Hi,

Thank you for using the PGVector integration!

I tested it with Neon DB—even though I didn’t have prior experience with it, it looks really good.

I’m not sure what went wrong in your run. I tried it myself and it worked — you can see my run here.

Could you please try again?
Maybe start with a smaller dataset just to test.

Also, please double-check that your Postgres settings are correct. Unfortunately, it’s hard to debug on my end since I can’t reproduce the issue :(

Thank you, Jiri

Hi,

I just tried it again. No luck.

Failed to connect/get database. Please ensure the following: 1. Database credentials are correct and the database is configure properly. 2. The vector dimension of your embedding model in the Actor input (Embedding settings -> model) matches the one set up in the database. Database error message: Can't load plugin: sqlalchemy.dialects:postgres

My database credentials are correct. Do I need to do anything to configure the database properly? I was assuming that the actor would create the tables needed etc. If not, are there any instructions here? Since I did not create the table, I do not know what the vector dimensions that I need to set are. Can you provide some guidance here.

Thanks

Hi, I’m really sorry to hear that you're running into this issue.

I haven’t encountered the exact same error myself:

| Database error message: Can't load plugin: sqlalchemy.dialects:postgres

However, I found a relevant Stack Overflow post that explains the issue. According to it:

| "SQLAlchemy 1.4 removed the deprecated postgres dialect name. You must now use postgresql instead."

Could it be that your postgresSqlConnectionStr starts with postgres:// instead of postgresql://? For reference, my connection string looks like this: postgresql://neondb_owner:npg_****

Let me know if updating the prefix solves it. Jiri

Hi,

Thanks for getting back.

After a few attempts (using postgresql and removing the config as suggested in your docs from my embeddings config) I finally got it to work but I don't know what embedding is being used by default and i also do not know what the vector dimensions in the table are. I looked at the docs but was unable to figure it out.

Here is the JSON of my config (which worked) I've snipped the sensitive info

{
    "dataUpdatesPrimaryDatasetFields": [
        "url"
    ],
    "dataUpdatesStrategy": "deltaUpdates",
    "datasetFields": [
        "text"
    ],
    "datasetId": "udz1WeiXraNvbrxMq",
    "deleteExpiredObjects": true,
    "deltaUpdatesPrimaryDatasetFields": [
        "url"
    ],
    "embeddingsApiKey": "ENCRYPTED_VALUE:ZjR...snipped",
    "embeddingsProvider": "OpenAI",
    "enableDeltaUpdates": true,
    "performChunking": true,
    "postgresCollectionName": "apify-collection",
    "postgresSqlConnectionStr": "ENCRYPTED_VALUE:U5Oy...snipped",
}

If you could help me understand the following i.e.

• what embedding model is being used by default (I need this so I can get embeddings of the user query using the same model)
• what are the vector dimensions that were used by default in the table created (I need this so I can recreate this table as needed)

Thanks