openrag/docs/docs/_partial-onboarding.mdx
2025-12-16 16:24:20 -08:00

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import PartialOllamaModels from '@site/docs/_partial-ollama-models.mdx';
## Complete the application onboarding process {#application-onboarding}
The first time you start the OpenRAG application, you must complete the application onboarding process to select language and embedding models that are essential for OpenRAG features like the [**Chat**](/chat).
Some of these variables, such as the embedding models, can be changed seamlessly after onboarding.
Others are immutable and require you to destroy and recreate the OpenRAG containers.
For more information, see the [OpenRAG environment variables reference](/reference/configuration).
You can use different providers for your language model and embedding model, such as Anthropic for the language model and OpenAI for the embedding model.
Additionally, you can set multiple embedding models.
You only need to complete onboarding for your preferred providers.
<Tabs groupId="Provider">
<TabItem value="Anthropic" label="Anthropic" default>
:::info
Anthropic doesn't provide embedding models. If you select Anthropic for your language model, you must select a different provider for the embedding model.
:::
1. Enter your Anthropic API key, or enable **Get API key from environment variable** to pull the key from your [OpenRAG `.env` file](/reference/configuration).
If you set `ANTHROPIC_API_KEY` in your OpenRAG `.env` file, this value can be populated automatically.
2. Under **Advanced settings**, select the language model that you want to use.
3. Click **Complete**.
4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
For information about another provider's credentials and settings, see the instructions for that provider.
5. Click **Complete**.
After you configure the embedding model, OpenRAG uses your credentials and models to ingest some [initial documents](/knowledge#default-documents). This tests the connection, and it allows you to ask OpenRAG about itself in the [**Chat**](/chat).
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
Verify that the credential is valid and has access to the selected model, and then click **Complete** to retry ingestion.
6. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
</TabItem>
<TabItem value="IBM watsonx.ai" label="IBM watsonx.ai">
1. Use the values from your IBM watsonx deployment for the **watsonx.ai API Endpoint**, **IBM Project ID**, and **IBM API key** fields.
If you set `WATSONX_API_KEY`, `WATSONX_API_URL`, or `WATSONX_PROJECT_ID` in your [OpenRAG `.env` file](/reference/configuration), these values can be populated automatically.
2. Under **Advanced settings**, select the language model that you want to use.
3. Click **Complete**.
4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
For information about another provider's credentials and settings, see the instructions for that provider.
5. Click **Complete**.
After you configure the embedding model, OpenRAG uses your credentials and models to ingest some [initial documents](/knowledge#default-documents). This tests the connection, and it allows you to ask OpenRAG about itself in the [**Chat**](/chat).
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
Verify that the credentials are valid and have access to the selected model, and then click **Complete** to retry ingestion.
6. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
</TabItem>
<TabItem value="Ollama" label="Ollama">
Using Ollama as your language and embedding model provider offers greater flexibility and configuration options for hosting models.
However, it requires additional setup because Ollama isn't included with OpenRAG.
You must deploy Ollama separately if you want to use Ollama as a model provider.
:::info
<PartialOllamaModels />
:::
1. [Install Ollama locally or on a remote server](https://docs.ollama.com/), or [run models in Ollama Cloud](https://docs.ollama.com/cloud).
If you are running a remote server, it must be accessible from your OpenRAG deployment.
2. In OpenRAG onboarding, connect to your Ollama server:
* **Local Ollama server**: Enter your Ollama server's base URL and port. The default Ollama server address is `http://localhost:11434`.
* **Ollama Cloud**: Because Ollama Cloud models run at the same address as a local Ollama server and automatically offload to Ollama's cloud service, you can use the same base URL and port as you would for a local Ollama server. The default address is `http://localhost:11434`.
* **Remote server**: Enter your remote Ollama server's base URL and port, such as `http://your-remote-server:11434`.
If the connection succeeds, OpenRAG populates the model lists with the server's available models.
3. Select the model that your Ollama server is running.
Language model and embedding model selections are independent.
You can use the same or different servers for each model.
To use different providers for each model, you must configure both providers, and select the relevant model for each provider.
4. Click **Complete**.
After you configure the embedding model, OpenRAG uses the address and models to ingest some [initial documents](/knowledge#default-documents). This tests the connection, and it allows you to ask OpenRAG about itself in the [**Chat**](/chat).
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
Verify that the server address is valid, and that the selected model is running on the server.
Then, click **Complete** to retry ingestion.
5. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
</TabItem>
<TabItem value="OpenAI" label="OpenAI (default)">
1. Enter your OpenAI API key, or enable **Get API key from environment variable** to pull the key from your [OpenRAG `.env` file](/reference/configuration).
If you set `OPENAI_API_KEY` in your OpenRAG `.env` file, this value can be populated automatically.
2. Under **Advanced settings**, select the language model that you want to use.
3. Click **Complete**.
4. Select a provider for embeddings, provide the required information, and then select the embedding model you want to use.
For information about another provider's credentials and settings, see the instructions for that provider.
5. Click **Complete**.
After you configure the embedding model, OpenRAG uses your credentials and models to ingest some [initial documents](/knowledge#default-documents). This tests the connection, and it allows you to ask OpenRAG about itself in the [**Chat**](/chat).
If there is a problem with the model configuration, an error occurs and you are redirected back to the application onboarding screen.
Verify that the credential is valid and has access to the selected model, and then click **Complete** to retry ingestion.
6. Continue through the overview slides for a brief introduction to OpenRAG, or click <Icon name="ArrowRight" aria-hidden="true"/> **Skip overview**.
The overview demonstrates some basic functionality that is covered in the [quickstart](/quickstart#chat-with-documents) and in other parts of the OpenRAG documentation.
</TabItem>
</Tabs>