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Prepare docs for v0.15.0 release (#4077)

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### What problem does this PR solve?


### Type of change

- [x] Documentation Update
This commit is contained in:
Kevin Hu
2024-12-18 15:32:15 +08:00
committed by GitHub
parent e513ad2f16
commit a45ba3a91e
17 changed files with 86 additions and 68 deletions
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4
docs/configurations.md
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@ -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:v0.14.1-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.14.1`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.15.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.15.0`: 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.md
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@ -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 v0.14.1, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
As of RAGFlow v0.15.0, 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/manage_files.md
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@ -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 v0.14.1, bulk download is not supported, nor can you download an entire folder.
> As of RAGFlow v0.15.0, bulk download is not supported, nor can you download an entire folder.

6
docs/guides/upgrade_ragflow.mdx
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@ -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., `v0.14.1`:
2. Switch to the latest, officially published release, e.g., `v0.15.0`:
```bash
git checkout -f v0.14.1
git checkout -f v0.15.0
```
3. Update **ragflow/docker/.env** as follows:
```bash
RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1
RAGFLOW_IMAGE=infiniflow/ragflow:v0.15.0
```
4. Update the RAGFlow image and restart RAGFlow:

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docs/quickstart.mdx
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@ -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 v0.14.1 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 v0.15.0 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
$ git checkout -f v0.14.1
$ git checkout -f v0.15.0
```
3. Use the pre-built Docker images and start up the server:
:::tip NOTE
The command below downloads the `v0.14.1-slim` edition of the RAGFlow Docker image. Refer to the following table for descriptions of different RAGFlow editions. To download an RAGFlow edition different from `v0.14.1-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:v0.14.1` for the full edition `v0.14.1`.
The command below downloads the `v0.15.0-slim` edition of the RAGFlow Docker image. Refer to the following table for descriptions of different RAGFlow editions. To download an RAGFlow edition different from `v0.14.1-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:v0.14.1` for the full edition `v0.14.1`.
:::
```bash
@ -198,10 +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? |
| ------------------- | --------------- | ----------------------------------------- | ------------------------ |
| `v0.14.1` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.14.1-slim` | &approx;2 | ❌ | Stable release |
| `v0.15.0-dev1` | &approx;9 | :heavy_check_mark: | *Unstable* beta release |
| `v0.15.0-dev1-slim` | &approx;2 | ❌ | *Unstable* beta release |
| `v0.15.0` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.15.0-slim` | &approx;2 | ❌ | Stable release |
| `nightly` | &approx;9 | :heavy_check_mark: | *Unstable* nightly build |
| `nightly-slim` | &approx;2 | ❌ | *Unstable* nightly build |

6
docs/references/faq.md
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@ -42,10 +42,10 @@ 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, `v0.14.1-slim` and `v0.14.1`:
RAGFlow offers two Docker image editions, `v0.15.0-slim` and `v0.15.0`:
- `infiniflow/ragflow:v0.14.1-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.14.1`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.15.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.15.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`