37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import importlib
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import logging
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from typing import Optional
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from embedchain.config import BaseLlmConfig
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from embedchain.helper.json_serializable import register_deserializable
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from embedchain.llm.base import BaseLlm
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@register_deserializable
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class VertexAILlm(BaseLlm):
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def __init__(self, config: Optional[BaseLlmConfig] = None):
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try:
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importlib.import_module("vertexai")
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except ModuleNotFoundError:
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raise ModuleNotFoundError(
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"The required dependencies for VertexAI are not installed."
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'Please install with `pip install --upgrade "embedchain[vertexai]"`'
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) from None
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super().__init__(config=config)
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def get_llm_model_answer(self, prompt):
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return VertexAILlm._get_answer(prompt=prompt, config=self.config)
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@staticmethod
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def _get_answer(prompt: str, config: BaseLlmConfig) -> str:
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from langchain.chat_models import ChatVertexAI
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chat = ChatVertexAI(temperature=config.temperature, model=config.model)
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if config.top_p and config.top_p != 1:
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logging.warning("Config option `top_p` is not supported by this model.")
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messages = BaseLlm._get_messages(prompt, system_prompt=config.system_prompt)
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return chat(messages).content
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