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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) |