Skip to content

Commit

Permalink
Release new docs
Browse files Browse the repository at this point in the history
  • Loading branch information
Milvus-doc-bot authored and Milvus-doc-bot committed Sep 18, 2024
1 parent 4de5841 commit 0121205
Show file tree
Hide file tree
Showing 8 changed files with 629 additions and 0 deletions.
Binary file added v2.4.x/assets/graph_rag_with_milvus_1.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added v2.4.x/assets/graph_rag_with_milvus_2.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added v2.4.x/assets/kotaemon_1.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added v2.4.x/assets/kotaemon_2.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Binary file added v2.4.x/assets/kotaemon_3.png
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
83 changes: 83 additions & 0 deletions v2.4.x/site/en/integrations/kotaemon_with_milvus.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,83 @@
---
id: kotaemon_with_milvus.md
summary: This tutorial will guide you on how to customize your kotaemon application using Milvus.
title: Kotaemon RAG with Milvus
---

# Kotaemon RAG with Milvus

[Kotaemon](https://github.com/Cinnamon/kotaemon) is an open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind.

Kotaemon provides a customizable, multi-user document QA web-UI supporting local and API-based LLMs. It offers a hybrid RAG pipeline with full-text and vector retrieval, multi-modal QA for documents with figures and tables, and advanced citations with document previews. It supports complex reasoning methods like ReAct and ReWOO, and provides configurable settings for retrieval and generation.

This tutorial will guide you on how to customize your kotaemon application using [Milvus](https://milvus.io/).


## Prerequisites

### Installation

We recommend installing kotaemon in this way:

```shell
# optional (setup env)
conda create -n kotaemon python=3.10
conda activate kotaemon

git clone https://github.com/Cinnamon/kotaemon
cd kotaemon

pip install -e "libs/kotaemon[all]"
pip install -e "libs/ktem"
```

Besides this way, there are some other ways to install kotaemon. You can refer to the [official documentation](https://github.com/Cinnamon/kotaemon?tab=readme-ov-file#installation) for more details.

### Set Milvus as the default vector storage

To change the default vector storage to Milvus, you have to modify the `flowsettings.py` file by switching `KH_VECTORSTORE` to:

```python
"__type__": "kotaemon.storages.MilvusVectorStore"
```

### Set Environment Variables

you can configure the models via the `.env` file with the information needed to connect to the LLMs and embedding models. e.g. OpenAI, Azure, Ollama, etc.

### Run Kotaemon

After setting up the environment variables and changing the vector storage, you can run kotaemon by running the following command:

```shell
python app.py
```

Default username / password are: `admin` / `admin`

## Start RAG with kotaemon

### 1. Add your AI models

![](../../../assets/kotaemon_1.png)

In the `Resources` tab, you can add and set your LLMs and embedding models. You can add multiple models and set them as active or inactive. You only need to provide at least one. You can also provide multiple models to allow switching between them.

### 2. Upload your documents

![](../../../assets/kotaemon_2.png)

In order to do QA on your documents, you need to upload them to the application first.
Navigate to the `File Index` tab, and you can upload and manage your custom documents.

By default, all application data are stored in `./ktem_app_data` folder. The Milvus database data is stored in `./ktem_app_data/user_data/vectorstore`. You can back up or copy this folder to move your installation to a new machine.

### 3. Chat with your documents

![](../../../assets/kotaemon_3.png)

Now navigate back to the `Chat` tab. The Chat tab consists of 3 regions: the Conversation Settings Panel, where you manage conversations and file references; the Chat Panel for interacting with the chatbot; and the Information Panel, which displays supporting evidence, confidence scores, and relevance ratings for answers.

You can select your documents in the Conversation Settings Panel. Then just start RAG with your documents by typing a message in the input box and send it to the chatbot.

If you want to dive deep into how to use kotaemon, you can get a full guidance from the [official documentation](https://cinnamon.github.io/kotaemon/usage/).
12 changes: 12 additions & 0 deletions v2.4.x/site/en/menuStructure/en.json
Original file line number Diff line number Diff line change
Expand Up @@ -1263,6 +1263,12 @@
"id": "llama_agents_metadata.md",
"order": 1,
"children": []
},
{
"label": "Kotaemon",
"id": "kotaemon_with_milvus.md",
"order": 2,
"children": []
}
]
},
Expand Down Expand Up @@ -1462,6 +1468,12 @@
"order": 4,
"children": []
},
{
"label": "Graph RAG with Milvus",
"id": "graph_rag_with_milvus.md",
"order": 5,
"children": []
},
{
"label": "Explore More",
"id": "explore-more",
Expand Down
Loading

0 comments on commit 0121205

Please sign in to comment.