from fastapi import FastAPI, Request
from fastapi.templating import Jinja2Templates
from huggingface_hub import InferenceClient

app = FastAPI()
templates = Jinja2Templates(directory="templates")

client = InferenceClient(
    "mistralai/Mistral-7B-Instruct-v0.1"
)


async def format_prompt(message, history):
    prompt = "<s>"
    for user_prompt, bot_response in history:
        prompt += f"[INST] {user_prompt} [/INST]"
        prompt += f" {bot_response}</s> "
    prompt += f"[INST] {message} [/INST]"
    return prompt


async def generate(
    prompt: str,
    temperature: float = 0.9,
    max_new_tokens: int = 256,
    top_p: float = 0.95,
    repetition_penalty: float = 1.0,
):
    temperature = float(temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(top_p)

    generate_kwargs = {
        "temperature": temperature,
        "max_new_tokens": max_new_tokens,
        "top_p": top_p,
        "repetition_penalty": repetition_penalty,
        "do_sample": True,
        "seed": 42,
    }

    formatted_prompt = await format_prompt(prompt, [])

    response = client.text_generation(formatted_prompt, **generate_kwargs, stream=False, details=False, return_full_text=True)
    return response


@app.get("/")
async def index(request: Request):
    return templates.TemplateResponse("index.html", {"request": request})


@app.post("/generate/")
async def chatbot_response(prompt: str):
    response = await generate(prompt)
    return {"response": response}