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

Miscellaneous updates (#5670)

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

#5625 #5614 

### Type of change


- [x] Documentation Update
This commit is contained in:
writinwaters
2025-03-06 09:55:27 +08:00
committed by GitHub
parent a54843cc65
commit 5f62f0c9d7
8 changed files with 29 additions and 23 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
docs/develop/launch_ragflow_from_source.md
View File

@ -3,7 +3,7 @@ sidebar_position: 2
slug: /launch_ragflow_from_source
---
# Launch RAGFlow service from source
# Launch service from source
A guide explaining how to set up a RAGFlow service from its source code. By following this guide, you'll be able to debug using the source code.

4
docs/guides/agent/embed_agent_into_webpage.md
View File

@ -7,6 +7,10 @@ slug: /embed_agent_into_webpage
You can use iframe to embed an agent into a third-party webpage.
:::caution WARNING
If your agent's **Begin** component takes a key of **file** type (a **file** type variable), you *cannot* embed it into a webpage.
:::
1. Before proceeding, you must [acquire an API key](../models/llm_api_key_setup.md); otherwise, an error message would appear.
2. On the **Agent** page, click an intended agent **>** **Edit** to access its editing page.
3. Click **Embed into webpage** on the top right corner of the canvas to show the **iframe** window:

3
docs/guides/dataset/accelerate_doc_indexing.mdx
View File

@ -15,4 +15,5 @@ Please note that some of your settings may consume a significant amount of time.
- Use GPU to reduce embedding time.
- On the configuration page of your knowledge base, switch off **Use RAPTOR to enhance retrieval**.
- Extracting knowledge graph (GraphRAG) is time-consuming.
- Disable **Auto-keyword** and **Auto-question** on the configuration page of yor knowledge base, as both depend on the LLM.
- Disable **Auto-keyword** and **Auto-question** on the configuration page of yor knowledge base, as both depend on the LLM.
- **v0.17.0:** If your document is plain text PDF and does not require GPU-intensive processes like OCR (Optical Character Recognition), TSR (Table Structure Recognition), or DLA (Document Layout Analysis), you can choose **Naive** over **DeepDoc** or other time-consuming large model options in the **Document parser** dropdown. This will substantially reduce document parsing time.

3
docs/guides/manage_team_members.md
View File

@ -11,8 +11,9 @@ Invite or remove team members, join or leave a team.
By default, each RAGFlow user is assigned a single team named after their name. RAGFlow allows you to invite RAGFlow users to your team. Your team members can help you:
- Upload documents to your datasets.
- Upload documents to your datasets (knowledge bases).
- Update document configurations in your datasets.
- Update the default configurations for your datasets.
- Parse documents in your datasets.
:::tip NOTE

18
docs/release_notes.md
View File

@ -13,15 +13,15 @@ Released on March 3, 2025.
### New features
1. AI chat: Implements Deep Research for agentic reasoning. To activate this, enable the **Reasoning** toggle under the **Prompt Engine** tab of your chat assistant dialogue.
2. AI chat: Leverages Tavily-based web search to enhance contexts in agentic reasoning. To activate this, enter the correct Tavily API key under the **Assistant Setting** tab of your chat assistant dialogue.
3. AI chat: Supports initiating a chat without specifying knowledge bases.
4. AI chat: HTML files can also be previewed and referenced, in addition to PDF files.
5. Dataset: Adds a **Layout recognition & OCR** dropdown menu to dataset configurations. This includes a DeepDoc model option, which is time-consuming, a much faster **naive** option (plain text), which skips DLR (Document Layout Recognition), OCR (Optimal Character Recognition), and TSR (Table Structure Recognition) tasks, and several currently *experimental* large model options.
6. Agent component: **(x)** or a forward slash `/` can be used to insert available keys (variables) in the system prompt field of the **Generate** or **Template** component.
7. Object storage: Supports using Aliyun OSS (Object Storage Service) as a file storage option.
8. Models: Updates the supported model list for Tongyi-Qianwen, adding DeepSeek-specific models; adds ModelScope as a model provider.
9. APIs: Document metadata can be updated through an API.
- AI chat: Implements Deep Research for agentic reasoning. To activate this, enable the **Reasoning** toggle under the **Prompt Engine** tab of your chat assistant dialogue.
- AI chat: Leverages Tavily-based web search to enhance contexts in agentic reasoning. To activate this, enter the correct Tavily API key under the **Assistant Setting** tab of your chat assistant dialogue.
- AI chat: Supports starting a chat without specifying knowledge bases.
- AI chat: HTML files can also be previewed and referenced, in addition to PDF files.
- Dataset: Adds a **Document parser** dropdown menu to dataset configurations. This includes a DeepDoc model option, which is time-consuming, a much faster **naive** option (plain text), which skips DLA (Document Layout Analysis), OCR (Optical Character Recognition), and TSR (Table Structure Recognition) tasks, and several currently *experimental* large model options.
- Agent component: **(x)** or a forward slash `/` can be used to insert available keys (variables) in the system prompt field of the **Generate** or **Template** component.
- Object storage: Supports using Aliyun OSS (Object Storage Service) as a file storage option.
- Models: Updates the supported model list for Tongyi-Qianwen, adding DeepSeek-specific models; adds ModelScope as a model provider.
- APIs: Document metadata can be updated through an API.
The following diagram illustrates the workflow of RAGFlow's Deep Research: