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sidebar_position: 1
slug: /release_notes
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---
# Releases

Key features, improvements and bug fixes in the latest releases.

## v0.26.2

Released on June 26, 2026.

### New features

- Chat channels:
  - Integrates WhatsApp via a QR code scan. [#16238](https://github.com/infiniflow/ragflow/pull/16238)
  - Integrates DingTalk via bot API credentials. [#16183](https://github.com/infiniflow/ragflow/pull/16183)
  - Integrates WeCom via WebSocket connection. [#16175](https://github.com/infiniflow/ragflow/pull/16175)
- File parsing: Adds fallback logic for PP-OCRv6 and similar text recognition models, and integrates image parsing within the PaddleOCR pipeline. [#16150](https://github.com/infiniflow/ragflow/pull/16150)

### Improvements

- Datasets
  - Adds an edge-case check to the file ingestion logic to safely link empty folders to a dataset. [#16296](https://github.com/infiniflow/ragflow/pull/16296)
  - Adds pagination to the `get_flatted_meta_by_kbs()` method to prevent CRUD failures relating to datasets with more than 10,000 documents. [#16095](https://github.com/infiniflow/ragflow/pull/16095)
- Chat channels: Ensures end-user conversation histories persist across restarts but still separate when a channel is bound to a new dialog. [#16274](https://github.com/infiniflow/ragflow/pull/16274)

### i18n

- Expands i18n coverage and refines translations for the Korean UI. [#16203](https://github.com/infiniflow/ragflow/pull/16203)；
- Adds missing French translations for chat channels, username validation, and model editing. [#16217](https://github.com/infiniflow/ragflow/pull/16217)

### Bug fixes

- File parsing:
  - A `ValueError` was raised during `.docx` parsing on 'Heading' styles. [#16284](https://github.com/infiniflow/ragflow/pull/16284)
  - Tables in `.docx` files were silently removed by the laws document parser. [#16155](https://github.com/infiniflow/ragflow/pull/16155)
  - Lone Markdown headers were separated from their subsequent sections when a DeepDoc delimiter was set. [#16109](https://github.com/infiniflow/ragflow/pull/16109)
  - Markdown tables appeared twice in chunk results, once as a standalone chunk and again within a regular text chunk. [#16143](https://github.com/infiniflow/ragflow/pull/16143)
- MCP
  - The MCP server hung indefinitely when encountering empty document pages; the final page of documents was silently dropped due to flawed pagination. [#16285](https://github.com/infiniflow/ragflow/pull/16285)
  - The MCP connection and dataset discovery process failed because the server's hardcoded fetch limit exceeded the introduced `page_size` restriction. [#16148](https://github.com/infiniflow/ragflow/pull/16148)
- Dataflow
  - Restores the dataflow rerun endpoint and ensures the ingestion response includes the DSL payload to reliably render the timeline and parser views. [#16292](https://github.com/infiniflow/ragflow/pull/16292)
  - Restores dataflow parser defaults and returns the actual SSE payload, ensuring pipeline runs correctly surface message IDs and log updates. [#16290](https://github.com/infiniflow/ragflow/pull/16290)
- LLM: Failed to use the new `gemini-3.5-flash` model via the Google Cloud (Vertex AI) provider using `eu` or `us` region endpoint. This is resolved by explicitly multi-region routing requests to the required `aiplatform.<region>.rep.googleapis.com` domains instead of synthesized `<region>-aiplatform.googleapis.com` hosts. [#15990](https://github.com/infiniflow/ragflow/pull/15990)
- UI/UX: The metadata add modal sent empty values to the backend. [#15229](https://github.com/infiniflow/ragflow/pull/15229)

## v0.26.1

Released on June 17, 2026.

### New features

- **Model providers**: Allows users to modify the model type of existing model configurations. [#16029](https://github.com/infiniflow/ragflow/pull/16029)
- **Chat channels**: Enables users to deploy RAGFlow assistants as chatbots within external messaging platforms like Discord and Feishu. [#15850](https://github.com/infiniflow/ragflow/pull/15850)
- **Observability**: Groups multi-turn chat traces by session within Langfuse to facilitate conversation debugging and replay. [#15679](https://github.com/infiniflow/ragflow/pull/15679)

### i18n

- Adds ~70 missing translation keys for the French UI. [#15983](https://github.com/infiniflow/ragflow/pull/15983)

### Bug fixes

- **Model provider**: Fixes inaccurate token billing, corrects embedding truncation limits to prevent indexing failures, and refactors error handling to surface root error causes. [#15424](https://github.com/infiniflow/ragflow/pull/15424)
- **API**: Adds a legacy mode to the `/chat/completions` endpoint to restore the v0.23.0 style `<think>` output for backward compatibility. [#16014](https://github.com/infiniflow/ragflow/pull/16014) See also [Converse with chat assistant](./references/http_api_reference.md#converse-with-chat-assistant).

## v0.26.0

Released on June 11, 2026.

### New features

- **Model providers**
  - Implements auto-populated model lists for multiple providers, eliminating the need to type model names manually. This feature currently supports: Ollama, OpenRouter, vLLM, OpenAI-API-Compatible, LM-Studio, VolcEngine, Xinference, LocalAI, BaiduYiyan, GPUStack, and Fish Audio.
  - Allows configuring multiple API keys for the same model provider. [#14595](https://github.com/infiniflow/ragflow/pull/14595)
  - Dynamically populates model selection dropdowns in the UI by fetching the currently available models directly from remote model providers. [#15711](https://github.com/infiniflow/ragflow/pull/15711)
- **Data source connectors**: Implements new data source connectors for Outlook, OneDrive, Microsoft Teams, Slack, SharePoint, Salesforce, and Azure Blob Storage. [#15333](https://github.com/infiniflow/ragflow/pull/15333)[#15330](https://github.com/infiniflow/ragflow/pull/15330)[#15332](https://github.com/infiniflow/ragflow/pull/15332)[#15188](https://github.com/infiniflow/ragflow/pull/15188)[#15190](https://github.com/infiniflow/ragflow/pull/15190)[#15462](https://github.com/infiniflow/ragflow/pull/15462)[#15466](https://github.com/infiniflow/ragflow/pull/15466)
- **Dataset** - Implements a checkpoint and resume feature for community extraction and entity resolution, the most expensive and time-consuming parts of the GraphRAG indexing pipeline. [#15518](https://github.com/infiniflow/ragflow/issues/15518)[#15523](https://github.com/infiniflow/ragflow/pull/15523)

### Improvements

- Removes `<think>` text buffering to ensure reasoning-capable models feel faster and more transparent during interactions. [#15891](https://github.com/infiniflow/ragflow/pull/15891)
- Marks MySQL migrations as applied. [#15504](https://github.com/infiniflow/ragflow/pull/15504)

### Model Support

- Four new SiliconFlow models [#15383](https://github.com/infiniflow/ragflow/pull/15383)
- MiniMax-M3 model [#15513](https://github.com/infiniflow/ragflow/pull/15513)
- Latest Anthropic models [#15516](https://github.com/infiniflow/ragflow/pull/15516)
- Voyage 4 model family [#15516](https://github.com/infiniflow/ragflow/pull/15516)
- Cohere model list. [#15576](https://github.com/infiniflow/ragflow/pull/15576)

### i18n

- Completes Korean translation. [#15863](https://github.com/infiniflow/ragflow/pull/15863)
- Completes Italian translation. [#15729](https://github.com/infiniflow/ragflow/pull/15729)

