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Docs: update for v0.19.0 (#7823)

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### What problem does this PR solve?

update for v0.19.0

### Type of change

- [x] Documentation Update
This commit is contained in:
liu an
2025-05-23 18:18:58 +08:00
committed by Yingfeng Zhang
parent c283ea57fd
commit 590b9dabab
24 changed files with 67 additions and 67 deletions
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4
docs/configurations.md
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@ -99,8 +99,8 @@ RAGFlow utilizes MinIO as its object storage solution, leveraging its scalabilit
- `RAGFLOW-IMAGE`
The Docker image edition. Available editions:
- `infiniflow/ragflow:v0.18.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.18.0`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.19.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.19.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `maidalun1020/bce-embedding-base_v1`

2
docs/develop/build_docker_image.mdx
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@ -77,7 +77,7 @@ After building the infiniflow/ragflow:nightly-slim image, you are ready to launc
1. Edit Docker Compose Configuration
Open the `docker/.env` file. Find the `RAGFLOW_IMAGE` setting and change the image reference from `infiniflow/ragflow:v0.18.0-slim` to `infiniflow/ragflow:nightly-slim` to use the pre-built image.
Open the `docker/.env` file. Find the `RAGFLOW_IMAGE` setting and change the image reference from `infiniflow/ragflow:v0.19.0-slim` to `infiniflow/ragflow:nightly-slim` to use the pre-built image.
2. Launch the Service

10
docs/faq.mdx
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@ -30,17 +30,17 @@ The "garbage in garbage out" status quo remains unchanged despite the fact that
Each RAGFlow release is available in two editions:
- **Slim edition**: excludes built-in embedding models and is identified by a **-slim** suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0-slim`
- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0`
- **Slim edition**: excludes built-in embedding models and is identified by a **-slim** suffix added to the version name. Example: `infiniflow/ragflow:v0.19.0-slim`
- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.19.0`
---
### Which embedding models can be deployed locally?
RAGFlow offers two Docker image editions, `v0.18.0-slim` and `v0.18.0`:
RAGFlow offers two Docker image editions, `v0.19.0-slim` and `v0.19.0`:
- `infiniflow/ragflow:v0.18.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.18.0`: The RAGFlow Docker image with embedding models including:
- `infiniflow/ragflow:v0.19.0-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:v0.19.0`: The RAGFlow Docker image with embedding models including:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `maidalun1020/bce-embedding-base_v1`

2
docs/guides/chat/start_chat.md
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@ -48,7 +48,7 @@ You start an AI conversation by creating an assistant.
- If no target language is selected, the system will search only in the language of your query, which may cause relevant information in other languages to be missed.
- **Variable** refers to the variables (keys) to be used in the system prompt. `{knowledge}` is a reserved variable. Click **Add** to add more variables for the system prompt.
- If you are uncertain about the logic behind **Variable**, leave it *as-is*.
- As of v0.18.0, if you add custom variables here, the only way you can pass in their values is to call:
- As of v0.19.0, if you add custom variables here, the only way you can pass in their values is to call:
- HTTP method [Converse with chat assistant](../../references/http_api_reference.md#converse-with-chat-assistant), or
- Python method [Converse with chat assistant](../../references/python_api_reference.md#converse-with-chat-assistant).

2
docs/guides/dataset/configure_knowledge_base.md
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@ -128,7 +128,7 @@ See [Run retrieval test](./run_retrieval_test.md) for details.
## Search for knowledge base
As of RAGFlow v0.18.0, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
As of RAGFlow v0.19.0, 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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@ -87,4 +87,4 @@ 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 v0.18.0, bulk download is not supported, nor can you download an entire folder.
> As of RAGFlow v0.19.0, bulk download is not supported, nor can you download an entire folder.

2
docs/guides/tracing.mdx
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@ -18,7 +18,7 @@ RAGFlow ships with a built-in [Langfuse](https://langfuse.com) integration so th
Langfuse stores traces, spans and prompt payloads in a purpose-built observability backend and offers filtering and visualisations on top.
:::info NOTE
• RAGFlow **≥ 0.18.0** (contains the Langfuse connector)
• RAGFlow **≥ 0.19.0** (contains the Langfuse connector)
• A Langfuse workspace (cloud or self-hosted) with a _Project Public Key_ and _Secret Key_
:::

10
docs/guides/upgrade_ragflow.mdx
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@ -66,16 +66,16 @@ 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., `v0.18.0`:
2. Switch to the latest, officially published release, e.g., `v0.19.0`:
```bash
git checkout -f v0.18.0
git checkout -f v0.19.0
```
3. Update **ragflow/docker/.env** as follows:
```bash
RAGFLOW_IMAGE=infiniflow/ragflow:v0.18.0
RAGFLOW_IMAGE=infiniflow/ragflow:v0.19.0
```
4. Update the RAGFlow image and restart RAGFlow:
@ -92,10 +92,10 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
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.v0.18.0.tar infiniflow/ragflow:v0.18.0
docker save -o ragflow.v0.19.0.tar infiniflow/ragflow:v0.19.0
```
3. Copy the **.tar** file to the target server.
4. Load the **.tar** file into Docker:
```bash
docker load -i ragflow.v0.18.0.tar
docker load -i ragflow.v0.19.0.tar
```

12
docs/quickstart.mdx
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@ -44,7 +44,7 @@ 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 v0.18.0 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 v0.19.0 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"
@ -184,13 +184,13 @@ 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 v0.18.0
$ git checkout -f v0.19.0
```
3. Use the pre-built Docker images and start up the server:
:::tip NOTE
The command below downloads the `v0.18.0-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 `v0.18.0-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:v0.18.0` for the full edition `v0.18.0`.
The command below downloads the `v0.19.0-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 `v0.19.0-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:v0.19.0` for the full edition `v0.19.0`.
:::
```bash
@ -207,8 +207,8 @@ 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?:collision: | Stable? |
| ------------------- | --------------- | ----------------------------------------- | ------------------------ |
| `v0.18.0` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.18.0-slim` | &approx;2 | ❌ | Stable release |
| `v0.19.0` | &approx;9 | :heavy_check_mark: | Stable release |
| `v0.19.0-slim` | &approx;2 | ❌ | Stable release |
| `nightly` | &approx;9 | :heavy_check_mark: | *Unstable* nightly build |
| `nightly-slim` | &approx;2 | ❌ | *Unstable* nightly build |
@ -217,7 +217,7 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
```
:::danger IMPORTANT
:collision: The embedding models included in `v0.18.0` and `nightly` are:
:collision: The embedding models included in `v0.19.0` and `nightly` are:
- BAAI/bge-large-zh-v1.5
- maidalun1020/bce-embedding-base_v1

4
docs/release_notes.md
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@ -9,8 +9,8 @@ Key features, improvements and bug fixes in the latest releases.
:::info
Each RAGFlow release is available in two editions:
- **Slim edition**: excludes built-in embedding models and is identified by a **-slim** suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0-slim`
- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.18.0`
- **Slim edition**: excludes built-in embedding models and is identified by a **-slim** suffix added to the version name. Example: `infiniflow/ragflow:v0.19.0-slim`
- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.19.0`
:::
:::danger IMPORTANT