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

#Model loading
llm = AutoModelForCausalLM.from_pretrained("TheBloke/Toppy-M-7B-GGUF", 
                                           model_file="toppy-m-7b.Q5_K_M.gguf", 
                                           model_type="mistral", 
                                           context_length=4096,
                                           temperature=1,
                                           gpu_layers=50)

# llm = AutoModelForCausalLM.from_pretrained("TheDrummer/Moistral-11B-v3-GGUF", 
#                                            model_file="Moistral-11B-v3-Q6_K.gguf", 
#                                            model_type="mistral", 
#                                            context_length=4096,
#                                            temperature=0.6,
#                                            gpu_layers=50)


#Pydantic object
class validation(BaseModel):
    prompt: str
    
#Fast API
app = FastAPI()

#Zephyr completion
@app.post("/llm_on_gpu")
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)