from fastapi import FastAPI, Depends, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from huggingface_hub import InferenceClient
import os
from fastapi.security import OAuth2PasswordBearer
from typing import Annotated

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

app = FastAPI()

# Allow all CORS
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
# client = InferenceClient("mistralai/Mistral-Nemo-Instruct-2407")

class Item(BaseModel):
    prompt: str
    history: list
    system_prompt: str
    temperature: float = 0.0
    max_new_tokens: int = 2048
    top_p: float = 0.15
    repetition_penalty: float = 1.0

def format_prompt(message, history):
    return message

def generate(item: Item):
    temperature = float(item.temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(item.top_p)

    generate_kwargs = dict(
        temperature=temperature,
        max_new_tokens=item.max_new_tokens,
        top_p=top_p,
        repetition_penalty=item.repetition_penalty,
        do_sample=True,
        seed=42,
    )

    formatted_prompt = format_prompt(f"{item.system_prompt}, {item.prompt}", item.history)
    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""

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

@app.get("/")
async def root():
    return {"status": "ok"}

@app.head("/")
async def root():
    return {"status": "ok"}


@app.post("/generate")
async def generate_text(item: Item, token: Annotated[str, Depends(oauth2_scheme)]):
    # Reject if not authenticated
    apiKey = os.environ.get("API_KEY")
    if apiKey != token:
        raise HTTPException(status_code=403, detail="Invalid API key")

    return {
        "response": generate(item)
    }