Miscellaneous doc updates and refactored team management doc. (#6730)

### What problem does this PR solve?

#5576, #6672

### Type of change


- [x] Documentation and UI Update
This commit is contained in:
writinwaters
2025-04-01 19:05:30 +08:00
committed by GitHub
parent 132eae9d5b
commit 31296ad70f
19 changed files with 134 additions and 84 deletions

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@ -65,14 +65,6 @@ An embedding model converts chunks into embeddings. It cannot be changed once th
The following embedding models can be deployed locally:
- BAAI/bge-large-zh-v1.5
- BAAI/bge-base-en-v1.5
- BAAI/bge-large-en-v1.5
- BAAI/bge-small-en-v1.5
- BAAI/bge-small-zh-v1.5
- jinaai/jina-embeddings-v2-base-en
- jinaai/jina-embeddings-v2-small-en
- nomic-ai/nomic-embed-text-v1.5
- sentence-transformers/all-MiniLM-L6-v2
- maidalun1020/bce-embedding-base_v1
### Upload file

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@ -36,4 +36,4 @@ If you set the page rank value to a non-integer, say 1.7, it will be rounded dow
If you configure a chat assistant's **similarity threshold** to 0.2, only chunks with a hybrid score greater than 0.2 x 100 = 20 will be retrieved and sent to the chat model for content generation. This initial filtering step is crucial for narrowing down relevant information.
If you have assigned a page rank of 1 to knowledge base A (2024 news) and 0 to knowledge base B (2023 news), the final hybrid scores of the retrieved chunks will be adjusted accordingly. A chunk from knowledge base A with an initial score of 50 will receive a boost of 1 x 100 = 100 points, resulting in a final score of 50 + 1 x 100 = 150. In this way, chunks retrieved from knowledge base A will always precede chunks from knowledge base B.
If you have assigned a page rank of 1 to knowledge base A (2024 news) and 0 to knowledge base B (2023 news), the final hybrid scores of the retrieved chunks will be adjusted accordingly. A chunk retrieved from knowledge base A with an initial score of 50 will receive a boost of 1 x 100 = 100 points, resulting in a final score of 50 + 1 x 100 = 150. In this way, chunks retrieved from knowledge base A will always precede chunks from knowledge base B.

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@ -1,5 +1,5 @@
---
sidebar_position: 5
sidebar_position: 6
slug: /manage_files
---

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@ -1,51 +0,0 @@
---
sidebar_position: 4
slug: /manage_team_members
---
# Team
Invite or remove team members, join or leave a team.
---
By default, each RAGFlow user is assigned a single team named after their name. RAGFlow allows you to invite RAGFlow users to your team. Your team members can help you:
- Upload documents to your datasets (knowledge bases).
- Update document configurations in your datasets.
- Update the default configurations for your datasets.
- Parse documents in your datasets.
:::danger IMPORTANT
To allow your team members to view and update your knowledge base, ensure that you set **Permissions** on its **Configuration** page from **Only me** to **Team**.
:::
:::tip NOTE
Team members are currently *not* allowed to invite users to your team, and only you, the team owner, is permitted to do so.
:::
To enter the **Team** page, click on your avatar in the top right corner of the page **>** Team:
![team](https://github.com/user-attachments/assets/0eac2503-26bc-4568-b3f2-bcd84069a07a)
_On the **Team** page, you can view the information about members of your team and the teams you have joined._
## Invite team members
You are, by default, the owner of your own team and the only person permitted to invite users to join your team or remove team members.
:::danger IMPORTANT
When using email address to invite a team member, ensure it is associated with an existing RAGFlow account to avoid errors.
:::
![invite_team_member](https://github.com/user-attachments/assets/d85b55c3-7e86-4f04-a414-ca18a9ee8963)
## Remove team members
![remove_members](https://github.com/user-attachments/assets/5c1a6ab5-8862-47a0-ad09-77fe88866508)
## Accept or decline team invite
![accept_or_decline_team_invite](https://github.com/user-attachments/assets/6a2cb61f-03d5-4423-9ed1-71df97ff4114)
_After accepting the team invite, you should be able to view and update the team owner's knowledge bases whose **Permissions** is set to **Team**._

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---
sidebar_position: 7
sidebar_position: 8
slug: /run_health_check
---

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@ -0,0 +1,8 @@
{
"label": "Team",
"position": 4,
"link": {
"type": "generated-index",
"description": "Team-specific guides."
}
}

