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

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="google/flan-t5-small",
        max_new_tokens=128,
        do_sample=True,
        temperature=0.7,
    )

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=128)
    answer = outputs[0]["generated_text"].split("Assistant:")[-1].strip()
    return answer

def save_profile_and_log(name, city, job, about, freeform):
    today = str(date.today())
    profile.update({
        "name": name,
        "city": city,
        "job": job,
        "about": about
    })
    save_json(PROFILE_FILE, profile)
    daily[today] = {"log": freeform}
    save_json(DAILY_FILE, daily)
    logs = ""
    for d in sorted(daily.keys(), reverse=True)[:5]:
        logs += f"**{d}**: {daily[d]['log']}\n"
    return (
        "✅ Profile & log updated!",
        logs
    )

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

SECRET_CODE = "1234"  # Change this to your secret

def build_ui(request: gr.Request):
    # Check for secret in URL, e.g., ?admin=1234
    query_params = dict(request.query_params)
    show_admin = query_params.get("admin", [None])[0] == SECRET_CODE

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

        if show_admin:
            with gr.Tab("📝 Admin (Sheetal)"):
                with gr.Row():
                    name = gr.Textbox(label="Name", value=profile.get("name", "Sheetal"), max_lines=1)
                    city = gr.Textbox(label="City", value=profile.get("city", ""), max_lines=1)
                    job = gr.Textbox(label="Profession", value=profile.get("job", ""), max_lines=1)
                about = gr.Textbox(label="About You", value=profile.get("about", ""), lines=2, max_lines=3)
                today_log = gr.Textbox(label="What do you want to remember about today?", value=daily.get(str(date.today()), {}).get("log", ""), lines=2, max_lines=3)
                save_btn = gr.Button("💾 Save Profile & Today's Log")
                admin_status = gr.Markdown("")
                logs_output = gr.Markdown(recent_logs())
                save_btn.click(
                    fn=save_profile_and_log,
                    inputs=[name, city, job, about, today_log],
                    outputs=[admin_status, logs_output]
                )

        with gr.Tab("💬 Ask 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, lines=2, max_lines=4)
            ask_btn.click(
                fn=chatbot_qa,
                inputs=user_q,
                outputs=answer_box
            )
    return demo

gr.mount_gradio_app(app=build_ui, path="/", root_path="")

# For Hugging Face Spaces, use this launch line:
demo = build_ui
if __name__ == "__main__":
    demo.launch()