From 0735475ed35bafc924fcdc5f1505e1d3ee7f0b1b Mon Sep 17 00:00:00 2001 From: Disha Prakash Date: Thu, 20 Mar 2025 16:45:03 +0000 Subject: [PATCH 1/4] docs: update the readme to note Google provided integrations --- README.md | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/README.md b/README.md index 06c0a0f6..bf11a466 100644 --- a/README.md +++ b/README.md @@ -83,3 +83,25 @@ print(chat_history.messages) ### Vectorstore See example for the [PGVector vectorstore here](https://github.com/langchain-ai/langchain-postgres/blob/main/examples/vectorstore.ipynb) + +## Google Cloud Integrations + +[Google Cloud](https://python.langchain.com/docs/integrations/providers/google/) provides Vector Store, Chat Message History, and Data Loader integrations for [AlloyDB](https://cloud.google.com/alloydb) and [Cloud SQL](https://cloud.google.com/sql) for PostgreSQL databases via the following PyPi packages: + +* [`langchain-google-alloydb-pg`](https://github.com/googleapis/langchain-google-alloydb-pg-python) + +* [`langchain-google-cloud-sql-pg`](https://github.com/googleapis/langchain-google-cloud-sql-pg-python) + +Using the Google Cloud provided integrations provides the following benefits: + +- **Enhanced security**: Easily and securely connect to Google Cloud databases utilizing IAM for authorization and database authentication without needing to manage SSL certificates, configure firewall rules, or enable authorized networks. +- **Simplified and Secure Connections:** Connect to Google Cloud databases effortlessly using the instance name instead of complex connection strings. The integrations creates a secure connection pool that can be easily shared across your application using the `engine` object. + +Learn how to [migrate a `PGVector` vector store to `AlloyDBVectorStore`](https://github.com/googleapis/langchain-google-alloydb-pg-python/blob/main/samples/migrations/migrate_pgvector_to_alloydb.md) to gain the following benefits: + +- **Simplified management**: a single table contains data corresponding to a single collection, making it easier to query, update, and maintain. +- **Schema flexibility**: allow users to add tables into any database schema. +- **Improved performance**: using a single-table schema can lead to faster query execution, especially for large collections. +- **Improved metadata handling**: store metadata in columns instead of JSON, resulting in significant performance improvements. +- **Clear separation**: clearly separate table and extension creation, allowing for distinct permissions and streamlined workflows. +- **Better integration with AlloyDB**: take advantage of AlloyDB's advanced indexing and scalability capabilities. From 945942a9bd3f480dfd8116812b5054f2fa6b74e7 Mon Sep 17 00:00:00 2001 From: Disha Prakash Date: Fri, 21 Mar 2025 08:27:44 +0000 Subject: [PATCH 2/4] Change format into a table of features --- README.md | 15 ++++++--------- 1 file changed, 6 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index bf11a466..ee784c57 100644 --- a/README.md +++ b/README.md @@ -92,16 +92,13 @@ See example for the [PGVector vectorstore here](https://github.com/langchain-ai/ * [`langchain-google-cloud-sql-pg`](https://github.com/googleapis/langchain-google-cloud-sql-pg-python) -Using the Google Cloud provided integrations provides the following benefits: +Using the Google Cloud integrations provides the following benefits: -- **Enhanced security**: Easily and securely connect to Google Cloud databases utilizing IAM for authorization and database authentication without needing to manage SSL certificates, configure firewall rules, or enable authorized networks. +- **Enhanced Security**: Securely connect to Google Cloud databases utilizing IAM for authorization and database authentication without needing to manage SSL certificates, configure firewall rules, or enable authorized networks. - **Simplified and Secure Connections:** Connect to Google Cloud databases effortlessly using the instance name instead of complex connection strings. The integrations creates a secure connection pool that can be easily shared across your application using the `engine` object. -Learn how to [migrate a `PGVector` vector store to `AlloyDBVectorStore`](https://github.com/googleapis/langchain-google-alloydb-pg-python/blob/main/samples/migrations/migrate_pgvector_to_alloydb.md) to gain the following benefits: +| Vector Store | Metadata filtering | Async support | Schema Flexibility | Improved metadata handling | Hybrid Search | +|--------------------------|--------------------|----------------|--------------------|----------------------------|---------------| +| Google AlloyDB | ✓ | ✓ | ✓ | ✓ | ✓ | +| Google Cloud SQL Postgres| ✓ | ✓ | ✓ | ✓ | ✓ | -- **Simplified management**: a single table contains data corresponding to a single collection, making it easier to query, update, and maintain. -- **Schema flexibility**: allow users to add tables into any database schema. -- **Improved performance**: using a single-table schema can lead to faster query execution, especially for large collections. -- **Improved metadata handling**: store metadata in columns instead of JSON, resulting in significant performance improvements. -- **Clear separation**: clearly separate table and extension creation, allowing for distinct permissions and streamlined workflows. -- **Better integration with AlloyDB**: take advantage of AlloyDB's advanced indexing and scalability capabilities. From 93d2f9bbfa5157bf6bdd7dd650eff8e75d640dc4 Mon Sep 17 00:00:00 2001 From: Disha Prakash Date: Fri, 21 Mar 2025 08:31:01 +0000 Subject: [PATCH 3/4] Minor fix --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ee784c57..b3fc7846 100644 --- a/README.md +++ b/README.md @@ -99,6 +99,6 @@ Using the Google Cloud integrations provides the following benefits: | Vector Store | Metadata filtering | Async support | Schema Flexibility | Improved metadata handling | Hybrid Search | |--------------------------|--------------------|----------------|--------------------|----------------------------|---------------| -| Google AlloyDB | ✓ | ✓ | ✓ | ✓ | ✓ | -| Google Cloud SQL Postgres| ✓ | ✓ | ✓ | ✓ | ✓ | +| Google AlloyDB | ✓ | ✓ | ✓ | ✓ | ✗ | +| Google Cloud SQL Postgres| ✓ | ✓ | ✓ | ✓ | ✗ | From f70a66aa2f5fca82f692be47e466dbf6e22b4aa2 Mon Sep 17 00:00:00 2001 From: Disha Prakash Date: Fri, 21 Mar 2025 08:35:50 +0000 Subject: [PATCH 4/4] Layout fix --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index b3fc7846..f2ebe469 100644 --- a/README.md +++ b/README.md @@ -97,8 +97,8 @@ Using the Google Cloud integrations provides the following benefits: - **Enhanced Security**: Securely connect to Google Cloud databases utilizing IAM for authorization and database authentication without needing to manage SSL certificates, configure firewall rules, or enable authorized networks. - **Simplified and Secure Connections:** Connect to Google Cloud databases effortlessly using the instance name instead of complex connection strings. The integrations creates a secure connection pool that can be easily shared across your application using the `engine` object. -| Vector Store | Metadata filtering | Async support | Schema Flexibility | Improved metadata handling | Hybrid Search | +| Vector Store | Metadata filtering | Async support | Schema Flexibility | Improved metadata handling | Hybrid Search | |--------------------------|--------------------|----------------|--------------------|----------------------------|---------------| -| Google AlloyDB | ✓ | ✓ | ✓ | ✓ | ✗ | -| Google Cloud SQL Postgres| ✓ | ✓ | ✓ | ✓ | ✗ | +| Google AlloyDB | ✓ | ✓ | ✓ | ✓ | ✗ | +| Google Cloud SQL Postgres| ✓ | ✓ | ✓ | ✓ | ✗ |