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This PR rolls out part of the new proposed interface for vectorstores (https://github.com/langchain-ai/langchain/pull/23544) to existing store implementations. The PR makes the following changes: 1. Adds standard upsert, streaming_upsert, aupsert, astreaming_upsert methods to the vectorstore. 2. Updates `add_texts` and `aadd_texts` to be non required with a default implementation that delegates to `upsert` and `aupsert` if those have been implemented. The original `add_texts` and `aadd_texts` methods are problematic as they spread object specific information across document and **kwargs. (e.g., ids are not a part of the document) 3. Adds a default implementation to `add_documents` and `aadd_documents` that delegates to `upsert` and `aupsert` respectively. 4. Adds standard unit tests to verify that a given vectorstore implements a correct read/write API. A downside of this implementation is that it creates `upsert` with a very similar signature to `add_documents`. The reason for introducing `upsert` is to: * Remove any ambiguities about what information is allowed in `kwargs`. Specifically kwargs should only be used for information common to all indexed data. (e.g., indexing timeout). *Allow inheriting from an anticipated generalized interface for indexing that will allow indexing `BaseMedia` (i.e., allow making a vectorstore for images/audio etc.) `add_documents` can be deprecated in the future in favor of `upsert` to make sure that users have a single correct way of indexing content. --------- Co-authored-by: ccurme <chester.curme@gmail.com>
langchain-standard-tests
This is an INTERNAL library for the LangChain project. It contains the base classes for a standard set of tests.
Installation
This package will NOT be regularly published to pypi. It is intended to be installed directly from github at test time.
Pip:
```bash
pip install git+https://github.com/langchain-ai/langchain.git#subdirectory=libs/standard-tests
```
Poetry:
```bash
poetry add git+https://github.com/langchain-ai/langchain.git#subdirectory=libs/standard-tests
```
Usage
To add standard tests to an integration package's e.g. ChatModel, you need to create
- A unit test class that inherits from ChatModelUnitTests
- An integration test class that inherits from ChatModelIntegrationTests
tests/unit_tests/test_standard.py:
"""Standard LangChain interface tests"""
from typing import Type
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_standard_tests.unit_tests import ChatModelUnitTests
from langchain_parrot_chain import ChatParrotChain
class TestParrotChainStandard(ChatModelUnitTests):
@pytest.fixture
def chat_model_class(self) -> Type[BaseChatModel]:
return ChatParrotChain
tests/integration_tests/test_standard.py:
"""Standard LangChain interface tests"""
from typing import Type
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_standard_tests.integration_tests import ChatModelIntegrationTests
from langchain_parrot_chain import ChatParrotChain
class TestParrotChainStandard(ChatModelIntegrationTests):
@pytest.fixture
def chat_model_class(self) -> Type[BaseChatModel]:
return ChatParrotChain
Reference
The following fixtures are configurable in the test classes. Anything not marked as required is optional.
chat_model_class(required): The class of the chat model to be testedchat_model_params: The keyword arguments to pass to the chat model constructorchat_model_has_tool_calling: Whether the chat model can call tools. By default, this is set tohasattr(chat_model_class, 'bind_tools)chat_model_has_structured_output: Whether the chat model can structured output. By default, this is set tohasattr(chat_model_class, 'with_structured_output')