-
Notifications
You must be signed in to change notification settings - Fork 6
DA 1153 Autovec Unstructured Data #57
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Changes from all commits
7088c3e
eec1a72
fa4de94
84832ae
c5d565f
055b78f
File filter
Filter by extension
Conversations
Jump to
Diff view
Diff view
There are no files selected for viewing
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,43 @@ | ||
# Couchbase Capella AI Services Auto-Vectorization with LangChain | ||
|
||
This guide is a comprehensive tutorial demonstrating how to use Couchbase Capella's AI Services auto-vectorization feature for unstructured data to automatically convert your data into vector embeddings and perform semantic search using LangChain. | ||
|
||
## 🚀 Quick Start | ||
|
||
### Prerequisites | ||
|
||
- Python 3.8 or higher | ||
- A Couchbase Capella account | ||
- Basic understanding of vector databases and embeddings | ||
|
||
### Installation Steps | ||
|
||
1. **Clone or download this repository** | ||
```bash | ||
git clone https://github.com/couchbase-examples/vector-search-cookbook.git | ||
cd vector-search-cookbook/autovec-unstructured | ||
``` | ||
|
||
2. **Install Python dependencies** | ||
```bash | ||
pip install jupyter | ||
pip install couchbase | ||
pip install langchain-couchbase | ||
pip install langchain-nvidia-ai-endpoints | ||
``` | ||
|
||
3. **Start Jupyter Notebook** | ||
```bash | ||
jupyter notebook | ||
``` | ||
or | ||
```bash | ||
jupyter lab | ||
``` | ||
|
||
4. **Open the tutorial notebook** | ||
- Navigate to `autovec_unstructured.ipynb` in the Jupyter interface | ||
- Follow the step-by-step instructions in the notebook | ||
``` | ||
|
||
**Note**: This tutorial is designed for educational purposes. For production deployments, ensure proper security configurations and SSL/TLS verification. |
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Looks good for the most part.
|
Large diffs are not rendered by default.
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,18 @@ | ||
--- | ||
# frontmatter | ||
path: "/tutorial-couchbase-autovectorization-langchain" | ||
title: Auto-Vectorization with Couchbase Capella AI Services and LangChain | ||
short_title: Auto-Vectorization with Couchbase and LangChain | ||
description: | ||
- Learn how to use Couchbase Capella's AI Services auto-vectorization feature to automatically convert your data into vector embeddings. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. convert your unstructured data into vector embeddings |
||
- This tutorial demonstrates how to set up automated embedding generation workflows and perform semantic search using LangChain. | ||
content_type: tutorial | ||
filter: sdk | ||
technology: | ||
- vector search | ||
tags: | ||
- LangChain | ||
sdk_language: | ||
- python | ||
length: 20 Mins | ||
--- |
Uh oh!
There was an error while loading. Please reload this page.