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533 lines
23 KiB
Markdown
533 lines
23 KiB
Markdown
---
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sidebar_position: 2
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slug: /release_notes
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---
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# Releases
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Key features, improvements and bug fixes in the latest releases.
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:::info
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Each RAGFlow release is available in two editions:
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- **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`
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- **Full edition**: includes built-in embedding models and has no suffix added to the version name. Example: `infiniflow/ragflow:v0.19.0`
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:::
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:::danger IMPORTANT
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The embedding models included in a full edition are:
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- BAAI/bge-large-zh-v1.5
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- maidalun1020/bce-embedding-base_v1
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These two embedding models are optimized specifically for English and Chinese, so performance may be compromised if you use them to embed documents in other languages.
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:::
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## v0.19.0
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Released on May 26, 2025.
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### New features
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- [Cross-language search](./references/glossary.mdx#cross-language-search) is supported in the Knowledge and Chat modules, enhancing search accuracy and user experience in multilingual environments, such as in Chinese-English knowledge bases.
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- Agent component: A new Code component supports Python and JavaScript scripts, enabling developers to handle more complex tasks like dynamic data processing.
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- Enhanced image display: Images in Chat and Search now render directly within responses, rather than as external references. Knowledge retrieval testing can retrieve images directly, instead of texts extracted from images.
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- Claude 4 and ChatGPT o3: Developers can now use the newly released, most advanced Claude model alongside OpenAI’s latest ChatGPT o3 inference model.
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> The following features are contributed by our community contributors:
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- Agent component: Enables tool calling within the Generate Component. Thanks to [notsyncing](https://github.com/notsyncing).
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- Markdown rendering: Image references in a markdown file can be displayed after chunking. Thanks to [Woody-Hu](https://github.com/Woody-Hu).
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- Document engine support: OpenSearch can now be used as RAGFlow's document engine. Thanks to [pyyuhao](https://github.com/pyyuhao).
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### Documentation
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#### Added documents
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- [Select PDF parser](./guides/dataset/select_pdf_parser.md)
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- [Enable Excel2HTML](./guides/dataset/enable_excel2html.md)
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- [Code component](./guides/agent/agent_component_reference/code.mdx)
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## v0.18.0
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Released on April 23, 2025.
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### Compatibility changes
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From this release onwards, built-in rerank models have been removed because they have minimal impact on retrieval rates but significantly increase retrieval time.
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### New features
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- MCP server: enables access to RAGFlow's knowledge bases via MCP.
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- DeepDoc supports adopting VLM model as a processing pipeline during document layout recognition, enabling in-depth analysis of images in PDF and DOCX files.
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- OpenAI-compatible APIs: Agents can be called via OpenAI-compatible APIs.
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- User registration control: administrators can enable or disable user registration through an environment variable.
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- Team collaboration: Agents can be shared with team members.
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- Agent version control: all updates are continuously logged and can be rolled back to a previous version via export.
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### Improvements
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- Enhanced answer referencing: Citation accuracy in generated responses is improved.
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- Enhanced question-answering experience: users can now manually stop streaming output during a conversation.
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### Documentation
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#### Added documents
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- [Set page rank](./guides/dataset/set_page_rank.md)
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- [Enable RAPTOR](./guides/dataset/enable_raptor.md)
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- [Set variables for your chat assistant](./guides/chat/set_chat_variables.md)
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- [Launch RAGFlow MCP server](./develop/mcp/launch_mcp_server.md)
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## v0.17.2
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Released on March 13, 2025.
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### Compatibility changes
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- Removes the **Max_tokens** setting from **Chat configuration**.
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- Removes the **Max_tokens** setting from **Generate**, **Rewrite**, **Categorize**, **Keyword** agent components.
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From this release onwards, if you still see RAGFlow's responses being cut short or truncated, check the **Max_tokens** setting of your model provider.
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### Improvements
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- Adds OpenAI-compatible APIs.
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- Introduces a German user interface.
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- Accelerates knowledge graph extraction.
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- Enables Tavily-based web search in the **Retrieval** agent component.
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- Adds Tongyi-Qianwen QwQ models (OpenAI-compatible).
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- Supports CSV files in the **General** chunking method.
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### Fixed issues
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- Unable to add models via Ollama/Xinference, an issue introduced in v0.17.1.
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### Related APIs
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#### HTTP APIs
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- [Create chat completion](./references/http_api_reference.md#openai-compatible-api)
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#### Python APIs
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- [Create chat completion](./references/python_api_reference.md#openai-compatible-api)
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## v0.17.1
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Released on March 11, 2025.
