- 🚀[2026-01-15] Q&A Copilot Juicer has been deployed on the official Doc Site | DingTalk | Discord of Data-Juicer. Feel free to ask Juicer anything related to Data-Juicer ecosystem!
- Check 📃 Deploy-ready codes | 🎬 More demos | 🎯 Dev Roadmap.
This repo maintains a suite of agents that enable users to interact with Data-Juicer's powerful data processing capabilities through natural language.
- In Data-Juicer ecosystem, Data-Juicer Agents (DJ-Agents) play a key role in the interface layer, bridging users with the powerful Data-Juicer infrastructure and toolkit for building data-centric applications.
- Unlike traditional API- or CLI-based interaction, DJ-Agents leverage agent-based interaction, tool use, and extensibility to enable non-expert users to access Data-Juicer’s data-processing capabilities through intuitive natural-language interactions.
- The long-term goal of DJ-Agents is to enable a development-free data processing lifecycle, allowing developers to focus on what to do rather than how to do it.
The Data-Juicer Agents family currently contains the following members:
- Data-Juicer Q&A Agent (DJ Q&A Agent)
- Data-Juicer Data Processing Agent (DJ Process Agent) [Beta version]
- Data-Juicer Code Development Agent (DJ Dev Agent) [Beta version]
Data-Juicer Agents adopts a multi-agent routing architecture for routing requests to the corresponding agent. Check agent info for more details.
- Q&A Copilot Juicer has been deployed on the official doc page of Data-Juicer! Feel free to ask Juicer anything related to Data-Juicer ecosystem.
More online agentic services are being planned and developed—check out our Roadmap and join us!
Follow the document to locally launch DJ-Agents.
If you encounter any issues, check common issues or ask our Q&A copilot Juicer at the doc page.
The long-term vision of DJ-Agents is to enable a development-free data processing lifecycle, allowing developers to focus on what to do rather than how to do it.
To achieve this vision, we are tackling two fundamental challenges:
- Agent Level: How to design and build powerful agents specialized in data processing
- Service Level: How to package these agents into ready-to-use, out-of-the-box products
We continuously iterate on both directions, and the roadmap may evolve accordingly as our understanding and capabilities improve.
Below is the current development checklist.
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Data-Juicer Q&A Agent (DJ Q&A Agent) - Answers Data-Juicer–related questions from both existing and potential users.
- Implemented
- [2026-01-15]: The current DJ Q&A Agent demonstrates strong performance in our internal evaluations and is considered production-ready.
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Data-Juicer Data Processing Agent (DJ Process Agent) - Automatically invokes Data-Juicer tools to fulfill data processing requests.
- In progress
- [2026-01-15]: The current DJ Process Agent is in beta. We are actively benchmarking and optimizing its capabilities.
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Data-Juicer Code Development Agent (DJ Dev Agent) - Automatically develops new data processing operators based on user requirements.
- In progress
- [2026-01-15]: The current DJ Dev Agent is in beta. Capability evaluation and optimization are ongoing.
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Q&A Copilot — Juicer
- [2026-01-15]: Juicer is currently available on the official Doc Site | DingTalk | Discord of Data-Juicer.
-
Interactive Data Analysis Studio (In Development)
- [2026-01-15]: A demo is available. The current version primarily relies on predefined workflows. We are working on integrating agent-based intelligence.
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MCP Service
- Planned
-
Workflows as Skills
Data-Juicer Hub hosts a growing collection of data processing recipes and workflows contributed by the Data-Juicer community.As data processing demands expand into new scenarios—such as RAG, Embodied Intelligence, and Data Lakehouse architectures—we plan to incorporate existing and newly developed workflows into DJ-Agents as reusable skills, enabling broader and more flexible data processing applications.
Q: How to get DashScope API key? A: Visit DashScope official website to register an account and apply for an API key.
Q: Why does operator retrieval fail? A: Please check network connection and API key configuration, or try switching to vector retrieval mode.
Q: How to debug custom operators? A: Ensure Data-Juicer path is configured correctly and check the example code provided by the code development agent.
Q: What to do if MCP service connection fails? A: Check if the MCP server is running and confirm the URL address in the configuration file is correct.
Q: Error: requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: http://localhost:3000/trpc/pushMessage A: Agents handle data via file references (paths) rather than direct uploads. Please confirm whether any non-text files were submitted.
- For large-scale data processing, it is recommended to use Data-Juicer's distributed mode
- Set batch size appropriately to balance memory usage and processing speed
- For more advanced data processing features (synthesis, Data-Model Co-Development), please refer to Data-Juicer documentation
- Data-Juicer has been used by a large number of Tongyi and Alibaba Cloud internal and external users, and has facilitated many research works. All code is continuously maintained and enhanced.
Welcome to visit GitHub, Star, Fork, submit Issues, and join the community!
- Project Repositories:
Contributing: Welcome to submit Issues and Pull Requests to improve Data-Juicer Agents, Data-Juicer, and AgentScope. If you encounter problems during use or have feature suggestions, please feel free to contact us.