pengjunjie/ragflow
1
0
Fork 1
mirror of https://github.com/infiniflow/ragflow.git synced 2025-12-08 20:42:30 +08:00
Code Issues Packages Projects Releases Wiki Activity

DOC: for release. (#5472)

Browse Source 
### What problem does this PR solve?


### Type of change

- [x] Documentation Update

---------

Co-authored-by: Jin Hai <haijin.chn@gmail.com>
This commit is contained in:
Kevin Hu
2025-03-02 18:47:06 +08:00
committed by GitHub
parent 3b30799b7e
commit d6836444c9
22 changed files with 215 additions and 220 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
docs/configurations.md
View File

@ -97,8 +97,8 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
- `RAGFLOW-IMAGE`
The Docker image edition. Available editions:
- `infiniflow/ragflow:v0.16.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.16.0`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.17.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.17.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`

2
docs/guides/configure_knowledge_base/configure_knowledge_base.md
View File

@ -128,7 +128,7 @@ RAGFlow uses multiple recall of both full-text search and vector search in its c
## Search for knowledge base
As of RAGFlow v0.16.0, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
As of RAGFlow v0.17.0, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
![search knowledge base](https://github.com/infiniflow/ragflow/assets/93570324/836ae94c-2438-42be-879e-c7ad2a59693e)

2
docs/guides/configure_knowledge_base/construct_knowledge_graph.md
View File

@ -13,7 +13,7 @@ To enhance multi-hop question-answering, RAGFlow adds a knowledge graph construc
![Image](https://github.com/user-attachments/assets/1ec21d8e-f255-4d65-9918-69b72dfa142b)
As of v0.16.0, RAGFlow supports constructing a knowledge graph on a knowledge base, allowing you to construct a *unified* graph across multiple files within your knowledge base. When a newly uploaded file starts parsing, the generated graph will automatically update.
As of v0.17.0, RAGFlow supports constructing a knowledge graph on a knowledge base, allowing you to construct a *unified* graph across multiple files within your knowledge base. When a newly uploaded file starts parsing, the generated graph will automatically update.
:::danger WARNING
Constructing a knowledge graph requires significant memory, computational resources, and tokens.

2
docs/guides/manage_files.md
View File

@ -81,4 +81,4 @@ RAGFlow's file management allows you to download an uploaded file:
![download_file](https://github.com/infiniflow/ragflow/assets/93570324/cf3b297f-7d9b-4522-bf5f-4f45743e4ed5)
> As of RAGFlow v0.16.0, bulk download is not supported, nor can you download an entire folder.
> As of RAGFlow v0.17.0, bulk download is not supported, nor can you download an entire folder.

6
docs/guides/upgrade_ragflow.mdx
View File

@ -62,16 +62,16 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
git clone https://github.com/infiniflow/ragflow.git
```
2. Switch to the latest, officially published release, e.g., `v0.16.0`:
2. Switch to the latest, officially published release, e.g., `v0.17.0`:
```bash
git checkout -f v0.16.0
git checkout -f v0.17.0
```
3. Update **ragflow/docker/.env** as follows:
```bash
RAGFLOW_IMAGE=infiniflow/ragflow:v0.16.0
RAGFLOW_IMAGE=infiniflow/ragflow:v0.17.0
```
4. Update the RAGFlow image and restart RAGFlow:

10
docs/quickstart.mdx
View File

@ -39,7 +39,7 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
`vm.max_map_count`. This value sets the maximum number of memory map areas a process may have. Its default value is 65530. While most applications require fewer than a thousand maps, reducing this value can result in abnormal behaviors, and the system will throw out-of-memory errors when a process reaches the limitation.
RAGFlow v0.16.0 uses Elasticsearch or [Infinity](https://github.com/infiniflow/infinity) for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.
RAGFlow v0.17.0 uses Elasticsearch or [Infinity](https://github.com/infiniflow/infinity) for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.
<Tabs
defaultValue="linux"
@ -179,13 +179,13 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
```bash
$ git clone https://github.com/infiniflow/ragflow.git
$ cd ragflow/docker
$ git checkout -f v0.16.0
$ git checkout -f v0.17.0
```
3. Use the pre-built Docker images and start up the server:
:::tip NOTE
The command below downloads the `v0.16.0-slim` edition of the RAGFlow Docker image. Refer to the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.16.0-slim`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server. For example: set `RAGFLOW_IMAGE=infiniflow/ragflow:v0.16.0` for the full edition `v0.16.0`.
The command below downloads the `v0.17.0-slim` edition of the RAGFlow Docker image. Refer to the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.17.0-slim`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server. For example: set `RAGFLOW_IMAGE=infiniflow/ragflow:v0.17.0` for the full edition `v0.17.0`.
:::
```bash
@ -198,8 +198,8 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
| RAGFlow image tag | Image size (GB) | Has embedding models and Python packages? | Stable? |
| ------------------- | --------------- | ----------------------------------------- | ------------------------ |
| `v0.16.0` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.16.0-slim` | &approx;2 | ❌ | Stable release |
| `v0.17.0` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.17.0-slim` | &approx;2 | ❌ | Stable release |
| `nightly` | &approx;9 | :heavy_check_mark: | *Unstable* nightly build |
| `nightly-slim` | &approx;2 | ❌ | *Unstable* nightly build |

10
docs/references/faq.md
View File

@ -37,12 +37,12 @@ If you build RAGFlow from source, the version number is also in the system log:
/ _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
2025-02-18 10:10:43,835 INFO 1445658 RAGFlow version: v0.16.0-50-g6daae7f2 full
2025-02-18 10:10:43,835 INFO 1445658 RAGFlow version: v0.17.0-50-g6daae7f2 full
```
Where:
- `v0.16.0`: The officially published release.
- `v0.17.0`: The officially published release.
- `50`: The number of git commits since the official release.
- `g6daae7f2`: `g` is the prefix, and `6daae7f2` is the first seven characters of the current commit ID.
- `full`/`slim`: The RAGFlow edition.
@ -71,10 +71,10 @@ We officially support x86 CPU and nvidia GPU. While we also test RAGFlow on ARM6
### Which embedding models can be deployed locally?
RAGFlow offers two Docker image editions, `v0.16.0-slim` and `v0.16.0`:
RAGFlow offers two Docker image editions, `v0.17.0-slim` and `v0.17.0`:
- `infiniflow/ragflow:v0.16.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.16.0`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.17.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.17.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`