--- sidebar_position: 2 slug: /release_notes --- # Releases Key features, improvements and bug fixes in the latest releases. ## v0.17.2 Released on March 13, 2025. ### 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** chunk method. ### Fixed issues - Unable to add models via Ollama/Xinference, an issue introduced in v0.17.1. ### Related APIs #### HTTP APIs [Create chat completion](./references/http_api_reference.md#openai-compatible-api) #### Python APIs [Create chat completion](./references/python_api_reference.md#openai-compatible-api) ## 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 (Excel97~2003) with improved corresponding error handling. - Supports Huggingface rerank models. - Enables relative time expressions ("now", "yesterday", "last week", "next year", and more) in the **Rewrite** agent component. ### Fixed issues - A repetitive knowledge graph extraction issue. - Issues with API calling. - Options in the **Document parser** dropdown are missing. - A Tavily web search issue. - Unable to preview diagrams or images in an AI chat. ### Documentation #### Added documents [Use tag set](./guides/dataset/use_tag_sets.md) ## 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 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 (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: ![Image](https://github.com/user-attachments/assets/f65d4759-4f09-4d9d-9549-c0e1fe907525) The following is a screenshot of a conversation that integrates Deep Research: ![Image](https://github.com/user-attachments/assets/165b88ff-1f5d-4fb8-90e2-c836b25e32e9) ### Related APIs #### HTTP APIs Adds a body parameter `"meta_fields"` to the [Update document](./references/http_api_reference.md#update-document) method. #### Python APIs Adds a key option `"meta_fields"` to the [Update document](./references/python_api_reference.md#update-document) method. ### Documentation #### Added documents [Run retrieval test](./guides/dataset/run_retrieval_test.md) ## 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](https://ragflow.io/docs/dev/construct_knowledge_graph). - Adds an **Iteration** agent component and a **Research report generator** agent template. See [here](./guides/agent/agent_component_reference/iteration.mdx). - New UI language: Portuguese. - Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See [here](./guides/dataset/set_metadata.md). - Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.6.0.dev3. - Supports GPU acceleration for DeepDoc (see [docker-compose-gpu.yml](https://github.com/infiniflow/ragflow/blob/main/docker/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](https://github.com/infiniflow/infinity) document engine. ::: ### Documentation #### Added documents - [Construct knowledge graph](./guides/dataset/construct_knowledge_graph.md) - [Set metadata](./guides/dataset/set_metadata.md) - [Begin component](./guides/agent/agent_component_reference/begin.mdx) - [Generate component](./guides/agent/agent_component_reference/generate.mdx) - [Interact component](./guides/agent/agent_component_reference/interact.mdx) - [Retrieval component](./guides/agent/agent_component_reference/retrieval.mdx) - [Categorize component](./guides/agent/agent_component_reference/categorize.mdx) - [Keyword component](./guides/agent/agent_component_reference/keyword.mdx) - [Message component](./guides/agent/agent_component_reference/message.mdx) - [Rewrite component](./guides/agent/agent_component_reference/rewrite.mdx) - [Switch component](./guides/agent/agent_component_reference/switch.mdx) - [Concentrator component](./guides/agent/agent_component_reference/concentrator.mdx) - [Template component](./guides/agent/agent_component_reference/template.mdx) - [Iteration component](./guides/agent/agent_component_reference/iteration.mdx) - [Note component](./guides/agent/agent_component_reference/note.mdx) ## v0.15.1 Released on December 25, 2024. ### Upgrades - Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.5.2. - Enhances the log display of document parsing status. ### Fixed issues This release fixes the following issues: - The `SCORE not found` and `position_int` errors returned by [Infinity](https://github.com/infiniflow/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. ### Related APIs #### HTTP APIs Adds an optional parameter `"user_id"` to the following APIs: - [Create session with chat assistant](https://ragflow.io/docs/dev/http_api_reference#create-session-with-chat-assistant) - [Update chat assistant's session](https://ragflow.io/docs/dev/http_api_reference#update-chat-assistants-session) - [List chat assistant's sessions](https://ragflow.io/docs/dev/http_api_reference#list-chat-assistants-sessions) - [Create session with agent](https://ragflow.io/docs/dev/http_api_reference#create-session-with-agent) - [Converse with chat assistant](https://ragflow.io/docs/dev/http_api_reference#converse-with-chat-assistant) - [Converse with agent](https://ragflow.io/docs/dev/http_api_reference#converse-with-agent) - [List agent sessions](https://ragflow.io/docs/dev/http_api_reference#list-agent-sessions) ## 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](https://github.com/infiniflow/infinity) as document engine. ### Related APIs #### HTTP APIs - [List agent sessions](https://ragflow.io/docs/dev/http_api_reference#list-agent-sessions) - [List agents](https://ragflow.io/docs/dev/http_api_reference#list-agents) #### Python APIs - [List agent sessions](https://ragflow.io/docs/dev/python_api_reference#list-agent-sessions) - [List agents](https://ragflow.io/docs/dev/python_api_reference#list-agents) ## v0.14.1 Released on November 29, 2024. ### Improvements 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) ### 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](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) - 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](https://github.com/andrewyng/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 As of this release, **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) 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](https://ragflow.io/docs/dev/upgrade_ragflow#upgrade-ragflow-to-the-most-recent-officially-published-release) before trying this new approach. ::: ### Related APIs #### HTTP APIs - [Create session with agent](https://ragflow.io/docs/dev/http_api_reference#create-session-with-agent) - [Converse with agent](https://ragflow.io/docs/dev/http_api_reference#converse-with-agent) #### Python APIs - [Create session with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent) - [Converse with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent) ### Documentation #### Added documents - [Configurations](https://ragflow.io/docs/dev/configurations) - [Manage team members](https://ragflow.io/docs/dev/manage_team_members) - [Run health check on RAGFlow's dependencies](https://ragflow.io/docs/dev/run_health_check) ## 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** chunk 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: ```bash pip install ragflow-sdk==0.13.0 ``` ::: ### Documentation #### Added documents - [Acquire a RAGFlow API key](./develop/acquire_ragflow_api_key.md) - [HTTP API Reference](./references/http_api_reference.md) - [Python API Reference](./references/python_api_reference.md) ## 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** chunk 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 As of this release, 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](https://ragflow.io/docs/dev/upgrade_ragflow) for instructions on upgrading. ### Documentation #### Added documents - [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow) ## 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: - [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 chunk 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 chunk method. - Supports DOCX, MD, and PDF files in the Q&A chunk 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 chunk 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 chunk 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.