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Updated obsolete faqs #3575

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9 changes: 7 additions & 2 deletions docker/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,7 @@ The [.env](./.env) file contains important environment variables for Docker.

- `infiniflow/ragflow:dev-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models including:
- Embedded embedding models:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`
- `maidalun1020/bce-embedding-base_v1`
Expand Down Expand Up @@ -117,6 +117,11 @@ The [.env](./.env) file contains important environment variables for Docker.
- `MACOS`
Optimizations for MacOS. It is disabled by default. You can uncomment this line if your OS is MacOS.

### Maximum file size

- `MAX_CONTENT_LENGTH`
The maximum file size for each uploaded file, in bytes. You can uncomment this line if you wish to change 128M file size limit.

## 🐋 Service configuration

[service_conf.yaml](./service_conf.yaml) specifies the system-level configuration for RAGFlow and is used by its API server and task executor. In a dockerized setup, this file is automatically created based on the [service_conf.yaml.template](./service_conf.yaml.template) file (replacing all environment variables by their values).
Expand Down Expand Up @@ -154,4 +159,4 @@ The [.env](./.env) file contains important environment variables for Docker.
- `api_key`: The API key for the specified LLM. You will need to apply for your model API key online.

> [!TIP]
> If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.
> If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.
8 changes: 4 additions & 4 deletions docs/configurations.md
Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
### MySQL

- `MYSQL_PASSWORD`
The password for MySQL.
The password for MySQL.
- `MYSQL_PORT`
The port used to expose the MySQL service to the host machine, allowing **external** access to the MySQL database running inside the Docker container. Defaults to `5455`.

Expand All @@ -75,7 +75,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con
- `MINIO_PORT`
The port used to expose the MinIO API service to the host machine, allowing **external** access to the MinIO object storage service running inside the Docker container. Defaults to `9000`.
- `MINIO_USER`
The username for MinIO.
The username for MinIO.
- `MINIO_PASSWORD`
The password for MinIO. accordingly.

Expand All @@ -95,7 +95,7 @@ The [.env](https://github.com/infiniflow/ragflow/blob/main/docker/.env) file con

- `infiniflow/ragflow:dev-slim` (default): The RAGFlow Docker image without embedding models.
- `infiniflow/ragflow:dev`: The RAGFlow Docker image with embedding models including:
- Embedded embedding models:
- Built-in embedding models:
- `BAAI/bge-large-zh-v1.5`
- `BAAI/bge-reranker-v2-m3`
- `maidalun1020/bce-embedding-base_v1`
Expand Down Expand Up @@ -181,4 +181,4 @@ The default LLM to use for a new RAGFlow user. It is disabled by default. To ena

:::tip NOTE
If you do not set the default LLM here, configure the default LLM on the **Settings** page in the RAGFlow UI.
:::
:::
24 changes: 12 additions & 12 deletions docs/quickstart.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -286,15 +286,15 @@ Once you have selected an embedding model and used it to parse a file, you are n
_When the file parsing completes, its parsing status changes to **SUCCESS**._

:::caution NOTE
- If your file parsing gets stuck at below 1%, see [FAQ 4.3](https://ragflow.io/docs/dev/faq#43-why-does-my-document-parsing-stall-at-under-one-percent).
- If your file parsing gets stuck at near completion, see [FAQ 4.4](https://ragflow.io/docs/dev/faq#44-why-does-my-pdf-parsing-stall-near-completion-while-the-log-does-not-show-any-error)
- If your file parsing gets stuck at below 1%, see [this FAQ](https://ragflow.io/docs/dev/faq#why-does-my-document-parsing-stall-at-under-one-percent).
- If your file parsing gets stuck at near completion, see [this FAQ](https://ragflow.io/docs/dev/faq#why-does-my-pdf-parsing-stall-near-completion-while-the-log-does-not-show-any-error)
:::

## Intervene with file parsing
## Intervene with file parsing

RAGFlow features visibility and explainability, allowing you to view the chunking results and intervene where necessary. To do so:
RAGFlow features visibility and explainability, allowing you to view the chunking results and intervene where necessary. To do so:

1. Click on the file that completes file parsing to view the chunking results:
1. Click on the file that completes file parsing to view the chunking results:

_You are taken to the **Chunk** page:_

Expand All @@ -306,8 +306,8 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin

![update chunk](https://github.com/infiniflow/ragflow/assets/93570324/1d84b408-4e9f-46fd-9413-8c1059bf9c76)

:::caution NOTE
You can add keywords to a file chunk to improve its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.
:::caution NOTE
You can add keywords to a file chunk to improve its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.
:::

4. In Retrieval testing, ask a quick question in **Test text** to double check if your configurations work:
Expand All @@ -318,17 +318,17 @@ You can add keywords to a file chunk to improve its ranking for queries containi

## Set up an AI chat

Conversations in RAGFlow are based on a particular knowledge base or multiple knowledge bases. Once you have created your knowledge base and finished file parsing, you can go ahead and start an AI conversation.
Conversations in RAGFlow are based on a particular knowledge base or multiple knowledge bases. Once you have created your knowledge base and finished file parsing, you can go ahead and start an AI conversation.

1. Click the **Chat** tab in the middle top of the mage **>** **Create an assistant** to show the **Chat Configuration** dialogue *of your next dialogue*.
> RAGFlow offer the flexibility of choosing a different chat model for each dialogue, while allowing you to set the default models in **System Model Settings**.

2. Update **Assistant Setting**:
2. Update **Assistant Setting**:

- Name your assistant and specify your knowledge bases.
- **Empty response**:
- If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then when it doesn't retrieve an answer, it *uniformly* responds with what you set here.
- If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, which may give rise to hallucinations.
- If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then when it doesn't retrieve an answer, it *uniformly* responds with what you set here.
- If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, which may give rise to hallucinations.

3. Update **Prompt Engine** or leave it as is for the beginning.

Expand All @@ -347,4 +347,4 @@ RAGFlow also offers HTTP and Python APIs for you to integrate RAGFlow's capabili
- [Acquire a RAGFlow API key](./guides/develop/acquire_ragflow_api_key.md)
- [HTTP API reference](./references/http_api_reference.md)
- [Python API reference](./references/python_api_reference.md)
:::
:::
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