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---
sidebar_position: 2
slug: /release_notes
---
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# Releases
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Key features, improvements and bug fixes in the latest releases.
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:::info
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`
- **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
- 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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:::
## v0.19.0
Released on May 26, 2025.
### 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.
- 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 ).
- Markdown rendering: Image references in a markdown file can be displayed after chunking. Thanks to [Woody-Hu ](https://github.com/Woody-Hu ).
- 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
#### Added documents
- [Select PDF parser ](./guides/dataset/select_pdf_parser.md )
- [Enable Excel2HTML ](./guides/dataset/enable_excel2html.md )
- [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
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
- 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.
- 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.

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### 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.
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### Documentation
#### Added documents
- [Set page rank ](./guides/dataset/set_page_rank.md )
- [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
Released on March 13, 2025.
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### 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.
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### 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).
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- Supports CSV files in the **General** chunking method.
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### Fixed issues
- Unable to add models via Ollama/Xinference, an issue introduced in v0.17.1.
### Related APIs
#### 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
Released on March 11, 2025.
### Improvements
- Improves English tokenization quality.
- Improves the table extraction logic in Markdown document parsing.
- 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
- A repetitive knowledge graph extraction issue.
- 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.
- Unable to preview diagrams or images in an AI chat.
### Documentation
#### 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.
### 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.
- 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.
- 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:

The following is a screenshot of a conversation that integrates Deep Research:

### 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
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- [Run retrieval test ](./guides/dataset/run_retrieval_test.md )
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## v0.16.0
Released on February 6, 2025.
### New features
- 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.
:::danger IMPORTANT
The **Tag knowledge base** feature is *unavailable* on the [Infinity ](https://github.com/infiniflow/infinity ) document engine.
:::
### Documentation
#### Added documents
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- [Construct knowledge graph ](./guides/dataset/construct_knowledge_graph.md )
- [Set metadata ](./guides/dataset/set_metadata.md )
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- [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 )
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## 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 ).
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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.
- 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 )
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## 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
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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.
### 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 )
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## v0.14.1
Released on November 29, 2024.
### 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
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.
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## v0.14.0
Released on November 26, 2024.
### 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.
- 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.
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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
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
#### 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 )
#### Python APIs
- [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 )
### Documentation
#### Added documents
- [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 )
## v0.13.0
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Released on October 31, 2024.
### New features
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- Adds the team management functionality for all users.
- 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.
- 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
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- [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 )
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## 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.
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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.
See [Upgrade RAGFlow ](https://ragflow.io/docs/dev/upgrade_ragflow ) for instructions on upgrading.
### Documentation
#### Added documents
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- [Upgrade RAGFlow ](https://ragflow.io/docs/dev/upgrade_ragflow )
## v0.11.0
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Released on September 14, 2024.
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### 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 )
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- [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.
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- 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** .
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## v0.9.0
Released on August 6, 2024.
### New features
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- Supports GraphRAG as a chunking method.
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- Introduces Agent component **Keyword** and search tools, including **Baidu** , **DuckDuckGo** , **PubMed** , **Wikipedia** , **Bing** , and **Google** .
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- 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** .
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- Supports DOCX files in the MANUAL chunking method.
- Supports DOCX, MD, and PDF files in the Q& A chunking method.
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## 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.
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- Supports HTML files in the GENERAL chunking method.
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- Provides HTTP and Python APIs for deleting documents by ID.
- Supports ARM64 platforms.
:::danger IMPORTANT
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While we also test RAGFlow on ARM64 platforms, we do not maintain RAGFlow Docker images for ARM.
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If you are on an ARM platform, follow [this guide ](./develop/build_docker_image.mdx ) to build a RAGFlow Docker image.
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:::
### 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.
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- Supports disabling **Layout Recognition** in the GENERAL chunking method to reduce file chunking time.
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### 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.