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- import os
- from typing import Optional
- from langchain.llms import Replicate
- from embedchain.config import BaseLlmConfig
- from embedchain.helper.json_serializable import register_deserializable
- from embedchain.llm.base import BaseLlm
- @register_deserializable
- class Llama2Llm(BaseLlm):
- def __init__(self, config: Optional[BaseLlmConfig] = None):
- if "REPLICATE_API_TOKEN" not in os.environ:
- raise ValueError("Please set the REPLICATE_API_TOKEN environment variable.")
- super().__init__(config=config)
- def get_llm_model_answer(self, prompt):
- # TODO: Move the model and other inputs into config
- if self.config.system_prompt:
- raise ValueError("Llama2App does not support `system_prompt`")
- llm = Replicate(
- model="a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5",
- input={"temperature": self.config.temperature or 0.75, "max_length": 500, "top_p": self.config.top_p},
- )
- return llm(prompt)
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