import gradio as gr
from transformers import pipeline

# -----------------------------
# 1. Model & pipeline setup
# -----------------------------

MODEL_NAME = "microsoft/Phi-3.5-mini-instruct"

# This will automatically download and load the model on CPU.
# Using pipeline keeps it simple and avoids many common errors.
generator = pipeline(
    "text-generation",
    model=MODEL_NAME,
    max_new_tokens=512,
    do_sample=True,
    temperature=0.4,
    top_p=0.9,
)

SYSTEM_PROMPT = """
You are HowToBot, an expert step-by-step instructor.

Your job:
- Explain HOW TO do things from very basic to very advanced.
- Break tasks into clear, numbered steps.
- Prefer practical, hands-on instructions over theory.
- Assume the user is smart but may be a beginner in that topic.
- When something is dangerous, illegal, or unethical, refuse and suggest a safer alternative.

Response format:
1. Start with a 1–2 line overview of the task.
2. Then give a clear step-by-step guide with numbered steps.
3. Use bullet lists and short paragraphs when helpful.
"""

def build_prompt(user_message: str, history: list) -> str:
    """
    Build a simple instruct-style prompt using a system message,
    a bit of chat history, and the latest user query.
    """
    conversation_text = f"System: {SYSTEM_PROMPT.strip()}\n\n"

    # Add last few exchanges for context
    if history:
        for user, bot in history[-4:]:
            conversation_text += f"User: {user}\nAssistant: {bot}\n\n"

    conversation_text += f"User: {user_message}\nAssistant:"
    return conversation_text

def respond(user_message, history):
    if history is None:
        history = []

    prompt = build_prompt(user_message, history)

    outputs = generator(
        prompt,
        num_return_sequences=1,
        pad_token_id=generator.tokenizer.eos_token_id,
    )

    full_text = outputs[0]["generated_text"]

    # Keep only what the assistant says after the last "Assistant:"
    if "Assistant:" in full_text:
        answer = full_text.split("Assistant:")[-1].strip()
    else:
        answer = full_text[len(prompt):].strip()

    history.append((user_message, answer))
    return answer, history

# -----------------------------
# 2. Gradio UI
# -----------------------------

chatbot = gr.ChatInterface(
    respond,
    title="HowToBot 🛠️",
    description=(
        "Ask me **how to do anything** — from basic tasks to advanced workflows.\n\n"
        "- I give clear, numbered steps.\n"
        "- I can simplify or go deep based on your follow-up questions.\n"
        "- Try: *'How to learn Python from scratch'* or *'How to design a database for an e-commerce site'*. "
    ),
    examples=[
        "How to boil an egg perfectly",
        "How to learn Python step by step in 3 months",
        "How to build a personal portfolio website and host it for free",
        "How to create a study timetable that I can actually follow",
    ],
)

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