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### Improvements
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- Improves English tokenization quality.
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- Improves the table extraction logic in Markdown document parsing.
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- Updates SiliconFlow's model list.
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- Supports parsing XLS files (Excel 97-2003) with improved corresponding error handling.
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- Supports Huggingface rerank models.
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- Enables relative time expressions ("now", "yesterday", "last week", "next year", and more) in chat assistant and the **Rewrite** agent component.
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### Fixed issues
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- A repetitive knowledge graph extraction issue.
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- Issues with API calling.
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- Options in the **PDF parser**, aka **Document parser**, dropdown are missing.
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- A Tavily web search issue.
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- Unable to preview diagrams or images in an AI chat.
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### Documentation
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#### Added documents
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- [Use tag set](./guides/dataset/use_tag_sets.md)
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## v0.17.0
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Released on March 3, 2025.
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### New features
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- 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.
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- 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 settings** tab of your chat assistant dialogue.
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- AI chat: Supports starting a chat without specifying knowledge bases.
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- AI chat: HTML files can also be previewed and referenced, in addition to PDF files.
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- Dataset: Adds a **PDF parser**, aka **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. See [here](./guides/dataset/select_pdf_parser.md).
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- 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.
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- Object storage: Supports using Aliyun OSS (Object Storage Service) as a file storage option.
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- Models: Updates the supported model list for Tongyi-Qianwen (Qwen), adding DeepSeek-specific models; adds ModelScope as a model provider.
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- APIs: Document metadata can be updated through an API.
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The following diagram illustrates the workflow of RAGFlow's Deep Research:
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The following is a screenshot of a conversation that integrates Deep Research:
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### Related APIs
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#### HTTP APIs
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Adds a body parameter `"meta_fields"` to the [Update document](./references/http_api_reference.md#update-document) method.
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#### Python APIs
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Adds a key option `"meta_fields"` to the [Update document](./references/python_api_reference.md#update-document) method.
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### Documentation
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#### Added documents
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- [Run retrieval test](./guides/dataset/run_retrieval_test.md)
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## v0.16.0
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Released on February 6, 2025.
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### New features
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- Supports DeepSeek R1 and DeepSeek V3.
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- GraphRAG refactor: Knowledge graph is dynamically built on an entire knowledge base (dataset) rather than on an individual file, and automatically updated when a newly uploaded file starts parsing. See [here](https://ragflow.io/docs/dev/construct_knowledge_graph).
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- Adds an **Iteration** agent component and a **Research report generator** agent template. See [here](./guides/agent/agent_component_reference/iteration.mdx).
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- New UI language: Portuguese.
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- Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See [here](./guides/dataset/set_metadata.md).
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- Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.6.0.dev3.
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- Supports GPU acceleration for DeepDoc (see [docker-compose-gpu.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose-gpu.yml)).
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- Supports creating and referencing a **Tag** knowledge base as a key milestone towards bridging the semantic gap between query and response.
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:::danger IMPORTANT
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The **Tag knowledge base** feature is *unavailable* on the [Infinity](https://github.com/infiniflow/infinity) document engine.
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:::
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### Documentation
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#### Added documents
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- [Construct knowledge graph](./guides/dataset/construct_knowledge_graph.md)
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- [Set metadata](./guides/dataset/set_metadata.md)
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- [Begin component](./guides/agent/agent_component_reference/begin.mdx)
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- [Generate component](./guides/agent/agent_component_reference/generate.mdx)
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- [Interact component](./guides/agent/agent_component_reference/interact.mdx)
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- [Retrieval component](./guides/agent/agent_component_reference/retrieval.mdx)
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- [Categorize component](./guides/agent/agent_component_reference/categorize.mdx)
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- [Keyword component](./guides/agent/agent_component_reference/keyword.mdx)
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- [Message component](./guides/agent/agent_component_reference/message.mdx)
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- [Rewrite component](./guides/agent/agent_component_reference/rewrite.mdx)
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- [Switch component](./guides/agent/agent_component_reference/switch.mdx)
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- [Concentrator component](./guides/agent/agent_component_reference/concentrator.mdx)
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- [Template component](./guides/agent/agent_component_reference/template.mdx)
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- [Iteration component](./guides/agent/agent_component_reference/iteration.mdx)
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- [Note component](./guides/agent/agent_component_reference/note.mdx)
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## v0.15.1
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Released on December 25, 2024.
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### Upgrades
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- Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.5.2.
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- Enhances the log display of document parsing status.
