app.py

import torch
import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

# ---------- CONFIG ----------
# Using an open-access model instead of gated Mistral
MODEL_NAME = "tiiuae/falcon-7b-instruct"

# Preload model and tokenizer
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_NAME,
    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
    device_map="auto"
)

generator = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    max_new_tokens=512,
    temperature=0.5,
    do_sample=True
)

# ---------- TECH FILTER ----------
def is_tech_query(message: str) -> bool:
    tech_keywords = [
        "python", "java", "javascript", "html", "css", "react", "angular",
        "node", "machine learning", "deep learning", "ai", "api", "code",
        "debug", "error", "technology", "computer", "programming", "software",
        "hardware", "cybersecurity", "database", "sql", "devops", "cloud"
    ]
    return any(k in message.lower() for k in tech_keywords)

# ---------- CHAT FUNCTION ----------
def chat_with_model(message, history):
    if not is_tech_query(message):
        return history + [[message, "⚠️ I can only answer technology-related queries."]]

    conversation = ""
    for user_msg, bot_msg in history:
        conversation += f"User: {user_msg}\nAssistant: {bot_msg}\n"
    conversation += f"User: {message}\nAssistant:"

    output = generator(conversation)[0]["generated_text"]
    if "Assistant:" in output:
        answer = output.split("Assistant:")[-1].strip()
    else:
        answer = output.strip()

    return history + [[message, answer]]

# ---------- LOGIN + UI ----------
session_state = {"authenticated": False}

def login(username, password):
    if (username == "admin" and password == "admin123") or (username == "techuser" and password == "techpass"):
        session_state["authenticated"] = True
        return gr.update(visible=False), gr.update(visible=True), ""
    else:
        return gr.update(), gr.update(visible=False), "❌ Invalid credentials."

with gr.Blocks(css=".gradio-container {max-width: 750px; margin: auto;}") as demo:
    # Login Page
    with gr.Group(visible=not session_state["authenticated"]) as login_group:
        gr.Markdown("# 🔐 Login to Tech Chatbot")
        username = gr.Textbox(label="Username")
        password = gr.Textbox(label="Password", type="password")
        login_btn = gr.Button("Login")
        login_status = gr.Markdown("")

    # Chatbot Page
    with gr.Group(visible=session_state["authenticated"]) as chat_group:
        gr.Markdown("# 💻 Tech Helper Chatbot")
        chatbot = gr.Chatbot(height=500)
        msg = gr.Textbox(placeholder="Type your tech question here...", label="Your Message")
        clear = gr.Button("Clear Chat")

        msg.submit(chat_with_model, [msg, chatbot], chatbot)
        clear.click(lambda: None, None, chatbot)

    # Button Logic
    login_btn.click(login, [username, password], [login_group, chat_group, login_status])

if __name__ == "__main__":
    demo.launch()