Improve search quality by adjusting how your knowledge base processes and indexes documents
Search results not quite right? The Settings panel lets you adjust how documents are processed and indexed so you can improve search quality over time. Click the Settings button in the top-right area of the knowledge base detail page.You’ll see the same settings from creation, with one key difference: permanent settings are now read-only.
These were locked at creation time.Embedding modelShows the model selected during creation. This can’t be changed because all your data was embedded with this model — switching would require re-processing everything from scratch.Advanced document analysis (beta)Enable or disable enhanced document analysis for newly added documents. When on, the AI generates summaries that improve metadata extraction and search relevance.Hybrid searchTurn this on when your users search for specific terms (product names, policy numbers, error codes) alongside conceptual questions — it combines keyword and semantic matching so both types of queries return accurate results.
These settings apply to all new documents going forward. Already-indexed documents keep their original settings — to update those, use the per-document Configure Item Indexing option.Chunk sizeControl how much content goes into each searchable piece. Smaller chunks (200–300) give more precise, focused answers; larger chunks (500–800) provide more surrounding context for complex questions.Chunk overlapReduce information loss at chunk boundaries by letting consecutive chunks share some content. Increase this if search results seem to miss context that spans two chunks. Must be less than the chunk size.Splitter methodChoose how documents are divided into chunks — pick the method that matches your content:
Method
Best for
Sentence
Unstructured text like emails, transcripts, or plain-text docs
Markdown
Documents with clear heading structure
Dynamic
Mixed or varied formats — adapts automatically
Code files are automatically split along meaningful boundaries (functions, classes) regardless of the method you choose here.
Processing modelChoose the model that handles your document types best:
Model
Best for
Default
General purpose text extraction
Llama Parse
Structured documents with complex layouts
Textract
Forms and tables (AWS-powered)
Docling
Layout-aware document understanding
Mistral OCR
Scanned documents and images with text
Contextual AI
Context-aware document processing
Unstructured
Flexible extraction for a wide range of unstructured document types
Apify keyEnter or update your Apify API key for URL scraping. Optional — leave blank to use VectorShift’s built-in scraping.Click Close to save and close the settings panel.
Search results not relevant enough? Start by adjusting chunk size and splitter method. For fact-based queries (“What’s our return policy?”), try smaller chunks (200–300). For context-heavy questions (“Summarize the findings”), try larger chunks (500–800).
Changes to default settings only apply to newly added documents. To update existing documents, reindex them individually from the document list.
