[FEATURE REQUEST] Configurable Embedding for Knowledge Base

[teedonk]

Is your feature request related to a problem? Please describe.
Currently, Knowledge Base only supports OpenAI for embeddings, requiring external API calls. This prevents fully offline/private RAG workflows, despite Sim already supporting local LLMs via Ollama.

Describe the solution you'd like
Add embedding provider selection to Knowledge Base settings (similar to LLM provider selection):
OpenAI (current default)
Ollama (nomic-embed-text, mxbai-embed-large, etc.)

Describe alternatives you've considered
Adding custom function blocks to the workflow: It requires coding
Current OpenAI works but prevents offline/private deployments

Additional context
Follows existing architecture pattern (Ollama/vLLM already supported for LLMs) where users bring their own models (like current Ollama setup)
Enables 100% offline RAG (local LLM + local embeddings)
Privacy-conscious users/enterprises need this for compliance

[waleedlatif1]

@teedonk i explored this, but the dimensions of the embeddings for models on ollama are variable, and we have to set the dimensions when making the table in pgvector so we set it to the text-embedding-3-small default, 1536x1536

[teedonk]

in that case, one embedding table with an untyped vector column while using partial HNSW indexes per dimension; or create separate typed vector tables per dimension (e.g embedding_768, embedding_1024) and route queries from the KB table based on its embeddingDimension value.
Would you be open to a PR implementing one of these options?