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### Fixed issues
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This release fixes the following issues:
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- The `SCORE not found` and `position_int` errors returned by [Infinity](https://github.com/infiniflow/infinity).
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- Once an embedding model in a specific knowledge base is changed, embedding models in other knowledge bases can no longer be changed.
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- Slow response in question-answering and AI search due to repetitive loading of the embedding model.
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- Fails to parse documents with RAPTOR.
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- Using the **Table** parsing method results in information loss.
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- Miscellaneous API issues.
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### Related APIs
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#### HTTP APIs
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Adds an optional parameter `"user_id"` to the following APIs:
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- [Create session with chat assistant](https://ragflow.io/docs/dev/http_api_reference#create-session-with-chat-assistant)
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- [Update chat assistant's session](https://ragflow.io/docs/dev/http_api_reference#update-chat-assistants-session)
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- [List chat assistant's sessions](https://ragflow.io/docs/dev/http_api_reference#list-chat-assistants-sessions)
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- [Create session with agent](https://ragflow.io/docs/dev/http_api_reference#create-session-with-agent)
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- [Converse with chat assistant](https://ragflow.io/docs/dev/http_api_reference#converse-with-chat-assistant)
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- [Converse with agent](https://ragflow.io/docs/dev/http_api_reference#converse-with-agent)
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- [List agent sessions](https://ragflow.io/docs/dev/http_api_reference#list-agent-sessions)
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## v0.15.0
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Released on December 18, 2024.
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### New features
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- Introduces additional Agent-specific APIs.
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- Supports using page rank score to improve retrieval performance when searching across multiple knowledge bases.
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- Offers an iframe in Chat and Agent to facilitate the integration of RAGFlow into your webpage.
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- Adds a Helm chart for deploying RAGFlow on Kubernetes.
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- Supports importing or exporting an agent in JSON format.
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- Supports step run for Agent components/tools.
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- Adds a new UI language: Japanese.
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- Supports resuming GraphRAG and RAPTOR from a failure, enhancing task management resilience.
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- Adds more Mistral models.
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- Adds a dark mode to the UI, allowing users to toggle between light and dark themes.
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### Improvements
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- Upgrades the Document Layout Analysis model in DeepDoc.
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- Significantly enhances the retrieval performance when using [Infinity](https://github.com/infiniflow/infinity) as document engine.
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### Related APIs
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#### HTTP APIs
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- [List agent sessions](https://ragflow.io/docs/dev/http_api_reference#list-agent-sessions)
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- [List agents](https://ragflow.io/docs/dev/http_api_reference#list-agents)
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#### Python APIs
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- [List agent sessions](https://ragflow.io/docs/dev/python_api_reference#list-agent-sessions)
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- [List agents](https://ragflow.io/docs/dev/python_api_reference#list-agents)
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## v0.14.1
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Released on November 29, 2024.
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### Improvements
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Adds [Infinity's configuration file](https://github.com/infiniflow/ragflow/blob/main/docker/infinity_conf.toml) to facilitate integration and customization of [Infinity](https://github.com/infiniflow/infinity) as a document engine. From this release onwards, updates to Infinity's configuration can be made directly within RAGFlow and will take effect immediately after restarting RAGFlow using `docker compose`. [#3715](https://github.com/infiniflow/ragflow/pull/3715)
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### Fixed issues
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This release fixes the following issues:
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- Unable to display or edit content of a chunk after clicking it.
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- A `'Not found'` error in Elasticsearch.
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- Chinese text becoming garbled during parsing.
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- A compatibility issue with Polars.
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- A compatibility issue between Infinity and GraphRAG.
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## v0.14.0
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Released on November 26, 2024.
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### New features
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- Supports [Infinity](https://github.com/infiniflow/infinity) or Elasticsearch (default) as document engine for vector storage and full-text indexing. [#2894](https://github.com/infiniflow/ragflow/pull/2894)
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- Enhances user experience by adding more variables to the Agent and implementing auto-saving.
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- Adds a three-step translation agent template, inspired by [Andrew Ng's translation agent](https://github.com/andrewyng/translation-agent).
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- Adds an SEO-optimized blog writing agent template.
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- Provides HTTP and Python APIs for conversing with an agent.
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- Supports the use of English synonyms during retrieval processes.
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- Optimizes term weight calculations, reducing the retrieval time by 50%.
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- Improves task executor monitoring with additional performance indicators.
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- Replaces Redis with Valkey.
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- Adds three new UI languages (*contributed by the community*): Indonesian, Spanish, and Vietnamese.
