mirror of
https://github.com/arc53/DocsGPT
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32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
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from application.llm.base import BaseLLM
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class HuggingFaceLLM(BaseLLM):
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def __init__(self, api_key, llm_name='Arc53/DocsGPT-7B'):
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global hf
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from langchain.llms import HuggingFacePipeline
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained(llm_name)
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model = AutoModelForCausalLM.from_pretrained(llm_name)
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pipe = pipeline(
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"text-generation", model=model,
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tokenizer=tokenizer, max_new_tokens=2000,
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device_map="auto", eos_token_id=tokenizer.eos_token_id
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)
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hf = HuggingFacePipeline(pipeline=pipe)
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def gen(self, model, engine, messages, stream=False, **kwargs):
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context = messages[0]['content']
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user_question = messages[-1]['content']
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prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n"
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result = hf(prompt)
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return result.content
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def gen_stream(self, model, engine, messages, stream=True, **kwargs):
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raise NotImplementedError("HuggingFaceLLM Streaming is not implemented yet.")
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