Autovectorization Tutorial #54

giriraj-singh-couchbase · 2025-09-15T22:39:20Z

This guide is a comprehensive tutorial demonstrating how to use Couchbase Capella's AI Services auto-vectorization feature to automatically convert your data into vector embeddings and perform semantic search using LangChain.

📋 Overview

The main tutorial is contained in the Jupyter notebook autovec_langchain.ipynb, which walks you through:

Couchbase Capella Setup - Creating account, cluster, and access controls
Data Upload & Processing - Using sample data
Model Deployment - Deploying embedding models for vectorization
Auto-Vectorization Workflow - Setting up automated embedding generation
LangChain Integration - Building semantic search applications with vector similarity

gemini-code-assist

Summary of Changes

Hello @giriraj-singh-couchbase, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request delivers a new, detailed tutorial designed to guide users through the process of leveraging Couchbase Capella's AI Services for automatic data vectorization. The tutorial provides a complete walkthrough, from initial Capella account and cluster setup to deploying embedding models and configuring auto-vectorization workflows, culminating in practical examples of semantic search using LangChain. The aim is to empower users to easily transform their data into vector embeddings and build intelligent search applications.

Highlights

New Auto-Vectorization Tutorial: Introduces a comprehensive tutorial demonstrating the use of Couchbase Capella's AI Services auto-vectorization feature to convert data into vector embeddings.
LangChain Integration: The tutorial showcases how to perform semantic search using the generated vector embeddings by integrating with LangChain.
Step-by-Step Guide: The tutorial covers essential steps including Couchbase Capella setup, data upload and processing, embedding model deployment, auto-vectorization workflow configuration, and practical LangChain integration examples.

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github-actions · 2025-09-15T22:39:34Z

Caution

Notebooks or Frontmatter Files Have Been Modified

Please ensure that a frontmatter.md file is accompanying the notebook file, and that the frontmatter is up to date.
These changes will be published to the developer portal tutorials only if frontmatter.md is included.
Proofread all changes before merging, as changes to notebook and frontmatter content will update the developer tutorial.

1 Notebook Files Modified:

Notebook File	Frontmatter Included?
`autovec-tutorial/autovec_langchain.ipynb`	❌

0 Frontmatter Files Modified:

Frontmatter File
Note: frontmatter will be checked and tested in the Test Frontmatter* workflow.*

gemini-code-assist

Code Review

This pull request introduces a comprehensive tutorial on using Couchbase Capella's AI Services for auto-vectorization with LangChain. The tutorial is well-structured, but there are several areas for improvement to enhance clarity, correctness, and security for the end-user. My review includes feedback on the README file and the Jupyter notebook, addressing issues such as placeholder values, dependency management, broken links, inconsistent formatting, typos, and a hardcoded credential. Addressing these points will make the tutorial more polished and easier for users to follow.

autovec-tutorial/autovec_langchain.ipynb

autovec-tutorial/README.md

autovec-tutorial/autovec_langchain.ipynb

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

…se-examples/vector-search-cookbook into DA-1096_autovec_tutorial

nithishr

Can you apply the same comments as in #57 to this one as well?

nithishr

Same comments as in #57 are relevant here as well.

nithishr · 2025-11-04T18:41:14Z

autovec-tutorial/autovec_langchain.ipynb

+   "source": [
+    "# Cluster Connection Setup\n",
+    "   - Defines the secure connection string, user credentials, and creates a `Cluster` object.\n",
+    "   - Disables TLS verification by `options = ClusterOptions(auth, tls_verify='none')` ONLY for quick local testing (not recommended in production) and applies the `wan_development` profile to tune timeouts for higher-latency networks."


We don't do it anymore

nithishr · 2025-11-04T18:45:19Z

autovec-tutorial/autovec_langchain.ipynb

+    "bucket_name = \"travel-sample\"\n",
+    "scope_name = \"inventory\"\n",
+    "collection_name = \"hotel\"\n",
+    "index_name = \"hybrid_autovec_workflow_vec_addr_descr_id\"  # This is the name of the search index that was created in step 4.5 and can also be seen in the search tab of the cluster.\n",


nit: This looks different from the one on the screenshot

nithishr · 2025-11-04T18:46:51Z

autovec-tutorial/autovec_langchain.ipynb

+    }
+   ],
+   "source": [
+    "query = \"Woodhead Road\"\n",


This again feels like FTS rather than vector search.
Maybe just index the description & ask for synonyms of descriptions?

nithishr · 2025-11-04T18:52:09Z

autovec-tutorial/autovec_langchain.ipynb

+   "source": [
+    "# Auto-Vectorization Using Couchbase Capella AI Services\n",
+    "\n",
+    "This comprehensive tutorial demonstrates how to use Couchbase Capella's new AI Services auto-vectorization feature to automatically convert your data into vector embeddings and perform semantic search using LangChain.\n"


We need a paragraph about this tutorial being about Vectorizing structured data stored in Couchbase. And link to the other tutorial along the lines of - If you are looking to vectorize data from unstructured sources such as S3, check this tutorial.
And vice versa for the other tutorial.
We have similar examples in the

Also the titles need to be adapted to add Structured/Unstructured to it.

nithishr · 2025-11-04T18:54:39Z

autovec-tutorial/__frontmatter__.md

@@ -0,0 +1,18 @@
+---
+# frontmatter
+path: "/tutorial-couchbase-autovectorization-langchain"


The path should also be different from the other autovec tutorial (#57 )

nithishr · 2025-11-04T18:55:26Z

autovec-tutorial/img/Access_control.png

You might also want to consider grouping the tutorials in different folders to avoid confusion/conflicts.

Updating AutoVec tutorial

807c392

giriraj-singh-couchbase requested a review from deniswsrosa September 15, 2025 22:39

gemini-code-assist bot reviewed Sep 15, 2025

View reviewed changes

giriraj-singh-couchbase and others added 13 commits September 16, 2025 04:34

Added frontmatter.md and updated the tutorial

68e04f3

Applied suggestions from code review

9bb439b

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Fixed frontmatter.md

dfca154

fixing minor details

e52bcd5

Merge branch 'DA-1096_autovec_tutorial' of https://github.com/couchba…

604bf29

…se-examples/vector-search-cookbook into DA-1096_autovec_tutorial

Fixed frontmatter.md

fc878a4

Updated autovec_langchain.ipynb

38d1792

fixed some screenshots

1e9bb07

updated screenshot

b85f7a4

fixed grammatical mistakes

69fe694

fixed capella free-tier issue and added some missing content

9bcf7b9

added missing content

0d870b1

Updatede doc

709cfe5

nithishr reviewed Oct 2, 2025

View reviewed changes

teetangh assigned giriraj-singh-couchbase Oct 28, 2025

giriraj-singh-couchbase added 3 commits October 30, 2025 21:40

added version of libraries, removed unnecessary files

55242d5

updated model service name

ce09c83

removed extra code

e48691b

nithishr reviewed Nov 4, 2025

View reviewed changes

Autovectorization Tutorial #54

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giriraj-singh-couchbase commented Sep 15, 2025

📋 Overview

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github-actions bot commented Sep 15, 2025 •

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