Releases
Key features, improvements and bug fixes in the latest releases.
v0.22.0
Released on November 12, 2025.
Breaking Changes
From this release onwards, we ship only the slim edition (without embedding models) Docker image and no longer append the -slim suffix to the image tag.
New Features
- Dataset:
- Supports data synchronization from five online sources (AWS S3, Google Drive, Notion, Confluence, and Discord).
- RAPTOR can be built across an entire dataset or on individual documents.
- Ingestion pipeline: Supports Docling document parsing in the Parser component.
- Launches a new administrative Web UI dashboard for graphical user management and service status monitoring.
- Agent:
- Supports structured output.
- Supports metadata filtering in the Retrieval component.
- Introduces a Variable aggregator component with data operation and session variable definition capabilities.
Improvements
- Agent: Supports visualizing previous components' outputs in the Await Response component.
- Revamps the model provider page.
- Upgrades RAGFlow's document engine Infinity to v0.6.5.
Added Models
- Kimi-K2-Thinking
New agent templates
- Interactive Agent, incorporates real-time user feedback to dynamically optimize Agent output.
v0.21.1
Released on October 23, 2025.
New features
- Experimental: Adds support for PDF document parsing using MinerU. See here.
Improvements
- Enhances UI/UX for the dataset and personal center pages.
- Upgrades RAGFlow's document engine, Infinity, to v0.6.1.
Fixed issues
- An issue with video parsing.
v0.21.0
Released on October 15, 2025.
New features
- Orchestratable ingestion pipeline: Supports customized data ingestion and cleansing workflows, enabling users to flexibly design their data flows or directly apply the official data flow templates on the canvas.
- GraphRAG & RAPTOR write process optimized: Replaces the automatic incremental build process with manual batch building, significantly reducing construction overhead.
- Long-context RAG: Automatically generates document-level table of contents (TOC) structures to mitigate context loss caused by inaccurate or excessive chunking, substantially improving retrieval quality. This feature is now available via a TOC extraction template. See here.
- Video file parsing: Expands the system's multimodal data processing capabilities by supporting video file parsing.
- Admin CLI: Introduces a new command-line tool for system administration, allowing users to manage and monitor RAGFlow's service status via command line.
Improvements
- Redesigns RAGFlow's Login and Registration pages.
- Upgrades RAGFlow's document engine Infinity to v0.6.0.
Added models
- Tongyi Qwen 3 series
- Claude Sonnet 4.5
- Meituan LongCat-Flash-Thinking
New agent templates
- Company Research Report Deep Dive Agent: Designed for financial institutions to help analysts quickly organize information, generate research reports, and make investment decisions.
- Orchestratable Ingestion Pipeline Template: Allows users to apply this template on the canvas to rapidly establish standardized data ingestion and cleansing processes.
v0.20.5
Released on September 10, 2025.
Improvements
- Agent:
- Agent Performance Optimized: Improves planning and reflection speed for simple tasks; optimizes concurrent tool calls for parallelizable scenarios, significantly reducing overall response time.
- Four framework-level prompt blocks are available in the System prompt section, enabling customization and overriding of prompts at the framework level, thereby enhancing flexibility and control. See here.
- Execute SQL component enhanced: Replaces the original variable reference component with a text input field, allowing users to write free-form SQL queries and reference variables. See here.
- Chat: Re-enables Reasoning and Cross-language search.
Added models
- Meituan LongCat
- Kimi: kimi-k2-turbo-preview and kimi-k2-0905-preview
- Qwen: qwen3-max-preview
- SiliconFlow: DeepSeek V3.1
Fixed issues
- Dataset: Deleted files remained searchable.
- Chat: Unable to chat with an Ollama model.
- Agent:
- A Cite toggle failure.
- An Agent in task mode still required a dialogue to trigger.
- Repeated answers in multi-turn dialogues.
- Duplicate summarization of parallel execution results.
API changes
HTTP APIs
- Adds a body parameter
"metadata_condition"to the Retrieve chunks method, enabling metadata-based chunk filtering during retrieval. #9877
Python APIs
- Adds a parameter
metadata_conditionto the Retrieve chunks method, enabling metadata-based chunk filtering during retrieval. #9877
v0.20.4
Released on August 27, 2025.
