diff --git a/docs/docs/get-started/install.mdx b/docs/docs/get-started/install.mdx index f2315a0c..03706199 100644 --- a/docs/docs/get-started/install.mdx +++ b/docs/docs/get-started/install.mdx @@ -17,7 +17,7 @@ If you prefer running Docker commands and manually editing `.env` files, see [De - [uv](https://docs.astral.sh/uv/getting-started/installation/) - [Docker](https://docs.docker.com/get-docker/) or [Podman](https://podman.io/docs/installation) installed - [Docker Compose](https://docs.docker.com/compose/install/) installed. If using Podman, use [podman-compose](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or alias Docker compose commands to Podman commands. -- [OpenAI API key](https://platform.openai.com/api-keys) +- Create an [OpenAI API key](https://platform.openai.com/api-keys) - Optional: GPU support requires an NVIDIA GPU with CUDA support and compatible NVIDIA drivers installed on the OpenRAG host machine. If you don't have GPU capabilities, OpenRAG provides an alternate CPU-only deployment. ## Install Python wheel {#install-python-wheel} diff --git a/docs/docs/get-started/quickstart.mdx b/docs/docs/get-started/quickstart.mdx index b071529b..c2f4b3a5 100644 --- a/docs/docs/get-started/quickstart.mdx +++ b/docs/docs/get-started/quickstart.mdx @@ -12,40 +12,6 @@ Get started with OpenRAG by loading your knowledge, swapping out your language m ## Prerequisites - [Install and start OpenRAG](/install) -- Create a [Langflow API key](https://docs.langflow.org/api-keys-and-authentication) -
- Create a Langflow API key - - A Langflow API key is a user-specific token you can use with Langflow. - It is **only** used for sending requests to the Langflow server. - It does **not** access to OpenRAG. - - To create a Langflow API key, do the following: - - 1. In Langflow, click your user icon, and then select **Settings**. - 2. Click **Langflow API Keys**, and then click
## Find your way around @@ -96,12 +62,44 @@ You can more quickly access the **Language Model** and **Agent Instructions** fi ## Integrate OpenRAG into your application To integrate OpenRAG into your application, use the [Langflow API](https://docs.langflow.org/api-reference-api-examples). -Make requests with Python, TypeScript, or any HTTP client to run one of OpenRAG's default flows and get a response, and then modify the flow further to improve results. +Make requests with Python, TypeScript, or any HTTP client to run one of OpenRAG's default flows and get a response, and then modify the flow further to improve results. Langflow provides code snippets to help you get started. -Langflow provides code snippets to help you get started with the Langflow API. - -1. To navigate to the OpenRAG OpenSearch Agent flow, click