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### Compatibility changes
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From this release onwards, **service_config.yaml.template** replaces **service_config.yaml** for configuring backend services. Upon Docker container startup, the environment variables defined in this template file are automatically populated and a **service_config.yaml** is auto-generated from it. [#3341](https://github.com/infiniflow/ragflow/pull/3341)
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This approach eliminates the need to manually update **service_config.yaml** after making changes to **.env**, facilitating dynamic environment configurations.
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:::danger IMPORTANT
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Ensure that you [upgrade **both** your code **and** Docker image to this release](https://ragflow.io/docs/dev/upgrade_ragflow#upgrade-ragflow-to-the-most-recent-officially-published-release) before trying this new approach.
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:::
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### Related APIs
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#### HTTP APIs
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- [Create session with agent](https://ragflow.io/docs/dev/http_api_reference#create-session-with-agent)
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- [Converse with agent](https://ragflow.io/docs/dev/http_api_reference#converse-with-agent)
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#### Python APIs
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- [Create session with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent)
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- [Converse with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent)
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### Documentation
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#### Added documents
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- [Configurations](https://ragflow.io/docs/dev/configurations)
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- [Manage team members](./guides/team/manage_team_members.md)
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- [Run health check on RAGFlow's dependencies](https://ragflow.io/docs/dev/run_health_check)
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## v0.13.0
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Released on October 31, 2024.
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### New features
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- Adds the team management functionality for all users.
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- Updates the Agent UI to improve usability.
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- Adds support for Markdown chunking in the **General** chunking method.
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- Introduces an **invoke** tool within the Agent UI.
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- Integrates support for Dify's knowledge base API.
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- Adds support for GLM4-9B and Yi-Lightning models.
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- Introduces HTTP and Python APIs for dataset management, file management within dataset, and chat assistant management.
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:::tip NOTE
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To download RAGFlow's Python SDK:
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```bash
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pip install ragflow-sdk==0.13.0
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```
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:::
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### Documentation
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#### Added documents
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- [Acquire a RAGFlow API key](./develop/acquire_ragflow_api_key.md)
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- [HTTP API Reference](./references/http_api_reference.md)
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- [Python API Reference](./references/python_api_reference.md)
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## v0.12.0
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Released on September 30, 2024.
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### New features
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- Offers slim editions of RAGFlow's Docker images, which do not include built-in BGE/BCE embedding or reranking models.
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- Improves the results of multi-round dialogues.
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- Enables users to remove added LLM vendors.
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- Adds support for **OpenTTS** and **SparkTTS** models.
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- Implements an **Excel to HTML** toggle in the **General** chunking method, allowing users to parse a spreadsheet into either HTML tables or key-value pairs by row.
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- Adds agent tools **YahooFinance** and **Jin10**.
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- Adds an investment advisor agent template.
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### Compatibility changes
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From this release onwards, RAGFlow offers slim editions of its Docker images to improve the experience for users with limited Internet access. A slim edition of RAGFlow's Docker image does not include built-in BGE/BCE embedding models and has a size of about 1GB; a full edition of RAGFlow is approximately 9GB and includes both built-in embedding models and embedding models that will be downloaded once you select them in the RAGFlow UI.
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The default Docker image edition is `nightly-slim`. The following list clarifies the differences between various editions:
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- `nightly-slim`: The slim edition of the most recent tested Docker image.
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- `v0.12.0-slim`: The slim edition of the most recent **officially released** Docker image.
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- `nightly`: The full edition of the most recent tested Docker image.
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- `v0.12.0`: The full edition of the most recent **officially released** Docker image.
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See [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow) for instructions on upgrading.
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### Documentation
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#### Added documents
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- [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow)
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## v0.11.0
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Released on September 14, 2024.
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### New features
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- Introduces an AI search interface within the RAGFlow UI.
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- Supports audio output via **FishAudio** or **Tongyi Qwen TTS**.
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- Allows the use of Postgres for metadata storage, in addition to MySQL.
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- Supports object storage options with S3 or Azure Blob.
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- Supports model vendors: **Anthropic**, **Voyage AI**, and **Google Cloud**.
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- Supports the use of **Tencent Cloud ASR** for audio content recognition.
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- Adds finance-specific agent components: **WenCai**, **AkShare**, **YahooFinance**, and **TuShare**.
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- Adds a medical consultant agent template.
