from ctransformers import AutoModelForCausalLM
from fastapi import FastAPI, Form
from pydantic import BaseModel


llm = AutoModelForCausalLM.from_pretrained("zephyr-7b-beta.Q4_K_S.gguf",
model_type='mistral',
max_new_tokens = 1096,
threads = 1,
)
   

#Pydantic object
class validation(BaseModel):
    prompt: str
#Fast API
app = FastAPI()
#Function contain tranlater API, RAG API, OpenAI API
@app.post("/llm_on_cpu")
async def stream(item: validation):
    system_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
    E_INST = "</s>"
    user, assistant = "<|user|>", "<|assistant|>"
    prompt = f"{system_prompt}{E_INST}\n{user}\n{item.prompt.strip()}{E_INST}\n{assistant}\n"
    return llm(prompt)

#def stream(user_prompt)
# system_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
# E_INST = "</s>"
# user, assistant = "<|user|>", "<|assistant|>"
# prompt = f"{system_prompt}{E_INST}\n{user}\n{user_prompt.strip()}{E_INST}\n{assistant}\n"
# for text in llm(prompt, stream=True):
#     print(text, end="", flush=True)