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Fix: dataset tag file setting cannot be saved (#17428)

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euvre
2026-08-05 15:55:34 +08:00
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commit 0a444343b9
48 changed files with 266 additions and 171 deletions
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4
docs/develop/contributing.md
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@@ -34,7 +34,7 @@ The list below mentions some contributions you can make, but it is not a complet
1. Fork our GitHub repository.
2. Clone your fork to your local machine:
`git clone git@github.com:<yourname>/ragflow.git`
3. Create a local branch:
3. Create a local branch:
`git checkout -b my-branch`
4. Provide sufficient information in your commit message
`git commit -m 'Provide sufficient info in your commit message'`
@@ -56,4 +56,4 @@ The list below mentions some contributions you can make, but it is not a complet
### Reviewing & Merging a PR
Ensure that your PR passes all Continuous Integration (CI) tests before merging it.
Ensure that your PR passes all Continuous Integration (CI) tests before merging it.

8
docs/develop/launch_ragflow_from_source.md
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@@ -40,7 +40,7 @@ cd ragflow/
### Install Python Dependencies
1. Install uv:
```bash
pipx install uv
```
@@ -98,7 +98,7 @@ docker compose -f docker/docker-compose-base.yml up -d
```
4. Check the configuration in **conf/service_conf.yaml**, ensuring all hosts and ports are correctly set.
5. Run the **entrypoint.sh** script to launch the backend service:
```shell
@@ -127,10 +127,10 @@ docker compose -f docker/docker-compose-base.yml up -d
3. Start up the RAGFlow frontend service:
```bash
npm run dev
npm run dev
```
*The following message appears, showing the IP address and port number of your frontend service:*
*The following message appears, showing the IP address and port number of your frontend service:*
![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)

