main.py

from fastapi import FastAPI, File, UploadFile, Form, Request
from fastapi.responses import HTMLResponse, FileResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from huggingface_hub import InferenceClient
import random

API_URL = "https://api-inference.huggingface.co/models/"

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

app = FastAPI()


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


def generate(prompt, history, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
    temperature = float(temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(top_p)

    generate_kwargs = dict(
        temperature=temperature,
        max_new_tokens=max_new_tokens,
        top_p=top_p,
        repetition_penalty=repetition_penalty,
        do_sample=True,
        seed=random.randint(0, 10**7),
    )

    formatted_prompt = format_prompt(prompt, history)

    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""
    word = ""

    for response in stream:
        token_text = response.token.text.strip()
        if token_text != "":
            # Decode the token text to handle encoded characters
            decoded_text = token_text.encode("utf-8", "backslashreplace").decode("utf-8")

            # Add the decoded letter to the current word
            word += decoded_text

            # If the token is a space or the end of the stream, add the word to the output and reset the word
            if token_text == " " or response.is_end_of_sequence:
                output += word + " "
                word = ""

    return output


@app.post("/generate/")
async def generate_chat(request: Request, prompt: str = Form(...), history: str = Form(...), temperature: float = Form(0.9), max_new_tokens: int = Form(512), top_p: float = Form(0.95), repetition_penalty: float = Form(1.0)):
    history = eval(history)  # Convert history string back to list
    response = generate(prompt, history, temperature, max_new_tokens, top_p, repetition_penalty)
    
    # Concatenate the generated response strings into a single coherent response
    coherent_response = " ".join(response)
    
    return {"response": coherent_response}

app.mount("/", StaticFiles(directory="static", html=True), name="static")

@app.get("/")
def index() -> FileResponse:
    return FileResponse(path="/app/static/index.html", media_type="text/html")