This package contains the LangChain integrations for AlloyDB for PostgreSQL.
🧪 Preview: This feature is covered by the Pre-GA Offerings Terms of the Google Cloud Terms of Service. Please note that pre-GA products and features might have limited support, and changes to pre-GA products and features might not be compatible with other pre-GA versions. For more information, see the launch stage descriptions
In order to use this library, you first need to go through the following steps:
- Select or create a Cloud Platform project.
- Enable billing for your project.
- Enable the Google Cloud AlloyDB API.
- Setup Authentication.
Install this library in a virtualenv
using pip. virtualenv
is a tool to
create isolated Python environments. The basic problem it addresses is one of
dependencies and versions, and indirectly permissions.
With virtualenv
, it's possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install langchain-google-alloydb-pg
Use a vector store to store embedded data and perform vector search.
from langchain_google_alloydb_pg import AlloyDBEngine, AlloyDBVectorstore
from langchain_google_vertexai import VertexAIEmbeddings
engine = AlloyDBEngine.from_instance("project-id", "region", "my-cluster", "my-instance", "my-database")
embeddings_service = VertexAIEmbeddings()
vectorstore = AlloyDBVectorStore(
engine,
table_name="my-table",
embeddings=embedding_service
)
See the full Vector Store tutorial.
Use a document loader to load data as LangChain Document
s.
from langchain_google_alloydb_pg import AlloyDBEngine, AlloyDBLoader
engine = AlloyDBEngine.from_instance("project-id", "region", "my-cluster", "my-instance", "my-database")
loader = PostgresSQLLoader(
engine,
table_name="my-table-name"
)
docs = loader.lazy_load()
See the full Document Loader tutorial.
Use ChatMessageHistory
to store messages and provide conversation history to LLMs.
from langchain_google_alloydb_pg import AlloyDBChatMessageHistory, AlloyDBEngine
engine = AlloyDBEngine.from_instance("project-id", "region", "my-cluster", "my-instance", "my-database")
history = AlloyDBChatMessageHistory(
engine,
table_name="my-message-store",
session_id="my-session-id"
)
See the full Chat Message History tutorial.
Contributions to this library are always welcome and highly encouraged.
See CONTRIBUTING for more information how to get started.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See Code of Conduct for more information.
Apache 2.0 - See LICENSE for more information.
This is not an officially supported Google product.