AFFiNE Error: Embedding Feature & Pgvector Fix

Are you experiencing the frustrating "Embedding feature not available, you may need to install pgvector extension to your database" error while using AFFiNE? This issue often pops up when you're trying to leverage the AI chat feature, particularly when uploading PDF files. Don't worry, you're not alone! Many users, including the original poster, have encountered this problem. In this article, we'll dive deep into the issue, explore potential causes, and offer solutions to get your AFFiNE experience back on track. We'll cover everything from verifying your pgvector installation to troubleshooting those pesky "Processing..." hang-ups.

Understanding the 'Embedding Feature Not Available' Error

Firstly, let's clarify what's happening when you see this error. The core issue lies within AFFiNE's ability to create and utilize vector embeddings. Vector embeddings are essentially numerical representations of text or other data, enabling the AI to understand and process information more effectively. The pgvector extension in PostgreSQL provides the necessary functionality to store and query these embeddings. When the extension isn't properly installed or accessible, AFFiNE can't perform these crucial embedding operations, leading to the error message. Essentially, the AI needs the pgvector to function properly, otherwise, it can't understand the content you are feeding it. This can lead to the inability of the AI to retrieve and store new data, causing errors when processing your files.

This problem usually surfaces when you're trying to upload a PDF file. However, this is not the only cause for this issue, sometimes the error might occur due to other reasons like the absence of the extension, incompatibility, or versioning conflicts. The error message is your cue that something's amiss with the pgvector setup.

Furthermore, the "Processing..." hang-up you might encounter when selecting a document in the AI chat is likely related to the same underlying problem. It suggests that AFFiNE is struggling to properly process and index the document's content, potentially because the embeddings aren't being generated or stored correctly in the database. When the processing gets stuck, the AI might still be able to read the document, but that is not an intended behavior, which indicates that there is a problem with how the app interacts with the data, either by accessing it or storing it.

Verifying Your pgvector Installation

One of the most common causes of this error is an incorrect pgvector installation. Let's make sure everything is set up correctly. First, confirm that the pgvector extension is actually installed in your AFFiNE database. You can do this by running a SQL query. If you're self-hosting, access your PostgreSQL database using a tool like psql or pgAdmin. Then, execute the following query:

SELECT * FROM pg_extension WHERE extname = 'vector';

If the query returns a row, pgvector is installed, this doesn't guarantee that the extension is properly configured. If no row is returned, you'll need to install the extension. Connect to your database using psql and execute the CREATE EXTENSION vector; command. If you can see the result, the extension is properly installed. If you are still seeing this error after the installation, then move on to the next steps. Sometimes, the issue is not just the installation, it may also be caused by version compatibility. Make sure that you are using the correct version of AFFiNE, and that the version is compatible with your PostgreSQL and pgvector installations. Updating these components might solve the problem.

Troubleshooting Steps for the Embedding Feature

Check Database User Permissions

Ensure that the database user used by AFFiNE has the necessary permissions to create, read, and write data within the database. Specifically, the user needs permissions to create and manage tables, indexes, and other database objects related to vector embeddings.

Verify Database Connection Details

Double-check that AFFiNE is configured with the correct database connection details. These details include the hostname or IP address, port number, database name, username, and password. Incorrect connection details can prevent AFFiNE from accessing the database and using the pgvector extension.

Inspect AFFiNE Logs

While the original poster noted no errors in the logs, it's always a good idea to thoroughly examine AFFiNE's logs for any clues. Look for any error messages or warnings related to database interactions, pgvector, or embedding operations. These logs can often provide valuable insights into the root cause of the problem. Make sure to check the logs after each troubleshooting step to see if any progress has been made.

Check Self-Hosting Setup

If you're self-hosting AFFiNE, make sure your server environment is properly configured. This includes verifying that PostgreSQL is running and accessible, and that all necessary dependencies are installed.

Consider the App Version

Make sure you're using a supported version of AFFiNE. Check the documentation or release notes for any known issues or compatibility requirements related to pgvector and vector embeddings.

Addressing the