### Bug fixes

- The thinking mode of MiniMax models was not correctly enabled. [#15496](https://github.com/infiniflow/ragflow/pull/15496)
- Infinite loops were triggered when the thinking mode was enabled for Qwen3.5 and Qwen3.6 models. [#15101](https://github.com/infiniflow/ragflow/pull/15101)
- Streamed answers were being duplicated when using the OpenAI-compatible chat completions API endpoint. [#15286](https://github.com/infiniflow/ragflow/issues/15286)[#15443](https://github.com/infiniflow/ragflow/pull/15443)
- Serialization errors were caused during chat completions when invalid numeric scores like `NaN` (Not-a-Number) or `Inf` (Infinity) were passed to the JSON encoder. [#15245](https://github.com/infiniflow/ragflow/issues/15245)[#15266](https://github.com/infiniflow/ragflow/pull/15266)
- Chat completions using LiteLLM providers were failing because unrecognized internal configuration parameters were not being filtered out before reaching the external APIs. [#15427](https://github.com/infiniflow/ragflow/issues/15427)[#15432](https://github.com/infiniflow/ragflow/pull/15432)
- The OpenAI-compatible chat completions API was defaulting to streamed responses. [#15356](https://github.com/infiniflow/ragflow/issues/15356)[#15394](https://github.com/infiniflow/ragflow/pull/15394)
- Empty `AND` results were incorrectly dropped during metadata filtering. [#15477](https://github.com/infiniflow/ragflow/pull/15477)
- Repetitive page chrome, such as headers and footers, was incorrectly extracted as main text by the MinerU parser. [#15335](https://github.com/infiniflow/ragflow/issues/15335)[#15387](https://github.com/infiniflow/ragflow/pull/15387)
- English chart titles were missing during document extraction in the DeepDoc module. [#15481](https://github.com/infiniflow/ragflow/pull/15481)
- Empty outputs were returned by the TitleChunker for `json` and `chunks` upstream formats [#14247](https://github.com/infiniflow/ragflow/pull/14247)[#15396](https://github.com/infiniflow/ragflow/pull/15396)
- An error message was missing when a .tsv file upload attempt failed. [#15284](https://github.com/infiniflow/ragflow/pull/15284)
- API tokens missing beta values caused token retrieval errors. [#15405](https://github.com/infiniflow/ragflow/pull/15405)
- Caps the maximum page size to fix system crashes or slowdowns from large queries. [#15292](https://github.com/infiniflow/ragflow/pull/15292)
- Client errors were caused by the OpenAI-compatible chat completion API incorrectly defaulting to streamed responses. [#15356](https://github.com/infiniflow/ragflow/issues/15356)[#15394](https://github.com/infiniflow/ragflow/pull/15394)
- HTTP 500 internal server errors were triggered instead of standard 4xx client errors when users attempted to download missing files from the storage backend. [#15369](https://github.com/infiniflow/ragflow/issues/15369)[#15371](https://github.com/infiniflow/ragflow/pull/15371)
- GraphRAG entity ranking was broken. [#15795](https://github.com/infiniflow/ragflow/issues/15795)[#15797](https://github.com/infiniflow/ragflow/pull/15797)

## v0.25.6

Released on May 26, 2026.

### New features

- Agent: Adds a **Browser** component that enables AI to autonomously navigate and interact with web pages. [#14888](https://github.com/infiniflow/ragflow/pull/14888)

### Improvements

- RAG: Stabilizes RAPTOR's AHC mode (Ψ-RAG), which was introduced in v0.25.3 to resolve previous semantic loss by building individual document trees and then merging them hierarchically. This new approach significantly accelerates index construction and outperforms the legacy GMM mode in Recall@5 and average F1. Users retain the option to switch between the two modes. [#14674](https://github.com/infiniflow/ragflow/issues/14674)[#14679](https://github.com/infiniflow/ragflow/pull/14679)
- Agent: Introduces lightweight `@tool` decorator to streamline Python function registration process for chat models. [#15047](https://github.com/infiniflow/ragflow/pull/15047)
- Agent: Enables agent messages to display base64-encoded images. [#15212](https://github.com/infiniflow/ragflow/pull/15212)
- Agent: Exposes **Doc Generator** component's file metadata as discrete variables. [#15080](https://github.com/infiniflow/ragflow/pull/15080)
- Agent: Allows developers to pass `chat_template_kwargs` to agent chat completion endpoint. [#14182](https://github.com/infiniflow/ragflow/issues/14182)[#14542](https://github.com/infiniflow/ragflow/pull/14542) See also [Converse with agent](./references/http_api_reference.md#converse-with-agent)

