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import os | |
from typing import Iterator | |
from text_generation import Client | |
model_id = 'HuggingFaceH4/zephyr-7b-beta' | |
API_URL = "https://api-inference.huggingface.co/models/" + model_id | |
HF_TOKEN = os.environ.get("HF_READ_TOKEN", None) | |
client = Client( | |
API_URL, | |
headers={"Authorization": f"Bearer {HF_TOKEN}"}, | |
) | |
EOS_STRING = "</s>" | |
EOT_STRING = "<EOT>" | |
def get_prompt(message: str, chat_history: list[tuple[str, str]], | |
system_prompt: str) -> str: | |
texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n'] | |
# The first user input is _not_ stripped | |
do_strip = False | |
for user_input, response in chat_history: | |
user_input = user_input.strip() if do_strip else user_input | |
do_strip = True | |
texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ') | |
message = message.strip() if do_strip else message | |
texts.append(f'{message} [/INST]') | |
return ''.join(texts) | |
def run(message: str, | |
chat_history: list[tuple[str, str]], | |
system_prompt: str, | |
max_new_tokens: int = 1024, | |
temperature: float = 0.1, | |
top_p: float = 0.9, | |
top_k: int = 50) -> Iterator[str]: | |
prompt = get_prompt(message, chat_history, system_prompt) | |
generate_kwargs = dict( | |
max_new_tokens=max_new_tokens, | |
do_sample=True, | |
top_p=top_p, | |
top_k=top_k, | |
temperature=temperature, | |
) | |
stream = client.generate_stream(prompt, **generate_kwargs) | |
output = "" | |
for response in stream: | |
if any([end_token in response.token.text for end_token in [EOS_STRING, EOT_STRING]]): | |
return output | |
else: | |
output += response.token.text | |
yield output | |
return output | |