Update default configuration

README.md

@@ -202,7 +202,7 @@ We apply a Retrieval Augment Generation (RAG) pattern, ie,
 
 This ensures that the answers are not only based on general AI knowledge but are also specifically tailored to Julia's ecosystem and best practices.
 
-The "knowledge packs" are sourced from documentation sites and then processed with DocsScraper.jl.
+The "knowledge packs" are sourced from documentation sites and then processed with [DocsScraper.jl](https://github.com/JuliaGenAI/DocsScraper.jl).
 
 > [!NOTE]
 > If you would like to set up an automated process to create a new knowledge pack for some package/organization, let us know!
@@ -235,6 +235,9 @@ A: Tavily's API is used to search the best matching snippets from the documentat
 **Q: Can we use Ollama (locally-hosted) models?**
 A: Yes, see the Advanced section in the docs.
 
+**Q: How can I build knowledge packs for my package(s)?**
+A: Check out package [DocsScraper.jl](https://github.com/JuliaGenAI/DocsScraper.jl). It's what we use to build the knowledge packs loaded in this package!
+
 ## Future Directions
 
 AIHelpMe is continuously evolving. Future updates may include:

src/pipeline_defaults.jl

@@ -156,7 +156,7 @@ function update_pipeline!(
         @warn "Invalid configuration for knowledge packs! For `nomic-embed-text`, `embedding_dimension` must be 0. See the available artifacts."
     end
     if model_embedding == "text-embedding-3-large" &&
-       (embedding_dimension ∉ [1024, 0] || !isnothing(embedding_dimension))
+       !(embedding_dimension in [1024, 0] || isnothing(embedding_dimension))
         @warn "Invalid configuration for knowledge packs! For `text-embedding-3-large`, `embedding_dimension` must be 0 or 1024. See the available artifacts."
     end
 
@@ -184,7 +184,6 @@ function update_pipeline!(
     ## Update GLOBAL variables
     MODEL_CHAT = model_chat
     MODEL_EMBEDDING = model_embedding
-    @info embedding_dimension
     EMBEDDING_DIMENSION = embedding_dimension
 
     ## Set the options