--- sidebar_position: 2 slug: /release_notes --- # Release notes Key features, improvements and bug fixes in the latest releases. ## 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](https://ragflow.io/docs/dev/acquire_ragflow_api_key) - [HTTP API Reference](https://ragflow.io/docs/dev/http_api_reference) - [Python API Reference](https://ragflow.io/docs/dev/python_api_reference) ## 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 **YahooFance** 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**, **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**, **DduckDuckGo**, **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 plan to maintain RAGFlow Docker images for ARM. If you are on an ARM platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) 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.