Vector Stores

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Vector Stores Page Overview

The Vector Stores page allows you to ingest and manage your project’s code and documents into Vector Stores. The ingested data can be utilized in GitHub Vector Store Nodes and Document Vector Store Nodes. Currently, two types of Vector Stores are supported:

• Document Vector Stores: Ingest PDF, TXT, and Markdown files
• GitHub Repositories: Ingest code and Pull Requests from GitHub repositories

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Document Vector Stores

Document Vector Stores allows you to upload PDF, TXT, and Markdown files to ingest into Vector Stores.

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Creating a Document Vector Store

1. Click the New Vector Store button
2. The “Create Vector Store” dialog opens
3. Configure the following items:

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Name

Enter a name for the Vector Store (e.g., “Product Docs”)

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Embedding Models

Select at least one embedding model to use Each model displays:

• Model name
• Provider
• Dimensions

4. Click Create to complete creation

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Managing Document Vector Stores

Created Document Vector Stores are displayed in the “Document Vector Stores” section. Each Vector Store card displays:

• Store name
• Store ID
• Action menu (three-dot icon)

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Action Menu

• Configure Sources: Update name, embedding models, and source files
• Delete: Delete the Document Vector Store

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Uploading and Managing Files

To upload files to a Document Vector Store:

1. Select Configure Sources from the action menu
2. The “Configure Sources” dialog opens

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Name Section

You can update the Vector Store name.

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Embedding Models Section

Select embedding models to use (at least one required)

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Source Files Section

Supported file formats: PDF, TXT, Markdown (.md) Maximum file size: 4.5MB File upload methods:

• Drag and drop to add files
• Click the Select files button to choose files

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Uploaded Files List

Uploaded files are displayed with the following information:

• File name: Truncated if long
• Status badge:
  • Pending (yellow, clock icon): Waiting for ingestion
  • Processing (blue, loading icon): Processing
  • Ready (green, check icon): Ingestion complete
  • Failed (red, alert icon): Ingestion failed
• Delete button: Can delete each file (trash icon)

3. Click Save to save changes

After uploading files, the ingestion process starts automatically.

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Deleting a Document Vector Store

To delete a Document Vector Store:

1. Select Delete from the action menu
2. Confirm in the “Delete Document Vector Store” dialog
3. Execute deletion

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GitHub Repositories

To use GitHub Vector Stores:

1. GitHub Account Authentication: Connect your GitHub account on the account authentication page
2. GitHub App Installation: Install Giselle’s GitHub App from Integrations settings

If these conditions are not met, a guidance message will be displayed on the Vector Stores page.

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Registering a Repository

Steps to register a GitHub repository to Vector Store:

1. Click the Register Repository button
2. The “Register GitHub Repository” dialog opens
3. Configure the following items:

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Owner / Organization

Select from installed GitHub Apps. You can choose a personal account or organization.

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Repository Name

Select from repositories under the selected Owner.

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Sources to Ingest

Select content types to ingest:

• Code: Ingest source code files (required, cannot be disabled)
• Pull Requests: Ingest merged Pull Request content and discussions (optional)

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Embedding Models

Select embedding models to use for indexing. At least one model must be selected. Available models:

• OpenAI (various sizes)
• Google (various sizes)

Each model displays provider name and dimensions.

4. Click Register to complete registration

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Managing Repositories

Registered repositories are displayed in the “GitHub Repositories” section. Each repository card displays:

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Repository Information

• Repository name (owner/repo format, click to go to GitHub)
• Action menu (three-dot icon)

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Action Menu

• Ingest Now: Manually trigger ingestion
• Configure Sources: Modify content types and embedding models
• Delete: Remove repository from Vector Store

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Embedding Model Status

A status card is displayed for each embedding model: Code Section:

• Status badge:
  • Enabled (green): Enabled
  • Running (blue, animated): Ingestion in progress
  • Idle (gray): Idle state
  • Error (red): Error occurred
  • Disabled (gray): Disabled
• Last sync: Last sync time (relative time format)
• Latest ingested commit SHA (first 7 characters)
• Error message and retry time (when failed)

Pull Requests Section:

• Similar status display as Code
• Latest ingested PR number (if ingested)

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Manual Ingestion

You can manually trigger ingestion with the Ingest Now button. Conditions for ingestion:

• Status is “Idle”, “Completed”, or “Failed” (if retry time has passed)
• At least one content type is enabled

During ingestion, the status changes to “Running” and updates to “Completed” or “Error” upon completion.

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Configure Sources

To modify repository settings:

1. Select Configure Sources from the action menu
2. The “Configure Vector Stores” dialog opens

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Sources Section

Select content types to ingest:

• Code: Always enabled (toggle disabled)
• Pull Requests: Optional (toggle to enable/disable)

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Embedding Models Section

Select embedding models to use (at least one required)

3. Click Save Changes to save modifications

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Deleting a Repository

To delete a repository from Vector Store:

1. Select Delete from the action menu
2. Confirm in the “Delete Repository” dialog
3. Execute deletion

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Diagnosing and Restoring Connection

If an error occurs accessing the repository:

1. Click the Check link on the Error status
2. The “Checking Repository Access” modal opens and performs diagnostics
3. Actions are displayed based on diagnostic results:

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If Restorable

• Title: “Connection can be restored”
• Message: “Click Restore Connection to reconnect and continue ingesting data from this repository.”
• Button: Restore Connection - Click to restore connection

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If Not Restorable

• Title: “Repository no longer accessible”
• Custom error message is displayed
• Button: Delete Repository - Delete the repository

Issues detected by diagnostics:

• GitHub App installation cannot access the repository
• Repository not found
• Other diagnostic errors

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Empty State

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Document Vector Stores

When no Document Vector Store is created:

• “No document vector stores yet.”
• ‘Use the “New Vector Store” button to create one.‘

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GitHub Repositories

When no repository is registered:

• “No repositories are registered.”
• ‘Please register a repository using the “Register Repository” button.‘

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Error Messages

The following errors may occur:

• Repository not found.: Repository not found
• Rate limited.: Rate limit reached
• Repository too large.: Repository is too large
• Repository error.: Repository error
• Failed to upload files: File upload failed
• Failed to delete file: File deletion failed

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Leveraging Vector Stores

Ingested data can be utilized in the following Nodes:

• Document Vector Store Node (Private Beta): Search and use uploaded documents
• GitHub Vector Store Node: Search and use code and Pull Requests ingested from GitHub repositories

By using these Nodes, you can integrate your project’s knowledge base into AI workflows.

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Support

If you encounter issues with Vector Stores configuration or have questions, please contact our support team at support@giselles.ai. For more details, please refer to the Vector Stores documentation.