Improvements
- Agent component: Completes Chinese localization for the Agent component.
- Introduces the
ENABLE_TIMEOUT_ASSERTIONenvironment variable to enable or disable timeout assertions for file parsing tasks. - Dataset:
- Improves Markdown file parsing, with AST support to avoid unintended chunking.
- Enhances HTML parsing, supporting bs4-based HTML tag traversal.
Added models
ZHIPU GLM-4.5
New Agent templates
Ecommerce Customer Service Workflow: A template designed to handle enquiries about product features and multi-product comparisons using the internal dataset, as well as to manage installation appointment bookings.
Fixed issues
- Dataset:
- Unable to share resources with the team.
- Inappropriate restrictions on the number and size of uploaded files.
- Chat:
- Unable to preview referenced files in responses.
- Unable to send out messages after file uploads.
- An OAuth2 authentication failure.
- A logical error in multi-conditioned metadata searches within a dataset.
- Citations infinitely increased in multi-turn conversations.
v0.20.3
Released on August 20, 2025.
Improvements
- Revamps the user interface for the Datasets, Chat, and Search pages.
- Search and Chat: Introduces document-level metadata filtering, allowing automatic or manual filtering during chats or searches.
- Search: Supports creating search apps tailored to various business scenarios
- Chat: Supports comparing answer performance of up to three chat model settings on a single Chat page.
- Agent:
- Implements a toggle in the Agent component to enable or disable citation.
- Introduces a drag-and-drop method for creating components.
- Documentation: Corrects inaccuracies in the API reference.
New Agent templates
- Report Agent: A template for generating summary reports in internal question-answering scenarios, supporting the display of tables and formulae. #9427
Fixed issues
- The timeout mechanism introduced in v0.20.0 caused tasks like GraphRAG to halt.
- Predefined opening greeting in the Agent component was missing during conversations.
- An automatic line break issue in the prompt editor.
- A memory leak issue caused by PyPDF. #9469
API changes
Deprecated
v0.20.1
Released on August 8, 2025.
New Features
- The Retrieval component now supports the dynamic specification of dataset names using variables.
- The user interface now includes a French language option.
Added Models
- GPT-5
- Claude 4.1
New agent templates (both workflow and agentic)
- SQL Assistant Workflow: Empowers non-technical teams (e.g., operations, product) to independently query business data.
- Choose Your Knowledge Base Workflow: Lets users select a dataset to query during conversations. #9325
- Choose Your Knowledge Base Agent: Delivers higher-quality responses with extended reasoning time, suited for complex queries. #9325
Fixed Issues
- The Agent component was unable to invoke models installed via vLLM.
- Agents could not be shared with the team.
- Embedding an Agent into a webpage was not functioning properly.
v0.20.0
Released on August 4, 2025.
Compatibility changes
From v0.20.0 onwards, Agents are no longer compatible with earlier versions, and all existing Agents from previous versions must be rebuilt following the upgrade.
New features
- Unified orchestration of both Agents and Workflows.
- A comprehensive refactor of the Agent, greatly enhancing its capabilities and usability, with support for Multi-Agent configurations, planning and reflection, and visual functionalities.
- Fully implemented MCP functionality, allowing for MCP Server import, Agents functioning as MCP Clients, and RAGFlow itself operating as an MCP Server.
- Access to runtime logs for Agents.
- Chat histories with Agents available through the management panel.
- Integration of a new, more robust version of Infinity, enabling the auto-tagging functionality with Infinity as the underlying document engine.
- An OpenAI-compatible API that supports file reference information.
- Support for new models, including Kimi K2, Grok 4, and Voyage embedding.
- RAGFlow’s codebase is now mirrored on Gitee.
- Introduction of a new model provider, Gitee AI.
New agent templates introduced
- Multi-Agent based Deep Research: Collaborative Agent teamwork led by a Lead Agent with multiple Subagents, distinct from traditional workflow orchestration.
- An intelligent Q&A chatbot leveraging internal datasets, designed for customer service and training scenarios.
- A resume analysis template used by the RAGFlow team to screen, analyze, and record candidate information.
- A blog generation workflow that transforms raw ideas into SEO-friendly blog content.
