diff --git a/404.html b/404.html index aeb47b2f..76608875 100644 --- a/404.html +++ b/404.html @@ -4,7 +4,7 @@
To start the Docling service, under Native Services, click Start.
To open the OpenRAG application, click Open App.
+To open the OpenRAG application, navigate to the TUI main menu, and then click Open App.
+Alternatively, in your browser, navigate to localhost:3000.
Continue with Application Onboarding.
@@ -168,7 +169,8 @@ When startup is complete, the TUI displays the following:To start the Docling service, under Native Services, click Start.
To open the OpenRAG application, click Open App. +
To open the OpenRAG application, navigate to the TUI main menu, and then click Open App.
+Alternatively, in your browser, navigate to localhost:3000.
You are presented with your provider's OAuth sign-in screen.
After sign-in, you are redirected to the redirect URI.
Two additional variables are available for Advanced Setup:
diff --git a/knowledge/index.html b/knowledge/index.html index 0b7563af..96987c90 100644 --- a/knowledge/index.html +++ b/knowledge/index.html @@ -4,7 +4,7 @@If ingestion fails, click Status to view the logged error.
+When you upload files, process folders, or sync documents, OpenRAG processes them as background tasks. +A badge appears on the Tasks icon when there are active tasks running. +To open the Tasks menu, click Tasks.
+Active Tasks shows tasks that are currently processing. +A Pending task is queued and waiting to start, a Running task is actively processing files, and a Processing task is performing ingestion operations. For each active task, you can find the task ID, start time, duration, the number of files processed so far, and the total files.
+You can cancel active tasks by clicking Cancel. Canceling a task stops processing immediately and marks the task as failed.
The Knowledge page lists the documents OpenRAG has ingested into the OpenSearch vector database's documents index.
To explore your current knowledge, click Knowledge. @@ -114,7 +122,7 @@ A new filter is created with default settings that match all documents.
You can use custom embedding models by specifying them in your configuration.
If you use an unknown embedding model, OpenRAG will automatically fall back to 1536 dimensions and log a warning. The system will continue to work, but search quality may be affected if the actual model dimensions differ from 1536.
The default embedding dimension is 1536 and the default model is text-embedding-3-small.
For models with known vector dimensions, see settings.py in the OpenRAG repository.