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- Supports running retrieval benchmarking on the following datasets:
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||
- [ms_marco_v1.1](https://huggingface.co/datasets/microsoft/ms_marco)
|
||
- [trivia_qa](https://huggingface.co/datasets/mandarjoshi/trivia_qa)
|
||
- [miracl](https://huggingface.co/datasets/miracl/miracl)
|
||
|
||
## v0.10.0
|
||
|
||
Released on August 26, 2024.
|
||
|
||
### New features
|
||
|
||
- Introduces a text-to-SQL template in the Agent UI.
|
||
- Implements Agent APIs.
|
||
- Incorporates monitoring for the task executor.
|
||
- Introduces Agent tools **GitHub**, **DeepL**, **BaiduFanyi**, **QWeather**, and **GoogleScholar**.
|
||
- Supports chunking of EML files.
|
||
- Supports more LLMs or model services: **GPT-4o-mini**, **PerfXCloud**, **TogetherAI**, **Upstage**, **Novita AI**, **01.AI**, **SiliconFlow**, **PPIO**, **XunFei Spark**, **Baidu Yiyan**, and **Tencent Hunyuan**.
|
||
|
||
## v0.9.0
|
||
|
||
Released on August 6, 2024.
|
||
|
||
### New features
|
||
|
||
- Supports GraphRAG as a chunking method.
|
||
- Introduces Agent component **Keyword** and search tools, including **Baidu**, **DuckDuckGo**, **PubMed**, **Wikipedia**, **Bing**, and **Google**.
|
||
- Supports speech-to-text recognition for audio files.
|
||
- Supports model vendors **Gemini** and **Groq**.
|
||
- Supports inference frameworks, engines, and services including **LM studio**, **OpenRouter**, **LocalAI**, and **Nvidia API**.
|
||
- Supports using reranker models in Xinference.
|
||
|
||
## v0.8.0
|
||
|
||
Released on July 8, 2024.
|
||
|
||
### New features
|
||
|
||
- Supports Agentic RAG, enabling graph-based workflow construction for RAG and agents.
|
||
- Supports model vendors **Mistral**, **MiniMax**, **Bedrock**, and **Azure OpenAI**.
|
||
- Supports DOCX files in the MANUAL chunking method.
|
||
- Supports DOCX, MD, and PDF files in the Q&A chunking method.
|
||
|
||
## v0.7.0
|
||
|
||
Released on May 31, 2024.
|
||
|
||
### New features
|
||
|
||
- Supports the use of reranker models.
|
||
- Integrates reranker and embedding models: [BCE](https://github.com/netease-youdao/BCEmbedding), [BGE](https://github.com/FlagOpen/FlagEmbedding), and [Jina](https://jina.ai/embeddings/).
|
||
- Supports LLMs Baichuan and VolcanoArk.
|
||
- Implements [RAPTOR](https://arxiv.org/html/2401.18059v1) for improved text retrieval.
|
||
- Supports HTML files in the GENERAL chunking method.
|
||
- Provides HTTP and Python APIs for deleting documents by ID.
|
||
- Supports ARM64 platforms.
|
||
|
||
:::danger IMPORTANT
|
||
While we also test RAGFlow on ARM64 platforms, we do not maintain RAGFlow Docker images for ARM.
|
||
|
||
If you are on an ARM platform, follow [this guide](./develop/build_docker_image.mdx) to build a RAGFlow Docker image.
|
||
:::
|
||
|
||
### Related APIs
|
||
|
||
#### HTTP API
|
||
|
||
- [Delete documents](https://ragflow.io/docs/dev/http_api_reference#delete-documents)
|
||
|
||
#### Python API
|
||
|
||
- [Delete documents](https://ragflow.io/docs/dev/python_api_reference#delete-documents)
|
||
|
||
## v0.6.0
|
||
|
||
Released on May 21, 2024.
|
||
|
||
### New features
|
||
|
||
- Supports streaming output.
|
||
- Provides HTTP and Python APIs for retrieving document chunks.
|
||
- Supports monitoring of system components, including Elasticsearch, MySQL, Redis, and MinIO.
|
||
- Supports disabling **Layout Recognition** in the GENERAL chunking method to reduce file chunking time.
|
||
|
||
### Related APIs
|
||
|
||
#### HTTP API
|
||
|
||
- [Retrieve chunks](https://ragflow.io/docs/dev/http_api_reference#retrieve-chunks)
|
||
|
||
#### Python API
|
||
|
||
- [Retrieve chunks](https://ragflow.io/docs/dev/python_api_reference#retrieve-chunks)
|
||
|
||
## v0.5.0
|
||
|
||
Released on May 8, 2024.
|
||
|
||
### New features
|
||
|
||
- Supports LLM DeepSeek.
|