### Bug fixes

- Fixes `/chat/completions` to allow sending only latest message in API payload and removes requirement to transmit full conversation history. [#15197](https://github.com/infiniflow/ragflow/pull/15197) See also [Converse with chat assistant](./references/http_api_reference.md#converse-with-chat-assistant).
- Weight assigned to vector similarity was not properly applied during the retrieval phase. [#15108](https://github.com/infiniflow/ragflow/pull/15108)
- Users were unable to save parser configurations on the dataset configuration page. [#15175](https://github.com/infiniflow/ragflow/issues/15175)[#15177](https://github.com/infiniflow/ragflow/pull/15177)
- Log text on a data source's details page was truncated. [#15056](https://github.com/infiniflow/ragflow/pull/15056)
- An unresponsive "Status" filter on the document list page prevented users from filtering or managing uploaded documents by their parsing status. [#15170](https://github.com/infiniflow/ragflow/issues/15170)[#15216](https://github.com/infiniflow/ragflow/pull/15216)
- Calling `GET /agents/<agent_id>/sessions/<session_id>` with a missing or invalid session ID caused a server error. [#14989](https://github.com/infiniflow/ragflow/issues/14989)[#15011](https://github.com/infiniflow/ragflow/pull/15011)
- RAG: RAPTOR construction process halted when using the [Infinity](https://github.com/infiniflow/infinity) document engine. [#14998](https://github.com/infiniflow/ragflow/pull/14998)
- The system failed to correctly parse structured content returned by Mistral reasoning models. [#14805](https://github.com/infiniflow/ragflow/pull/14805)
- The **Parser** component in an ingestion pipeline incorrectly retained raw HTML tags in its text output. [#14831](https://github.com/infiniflow/ragflow/issues/14831)[#14920](https://github.com/infiniflow/ragflow/pull/14920)
- The table parser incorrectly extracted or attached metadata during document processing. [#15127](https://github.com/infiniflow/ragflow/pull/15127)
- Asynchronous background tasks and nested event loops were not properly handled, causing backend instability. [#14755](https://github.com/infiniflow/ragflow/issues/14755)[#14761](https://github.com/infiniflow/ragflow/pull/14761)
- Prompt variables configured in the **Agent** component disappeared after being entered. [#15218](https://github.com/infiniflow/ragflow/pull/15218)

### i18n

- Fully translates the interface into French with the addition of roughly 1,400 localization keys. [#15192](https://github.com/infiniflow/ragflow/pull/15192)

## v0.25.5

Released on May 20, 2026.

### New features

- Introduces local and SSH provider options for sandbox environment settings within the admin interface, allowing administrators to configure execution environments without editing environment variables. [#15039](https://github.com/infiniflow/ragflow/pull/15039)

### Improvements

- Elasticsearch: Accelerates the retrieval process by removing unnecessary vector fetches during the main search phase, reducing latency by 50–100%. [#14970](https://github.com/infiniflow/ragflow/pull/14970)
- Pushes metadata filters down to the [Infinity](https://github.com/infiniflow/infinity) document engine, significantly improving retrieval performance. [#14974](https://github.com/infiniflow/ragflow/pull/14974)
- Introduces Redis-based caching for Text-to-Speech model outputs, eliminating redundant API calls for identical text to reduce latency and save provider quota. [#14851](https://github.com/infiniflow/ragflow/pull/14851)
- Reduces server startup time by 5-9 seconds and saves roughly 200MB of memory by replacing heavy module-level imports with lazy runtime loading. [#14973](https://github.com/infiniflow/ragflow/pull/14973)
- Optimizes the connector dashboard. [#14979](https://github.com/infiniflow/ragflow/pull/14979)
- Increases minimum supported Python version to 3.13. [#14767](https://github.com/infiniflow/ragflow/pull/14767)

### Bug fixes

- Atomic database updates: Wraps document and dataset chunk counter updates in atomic database transactions to prevent data drift. [#14866](https://github.com/infiniflow/ragflow/issues/14866)[#14867](https://github.com/infiniflow/ragflow/pull/14867)
- Data source: the GitHub data source connector was failing to sync any content by default. [#13975](https://github.com/infiniflow/ragflow/issues/13975)[#14062](https://github.com/infiniflow/ragflow/pull/14062)
- The Tongyi-Qianwen text embedding models were hitting the wrong API endpoints when configured with international or Chinese regional URLs. [#14784](https://github.com/infiniflow/ragflow/pull/14784)
- Agent: Fully aggregates message content, reference data, and structured outputs across all generated events to fix incomplete responses in the non-streaming `/api/v1/agentbots/<agent_id>/completions` endpoint. [#13384](https://github.com/infiniflow/ragflow/issues/13384)[#14848](https://github.com/infiniflow/ragflow/pull/14848)
- Prevents the **Retrieval** component's manual metadata filters from getting stuck on the first loop's value by making a temporary copy of the filter settings to preserve the original placeholder.[#12582](https://github.com/infiniflow/ragflow/issues/12582)[#14849](https://github.com/infiniflow/ragflow/pull/14849)
- Agent: Fixed MCP tool name duplication.[#14217](https://github.com/infiniflow/ragflow/pull/14217)
- Agent: top_k passing issues [#14760](https://github.com/infiniflow/ragflow/pull/14760)
- Chat file attachment loss. [#13993](https://github.com/infiniflow/ragflow/pull/13993)
- IMAP synchronization process crashed when multiple email addresses or quoted commas were detected in "From" header. [#14963](https://github.com/infiniflow/ragflow/issues/14963)[#14964](https://github.com/infiniflow/ragflow/issues/14964)[#15006](https://github.com/infiniflow/ragflow/pull/15006)
- Langfuse integration failed to track token consumption. [#9837](https://github.com/infiniflow/ragflow/issues/9837)[#13294](https://github.com/infiniflow/ragflow/pull/13294)
- Enhances the stability and fault tolerance of the reranking module by implementing network timeouts, crash-prevention safeguards, and specific provider bug fixes. [#14264](https://github.com/infiniflow/ragflow/pull/14264)
- Increases minimum supported Nginx to 1.31.0. [#14928](https://github.com/infiniflow/ragflow/issues/14928)[#15007](https://github.com/infiniflow/ragflow/pull/15007)