58
docs/develop/mcp/launch_mcp_server.md
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@@ -13,13 +13,13 @@ Launch an MCP server from source or via Docker.
---
A RAGFlow Model Context Protocol (MCP) server is designed as an independent component to complement the RAGFlow server. Note that an MCP server must operate alongside a properly functioning RAGFlow server.
A RAGFlow Model Context Protocol (MCP) server is designed as an independent component to complement the RAGFlow server. Note that an MCP server must operate alongside a properly functioning RAGFlow server.
An MCP server can start up in either self-host mode (default) or host mode:
An MCP server can start up in either self-host mode (default) or host mode:
- **Self-host mode**:
- **Self-host mode**:
When launching an MCP server in self-host mode, you must provide an API key to authenticate the MCP server with the RAGFlow server. In this mode, the MCP server can access *only* the datasets of a specified tenant on the RAGFlow server.
- **Host mode**:
- **Host mode**:
In host mode, each MCP client can access their own datasets on the RAGFlow server. However, each client request must include a valid API key to authenticate the client with the RAGFlow server.
Once a connection is established, an MCP server communicates with its client in MCP HTTP+SSE (Server-Sent Events) mode, unidirectionally pushing responses from the RAGFlow server to its client in real time.
@@ -35,7 +35,7 @@ If you wish to try out our MCP server without upgrading RAGFlow, community contr
## Launch an MCP Server
You can start an MCP server either from source code or via Docker.
You can start an MCP server either from source code or via Docker.
### Launch from Source Code
@@ -52,7 +52,7 @@ uv run mcp/server/server.py --host=127.0.0.1 --port=9382 --base-url=http://127.0
# uv run mcp/server/server.py --host=127.0.0.1 --port=9382 --base-url=http://127.0.0.1:9380 --mode=host
```
Where:
Where:
- `host`: The MCP server's host address.
- `port`: The MCP server's listening port.
@@ -98,7 +98,7 @@ The MCP server is designed as an optional component that complements the RAGFlow
# - --no-json-response # Disables JSON responses for the streamable-HTTP transport
```
Where:
Where:
- `mcp-host`: The MCP server's host address.
- `mcp-port`: The MCP server's listening port.
@@ -123,13 +123,13 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | Starting MCP Server on 0.0.0.0:9382 with base URL http://127.0.0.1:9380...
docker-ragflow-cpu-1 | Starting 1 task executor(s) on host 'dd0b5e07e76f'...
docker-ragflow-cpu-1 | 2025-04-18 15:41:18,816 INFO 27 ragflow_server log path: /ragflow/logs/ragflow_server.log, log levels: {'peewee': 'WARNING', 'pdfminer': 'WARNING', 'root': 'INFO'}
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | __ __ ____ ____ ____ _____ ______ _______ ____
docker-ragflow-cpu-1 | | \/ |/ ___| _ \ / ___|| ____| _ \ \ / / ____| _ \
docker-ragflow-cpu-1 | | |\/| | | | |_) | \___ \| _| | |_) \ \ / /| _| | |_) |
docker-ragflow-cpu-1 | | | | | |___| __/ ___) | |___| _ < \ V / | |___| _ <
docker-ragflow-cpu-1 | |_| |_|\____|_| |____/|_____|_| \_\ \_/ |_____|_| \_\
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | MCP launch mode: self-host
docker-ragflow-cpu-1 | MCP host: 0.0.0.0
docker-ragflow-cpu-1 | MCP port: 9382
@@ -142,13 +142,13 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | 2025-04-18 15:41:23,263 INFO 27 init database on cluster mode successfully
docker-ragflow-cpu-1 | 2025-04-18 15:41:25,318 INFO 27 load_model /ragflow/rag/res/deepdoc/det.onnx uses CPU
docker-ragflow-cpu-1 | 2025-04-18 15:41:25,367 INFO 27 load_model /ragflow/rag/res/deepdoc/rec.onnx uses CPU
docker-ragflow-cpu-1 | ____ ___ ______ ______ __
docker-ragflow-cpu-1 | ____ ___ ______ ______ __
docker-ragflow-cpu-1 | / __ \ / | / ____// ____// /____ _ __
docker-ragflow-cpu-1 | / /_/ // /| | / / __ / /_ / // __ \| | /| / /
docker-ragflow-cpu-1 | / _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
docker-ragflow-cpu-1 | /_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | / _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
docker-ragflow-cpu-1 | /_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 RAGFlow version: v0.18.0-285-gb2c299fa full
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 project base: /ragflow
docker-ragflow-cpu-1 | 2025-04-18 15:41:29,088 INFO 27 Current configs, from /ragflow/conf/service_conf.yaml:
@@ -157,12 +157,12 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
docker-ragflow-cpu-1 | * Running on all addresses (0.0.0.0)
docker-ragflow-cpu-1 | * Running on http://127.0.0.1:9380
docker-ragflow-cpu-1 | * Running on http://172.19.0.6:9380
docker-ragflow-cpu-1 | ______ __ ______ __
docker-ragflow-cpu-1 | ______ __ ______ __
docker-ragflow-cpu-1 | /_ __/___ ______/ /__ / ____/ _____ _______ __/ /_____ _____
docker-ragflow-cpu-1 | / / / __ `/ ___/ //_/ / __/ | |/_/ _ \/ ___/ / / / __/ __ \/ ___/
docker-ragflow-cpu-1 | / / / /_/ (__ ) ,< / /____> </ __/ /__/ /_/ / /_/ /_/ / /
docker-ragflow-cpu-1 | /_/ \__,_/____/_/|_| /_____/_/|_|\___/\___/\__,_/\__/\____/_/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | / / / /_/ (__ ) ,< / /____> </ __/ /__/ /_/ / /_/ /_/ / /
docker-ragflow-cpu-1 | /_/ \__,_/____/_/|_| /_____/_/|_|\___/\___/\__,_/\__/\____/_/
docker-ragflow-cpu-1 |
docker-ragflow-cpu-1 | 2025-04-18 15:41:34,501 INFO 32 TaskExecutor: RAGFlow version: v0.18.0-285-gb2c299fa full
docker-ragflow-cpu-1 | 2025-04-18 15:41:34,501 INFO 32 Use Elasticsearch http://es01:9200 as the doc engine.
...
@@ -174,11 +174,11 @@ Run `docker compose -f docker-compose.yml up` to launch the RAGFlow server toget
This section is contributed by our community contributor [yiminghub2024](https://github.com/yiminghub2024). 👏
:::
1. Prepare all MCP-specific files and directories.
i. Copy the [mcp/](https://github.com/infiniflow/ragflow/tree/main/mcp) directory to your local working directory.
ii. Copy [docker/docker-compose.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose.yml) locally.
iii. Copy [docker/entrypoint.sh](https://github.com/infiniflow/ragflow/blob/main/docker/entrypoint.sh) locally.
iv. Install the required dependencies using `uv`:
1. Prepare all MCP-specific files and directories.
i. Copy the [mcp/](https://github.com/infiniflow/ragflow/tree/main/mcp) directory to your local working directory.
ii. Copy [docker/docker-compose.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose.yml) locally.
iii. Copy [docker/entrypoint.sh](https://github.com/infiniflow/ragflow/blob/main/docker/entrypoint.sh) locally.
iv. Install the required dependencies using `uv`:
- Run `uv add mcp` or
- Copy [pyproject.toml](https://github.com/infiniflow/ragflow/blob/main/pyproject.toml) locally and run `uv sync --python 3.13`.
2. Edit **docker-compose.yml** to enable MCP (disabled by default).
@@ -198,7 +198,7 @@ docker logs docker-ragflow-cpu-1
## Security Considerations
As MCP technology is still at early stage and no official best practices for authentication or authorization have been established, RAGFlow currently uses [API key](../acquire_ragflow_api_key.md) to validate identity for the operations described earlier. However, in public environments, this makeshift solution could expose your MCP server to potential network attacks. Therefore, when running a local SSE server, it is recommended to bind only to localhost (`127.0.0.1`) rather than to all interfaces (`0.0.0.0`).
As MCP technology is still at early stage and no official best practices for authentication or authorization have been established, RAGFlow currently uses [API key](../acquire_ragflow_api_key.md) to validate identity for the operations described earlier. However, in public environments, this makeshift solution could expose your MCP server to potential network attacks. Therefore, when running a local SSE server, it is recommended to bind only to localhost (`127.0.0.1`) rather than to all interfaces (`0.0.0.0`).
For further guidance, see the [official MCP documentation](https://modelcontextprotocol.io/docs/concepts/transports#security-considerations).
@@ -206,11 +206,11 @@ For further guidance, see the [official MCP documentation](https://modelcontextp
### When to Use an API Key for Authentication?
The use of an API key depends on the operating mode of your MCP server.
The use of an API key depends on the operating mode of your MCP server.
- **Self-host mode** (default):
When starting the MCP server in self-host mode, you should provide an API key when launching it to authenticate it with the RAGFlow server:
- If launching from source, include the API key in the command.
- **Self-host mode** (default):
When starting the MCP server in self-host mode, you should provide an API key when launching it to authenticate it with the RAGFlow server:
- If launching from source, include the API key in the command.
- If launching from Docker, update the API key in **docker/docker-compose.yml**.
- **Host mode**:
- **Host mode**:
If your RAGFlow MCP server is working in host mode, include the API key in the `headers` of your client requests to authenticate your client with the RAGFlow server. An example is available [here](https://github.com/infiniflow/ragflow/blob/main/mcp/client/client.py).

