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Feature/sagemaker embedding (#1161)
* Sagemaker deployed embedding model support --------- Co-authored-by: Pablo Orgaz <pabloogc@gmail.com>
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9 changed files with 114 additions and 7 deletions
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@ -4,7 +4,7 @@ from __future__ import annotations
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import io
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import json
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import logging
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from typing import TYPE_CHECKING
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from typing import TYPE_CHECKING, Any
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import boto3 # type: ignore
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from llama_index.bridge.pydantic import Field
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@ -30,7 +30,6 @@ from llama_index.llms.llama_utils import (
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if TYPE_CHECKING:
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from collections.abc import Sequence
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from typing import Any
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from llama_index.callbacks import CallbackManager
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from llama_index.llms import (
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@ -36,7 +36,7 @@ class LLMComponent:
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from private_gpt.components.llm.custom.sagemaker import SagemakerLLM
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self.llm = SagemakerLLM(
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endpoint_name=settings.sagemaker.endpoint_name,
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endpoint_name=settings.sagemaker.llm_endpoint_name,
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)
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case "openai":
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from llama_index.llms import OpenAI
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