## v0.25.4

Released on May 14, 2026

### New features

- Introduces a generic RESTful API connector, enabling configurable data ingestion from niche or enterprise-specific platforms into RAGFlow. [#13545](https://github.com/infiniflow/ragflow/pull/13545)
- Agent: Implements tag management to help users categorize, filter, and sort their Agent apps. [#14799](https://github.com/infiniflow/ragflow/pull/14799)

### Improvements

- Adds widget customization and persistence, allowing users to tailor their chat interface and ensure their settings are retained across sessions. [#14603](https://github.com/infiniflow/ragflow/pull/14603)

### Model support

- Adds gpt-5.4-mini and gpt-5.4-nano to the OpenAI model list [#14908](https://github.com/infiniflow/ragflow/pull/14908)

### Bug fixes

- Corrects the API endpoint for downloading original files from a specified dataset. [#14910](https://github.com/infiniflow/ragflow/pull/14910) See also [Download document](./references/http_api_reference.md#download-document).

## v0.25.3

Released on May 13, 2026.

### New features

- Enables assigning specific roles like content, metadata, and primary key, to table columns. [#13710](https://github.com/infiniflow/ragflow/pull/13710)

### Improvements

- S3 connector: Implements ETag-based incremental synchronization for S3 data sources, drastically reducing sync time and AWS egress costs for users with massive-volumn S3-based datasets. [#14628](https://github.com/infiniflow/ragflow/issues/14628)[#14677](https://github.com/infiniflow/ragflow/pull/14677)
- API refactoring and security
  - Continues the transition of web APIs to RESTful conventions, ensuring backward compatibility for all legacy endpoints.
  - Binds the `user_id` in `POST /api/v1/messages` to the authenticated JWT principal. [#14745](https://github.com/infiniflow/ragflow/pull/14745)
  - Secures the sandbox executor against dynamic and indirect code execution bypasses. [#14690](https://github.com/infiniflow/ragflow/pull/14690)
  - Enforces HTTP request timeouts across the LLM integration layer. [#14313](https://github.com/infiniflow/ragflow/pull/14313)
- Refactors thread pool lifecycle management in `file_service.py` and `task_executor.py` for more efficient, lightweight resource handling. [#14668](https://github.com/infiniflow/ragflow/pull/14668)
- Agent: Enables the **Code** component to output and display file-based attachments, such as charts and images, directly in the chat. [#14787](https://github.com/infiniflow/ragflow/pull/14787)
- Reduces ingestion server boot time. [#14894](https://github.com/infiniflow/ragflow/pull/14894)

### Bug fixes

- Images in multi-sheet Excel workbooks were not scoped by sheet, causing images to be incorrectly attributed across different worksheets. [#14120](https://github.com/infiniflow/ragflow/pull/14120)
- Agent: Splits the **Message** component output into distinct 'waiting' and 'message' states when nested inside an **Iteration** component alongside a **Wait** component. [#14839](https://github.com/infiniflow/ragflow/pull/14839)
- Agent: The **Iteration** component failed to correctly pass array elements to its child components due to a naming mismatch between the expected `IterationItem` alias and the runtime `item` variable. [#14146](https://github.com/infiniflow/ragflow/pull/14146)
- Agent: Template strings in tool-type components like **Email** and **Invoke** failed to interpolate; `{{variable}}` placeholders were passed through as raw text. [#14601](https://github.com/infiniflow/ragflow/pull/14601)
- Volcengine (Doubao/Ark) endpoints were not visible in the provider list. [#14702](https://github.com/infiniflow/ragflow/pull/14702)

## v0.25.2

Released on May 11, 2026.

