lmm_use / model.py
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import os
from typing import Iterator
from text_generation import Client
model_id = 'mistralai/Mistral-7B-Instruct-v0.1'
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