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Docs: Added v0.19.1 release notes (#8398)
### What problem does this PR solve? ### Type of change - [x] Documentation Update
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@ -22,6 +22,24 @@ The embedding models included in a full edition are:
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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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:::
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## v0.19.1
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Released on June 23, 2025.
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### Fixed issues
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- A memory leak issue during high-concurrency requests.
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- A context error occurring when using Sandbox in standalone mode. [#8340](https://github.com/infiniflow/ragflow/pull/8340)
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- An excessive CPU usage issue caused by Ollama. [#8216](https://github.com/infiniflow/ragflow/pull/8216)
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- A bug in the Code Component. [#7949](https://github.com/infiniflow/ragflow/pull/7949)
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- Added support for models installed via Ollama or VLLM when creating a knowledge base through the API. [#8069](https://github.com/infiniflow/ragflow/pull/8069)
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- Enabled role-based authentication for S3 bucket access. [#8149](https://github.com/infiniflow/ragflow/pull/8149)
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### Added models
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- Qwen 3 Embedding. [#8184](https://github.com/infiniflow/ragflow/pull/8184)
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- Voyage Multimodal 3. [#7987](https://github.com/infiniflow/ragflow/pull/7987)
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## v0.19.0
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Released on May 26, 2025.
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@ -33,7 +51,7 @@ Released on May 26, 2025.
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- 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 and OpenAI’s latest ChatGPT o3 inference model.
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> The following features are contributed by our community contributors:
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> The following features have been contributed by our community:
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- Agent component: Enables tool calling within the Generate Component. Thanks to [notsyncing](https://github.com/notsyncing).
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- Markdown rendering: Image references in a markdown file can be displayed after chunking. Thanks to [Woody-Hu](https://github.com/Woody-Hu).
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