### Improvements

- API refactoring and unification: Continues the transition of web APIs to RESTful conventions, ensuring backward compatibility for all legacy endpoints.

### Data source

- Introduces a lightweight snapshot mechanism for synchronizing deleted files across eight data sources—including Moodle, DingTalk AI Table, and RSS—ensuring a faithful reflection of all remote data sources. [#14362](https://github.com/infiniflow/ragflow/issues/14362)[#14499](https://github.com/infiniflow/ragflow/pull/14499)

### Bug fixes

- Metadata visibility issues during v0.24.0 to v0.25.0 upgrades.
- Duplicate chat output.
- Metadata filtering was handled in-memory instead of leveraging Elasticsearch, incurring performance bottlenecks. [#14576](https://github.com/infiniflow/ragflow/pull/14576)

## v0.25.1

Released on April 29, 2026.

### Improvements

- API refactoring and unification: Standardizes web APIs to RESTful conventions across all endpoints, unifying document creation and indexing flows while maintaining backward compatibility.
- Parsing optimizations: Adds [OpenDataLoader](https://github.com/opendataloader-project/opendataloader-pdf) PDF parser backend. [#14097](https://github.com/infiniflow/ragflow/pull/14097)
- Introduces lazy loading and chunked parsing for large PDFs (&gt;50 pages), significantly reducing memory footprint. [#14385](https://github.com/infiniflow/ragflow/pull/14385)

### Data source

Enables synchronizing deleted files in Bitbucket, Gmail, Google Drive, and Airtable. [#14362](https://github.com/infiniflow/ragflow/issues/14362)

### Model support

- DeepSeek v4

### Model providers

- UCloud

### Bug fixes

- Metadata visibility issues during v0.24.0 to v0.25.0 upgrades.
- Duplicate chat output.

## v0.25.0

Released on April 21, 2026.

### New features

- Agent
  - Introduces seven prebuilt ingestion pipeline templates.
  - Agent apps can be published.
  - Supports sandbox code execution and chart generation.
  - Adds a beginner's data analytics Agent template.
- Memory: Supports user-level memory storage and retrieval.
- New UI language: Arabic (implemented a Right-to-Left layout), Bulgarian, and Turkish.
- Ecosystem integration: RAGFlow datasets are accessible via OpenClaw.

### Improvements

- Optimizes Docx parsing by supporting image lazy-loading, reducing memory footprint.
- Optimizes Chat, Agent, and Search embedded dialog pages for mobile compatibility.
- Underlying system & infrastructure optimization:
  - Bumps RAGFlow's document engine, Elasticsearch to 9.x.
  - Switches the default object storage container to `pgsty/minio` due to the deprecation of the official MinIO images.
  - Adds database migration scripts; see [this readme](https://github.com/infiniflow/ragflow/tree/74b44e1aa3ecd6687b3aa4ef731d0187720c3cb5/tools/scripts) for further details.

### Model support

- MiniMax-M2.7 series
- Perplexity embedding model (pplx-embed)
- Tongyi rerank model

### New model providers

- avian.io
- ragcon.ai

### Data sources

- Seafile
- RSS
- DingTalk AI Table
- GitHub: Enables synchronization for deleted files.

## v0.24.0

Released on February 10, 2026.

### New features

- Memory
  - Introduces memory management APIs (HTTP and Python).
  - Outputs Memory extraction log to the console.
- Dataset
  - Supports batch metadata management.
  - Renames "ToC (Table of Contents)" to "PageIndex". See [here](./guides/dataset/advanced/extract_table_of_contents.md).
- Agent
  - Launches a new Chat-like Agent conversation management interface that retains sessions and dialogue history.
  - Introduces a multi-Sandbox mechanism supporting local gVisor and Alibaba Cloud, with compatibility for mainstream Sandbox APIs (configurable in the Admin page).
- Chat
  - Adds a new "Thinking" mode and removes the previous "Reasoning" configuration option.
  - Optimizes retrieval strategies for deep-research scenarios, enhancing recall accuracy.
- Admin
  - Supports multiple Admin accounts.
- Model configuration center
  - Adds model connection test for new models.

