Here is a step-by-step guide on how to use RAG Assistants, upload a document, and start chatting with the assistant from the Playground.
First, enter the GeneXus Enterprise AI backoffice. On the left side of the screen, you can find the backoffice menu. In this menu, click
on RAG Assistants.
Next, in the Project Dynamic Combo Box, select the project you want to work with (in this case, the Default one is used).
By default, when opening the RAG Assistants section, a RAG Assistant named Default is displayed.
Create a New RAG Assistant by clicking on the CREATE NEW button.
After you click on the CREATE NEW button, a window will appear to enter a Name and Description:
Use the Based on option if you want to copy the configuration from another RAG Assistant. Notice that Documents are not considered, just configuration.
Next, click on the CONFIRM button.
To add documents, go to the RAG Assistants home page and click on ADD DOCUMENTS.
This will open a window similar to the one below. Click on the Add files button to upload files; check the supported formats here.
In addition, it is possible to add metadata by clicking on New row.
Note: Each file must not exceed 100 MB. In addition, it is possible to upload up to 100 files simultaneously.
The format is a key/value configuration for each row. For example:
Name: 'year'
Value: 2003
Later, during the retrieval process, it is possible to filter according to specific metadata. Possible options are:
Finally, click on START UPLOAD to upload the document.
Finally, you can test your RAG Assistant by clicking on Playground on the left side menu of the Backoffice window:
In the following image, you can see it running:
At the end of the page, the Sources section is displayed. This section includes the document links used to construct the answer:
- A temporary link to the files is provided if no url metadata is set; check here for more detail.
- The link will remain valid for 6 days.
Once the RAG Assistant is created, you return to the main page that provides the UPDATE option. This option allows you to customize the RAG Assistant to your needs.
For more information, see: RAG Assistants section.
This section allows you to configure indexes, which are essential for structuring unstructured documents so that LLMs can optimally interact with them.
To configure Indexes to your needs, go to the RAG Assistants main page and click on INDEX.
If you want to configure the default values taken by Index, click on UPDATE:
To customize the Chunk Size, Chunk Overlap, and Extra Chunks values, take into account that these parameters are critical to tailor LLM processing to your specific needs.
The default settings include the maximum character limit per chunk and the number of overlapping characters between adjacent chunks. Modifying these values allows you to adjust the document partitioning process according to your preferences and application requirements.
Note: Keep in mind that if you make changes to the chunks configuration, you must re-ingest the documents so that GeneXus Enterprise AI takes the new configuration into account. To do so, delete the existing documents and upload a new one.
In addition, you can explore additional partitioning strategies using the Extra Chunks element. This component gives you the flexibility to add additional chunks and test different configurations to determine the most effective partitioning strategy in your specific case.
For example, if you wish to add two additional chunks, you can populate the Extra Chunks parameter as shown below:
[
{
"chunkSize":500,
"chunkOverlap":80
},
{
"chunkSize":3000,
"chunkOverlap":100
}
]
In this case, each document will be chunked three times and ingested separately. Later on, when querying you can change the default namespace by appending the extra chunkSize value.
To save the changes, click on CONFIRM.
To view the documents and the details of each one, go to the RAG Assistants home page and click on VIEW DOCUMENTS.
In the specific case of MyRagAssistant, only one document called IRT is available. Here, you can click on the document name (IRT) to access its details or, if you prefer, delete the document.
By clicking on the document name, in this case IRT, you will find two subsections: General and Metadata
In the General section, you can view the following information:
By clicking on Document Url, you can view/download the document.
By clicking on Chunks, you can view/download the internal document associated to the chunking process.
In the Metadata section, you can view the following information:
Metadata Name: IRT
Metadata Value: 2015
To delete all documents loaded in your RAG, go to the RAG Assistant home page and click on the CLEANUP option.
Clicking CLEANUP starts a process that permanently deletes all files, clears the associated vectorstore namespace and updates the relevant information in the RDS (Relational Database Service).
The CLEANUP process essentially "wipes the slate clean" by removing all traces of your uploaded documents. Use this option with caution, as it cannot be undone.