50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import os
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from typing import Optional
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from langchain_community.llms import Bedrock
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from embedchain.config import BaseLlmConfig
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from embedchain.helpers.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 AWSBedrockLlm(BaseLlm):
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def __init__(self, config: Optional[BaseLlmConfig] = None):
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super().__init__(config)
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def get_llm_model_answer(self, prompt) -> str:
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response = self._get_answer(prompt, self.config)
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return response
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def _get_answer(self, prompt: str, config: BaseLlmConfig) -> str:
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try:
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import boto3
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except ModuleNotFoundError:
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raise ModuleNotFoundError(
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"The required dependencies for AWSBedrock are not installed."
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'Please install with `pip install --upgrade "embedchain[aws-bedrock]"`'
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) from None
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self.boto_client = boto3.client("bedrock-runtime", "us-west-2" or os.environ.get("AWS_REGION"))
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kwargs = {
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"model_id": config.model or "amazon.titan-text-express-v1",
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"client": self.boto_client,
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"model_kwargs": config.model_kwargs
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or {
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"temperature": config.temperature,
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},
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}
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if config.stream:
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from langchain.callbacks.streaming_stdout import \
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StreamingStdOutCallbackHandler
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callbacks = [StreamingStdOutCallbackHandler()]
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llm = Bedrock(**kwargs, streaming=config.stream, callbacks=callbacks)
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else:
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llm = Bedrock(**kwargs)
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return llm.invoke(prompt)
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