### MySQL alternative

- Supports OceanBase as an alternative to MySQL.

### Model support

- Kimi 2.5
- Stepfun 3
- doubao-embedding-vision
- PaddleOCR-VL

### Data sources

- Zendesk
- Bitbucket

### API changes

#### HTTP API

[Memory management API](./references/http_api_reference.md#memory-management)

#### Python API

[Memory management API](./references/python_api_reference.md#memory-management)

## v0.23.1

Released on December 31, 2025.

### Improvements

- Memory: Enhances the stability of memory extraction when all memory types are selected.
- RAG: Refines the context window extraction strategy for images and tables.

### Fixed issues

- Memory: 
  - The RAGFlow server failed to start if an empty memory object existed.
  - Unable to delete a newly created empty Memory.
- RAG: MDX file parsing was not supported.

### Data sources

- GitHub
- Gitlab
- Asana
- IMAP

## v0.23.0

Released on December 27, 2025.

### New features

- Memory
  - Implements a **Memory** interface for managing memory.
  - Supports configuring context via the **Retrieval** or **Message** component.
- Agent
  - Improves the **Agent** component's performance by refactoring the underlying architecture.
  - The **Agent** component can now output structured data for use in downstream components.
  - Supports using webhook to trigger agent execution.
  - Supports voice input/output.
  - Supports configuring multiple **Retrieval** components per **Agent** component.
- Ingestion pipeline
  - Supports extracting table of contents in the **Transformer** component to improve long-context RAG performance.
- Dataset
  - Supports configuring context window for images and tables.
  - Introduces parent-child chunking strategy.
  - Supports auto-generation of metadata during file parsing.
- Chat: Supports voice input.

### Improvements

- RAG: Accelerates GraphRAG generation significantly.
- Bumps RAGFlow's document engine, [Infinity](https://github.com/infiniflow/infinity) to v0.6.15 (backward compatible).

### Data sources

- Google Cloud Storage
- Gmail
- Dropbox
- WebDAV
- Airtable

### Model support

- GPT-5.2
- GPT-5.2 Pro
- GPT-5.1
- GPT-5.1 Instant
- Claude Opus 4.5
- MiniMax M2
- GLM-4.7.
- A MinerU configuration interface.
- AI Badgr (model provider).

### API changes

#### HTTP API

- [Converse with Agent](./references/http_api_reference.md#converse-with-agent) returns complete execution trace logs.
- [Create chat completion](./references/http_api_reference.md#create-chat-completion) supports metadata-based filtering.
- [Converse with chat assistant](./references/http_api_reference.md#converse-with-chat-assistant) supports metadata-based filtering.

## v0.22.1

Released on November 19, 2025.

### Improvements

- Agent:
  - Supports exporting Agent outputs in Word or Markdown formats.
  - Adds a **List operations** component.
  - Adds a **Variable aggregator** component.
- Data sources:
  - Supports S3-compatible data sources, e.g., MinIO.
  - Adds data synchronization with JIRA.
- Continues the redesign of the **Profile** page layouts.
- Upgrades the Flask web framework from synchronous to asynchronous, increasing concurrency and preventing blocking issues caused when requesting upstream LLM services.

### Fixed issues

- A v0.22.0 issue: Users failed to parse uploaded files or switch embedding model in a dataset containing parsed files using a built-in model from a `-full` RAGFlow edition.
- Image concatenated in Word documents. [#11310](https://github.com/infiniflow/ragflow/pull/11310)
- Mixed images and text were not correctly displayed in the chat history.

### Newly supported models

- Gemini 3 Pro Preview

## v0.22.0

Released on November 12, 2025.

### Breaking Changes

:::danger IMPORTANT
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](https://github.com/docling-project/docling) 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](./faq.mdx#how-to-use-mineru-to-parse-pdf-documents).

### Improvements

- Enhances UI/UX for the dataset and personal center pages.
- Upgrades RAGFlow's document engine, [Infinity](https://github.com/infiniflow/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](./guides/dataset/advanced/extract_table_of_contents.md).
- 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.

### Newly supported 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](./guides/agent/agent_component_reference/agent.mdx#system-prompt).
  - **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](./guides/agent/agent_component_reference/execute_sql.md).
- Chat: Re-enables **Reasoning** and **Cross-language search**.

