Best practices

This section includes information on how to use Context Grounding effectively.

Getting started

To start using Context Grounding, follow these steps:

1. Make sure you use Studio Web or Studio Desktop version 2024.4 or newer.
2. In Automation Cloud^TM, in Integration Service, establish a connection to the UiPath GenAI Activities connector.

   This allows you to use the GenAI Activities in Studio.

3. To create and manage indexes, access the Context Grounding tab in Automation Cloud™ > Admin > AI Trust Layer. You can then query indexes from Autopilot for everyone or from the GenAI Activities.

Context Grounding in UiPath GenAI Activities

To use Context Grounding you need a dataset (e.g., a group of documents) readily available. Then, Context Grounding can interact with your data in three phases:

1. Establish your data source for Context Grounding.
   • Context Grounding follows shared folder permissions. Use a folder with appropriate access to manage and query from data.
   • Create a connection to the supported Integration Service data sources or add data to a shared Orchestrator bucket location.
2. Ingest data from your data source into Context Grounding.
   • Use the Context Grounding tab in the AI Trust Layer admin to create, sync, and delete indexes.
   • Use the Update Context Grounding Index activity to sync an index you have created. This allows non-admins to help manage the data freshness of an index based on new data.
3. Query and ground prompts with your data.
   • Use the Content Generation activity or Autopilot for everyone to query over documents and use information to augment or ground prompts.

Managing the ingestion pipeline

You can manage the ingestion pipelines in two ways:

• Through the Context Grounding tab in AI Trust Layer. See Governing contextual data for GenAI features.
• Through the Update Context Grounding Index activity, part of the UiPath GenAI activities package.

Querying data with Context Grounding

The Content Generation activity features two options for working with documents: File resource and Existing index.

File resource

The File resource option allows you to use file variables from previous activities (like a document downloaded from Google Drive) and have Context Grounding perform a just-in-time (JIT) style of RAG. This means it ingests the document into an index, searches across it, augments the prompt, and then deletes the index, so the data is not persistent.

Note:

• Keep these documents smaller (under 50 pages). Integration Service activities have a timeout window in which all of the processing above must take place.
• If you have a PDF with scanned images, we recommend using the Document Understanding OCR option in the Extract Data activity after you have downloaded a file to extract the text from these images (as Context Grounding does not yet support images). Pass that extracted_data output into the prompt with that File Resource pointing at your downloaded file.

Existing index

The Existing index option allows you to use an index you have previously created through AI Trust Layer. You query across a persistent index into which you've ingested documents from your data source. You can re-use this index as many times as you like until you delete it.

Use the Log Message activity after Content Generation in the workflow sequence to gather detailed information:

• Input the Top Generated Text or Citations string output variables from Content Generation to see the LLM generation response after the workflow execution.
• Input the Citations string variable to see the semantic search results used to influence the generation output. This works only for PDF and JSON data types.