Databricks Community

Hi SaiVihAIDatabricks Vector Search currently does not support creating multi-vector indexes that are directly based on multiple embedding columns in a Delta table. Creating separate vector indexes for each embedding column is an option.Ref  How to c...

Hi SaiVihAIIn my opinion, Databricks utilizes Mosaic Vector Search, which is largely aided by the Hierarchial Navigable Small World (HNSW) algorithm for neighbor search and hybrid keyword similarity search.Ref   Mosaic AI Vector Search | Databricks D...

I think Teams/Slack channel as a chat bot will be more exciting use case. When we demoed the Genie to our executives we are in Retail Industry Client and we have lots of stores one of the thing they said is this would be awesome if this can be in Tea...

Hello @SaiVihAI, Yes, It uses in-query filtering. The algorithm takes a series of iterative steps to determine if the filtered set is small enough to execute brute-force search or if it proceeds with AN

Serving endpoints with external models will require creating Network Connectivity Configuration objects at the account level to connect to the Azure OpenAI resource. The feature is currently in private preview, please reach out to your Databricks acc...

Direct cloning of a vector index table may not be possible. However, if Databricks generates the embeddings, you can enable "Sync computed embeddings" to save them to a Unity Catalog table. Alternatively, you can set the parameter sync_computed_embed...

Hi MariuszK,I can confirm that the RAG architecture on Databricks works very well—we’ve taken it to production and are very satisfied with the results. As a first step, I'll try creating a Genie Room on the system table to see if it can help retrieve...

Hi @aero_g, Looks like it is not supported on your region, but I will get more details internally.

Actually, maybe root folder was imprecise. The point is that it gets file system access. It becomes a regular Workspace user, with too much access. If, however, you want to give it specific accesses beyond that, you could give it access to specific v...

Hello @Nawneet, Ensure that the input format for the agent evaluation matches the expected schema. Here is an example to structure your input data correctly: import mlflow import pandas as pd examples = { "request": [ {"messages": [{"ro...

Wow, Thank you so much for your help.

Hi @dileepkumar_t The UNBOUND_SQL_PARAMETER error in Databricks SQL Agent occurs when a parameter marker in a SQL query is not associated with a value. This error is raised because the SQL query is expecting a parameter to be provided, but it has not...

Hi @Mohanrajv27 The "Automated Serverless compute Pro" category in Databricks is designed to provide a serverless environment where compute resources are automatically managed and scaled by Databricks. Hope this answers your question!