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FAQ & Troubleshooting
1. I have added files to the EKG but cannot see it in the Agent building journey?
In order for an Enterprise Knowledge Garden (EKG) to be available and visible within the Agent building journey, it must be explicitly published.
After uploading files and completing your configurations (chunking, embedding, metadata, etc.), you must click the “Publish” button in the EKG interface. Only published EKGs are accessible to agents such as RAG or ReAct for knowledge grounding.
Draft or unpublished EKGs are considered incomplete and will not appear in the agent Knowledge configuration.
2. Some files in my EKG are still in processing (chunking/embedding), while others are ready for retrieval. What happens if I publish the EKG now?
If you publish the EKG while some files are still being processed:
- Only the files that are ready will be immediately available to RAG agents.
- The remaining files will continue processing in the background.
- Once these files are marked as "Ready for retrieval", they will be automatically included in the EKG used by agents, no need to republish.
The system dynamically updates the EKG context for RAG agents as new chunks become ready, ensuring real-time knowledge expansion without manual intervention.
3. What happens if I change the chunking strategy or embedding configuration after files are marked as "Ready for retrieval"?
If you modify the chunking strategy or embedding configuration after files have already been processed:
- The system will automatically delete the previously generated chunks and embeddings.
- The affected files will be reprocessed using the updated configuration.
- To ensure the updated content is available to RAG agents, you will need to republish the EKG if it was already published earlier.
Important: Configuration changes trigger a full reprocessing cycle of files. Plan changes carefully to avoid costs.
4. Can I update a Knowledge Garden after publishing?
Yes. You can import new files, reprocess content or reconfigure settings. However, remember to republish after changes for them to take effect.
5. Can I remove a file or chunk from a published EKG?
Yes. Files or individual chunks can be deleted or excluded. Remember to republish the EKG after changes.
6. If I change the visibility of an EKG from Public to Private, will the RAG agent using it continue to work?
Yes, the RAG agent will continue to function even if the EKG's visibility is changed from Public to Private. Changing the visibility does not retroactively remove access for agents that have already been configured to use the EKG. To revoke access: If you want to prevent a RAG agent from using a specific EKG, you must first remove the EKG from the agent configuration. Only then should you change the EKG visibility to Private to fully restrict future access.
7. My file is not uploading. What could be wrong?
Check the following:
- File format is supported : PDF, DOC, DOCX, PNG, JPEG, TIFF, JPG.
- File size is under 20MB and Image size is under 5MB
- File is not encrypted, zipped, or password protected
8. I uploaded a 20 MB file, but it’s not uploading. What could be the issue?
While your file may appear to be 20 MB on your local system, its actual size might be slightly more, for example, 20.1 MB which exceeds the upload limit.
Operating systems often round file sizes for display, so what shows as 20 MB might in reality exceed the system’s maximum allowed limit of 20.0 MB.
Tip: To avoid this issue, ensure your file is well below the 20 MB limit, ideally around 19.5 MB or less.
9. Chunks are not showing after upload. Why?
Ensure:
- Chunking and embedding configuration was properly set
- File status is “Ready for retrieval"
- Refresh the Chunk Editor tab
10. Retrieval results are not relevant. How can I improve accuracy
Try the following:
- Add or refine metadata/tags
- Use a more specific chunking strategy
- Enable the Reranker model
- Increase Top K for broader chunk selection
11. Why is my EKG not appearing in the Agent configuration?
An EKG may not be appearing in your Agent configuration if it has not been published and made accessible within your workspace.To resolve this issue, you should take the following steps:
- Verify the status of your EKG: Check to see if the EKG is currently in a "draft" or "unpublished" state.
- Publish the EKG: If it is not already published, follow the necessary steps within your specific platform to publish it. This action will make it officially available within your workspace.
- Confirm accessibility: After publishing, ensure that the EKG is accessible from the agent builder. This may involve checking permissions or visibility settings within your workspace.
12. Why is my RAG agent still missing chunks after I upload files?
The RAG agent is missing chunks because not all of your uploaded files have been fully processed yet.
For a RAG agent to access the information within your files, they must first be processed and indexed for retrieval. Only files that have completed this process and are marked as "Ready" will be available to the agent.
Any files still undergoing this procedure will be added to the agent's knowledge base automatically once their processing is complete.
13. How can I query relational databases using natural language (NL2SQL)?
The platform enables Natural Language to SQL (NL2SQL) functionality by connecting agents to relational databases via specialized connectors/tools. This process is orchestrated by the agent:
- The agent receives the natural language query from the user (e.g., a non-technical subject matter expert)
- It automatically translates the natural language into a valid SQL query from the system instructions (or a similar database query)
- It executes the query against the database
- It returns the final answer back to the user in natural language
14. What tools are available to refine and optimize RAG (Retrieval-Augmented Generation) performance?
The platform offers multiple avenues for RAG refinement:
EKG Features: Create an effective knowledge base using appropriate metadata, utilize different chunking methodologies, and select specialized embedding models. You can also test retrieval quality before agents use the knowledge base.
Agentic RAG (EDE) Features: Advanced controls include self-query and multi-query augmentation, setting specific top N and top K values for retrieval, and selecting reranker models to further improve the final output.
15. Where can I find an inventory of all active Enterprise Knowledge Gardens (EKGs)?
The Enterprise Knowledge Garden module provides a transparent inventory of all Knowledge Bases. This allows users to view and manage the data sources being utilized by agents, which is crucial for tracking data lineage and ensuring content governance.
16. How does the platform support faceted search capabilities?
Faceted search is enabled through metadata-driven advanced RAG. The EKG enriches all ingested data with structured metadata and categories, allowing users or agents to filter and refine search results dynamically. By utilizing agentic RAG and self-query techniques, searches can apply these facets to deliver highly precise, context-aware responses, moving beyond simple keyword matching.
17. Can the platform search across multiple, diverse data sources simultaneously?
Yes, Federated Search allows the platform to search across diverse data sources simultaneously without centralizing the data. This capability works with multiple vector databases, as well as structured data sources like databases and enterprise applications, all within a single multi-agent use-case, enabling a unified search experience.
18. Can the platform support metadata-driven search capabilities across data sources?
Yes, the platform facilitates metadata-driven and faceted search across diverse data sources through an advanced RAG. The EKG enriches all ingested data with structured metadata and categories, allowing users or agents to filter and refine search results dynamically. By utilizing agentic RAG and self-query techniques, searches can apply these facets to deliver highly precise, context-aware responses, moving beyond simple keyword matching.
19. Can the platform search across multiple, diverse data sources simultaneously?
Yes, the platform supports federated search that allows searching across diverse data sources simultaneously without centralizing the data. This capability works with multiple vector databases, as well as structured data sources like databases and enterprise applications, all within a single multi-agent use-case, enabling a unified search experience.