by HKUSTDial · Agent Tool · ★ 167
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DeepEye DeepEye harnesses the reasoning capabilities of large language models to autonomously orchestrate complex data analysis workflows. It combines a chat workspace, workflow orchestration, sandboxed execution, and artifact rendering for analytical outputs such as reports, dashboards, and data videos. Project Status: Active Development Preview DeepEye is being shared publicly while the codebase, documentation, tests, deployment workflow, and security hardening are still being actively improved. The repository is useful for local evaluation, collaboration, and understanding the architecture, but APIs, internal contracts, and setup details may continue to change as the project is refined. What DeepEye Does Turns data analysis requests into visible workflow drafts and execution runs. Works with uploaded files and database-backed data sources. Produces structured artifacts such as reports, dashboards, tables, files, and video previews. Provides a React workspace for chat, workflow inspection, output preview, and session state. Runs backend services, workers, storage, and runtime control through a local Docker Compose stack.
| Stars | 167 |
| Forks | 22 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 51.904/100 |
| Last Updated | 2026-05-04 |
| Created | 2018-07-10 |
| Platforms | python |
| Est. Tokens | ~869k |
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DeepEye is DeepEye: An Autonomous Data Agent System. It is categorized as a Agent Tool with 167 GitHub stars.
DeepEye is primarily written in Python. It covers topics such as agent, data-agent, data-agents.
You can find installation instructions and usage details in the DeepEye GitHub repository at github.com/HKUSTDial/DeepEye. The project has 167 stars and 22 forks, indicating an active community.
DeepEye is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to DeepEye on Agent Skills Hub include LiteWebAgent, Awesome-AI-For-Security, LiteMultiAgent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.