main.py

from typing import Union

from pydantic import BaseModel
from fastapi import FastAPI, Request
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
from huggingface_hub import InferenceClient


app = FastAPI()


# Class for input data for general prompt to model
class UserPrompt(BaseModel):
    query: str

# Class for the output data
class OutputData(BaseModel):
    response: str


@app.get("/")
async def start():
    return "Please go to /docs to try the API endpoints"




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

async def generate(prompt, temperature=0.7, max_new_tokens=1200, top_p=0.80, repetition_penalty=1.2):

    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=42,
    )


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

    for response in stream:
        output += response.token.text
        # yield output
    return output


"""
Prompt anything to the LLM & get response
"""
@app.post("/generation", response_model=OutputData)
async def generate_AI_response(request: Request, input_data: UserPrompt, q: Union[str, None] = None):

    try:
        query = input_data.query

        if query and query != "" and query != ".":
            
            response = await generate(query)
            
            # return StreamingResponse(generate(query), media_type='text/event-stream')

    except ValueError as error:
        print(error)

    return OutputData(response=response)