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@ -0,0 +1,42 @@
---
sidebar_position: 2
slug: /join_or_leave_team
---
# Join or leave a team
Accept a team invite to join a team, decline a team invite, or leave a team.
---
Once you join a team, you can do the following:
- Upload documents to the team owner's shared datasets (knowledge bases).
- Update document configurations in the team owner's shared datasets.
- Update the default configurations for the team owner's shared datasets.
- Parse documents in the team owner's shared datasets.
:::tip NOTE
You cannot invite users to a team unless you are its owner.
:::
## Prerequisites
1. Ensure that your Email address that received the team invitation is associated with a RAGFlow user account.
2. To view and update the team owner's shared knowledge base, The team owner must set a knowledge base's **Permissions** to **Team**.
## Accept or decline team invite
Click on your avatar in the top right corner of the page, then select **Team** in the left-hand panel to access the **Team** page.
![team](https://github.com/user-attachments/assets/0eac2503-26bc-4568-b3f2-bcd84069a07a)
_On the **Team** page, you can view the information about members of your team and the teams you have joined._
![accept_or_decline_team_invite](https://github.com/user-attachments/assets/6a2cb61f-03d5-4423-9ed1-71df97ff4114)
_After accepting the team invite, you should be able to view and update the team owner's knowledge bases whose **Permissions** is set to **Team**._
## Leave a joined team
![Image](https://github.com/user-attachments/assets/4e4c6971-131b-490b-85d8-b362e0811b86)

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@ -0,0 +1,43 @@
---
sidebar_position: 1
slug: /manage_team_members
---
# Team
Invite or remove team members.
---
By default, each RAGFlow user is assigned a single team named after their name. RAGFlow allows you to invite RAGFlow users to your team. Your team members can help you:
- Upload documents to your shared datasets (knowledge bases).
- Update document configurations in your shared datasets.
- Update the default configurations for your shared datasets.
- Parse documents in your shared datasets.
:::tip NOTE
- Your team members are currently *not* allowed to invite users to your team, and only you, the team owner, is permitted to do so.
- Sharing added models with team members is only available in RAGFlow's Enterprise edition.
:::
## Prerequisites
1. Ensure that the invited team member is a RAGFlow user and that the Email address used is associated with a RAGFlow user account.
2. To allow your team members to view and update your knowledge base, ensure that you set **Permissions** on its **Configuration** page from **Only me** to **Team**.
## Invite team members
Click on your avatar in the top right corner of the page, then select **Team** in the left-hand panel to access the **Team** page.
![team](https://github.com/user-attachments/assets/0eac2503-26bc-4568-b3f2-bcd84069a07a)
_On the **Team** page, you can view the information about members of your team and the teams you have joined._
You are, by default, the owner of your own team and the only person permitted to invite users to join your team or remove team members.
![invite_team_member](https://github.com/user-attachments/assets/d85b55c3-7e86-4f04-a414-ca18a9ee8963)
## Remove team members
![remove_members](https://github.com/user-attachments/assets/5c1a6ab5-8862-47a0-ad09-77fe88866508)

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@ -3,12 +3,16 @@ sidebar_position: 11
slug: /upgrade_ragflow
---
# Upgrade
# Upgrading
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
Upgrade RAGFlow to `nightly-slim`/`nightly` or the latest, published release.
:::info NOTE
Upgrading RAGFlow in itself will *not* remove your uploaded/historical data. However, be aware that `docker compose -f docker/docker-compose.yml down -v` will remove Docker container volumes, resulting in data loss.
:::
## Upgrade RAGFlow to `nightly-slim`/`nightly`, the most recent, tested Docker image
`nightly-slim` refers to the RAGFlow Docker image *without* embedding models, while `nightly` refers to the RAGFlow Docker image with embedding models. For details on their differences, see [ragflow/docker/.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env).
@ -79,4 +83,19 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
```bash
docker compose -f docker/docker-compose.yml pull
docker compose -f docker/docker-compose.yml up -d
```
```
## Frequently asked questions
### Upgrade RAGFlow in an offline environment (without Internet access)
1. From an environment with Internet access, pull the required Docker image.
2. Save the Docker image to a **.tar** file.
```bash
docker save -o ragflow.v0.17.2.tar infiniflow/ragflow:v0.17.2
```
3. Copy the **.tar** file to the target server.
4. Load the **.tar** file into Docker:
```bash
docker load -i ragflow.v0.17.2.tar
```

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@ -270,7 +270,7 @@ Ensure that you [upgrade **both** your code **and** Docker image to this release
#### Added documents
- [Configurations](https://ragflow.io/docs/dev/configurations)
- [Manage team members](https://ragflow.io/docs/dev/manage_team_members)
- [Manage team members](./guides/team/manage_team_members.md)
- [Run health check on RAGFlow's dependencies](https://ragflow.io/docs/dev/run_health_check)
## v0.13.0