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from huggingface_hub import InferenceClient | |
import os | |
from dotenv import load_dotenv | |
load_dotenv() | |
API_TOKEN = os.getenv('HF_TOKEN') | |
def format_prompt(message, history): | |
prompt = "<s>" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
def chat( | |
prompt, history, chat_client = "mistralai/Mistral-7B-Instruct-v0.1",temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, | |
): | |
client = InferenceClient( | |
chat_client, | |
token=API_TOKEN | |
) | |
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, | |
) | |
formatted_prompt = format_prompt(prompt, history) | |
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
output = "" | |
# for response in stream: | |
# # print(response) | |
# output += response.token["text"] | |
# yield output | |
# return output | |
return stream | |