partial-for-onboarding
This commit is contained in:
Mendon Kissling
parent
ddeeb7e5b6
commit
717b864fec
3 changed files with 59 additions and 40 deletions
51
docs/docs/_partial-onboarding.mdx
Normal file
51
docs/docs/_partial-onboarding.mdx
Normal file
|
|
@ -0,0 +1,51 @@
|
|||
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).
|
||||
|
|
@ -3,6 +3,8 @@ title: Docker deployment
|
|||
slug: /get-started/docker
|
||||
---
|
||||
|
||||
import PartialOnboarding from '@site/docs/_partial-onboarding.mdx';
|
||||
|
||||
There are two different Docker Compose files.
|
||||
They deploy the same applications and containers, but to different environments.
|
||||
|
||||
|
|
@ -34,7 +36,6 @@ To install OpenRAG with Docker Compose:
|
|||
```bash
|
||||
OPENSEARCH_PASSWORD=your_secure_password
|
||||
OPENAI_API_KEY=your_openai_api_key
|
||||
|
||||
LANGFLOW_SUPERUSER=admin
|
||||
LANGFLOW_SUPERUSER_PASSWORD=your_langflow_password
|
||||
LANGFLOW_SECRET_KEY=your_secret_key
|
||||
|
|
@ -75,7 +76,9 @@ To install OpenRAG with Docker Compose:
|
|||
- **Backend API**: http://localhost:8000
|
||||
- **Langflow**: http://localhost:7860
|
||||
|
||||
Continue with the [Quickstart](/quickstart).
|
||||
6. To use the OpenRAG application and continue with application onboarding, access the frontend at `http://localhost:3000`.
|
||||
|
||||
<PartialOnboarding />
|
||||
|
||||
## Rebuild all Docker containers
|
||||
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ slug: /install
|
|||
|
||||
import Tabs from '@theme/Tabs';
|
||||
import TabItem from '@theme/TabItem';
|
||||
import PartialOnboarding from '@site/docs/_partial-onboarding.mdx';
|
||||
|
||||
OpenRAG can be installed in multiple ways:
|
||||
|
||||
|
|
@ -79,46 +80,10 @@ For more information on virtual environments, see [uv](https://docs.astral.sh/uv
|
|||
Command completed successfully
|
||||
```
|
||||
|
||||
7. To open the OpenRAG application, click **Open App**, press <kbd>6</kbd>, or navigate to `http://localhost:3000`.
|
||||
7. To open the OpenRAG application and continue with application onboarding, click **Open App**, press <kbd>6</kbd>, or navigate to `http://localhost:3000`.
|
||||
The application opens.
|
||||
8. 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>
|
||||
9. If you already entered a value for `OPENAI_API_KEY` in the TUI in Step 5, enable **Get API key from environment variable**.
|
||||
10. Under **Advanced settings**, select your **Embedding Model** and **Language Model**.
|
||||
11. To load 2 sample PDFs, enable **Sample dataset**.
|
||||
This is recommended, but not required.
|
||||
12. Click **Complete**.
|
||||
|
||||
</TabItem>
|
||||
<TabItem value="IBM watsonx.ai" label="IBM watsonx.ai">
|
||||
9. Complete the fields for **watsonx.ai API Endpoint**, **IBM API key**, and **IBM Project ID**.
|
||||
These values are found in your IBM watsonx deployment.
|
||||
10. Under **Advanced settings**, select your **Embedding Model** and **Language Model**.
|
||||
11. To load 2 sample PDFs, enable **Sample dataset**.
|
||||
This is recommended, but not required.
|
||||
12. Click **Complete**.
|
||||
|
||||
</TabItem>
|
||||
<TabItem value="Ollama" label="Ollama">
|
||||
9. 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.
|
||||
10. Select the **Embedding Model** and **Language Model** your Ollama server is running.
|
||||
OpenRAG automatically lists the available models from your Ollama server.
|
||||
11. To load 2 sample PDFs, enable **Sample dataset**.
|
||||
This is recommended, but not required.
|
||||
12. Click **Complete**.
|
||||
|
||||
</TabItem>
|
||||
</Tabs>
|
||||
|
||||
13. Continue with the [Quickstart](/quickstart).
|
||||
<PartialOnboarding />
|
||||
|
||||
### Advanced Setup {#advanced-setup}
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue