app.py

import gradio as gr
import json
import os
from datetime import date
from transformers import pipeline

PROFILE_FILE = "about_me.json"
DAILY_FILE = "daily_status.json"

def load_json(path, default):
    if os.path.exists(path):
        with open(path) as f:
            return json.load(f)
    return default

def save_json(path, data):
    with open(path, "w") as f:
        json.dump(data, f, indent=2)

profile = load_json(PROFILE_FILE, {})
daily = load_json(DAILY_FILE, {})

def build_context(profile, daily):
    recent_days = sorted(daily.keys(), reverse=True)[:7]
    daily_lines = "\n".join([f"{d}: {daily[d].get('log','')}" for d in recent_days])
    context = (
        f"Profile:\n{json.dumps(profile, indent=2)}\n"
        f"Recent daily logs:\n{daily_lines}\n"
        "You are a helpful assistant. Answer only using the provided information. "
        "If you don't know the answer, reply: 'Sheetal hasn't shared that yet!'"
    )
    return context

def get_llm():
    return pipeline(
        "text-generation",
        model="HuggingFaceH4/zephyr-7b-beta",
        max_new_tokens=256,
        do_sample=True,
        temperature=0.7,
        trust_remote_code=True,
    )

llm = None

def chatbot_qa(user_q):
    global llm
    if llm is None:
        llm = get_llm()
    context = build_context(profile, daily)
    prompt = f"System: {context}\nUser: {user_q}\nAssistant:"
    outputs = llm(prompt, max_new_tokens=256)
    answer = outputs[0]["generated_text"].split("Assistant:")[-1].strip()
    return answer

def update_profile(name, city, job, about):
    profile.update({
        "name": name,
        "city": city,
        "job": job,
        "about": about
    })
    save_json(PROFILE_FILE, profile)
    return "Profile updated!"

def update_daily_log(freeform):
    today = str(date.today())
    daily[today] = {"log": freeform}
    save_json(DAILY_FILE, daily)
    return f"Today's log saved! ({today})"

def get_profile_defaults():
    return (
        profile.get("name", "Sheetal"),
        profile.get("city", ""),
        profile.get("job", ""),
        profile.get("about", "")
    )

def get_today_log():
    today = str(date.today())
    return daily.get(today, {}).get("log", "")

def recent_logs():
    logs = ""
    for d in sorted(daily.keys(), reverse=True)[:5]:
        logs += f"**{d}**: {daily[d]['log']}\n"
    return logs

with gr.Blocks(title="Sheetal's Personal Chatbot") as demo:
    gr.Markdown("# 🌸 Sheetal's Personal Chatbot")

    with gr.Tab("📝 Admin (Sheetal)"):
        gr.Markdown("### Edit Your Profile")
        with gr.Row():
            name = gr.Textbox(label="Name", value=profile.get("name", "Sheetal"))
            city = gr.Textbox(label="City", value=profile.get("city", ""))
            job = gr.Textbox(label="Profession", value=profile.get("job", ""))
        about = gr.Textbox(label="A few lines about you", value=profile.get("about", ""))
        save_profile_btn = gr.Button("Save Profile")
        profile_output = gr.Textbox(label="", interactive=False)

        save_profile_btn.click(
            fn=update_profile,
            inputs=[name, city, job, about],
            outputs=profile_output
        )

        gr.Markdown("---")
        gr.Markdown("### 🌱 Add Your Daily Status (free text!)")
        today_log = gr.Textbox(label="What do you want to remember about today?", value=get_today_log())
        save_log_btn = gr.Button("Save Today's Log")
        log_output = gr.Textbox(label="", interactive=False)

        save_log_btn.click(
            fn=update_daily_log,
            inputs=today_log,
            outputs=log_output
        )

        gr.Markdown("#### 📅 Recent Logs")
        recent_logs_box = gr.Markdown(recent_logs())

    with gr.Tab("💬 Ask About Sheetal"):
        gr.Markdown("### 💬 Ask Anything About Sheetal")
        user_q = gr.Textbox(label="Type your question here:")
        ask_btn = gr.Button("Ask")
        answer_box = gr.Textbox(label="Bot answer", interactive=False)

        ask_btn.click(
            fn=chatbot_qa,
            inputs=user_q,
            outputs=answer_box
        )

demo.launch()