51 lines
No EOL
3 KiB
Text
51 lines
No EOL
3 KiB
Text
import Tabs from '@theme/Tabs';
|
|
import TabItem from '@theme/TabItem';
|
|
|
|
### Application onboarding
|
|
|
|
The first time you start OpenRAG, whether using the TUI or a `.env` file, a `config.yaml` file is generated if OpenRAG detects one doesn't exist.
|
|
The `config.yaml` file controls application configuration, including language model and embedding model provider, Docling ingestion settings, and API keys.
|
|
|
|
Values input during onboarding can be changed later in the OpenRAG **Settings** page, except for the language model and embedding model _provider_. The provider can only be selected during onboarding, and you must use the same provider for your language model and embedding model.
|
|
|
|
1. Select your language model and embedding model provider, and complete the required fields.
|
|
**Your provider can only be selected once, and you must use the same provider for your language model and embedding model.**
|
|
The language model can be changed, but the embeddings model cannot be changed.
|
|
To change your provider selection, you must restart OpenRAG and delete the `config.yml` file.
|
|
|
|
<Tabs groupId="Embedding provider">
|
|
<TabItem value="OpenAI" label="OpenAI" default>
|
|
2. If you already entered a value for `OPENAI_API_KEY` in the TUI in Step 5, enable **Get API key from environment variable**.
|
|
3. Under **Advanced settings**, select your **Embedding Model** and **Language Model**.
|
|
4. To load 2 sample PDFs, enable **Sample dataset**.
|
|
This is recommended, but not required.
|
|
5. Click **Complete**.
|
|
|
|
</TabItem>
|
|
<TabItem value="IBM watsonx.ai" label="IBM watsonx.ai">
|
|
2. Complete the fields for **watsonx.ai API Endpoint**, **IBM API key**, and **IBM Project ID**.
|
|
These values are found in your IBM watsonx deployment.
|
|
3. Under **Advanced settings**, select your **Embedding Model** and **Language Model**.
|
|
4. To load 2 sample PDFs, enable **Sample dataset**.
|
|
This is recommended, but not required.
|
|
5. Click **Complete**.
|
|
|
|
</TabItem>
|
|
<TabItem value="Ollama" label="Ollama">
|
|
:::tip
|
|
Ollama is not included with OpenRAG. To install Ollama, see the [Ollama documentation](https://docs.ollama.com/).
|
|
:::
|
|
2. Enter your Ollama server's base URL address.
|
|
The default Ollama server address is `http://localhost:11434`.
|
|
Since OpenRAG is running in a container, you may need to change `localhost` to access services outside of the container. For example, change `http://localhost:11434` to `http://host.docker.internal:11434` to connect to Ollama.
|
|
OpenRAG automatically sends a test connection to your Ollama server to confirm connectivity.
|
|
3. Select the **Embedding Model** and **Language Model** your Ollama server is running.
|
|
OpenRAG automatically lists the available models from your Ollama server.
|
|
4. To load 2 sample PDFs, enable **Sample dataset**.
|
|
This is recommended, but not required.
|
|
5. Click **Complete**.
|
|
|
|
</TabItem>
|
|
</Tabs>
|
|
|
|
6. Continue with the [Quickstart](/quickstart). |