4
docs/develop/mcp/mcp_client_example.md
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@@ -39,11 +39,11 @@ When interacting with the MCP server via HTTP requests, follow this initializati
1. **The client sends an `initialize` request** with protocol version and capabilities.
2. **The server replies with an `initialize` response**, including the supported protocol and capabilities.
3. **The client confirms readiness with an `initialized` notification**.
3. **The client confirms readiness with an `initialized` notification**.
_The connection is established between the client and the server, and further operations (such as tool listing) may proceed._
:::tip NOTE
For more information about this initialization process, see [here](https://modelcontextprotocol.io/docs/concepts/architecture#1-initialization).
For more information about this initialization process, see [here](https://modelcontextprotocol.io/docs/concepts/architecture#1-initialization).
:::
In the following sections, we will walk you through a complete tool calling process.

2
docs/develop/mcp/mcp_tools.md
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@@ -13,4 +13,4 @@ The MCP server currently offers a specialized tool to assist users in searching
- **retrieve**: Fetches relevant chunks from specified `dataset_ids` and optional `document_ids` using the RAGFlow retrieve interface, based on a given question. Details of all available datasets, namely, `id` and `description`, are provided within the tool description for each individual dataset.
For more information, see our Python implementation of the [MCP server](https://github.com/infiniflow/ragflow/blob/main/mcp/server/server.py).
For more information, see our Python implementation of the [MCP server](https://github.com/infiniflow/ragflow/blob/main/mcp/server/server.py).

2
docs/develop/switch_doc_engine.md
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@@ -35,4 +35,4 @@ Switching to Infinity on a Linux/arm64 machine is not yet officially supported.
```bash
$ docker compose -f docker-compose.yml up -d
```
```