53 lines
1.8 KiB
Python
53 lines
1.8 KiB
Python
import importlib
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import os
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from typing import Optional
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from langchain.llms import Replicate
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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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try:
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importlib.import_module("replicate")
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except ModuleNotFoundError:
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raise ModuleNotFoundError(
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"The required dependencies for Llama2 are not installed."
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'Please install with `pip install --upgrade "embedchain[llama2]"`'
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) from None
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@register_deserializable
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class Llama2Llm(BaseLlm):
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def __init__(self, config: Optional[BaseLlmConfig] = None):
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if "REPLICATE_API_TOKEN" not in os.environ:
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raise ValueError("Please set the REPLICATE_API_TOKEN environment variable.")
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# Set default config values specific to this llm
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if not config:
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config = BaseLlmConfig()
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# Add variables to this block that have a default value in the parent class
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config.max_tokens = 500
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config.temperature = 0.75
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# Add variables that are `none` by default to this block.
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if not config.model:
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config.model = (
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"a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5"
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)
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super().__init__(config=config)
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def get_llm_model_answer(self, prompt):
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# TODO: Move the model and other inputs into config
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if self.config.system_prompt:
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raise ValueError("Llama2App does not support `system_prompt`")
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llm = Replicate(
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model=self.config.model,
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input={
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"temperature": self.config.temperature,
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"max_length": self.config.max_tokens,
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"top_p": self.config.top_p,
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},
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)
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return llm(prompt)
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