from huggingface_hub import InferenceClient import os from dotenv import load_dotenv load_dotenv() API_TOKEN = os.getenv("HF_TOKEN") def format_prompt(session_state ,query, history, chat_client): if chat_client=="NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO" : model_input = f"""<|im_start|>system {session_state.system_instruction} """ for user_prompt, bot_response in history: model_input += f"""<|im_start|>user {user_prompt}<|im_end|> """ model_input += f"""<|im_start|>assistant {bot_response}<|im_end|> """ model_input += f"""<|im_start|>user {query}<|im_end|> <|im_start|>assistant""" return model_input else : model_input = "" for user_prompt, bot_response in history: model_input += f"[INST] {user_prompt} [/INST]" model_input += f" {bot_response} " model_input += f"[INST] {query} [/INST]" return model_input def chat(session_state, query, config): chat_bot_dict = config["CHAT_BOTS"] chat_client = chat_bot_dict[session_state.chat_bot] temperature = session_state.temp max_new_tokens = session_state.max_tokens repetion_penalty = session_state.repetion_penalty history = session_state.history client = InferenceClient(chat_client, token=API_TOKEN) temperature = float(temperature) if temperature < 1e-2: temperature = 1e-2 top_p = float(0.95) generate_kwargs = dict( temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetion_penalty, do_sample=True, seed=42, ) formatted_prompt = format_prompt(session_state, query, history, chat_client) stream = client.text_generation( formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False, truncate = 32000 ) return stream