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quickstart

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Mendon Kissling 2025-10-28 17:08:12 -04:00
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docs/docs/_partial-onboarding.mdx
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@ -3,7 +3,9 @@ import TabItem from '@theme/TabItem';
## Application onboarding
The first time you start OpenRAG, whether using the TUI or a `.env` file, you must complete application onboarding.
The first time you start OpenRAG, whether using the TUI or a `.env` file, it's recommended that you complete application onboarding.
To skip onboarding, click **Skip onboarding**.
Values from onboarding can be changed later in the OpenRAG **Settings** page.

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docs/docs/get-started/quickstart.mdx
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@ -7,7 +7,7 @@ import Icon from "@site/src/components/icon/icon";
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the OpenRAG API.
Get started with OpenRAG by loading your knowledge, swapping out your language model, and then chatting with the Langflow API.
## Prerequisites
@ -17,20 +17,20 @@ Get started with OpenRAG by loading your knowledge, swapping out your language m
1. In OpenRAG, click <Icon name="MessageSquare" aria-hidden="true"/> **Chat**.
The chat is powered by the OpenRAG OpenSearch Agent.
For more information, see [Langflow Agents](/agents).
For more information, see [Langflow in OpenRAG](/agents).
2. Ask `What documents are available to you?`
The agent responds with a message summarizing the documents that OpenRAG loads by default.
Knowledge is stored in OpenSearch.
For more information, see [Knowledge](/knowledge).
For more information, see [OpenSearch in OpenRAG](/knowledge).
3. To confirm the agent is correct about the default knowledge, click <Icon name="Library" aria-hidden="true"/> **Knowledge**.
The **Knowledge** page lists the documents OpenRAG has ingested into the OpenSearch vector database.
Click on a document to display the chunks derived from splitting the default documents into the vector database.
4. To add documents to your knowledge base, click <Icon name="Plus" aria-hidden="true"/> **Add Knowledge**.
* Select **Add File** to add a single file from your local machine.
* Select **Process Folder** to process an entire folder of documents from your local machine.
Click on a document to display the chunks derived from splitting the default documents into the OpenSearch vector database.
4. To add documents to your knowledge base, click **Add Knowledge**.
* Select <Icon name="File" aria-hidden="true"/> **File** to add a single file from your local machine.
* Select <Icon name="Folder" aria-hidden="true"/> **Folder** to process an entire folder of documents from your local machine. The default directory is `/documents` in your OpenRAG directory.
* Select your cloud storage provider to add knowledge from an OAuth-connected storage provider. For more information, see [OAuth ingestion](/knowledge#oauth-ingestion).
5. Return to the Chat window and ask a question about your loaded data.
For example, with a manual about a PC tablet loaded, ask `How do I connect this device to WiFI?`
For example, with a manual about a PC tablet loaded, ask `How do I connect this device to WiFi?`
The agent responds with a message indicating it now has your knowledge as context for answering questions.
6. Click <Icon name="Gear" aria-hidden="true"/> **Function Call: search_documents (tool_call)**.
This log describes how the agent uses tools.
@ -44,8 +44,12 @@ In this example, you'll try a different LLM to demonstrate how the Agent's respo
1. To edit the Agent's behavior, click **Edit in Langflow**.
You can more quickly access the **Language Model** and **Agent Instructions** fields in this page, but for illustration purposes, navigate to the Langflow visual builder.
To revert the flow to its initial state, click **Restore flow**.
2. OpenRAG warns you that you're entering Langflow. Click **Proceed**.
The OpenRAG OpenSearch Agent flow appears in a new browser window.
If Langflow requests login information, enter the `LANGFLOW_SUPERUSER` and `LANGFLOW_SUPERUSER_PASSWORD` from the `.env` file in your OpenRAG directory.
The OpenRAG OpenSearch Agent flow appears in a new browser window.
![OpenRAG Open Search Agent Flow](/img/opensearch-agent-flow.png)
3. Find the **Language Model** component, and then change the **Model Name** field to a different OpenAI model.