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86 changes: 59 additions & 27 deletions site/content/3.12/data-science/graphrag/web-interface.md
Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,7 @@ title: How to use GraphRAG in the ArangoDB Platform web interface
menuTitle: Web Interface
weight: 5
description: >-
Learn how to create, configure, and run a full GraphRAG workflow in four steps
using the Platform web interface
Learn how to create, configure, and run a full GraphRAG workflow in just a few steps using the Platform web interface
---
{{< tag "ArangoDB Platform" >}}

Expand All @@ -19,9 +18,10 @@ the ArangoDB team.
The entire process is organized into sequential steps within a **Project**:

1. Creating the importer service
2. Uploading your file and exploring the generated Knowledge Graph
3. Creating the retriever service
4. Chatting with your Knowledge Graph
2. Adding data sources
3. Exploring the generated Knowledge Graph
4. Creating the retriever service
5. Chatting with your Knowledge Graph

## Create a GraphRAG project

Expand All @@ -35,12 +35,22 @@ To create a new GraphRAG project using the ArangoDB Platform web interface, foll
a description for your project.
5. Click the **Create project** button to finalize the creation.

## Project Settings

The **Project Settings** dialog allows you to configure and manage your
Importer and Retriever services.

You can open the **Project Settings** dialog in two ways:
- In the **Data Sources** section, click **Add data source** and then click on
the **Open project settings** button.
- In the **Graph** section, click on the gear icon.

## Configure the Importer service

Configure a service to import, parse, and retrieve all the needed data from a
Configure a service to import, parse, and extract all the needed data from a
file. This service uses the LLM API provider and model of your choice.

After clicking on a project name, you are taken to a screen where you can
After opening the **Project Settings**, you are taken to a dialog where you can
configure and start a new importer service job. Follow the steps below.

{{< tabs "importer-service" >}}
Expand All @@ -52,20 +62,20 @@ configure and start a new importer service job. Follow the steps below.
3. Enter your **OpenAI API Key**.
4. Click the **Start importer service** button.

![Configure Importer service using OpenAI](../../../images/graphrag-ui-configure-importer-openai.png)
![Configure Importer service using OpenAI](../../../images/graphrag-ui-configure-importer-openai.png)
{{< /tab >}}

{{< tab "OpenRouter" >}}
1. Select **OpenRouter** from the **LLM API Provider** dropdown menu.
2. Select the model you want to use from the **Model** dropdown menu. By default,
the service is using **Mistral AI - Mistral Nemo**.
1. Enter your **OpenAI API Key**.
2. Enter your **OpenRouter API Key**.
3. Click the **Start importer service** button.
the service uses **Mistral AI - Mistral Nemo**.
3. Enter your **OpenAI API Key**.
4. Enter your **OpenRouter API Key**.
5. Click the **Start importer service** button.

{{< info >}}
When using the OpenRouter option, the LLM responses are served via OpenRouter
while OpenAI is used for the embedding model.
When using OpenRouter, you need both API keys because the LLM responses are served
via OpenRouter while OpenAI is used for the embedding model.
{{< /info >}}

![Configure Importer service using OpenRouter](../../../images/graphrag-ui-configure-importer-openrouter.png)
Expand All @@ -88,31 +98,53 @@ service automatically downloads and loads models from the MLflow registry.

See also the [GraphRAG Importer](services/importer.md) service documentation.

## Upload your file
## Add data source

To add your first data source:

1. Upload a file by dragging and dropping it in the designated upload area.
The importer service you previously launched parses and creates the
Knowledge Graph automatically.
2. Enter a file name.
3. Click the **Start import** button.
1. In the **Data Sources** section, click the **Add data source** button.
2. Upload a file by dragging and dropping it in the designated upload area.
The importer service you previously configured will automatically parse the file
and create the Knowledge Graph.
3. Enter a descriptive name for your file.
4. Click the **Start import** button.

{{< info >}}
You can only import a single file, either in `.md` or `.txt` format.
Currently, you can import one file at a time in either Markdown (`.md`) or
plain text (`.txt`) format. Additional files can be added to update the Knowledge Graph.
{{< /info >}}

![Upload file in GraphRAG web interface](../../../images/graphrag-ui-upload-file.png)

## Explore the Knowledge Graph

You can open and explore the Knowledge Graph that has been generated by clicking
on the **Explore in visualizer** button.
After your file is processed, you can view and explore the generated Knowledge Graph
in the **Graph** section.

![Explore Knowledge Graph in GraphRAG web interface](../../../images/graphrag-ui-explore-knowledge-graph.png)

For a more detailed exploration, click the **Explore** button to open the Knowledge Graph in the dedicated Graph Visualizer.

For more information, see the [Graph Visualizer](../../graphs/graph-visualizer.md) documentation.

## Update the Knowledge Graph

Once you have created your initial Knowledge Graph, you can update it by uploading
additional files using the same process described in the [Add data source](#add-data-source) section.
The importer service will automatically update the existing Knowledge Graph and
underlying collections with the new data.

To update your Knowledge Graph:

1. In the **Data Sources** section, click the **Add data source** button again.
2. Upload a new file by dragging and dropping it in the designated upload area.
3. The importer service will process the new file and update the existing Knowledge Graph along with the underlying collections.

## Configure the Retriever service

Creating the retriever service allows you to extract information from
the generated Knowledge Graph. Follow the steps below to configure the service.
The retriever service enables you to query and extract information from
the generated Knowledge Graph. To configure the retriever service, open the
**Project Settings** and follow the steps below.

{{< tabs "retriever-service" >}}

Expand All @@ -134,8 +166,8 @@ the generated Knowledge Graph. Follow the steps below to configure the service.
4. Click the **Start retriever service** button.

{{< info >}}
When using the OpenRouter option, the LLM responses are served via OpenRouter
while OpenAI is used for the embedding model.
When using OpenRouter, the LLM responses are served via OpenRouter while OpenAI
is used for the embedding model.
{{< /info >}}

![Configure Retriever Service using OpenRouter](../../../images/graphrag-ui-configure-retriever-openrouter.png)
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