sidebar_position: 2
slug: /release_notes
Releases
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:v0.20.5-slimFull edition: includes built-in embedding models and has no suffix added to the version name. Example:
infiniflow/ragflow:v0.20.5
:::
:::danger IMPORTANT
The embedding models included in a full edition are:
BAAI/bge-large-zh-v1.5
maidalun1020/bce-embedding-base_v1
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.
:::
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.
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 knowledge base, 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 knowledge base 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 knowledge base 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 knowledge bases, 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 knowledge bases 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 knowledge base 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 knowledge bases.
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 knowledge bases 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 knowledge bases.
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:
API changes
HTTP APIs
Adds a body parameter "meta_fields" to the Update document method.
Python APIs
Adds a key option "meta_fields" to the Update document method.
Documentation
Added documents
v0.16.0
Released on February 6, 2025.
New features
Supports DeepSeek R1 and DeepSeek V3.
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.
Adds an Iteration agent component and a Research report generator agent template. See here.
New UI language: Portuguese.
Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See here.
Upgrades RAGFlow's document engine Infinity to v0.6.0.dev3.
Supports GPU acceleration for DeepDoc (see docker-compose-gpu.yml).
Supports creating and referencing a Tag knowledge base as a key milestone towards bridging the semantic gap between query and response.
:::danger IMPORTANT
The Tag knowledge base feature is unavailable on the Infinity document engine.
:::
Documentation
Added documents
v0.15.1
Released on December 25, 2024.
Upgrades
Upgrades RAGFlow's document engine Infinity to v0.5.2.
Enhances the log display of document parsing status.
Fixed issues
This release fixes the following issues:
The
SCORE not foundandposition_interrors returned by Infinity.Once an embedding model in a specific knowledge base is changed, embedding models in other knowledge bases can no longer be changed.
Slow response in question-answering and AI search due to repetitive loading of the embedding model.
Fails to parse documents with RAPTOR.
Using the Table parsing method results in information loss.
Miscellaneous API issues.
API changes
HTTP APIs
Adds an optional parameter "user_id" to the following APIs:
v0.15.0
Released on December 18, 2024.
New features
Introduces additional Agent-specific APIs.
Supports using page rank score to improve retrieval performance when searching across multiple knowledge bases.
Offers an iframe in Chat and Agent to facilitate the integration of RAGFlow into your webpage.
Adds a Helm chart for deploying RAGFlow on Kubernetes.
Supports importing or exporting an agent in JSON format.
Supports step run for Agent components/tools.
Adds a new UI language: Japanese.
Supports resuming GraphRAG and RAPTOR from a failure, enhancing task management resilience.
Adds more Mistral models.
Adds a dark mode to the UI, allowing users to toggle between light and dark themes.
Improvements
Upgrades the Document Layout Analysis model in DeepDoc.
Significantly enhances the retrieval performance when using Infinity as document engine.
API changes
HTTP APIs
Python APIs
v0.14.1
Released on November 29, 2024.
Improvements
Adds Infinity's configuration file to facilitate integration and customization of 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
Fixed issues
This release fixes the following issues:
Unable to display or edit content of a chunk after clicking it.
A
'Not found'error in Elasticsearch.Chinese text becoming garbled during parsing.
A compatibility issue with Polars.
A compatibility issue between Infinity and GraphRAG.
v0.14.0
Released on November 26, 2024.
New features
Supports Infinity or Elasticsearch (default) as document engine for vector storage and full-text indexing. #2894
Enhances user experience by adding more variables to the Agent and implementing auto-saving.
Adds a three-step translation agent template, inspired by Andrew Ng's translation agent.
Adds an SEO-optimized blog writing agent template.
Provides HTTP and Python APIs for conversing with an agent.
Supports the use of English synonyms during retrieval processes.
Optimizes term weight calculations, reducing the retrieval time by 50%.
Improves task executor monitoring with additional performance indicators.
Replaces Redis with Valkey.
Adds three new UI languages (contributed by the community): Indonesian, Spanish, and Vietnamese.
Compatibility changes
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
This approach eliminates the need to manually update service_config.yaml after making changes to .env, facilitating dynamic environment configurations.
:::danger IMPORTANT
Ensure that you upgrade both your code and Docker image to this release before trying this new approach.
:::
API changes
HTTP APIs
Python APIs
Documentation
Added documents
v0.13.0
Released on October 31, 2024.
New features
Adds the team management functionality for all users.
Updates the Agent UI to improve usability.
Adds support for Markdown chunking in the General chunking method.
Introduces an invoke tool within the Agent UI.
Integrates support for Dify's knowledge base API.
Adds support for GLM4-9B and Yi-Lightning models.
Introduces HTTP and Python APIs for dataset management, file management within dataset, and chat assistant management.
:::tip NOTE
To download RAGFlow's Python SDK:
pip install ragflow-sdk==0.13.0
:::
Documentation
Added documents
v0.12.0
Released on September 30, 2024.
New features
Offers slim editions of RAGFlow's Docker images, which do not include built-in BGE/BCE embedding or reranking models.
Improves the results of multi-round dialogues.
Enables users to remove added LLM vendors.
Adds support for OpenTTS and SparkTTS models.
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.
Adds agent tools YahooFinance and Jin10.
Adds an investment advisor agent template.
Compatibility changes
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.
The default Docker image edition is nightly-slim. The following list clarifies the differences between various editions:
nightly-slim: The slim edition of the most recent tested Docker image.v0.12.0-slim: The slim edition of the most recent officially released Docker image.nightly: The full edition of the most recent tested Docker image.v0.12.0: The full edition of the most recent officially released Docker image.
See Upgrade RAGFlow for instructions on upgrading.
Documentation
Added documents
v0.11.0
Released on September 14, 2024.
New features
Introduces an AI search interface within the RAGFlow UI.
Supports audio output via FishAudio or Tongyi Qwen TTS.
Allows the use of Postgres for metadata storage, in addition to MySQL.
Supports object storage options with S3 or Azure Blob.
Supports model vendors: Anthropic, Voyage AI, and Google Cloud.
Supports the use of Tencent Cloud ASR for audio content recognition.
Adds finance-specific agent components: WenCai, AkShare, YahooFinance, and TuShare.
Adds a medical consultant agent template.
Supports running retrieval benchmarking on the following datasets:
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, BGE, and Jina.
Supports LLMs Baichuan and VolcanoArk.
Implements RAPTOR 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 to build a RAGFlow Docker image.
:::
API changes
HTTP API
Python API
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.
API changes
HTTP API
Python API
v0.5.0
Released on May 8, 2024.
New features
Supports LLM DeepSeek.