- An intelligent customer service workflow.
- A user feedback analysis template that directs user feedback to appropriate teams through semantic analysis.
- Trip Planner: Uses web search and map MCP servers to assist with travel planning.
- Image Lingo: Translates content from uploaded photos.
- An information search assistant that retrieves answers from both internal datasets and the web.
v0.19.1
Released on June 23, 2025.
Fixed issues
- A memory leak issue during high-concurrency requests.
- Large file parsing freezes when GraphRAG entity resolution is enabled. #8223
- A context error occurring when using Sandbox in standalone mode. #8340
- An excessive CPU usage issue caused by Ollama. #8216
- A bug in the Code Component. #7949
- Added support for models installed via Ollama or VLLM when creating a dataset through the API. #8069
- Enabled role-based authentication for S3 bucket access. #8149
Added models
v0.19.0
Released on May 26, 2025.
New features
- 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 datasets.
- Agent component: A new Code component supports Python and JavaScript scripts, enabling developers to handle more complex tasks like dynamic data processing.
- 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.
- Claude 4 and ChatGPT o3: Developers can now use the newly released, most advanced Claude model and OpenAI’s latest ChatGPT o3 inference model.
The following features have been contributed by our community:
- Agent component: Enables tool calling within the Generate Component. Thanks to notsyncing.
- Markdown rendering: Image references in a markdown file can be displayed after chunking. Thanks to Woody-Hu.
- Document engine support: OpenSearch can now be used as RAGFlow's document engine. Thanks to pyyuhao.
Documentation
Added documents
v0.18.0
Released on April 23, 2025.
Compatibility changes
From this release onwards, built-in rerank models have been removed because they have minimal impact on retrieval rates but significantly increase retrieval time.
New features
- MCP server: enables access to RAGFlow's datasets via MCP.
- DeepDoc supports adopting VLM model as a processing pipeline during document layout recognition, enabling in-depth analysis of images in PDF and DOCX files.
- OpenAI-compatible APIs: Agents can be called via OpenAI-compatible APIs.
- User registration control: administrators can enable or disable user registration through an environment variable.
- Team collaboration: Agents can be shared with team members.
- Agent version control: all updates are continuously logged and can be rolled back to a previous version via export.

Improvements
- Enhanced answer referencing: Citation accuracy in generated responses is improved.
- Enhanced question-answering experience: users can now manually stop streaming output during a conversation.
Documentation
Added documents
v0.17.2
Released on March 13, 2025.
Compatibility changes
- Removes the Max_tokens setting from Chat configuration.
- Removes the Max_tokens setting from Generate, Rewrite, Categorize, Keyword agent components.
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.
Improvements
- Adds OpenAI-compatible APIs.
- Introduces a German user interface.
- Accelerates knowledge graph extraction.
- Enables Tavily-based web search in the Retrieval agent component.
- Adds Tongyi-Qianwen QwQ models (OpenAI-compatible).
- Supports CSV files in the General chunking method.
Fixed issues
- Unable to add models via Ollama/Xinference, an issue introduced in v0.17.1.
API changes
HTTP APIs
Python APIs
v0.17.1
Released on March 11, 2025.
Improvements
- Improves English tokenization quality.
- Improves the table extraction logic in Markdown document parsing.
- Updates SiliconFlow's model list.
- Supports parsing XLS files (Excel 97-2003) with improved corresponding error handling.
- Supports Huggingface rerank models.
- Enables relative time expressions ("now", "yesterday", "last week", "next year", and more) in chat assistant and the Rewrite agent component.
Fixed issues
- A repetitive knowledge graph extraction issue.
- Issues with API calling.
- Options in the PDF parser, aka Document parser, dropdown are missing.
- A Tavily web search issue.
- Unable to preview diagrams or images in an AI chat.
Documentation
Added documents
v0.17.0
Released on March 3, 2025.
New features
- 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 settings tab of your chat assistant dialogue.
- AI chat: Supports starting a chat without specifying datasets.
- AI chat: HTML files can also be previewed and referenced, in addition to PDF files.
- 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.
- 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 (Qwen), 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:
The following is a screenshot of a conversation that integrates Deep Research: