QAnything
NetEase Youdao has launched a local knowledge base question-answering system, which, according to the official statement, is built on the self-developed Ziyue large model and retrieval-augmented generation capabilities. It supports uploading documents in various formats and can be deployed offline in a private environment.
Updated: 2026-10-26
What is QAnything?
QAnything is a local knowledge base question answering system launched by NetEase Youdao, and its full official website name is "Question and Answer based on Anything". Its idea is very straightforward: feed any local files of various formats into it, and you can get fast and accurate answers. The key words listed in the official warehouse include data security, cross-lingual question answering, support for question answering on massive data, and direct availability in production environments. It also emphasizes support for installation and use with the network cable unplugged throughout the process.
Who is it for?
- Technical teams of government, enterprise and financial institutions that have internal knowledge bases but whose data cannot leave the intranet.
- Academic researchers who need to retrieve a large number of documents and materials.
- Enterprise IT teams that want to turn product documentation and work orders into a question-and-answer system.
- Engineers who want to run an open-source retrieval solution on their own GPUs for secondary development.
Key features
6Multi-format Support
The official website lists supported formats including PDF, Word, PPT, Excel, Markdown, emails, TXT, images, CSV and web links.
Data Security
The official version states that it supports installation and usage with a complete network disconnection, making it suitable for intranet and private deployment scenarios.
Cross-lingual Q&A
Switch freely between Chinese and English Q&A, unrestricted by the language of the documents themselves.
Question Answering on Massive Data
The official solution adopts a two-stage retrieval and ranking approach, claiming to resolve the issue of performance degradation in large-scale data retrieval, delivering better results with more data.
Multi-knowledgebase Q&A
Supports selecting multiple knowledgebases for Q&A at one time.
Two Deployment Methods
The official version provides both Python and Docker editions. The Python edition is suitable for quickly experiencing new features, while the Docker edition supports production environments, offline installation, high concurrency, and multi-GPU inference.
How to use QAnything
- For production environments and offline deployment, choose the Docker version.
- The official clearly states that the Python version does not support production environments and offline installation.
- First verify the retrieval quality on a small number of documents before importing the full dataset to avoid being misled by early conclusions.
- The open-source version is based on open-source large models and has undergone question-and-answer fine-tuning.
- The official note states that commercial use must comply with the licenses of the corresponding models, and the license agreement should be reviewed before deployment.
- The official provides an online experience site and access points such as Youdao Speed Reading, where you can try it online first before deciding to deploy it on your own.
- For data involving personal privacy and commercial confidentiality, data anonymization and access control must still be implemented in accordance with the requirements of the organization.
- The official website and repository update functions with each version, so please refer to the documentation for the specific version before installation.
- The official README mentions that the project includes an FAQ and a feedback channel for feature requests.
- if you encounter issues, you can check the FAQ first before submitting feedback.
Traffic & popularity
Data month Sep 2026
QAnything receives about 1.5K visits per month and ranks #10,935,151 worldwide.
Monthly visits
12 monthsTraffic sources
- Direct40.1%
- Search32.7%
- Referrals10.7%
- Social6.1%
- Mail3.3%
- Other7.1%
Top countries
- United States90.3%
- Taiwan, China9.7%
Estimated from third-party traffic data.
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