUCTION = "You are a professional, empathetic, and supportive Mental Health Therapist named 'MindEase AI'."


def user_message(user_msg_dict, history):
    if not user_msg_dict or not user_msg_dict.get("text"):
        return history
    
    text = user_msg_dict["text"]
    history.append({"role": "user", "content": text})
    
    return history

def bot_response(history, model, temperature, max_tokens):
    time.sleep(1.5)
    messages = [{"role": "system", "content": SYSTEM_INSTRUCTION}]
    
    for msg in history:
        if msg.get("content"):
            messages.append({"role": msg["role"], "content": msg["content"]})

    try:
        completion = client.chat.completions.create(
            model=model,
            messages=messages,
            temperature=temperature,
            max_tokens=max_tokens,
            stream=False 
        )
        response_content = completion.choices[0].message.content
        history.append({"role": "assistant", "content": response_content})
        
    except Exception as e:
        history.append({"role": "assistant", "content": f"Error: {str(e)}"})
    
    return history

def generate_static_advice(mood):
    if not mood: return "Please enter your mood first."
    time.sleep(1) 
    try:
        c = client.chat.completions.create(
            model="llama-3.3-70b-versatile",
            messages=[{"role": "user", "content": f"Give me one short mental health tip for feeling {mood}"}],
            stream=False
        )
        return c.choices[0].message.content
    except Exception as e:
        return f"Error: {str(e)}"

with gr.Blocks() as demo:
    
    gr.Markdown(f"# {APP_NAME}")
    gr.Markdown("Supportive conversations for a better mental well-being.")

    chatbot = gr.Chatbot(label="Chatbot", height=500)

    gr.Markdown("### 💡 Suggestions")
    with gr.Row():
        btn_ex1 = gr.Button("I feel overwhelmed 😓", variant="secondary")
        btn_ex2 = gr.Button("Suggest a sleep routine 🌙", variant="secondary")
        btn_ex3 = gr.Button("I need motivation 💪", variant="secondary")

    
    msg_input = gr.MultimodalTextbox(
        interactive=True,
        file_count="none",
        placeholder="Type your message here...",
        show_label=False,
        container=False,
        scale=1,
        autofocus=True
    )

    with gr.Accordion("⚙️ Additional Inputs & Tools", open=False):
        with gr.Row():
            model_dd = gr.Dropdown(choices=["llama-3.3-70b-versatile", "llama3-8b-8192"], value="llama-3.3-70b-versatile", label="Model")
            temp_sl = gr.Slider(minimum=0, maximum=2, value=0.7, step=0.1, label="Temperature")
            tokens_sl = gr.Slider(minimum=256, maximum=4096, value=2048, label="Max Tokens")
        
        gr.Markdown("---")
        gr.Markdown("### ⚡ Quick Static Advice")
        with gr.Row():
            static_input = gr.Textbox(placeholder="Enter mood...", show_label=False, scale=4)
            static_btn = gr.Button("Get Tip", scale=1)
        static_output = gr.Markdown("Advice will appear here...")

    msg_input.submit(
        fn=user_message, 
        inputs=[msg_input, chatbot], 
        outputs=[chatbot], 
        queue=False
    ).then(
        fn=bot_response,
        inputs=[chatbot, model_dd, temp_sl, tokens_sl],
        outputs=chatbot
    )

    def suggestion_click(text, history):
        history.append({"role": "user", "content": text})
        return history

    btn_ex1.click(
        fn=suggestion_click,
        inputs=[gr.State("I feel overwhelmed"), chatbot],
        outputs=chatbot,
        queue=False
    ).then(
        fn=bot_response,
        inputs=[chatbot, model_dd, temp_sl, tokens_sl],
        outputs=chatbot
    )
    
    btn_ex2.click(
        fn=suggestion_click,
        inputs=[gr.State("Can you suggest a sleep routine?"), chatbot],
        outputs=chatbot,
        queue=False
    ).then(
        fn=bot_response,
        inputs=[chatbot, model_dd, temp_sl, tokens_sl],
        outputs=chatbot
    )

    btn_ex3.click(
        fn=suggestion_click,
        inputs=[gr.State("I need motivation"), chatbot],
        outputs=chatbot,
        queue=False
    ).then(
        fn=bot_response,
        inputs=[chatbot, model_dd, temp_sl, tokens_sl],
        outputs=chatbot
    )

    static_btn.click(fn=generate_static_advice, inputs=static_input, outputs=static_output)

if __name__ == "__main__":
    demo.launch(theme=gr.themes.Soft(), css=".suggestion-btn {font-size: 14px;}")