feat: search Astra DB with LangFlow #23
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Hi @kndeepa-ibm -- would you please review this doc when you get a chance? Thanks. |
JoefHuang
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| # How to use LangFlow to ingest data into Astra DB to be used as the knowledge source of Agent Knowledge | |||
| This document explains how to use LangFlow to ingest data into Astra DB, to be used as the knowledge source of Agent Knowledge. | |||
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| This document explains how to use LangFlow to ingest data into Astra DB, to be used as the knowledge source of Agent Knowledge. | |
| This document explains how to use LangFlow to ingest data into Astra DB, which can then be used as a knowledge source in Agent Knowledge. |
| 1. Sign up for Astra DB | ||
| * To sign up for Astra DB, see [Sign up for Astra DB](https://astra.datastax.com/) | ||
| 2. Get access to LangFlow | ||
| * To install LangFlow Desktop, see [Install LangFlow Desktop](https://www.langflow.org/desktop) |
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| * To install LangFlow Desktop, see [Install LangFlow Desktop](https://www.langflow.org/desktop) | |
| * To install the desktop version: [Install LangFlow Desktop](https://www.langflow.org/desktop) |
| * To sign up for Astra DB, see [Sign up for Astra DB](https://astra.datastax.com/) | ||
| 2. Get access to LangFlow | ||
| * To install LangFlow Desktop, see [Install LangFlow Desktop](https://www.langflow.org/desktop) | ||
| * To sign up for managed LangFlow, see [Sign up for managed LangFlow](https://astra.datastax.com/langflow) |
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| * To sign up for managed LangFlow, see [Sign up for managed LangFlow](https://astra.datastax.com/langflow) | |
| * To use the managed version: [Sign up for managed LangFlow](https://astra.datastax.com/langflow) |
| * [Add other components](#add-other-components) | ||
| * [Connect the components and run the ingestion](#connect-the-components-and-run-the-ingestion) | ||
| * [Step 3: Connect to Agent Knowledge in watsonx Orchestrate](#step-3-connect-to-agent-knowledge-in-watsonx-orchestrate) | ||
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Step 1: Prepare Astra DB and collect connection information
Prepare Astra DB
Collect connection information
Step 2: Ingest Data into Astra DB using LangFlow
Add the Astra DB component
Add other components
Connect components and run ingestion
Step 3: Connect to Agent Knowledge in watsonx Orchestrate
| This document explains how to use LangFlow to ingest data into Astra DB, to be used as the knowledge source of Agent Knowledge. | ||
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| ## Before you begin | ||
| 1. Sign up for Astra DB |
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Before starting the ingestion process, ensure you have access to both Astra DB and LangFlow. This section provides links to sign up or install the necessary tools.
| * [Connect the components and run the ingestion](#connect-the-components-and-run-the-ingestion) | ||
| * [Step 3: Connect to Agent Knowledge in watsonx Orchestrate](#step-3-connect-to-agent-knowledge-in-watsonx-orchestrate) | ||
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| ## Step 1: Prepare Astra DB and collect the connection information |
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To ingest data into Astra DB, you first need to set up your database and collection, and gather the necessary credentials.
| ## Step 3: Connect to Agent Knowledge in watsonx Orchestrate | ||
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| This option allows you to integrate with your Astra DB service through the Agent Knowledge feature of watsonx Orchestrate. | ||
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After ingestion, you can integrate Astra DB with Agent Knowledge in watsonx Orchestrate. This section points you to the official documentation for completing the connection setup.
| ### Prepare Astra DB | ||
| 1. Login to Astra DB | ||
| 2. Create a new database, or select an existing database | ||
| 3. Go to `Data Explorer` tab > `Collections and Tables` drop down, select `Create collection` |
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Go to the Data Explorer tab > Collections and Tables > Create Collection.
| 1. Login to Astra DB | ||
| 2. Create a new database, or select an existing database | ||
| 3. Go to `Data Explorer` tab > `Collections and Tables` drop down, select `Create collection` | ||
| 4. Enter `Collection name`, toggle on `Vector-enabled collection`, select `Embedding generation method`, `Embedding model`, `Dimension`, `Similarity metric`, click `Create collection` |
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Enter the Collection name, enable Vector-enabled collection, and configure...
| ### Collect the connection information | ||
| #### Token | ||
| 1. Login to Astra DB | ||
| 2. On the upper right of the portal, click `Settings` > `Tokens` |
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- Go to
Settings>Tokenson the top-right corner.
| 1. Login to Astra DB | ||
| 2. On the upper right of the portal, click `Settings` > `Tokens` | ||
| 3. Choose `Role`, `Description`, `Expiration`, and click on `Generate token` | ||
| 4. Take a note of the generated token |
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| 4. Take a note of the generated token | |
| 4. Save the generated token securely. |
| 2. In `Components` > `Vector Stores`, drag and drop `Astra DB` to the canvas | ||
| 3. In the `Astra DB` component, fill in `Astra DB Application Token` | ||
| 4. Select `Database` and `Collection` as used in `Step 1` | ||
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- Launch LangFlow and create a new project.
- Under
Components>Vector Stores, drag and drop theAstra DBcomponent onto the canvas. - Enter your
Astra DB Application Token. - Select the
DatabaseandCollectionfrom Step 1.
| 4. Select `Database` and `Collection` as used in `Step 1` | ||
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| ### Add other components | ||
| 1. In `Components` > `Data`, drag and drop `File` to the canvas, and choose the file(s) to upload |
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| 1. In `Components` > `Data`, drag and drop `File` to the canvas, and choose the file(s) to upload | |
| 1. In `Components` > `Data`, drag and drop `File` component and upload your file. |
| 1. In `Components` > `Data`, drag and drop `File` to the canvas, and choose the file(s) to upload | ||
| 2. In `Components` > `Processing`, drag and drop `Split text` to the canvas, and enter `Chunk Overlap` and `Chunk Size` | ||
| 3. In `Components` > `Outputs`, drag and drop `Chat Output` to the canvas | ||
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In Components > Outputs, add the Chat Output component.
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Search Astra DB with LangFlow