app.py

import gradio as gr
import datetime
import matplotlib.pyplot as plt
from openai import OpenAI
import io
from PIL import Image

# -------- GROQ API Client --------
client = OpenAI(
    api_key="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",  # <-- replace with your key
    base_url="https://api.groq.com/openai/v1",
)

# -------- Mood Log --------
mood_log = []

def log_mood(mood, description):
    now = datetime.datetime.now().strftime('%Y-%m-%d %H:%M')
    mood_log.append({
        "datetime": now,
        "mood": mood,
        "description": description
    })
    return f"✔ Logged: {now} - {mood}"

def show_entries():
    if not mood_log:
        return "No entries yet today."
    text = ""
    for entry in mood_log:
        text += f"{entry['datetime']} — {entry['mood']} — {entry['description']}\n"
    return text

def analyze_mood():
    if not mood_log:
        return "Please log at least one mood first."
    
    prompt = """
You are an emotional AI assistant. Analyze the user's mood logs:

- Rate each mood from 1–10 (1 = very negative, 10 = very positive)
- Analyze emotional tone
- Identify patterns like stress, fatigue, sadness, happiness, or anxiety
- Provide an overall summary and advice

Mood entries:
"""
    for entry in mood_log:
        prompt += f"- {entry['datetime']}: {entry['mood']} — {entry['description']}\n"

    prompt += "\nProvide a detailed analysis:"
    
    try:
        response = client.responses.create(
            model="llama-3.3-70b-versatile",
            input=prompt,
            temperature=0.7,
            top_p=0.9
        )
        return response.output_text
    except Exception as e:
        return f"API Error: {e}"

def mood_chart():
    if not mood_log:
        return Image.new("RGB", (600, 400), color="white")
    
    moods = [entry["mood"] for entry in mood_log]
    counts = {}
    for m in moods:
        counts[m] = counts.get(m, 0) + 1

    plt.figure(figsize=(6,4))
    plt.bar(counts.keys(), counts.values(), color="#4f46e5")
    plt.title("Mood Trend Today", fontsize=16)
    plt.xlabel("Mood")
    plt.ylabel("Count")

    buf = io.BytesIO()
    plt.savefig(buf, format="png", bbox_inches='tight')
    buf.seek(0)
    plt.close()
    return Image.open(buf)

# -------- Gradio Gen-AI Style UI --------
with gr.Blocks(theme=gr.themes.Base()) as app:
    gr.Markdown(
        """
        <h1 style="text-align:center; color:#4f46e5;">🌈 AI Mood Tracker</h1>
        <p style="text-align:center; font-size:18px;">Track your moods, get AI emotional insights, and visualize your day!</p>
        """
    )

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### 📥 Log Your Mood")
            mood = gr.Dropdown(
                ["😊 Happy","😔 Sad","😩 Tired","😰 Anxious","😡 Angry","😐 Neutral"],
                label="Select Mood"
            )
            description = gr.Textbox(
                label="Describe your feeling",
                placeholder="Write a few words about how you feel...",
                lines=4
            )
            log_button = gr.Button("Log Mood")
            log_output = gr.Textbox(label="Status", lines=2)

            entries_button = gr.Button("Show Entries")
            entries_output = gr.Textbox(label="Today's Logs", lines=8)

        with gr.Column(scale=1):
            gr.Markdown("### 🤖 AI Mood Analysis")
            analyze_button = gr.Button("Analyze My Mood")
            analyze_output = gr.Textbox(
                label="AI Analysis",
                placeholder="Your mood analysis will appear here...",
                lines=20,
                interactive=False
            )

            gr.Markdown("### 📊 Mood Trend Chart")
            chart_button = gr.Button("Show Chart")
            chart_output = gr.Image(label="Mood Chart")

    log_button.click(log_mood, [mood, description], log_output)
    entries_button.click(show_entries, None, entries_output)
    analyze_button.click(analyze_mood, None, analyze_output)
    chart_button.click(mood_chart, None, chart_output)

app.launch()