### Newly supported 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](./references/http_api_reference.md#retrieve-chunks) method, enabling metadata-based chunk filtering during retrieval. [#9877](https://github.com/infiniflow/ragflow/pull/9877)

#### Python APIs

- Adds a parameter `metadata_condition` to the [Retrieve chunks](./references/python_api_reference.md#retrieve-chunks) method, enabling metadata-based chunk filtering during retrieval. [#9877](https://github.com/infiniflow/ragflow/pull/9877)

## v0.20.4

Released on August 27, 2025.

### Improvements

- Agent component: Completes Chinese localization for the Agent component.
- Introduces the `ENABLE_TIMEOUT_ASSERTION` environment 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.

### Newly supported 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](https://github.com/infiniflow/ragflow/pull/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](https://github.com/infiniflow/ragflow/pull/9469)

### API changes

#### Deprecated

[Create session with agent](./references/http_api_reference.md#create-session-with-agent)

## 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.

### Newly supported models

- GPT-5
- Claude 4.1

### New agent templates (both workflow and agentic)

- Text-to-SQL data expert 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](https://github.com/infiniflow/ragflow/pull/9325)
- Choose Your Knowledge Base Agent: Delivers higher-quality responses with extended reasoning time, suited for complex queries. [#9325](https://github.com/infiniflow/ragflow/pull/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.
- Photo text translator: 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](https://github.com/infiniflow/ragflow/pull/8223)
- A context error occurring when using Sandbox in standalone mode. [#8340](https://github.com/infiniflow/ragflow/pull/8340)
- An excessive CPU usage issue caused by Ollama. [#8216](https://github.com/infiniflow/ragflow/pull/8216)
- A bug in the Code Component. [#7949](https://github.com/infiniflow/ragflow/pull/7949)
- Added support for models installed via Ollama or VLLM when creating a dataset through the API. [#8069](https://github.com/infiniflow/ragflow/pull/8069)
- Enabled role-based authentication for S3 bucket access. [#8149](https://github.com/infiniflow/ragflow/pull/8149)

### Newly supported models

- Qwen 3 Embedding. [#8184](https://github.com/infiniflow/ragflow/pull/8184) 
- Voyage Multimodal 3. [#7987](https://github.com/infiniflow/ragflow/pull/7987)

## v0.19.0

Released on May 26, 2025.

### New features

- [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 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](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).

### 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)

## 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.

![export_agent](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/export_agent_as_json.jpg)

### 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

- [Set page rank](./guides/dataset/set_page_rank.md)
- [Enable RAPTOR](./guides/dataset/advanced/enable_raptor.md)
- [Set variables for your chat assistant](./guides/chat/set_chat_variables.md)
- [Launch RAGFlow MCP server](./develop/mcp/launch_mcp_server.md)

## 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

- [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 (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

- [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 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](./guides/dataset/select_pdf_parser.md).
- 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)

### API changes

#### 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 dataset rather than on an individual file, and automatically updated when a newly uploaded file starts parsing. See [here](./guides/dataset/advanced/construct_knowledge_graph.md).
- 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 dataset 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** dataset as a key milestone towards bridging the semantic gap between query and response.

:::danger IMPORTANT
The **Tag dataset** feature is *unavailable* on the [Infinity](https://github.com/infiniflow/infinity) document engine.
:::

### Documentation

#### Added documents

- [Construct knowledge graph](./guides/dataset/advanced/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 dataset is changed, embedding models in other datasets 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:

- [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 datasets.
- 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.

### API changes

#### 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

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)

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](./administrator/upgrade_ragflow.mdx#upgrade-ragflow-to-the-most-recent-officially-published-release) before trying this new approach.
:::

### API changes

#### 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](./guides/team/manage_team_members.md)
- [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** 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:

```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** 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 two built-in embedding models.

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](./administrator/upgrade_ragflow.mdx) for instructions on upgrading.

### Documentation

#### Added documents

- [Upgrade RAGFlow](./administrator/upgrade_ragflow.mdx)

## 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**, **Jiekou.AI**, **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](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 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](./develop/build_docker_image.mdx) to build a RAGFlow Docker image.
:::

### API changes

#### 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 chunking method to reduce file chunking time.

### API changes

#### 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.
