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8516a03a02
This PR upgrades langchain-community to pydantic 2.
* Most of this PR was auto-generated using code mods with gritql
(https://github.com/eyurtsev/migrate-pydantic/tree/main)
* Subsequently, some code was fixed manually due to accommodate
differences between pydantic 1 and 2
Breaking Changes:
- Use TEXTEMBED_API_KEY and TEXTEMBEB_API_URL for env variables for text
embed integrations:
cbea780492
Other changes:
- Added pydantic_settings as a required dependency for community. This
may be removed if we have enough time to convert the dependency into an
optional one.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
82 lines
2.3 KiB
Python
82 lines
2.3 KiB
Python
"""Util that calls Lambda."""
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import json
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, ConfigDict, model_validator
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class LambdaWrapper(BaseModel):
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"""Wrapper for AWS Lambda SDK.
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To use, you should have the ``boto3`` package installed
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and a lambda functions built from the AWS Console or
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CLI. Set up your AWS credentials with ``aws configure``
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Example:
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.. code-block:: bash
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pip install boto3
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aws configure
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"""
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lambda_client: Any #: :meta private:
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"""The configured boto3 client"""
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function_name: Optional[str] = None
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"""The name of your lambda function"""
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awslambda_tool_name: Optional[str] = None
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"""If passing to an agent as a tool, the tool name"""
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awslambda_tool_description: Optional[str] = None
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"""If passing to an agent as a tool, the description"""
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model_config = ConfigDict(
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extra="forbid",
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)
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@model_validator(mode="before")
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@classmethod
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def validate_environment(cls, values: Dict) -> Any:
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"""Validate that python package exists in environment."""
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try:
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import boto3
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except ImportError:
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raise ImportError(
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"boto3 is not installed. Please install it with `pip install boto3`"
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)
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values["lambda_client"] = boto3.client("lambda")
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return values
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def run(self, query: str) -> str:
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"""
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Invokes the lambda function and returns the
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result.
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Args:
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query: an input to passed to the lambda
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function as the ``body`` of a JSON
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object.
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"""
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res = self.lambda_client.invoke(
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FunctionName=self.function_name,
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InvocationType="RequestResponse",
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Payload=json.dumps({"body": query}),
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)
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try:
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payload_stream = res["Payload"]
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payload_string = payload_stream.read().decode("utf-8")
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answer = json.loads(payload_string)["body"]
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except StopIteration:
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return "Failed to parse response from Lambda"
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if answer is None or answer == "":
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# We don't want to return the assumption alone if answer is empty
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return "Request failed."
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else:
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return f"Result: {answer}"
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