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import os |
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from typing import Iterator |
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from text_generation import Client |
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_MODEL_ID = 'mistralai/Mistral-7B-Instruct-v0.1' |
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API_URL = "https://api-inference.huggingface.co/models/" + _MODEL_ID |
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HF_TOKEN = os.environ.get("HF_READ_TOKEN", None) |
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client = Client( |
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API_URL, |
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headers={"Authorization": f"Bearer {HF_TOKEN}"}, |
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) |
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EOS_STRING = "</s>" |
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EOT_STRING = "<EOT>" |
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def get_prompt(message: str, chat_history: list[tuple[str, str]], |
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system_prompt: str) -> str: |
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texts = [f'<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n'] |
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do_strip = False |
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for user_input, response in chat_history: |
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user_input = user_input.strip() if do_strip else user_input |
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do_strip = True |
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texts.append(f'{user_input} [/INST] {response.strip()} </s><s>[INST] ') |
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message = message.strip() if do_strip else message |
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texts.append(f'{message} [/INST]') |
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return ''.join(texts) |
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def run(message: str, |
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chat_history: list[tuple[str, str]], |
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system_prompt: str, |
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max_new_tokens: int = 1024, |
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temperature: float = 0.1, |
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top_p: float = 0.9, |
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top_k: int = 50) -> Iterator[str]: |
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prompt = get_prompt(message, chat_history, system_prompt) |
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generate_kwargs = dict( |
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max_new_tokens=max_new_tokens, |
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do_sample=True, |
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top_p=top_p, |
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top_k=top_k, |
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temperature=temperature, |
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) |
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stream = client.generate_stream(prompt, **generate_kwargs) |
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output = "" |
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for response in stream: |
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if any([end_token in response.token.text for end_token in [EOS_STRING, EOT_STRING]]): |
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return output |
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else: |
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output += response.token.text |
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yield output |
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return output |