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DeepCode
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DeepCode

Active·★ 16.7k·MIT·Updated 2026-10-14
★ Most Popular★ Trending★ Essential

DeepCode, from the HKU Data Intelligence Lab (HKUDS), is an open-source coding agent aimed at real software engineering rather than one-shot code generation. It can understand a project, edit files, run commands and tests, verify results and continue after an interruption, restart or model switch. The project describes four kinds of "depth": deep context, deep execution, deep verification and deep continuity.

It suits developers who want an agent for longer, multi-step tasks such as cross-file refactors, feature work or bug fixing with tests. You give it a natural-language goal and it keeps analysing, implementing, verifying and fixing, while you can add information, revise acceptance criteria, pause or resume. It decides completion from evidence that fits the task, such as tests, build output, diagnostics or diffs. Sessions, skills and permissions are shared across a terminal UI, a desktop app and a web interface, and parallel agents avoid file collisions. Its original research direction, Paper2Code, reproduces research from papers or documents into working, verified code.

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Getting started: requires Python 3.12+ and uv. Run `uv tool install --python 3.12 deepcode-hku` and `deepcode init`, configure a model, then start the TUI, or install the desktop app from GitHub Releases.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-10.

License
MIT
Latest release
v2.3.0 · 2026-09-28
Last commit
2026-09-28
Contributors
30
Forks
2,169
Open issues and PRs
26
First published
2025-05-14
PyPI package
deepcode-hku 2.3.0 · 93 downloads last week

Source: GitHub, npm and PyPI public APIs.

#Multi-Agent AI#Code Generation#Software Engineering#Algorithm Implementation#Python#Web Browsing#Coding
$ Install
$ uv tool install --python 3.12 deepcode-hku
↗ Visit site★ GitHub
01

Features

01Automated Implementation of Complex Algorithms (Paper2Code)
02Automated Front-End Web Development (Text2Web)
03Automated Back-End Development (Text2Backend)
04Research-to-Production Pipeline for scientific papers
05Quality Assurance Automation with unit test generation
02

Why choose it

+Goal-driven loops with the ability to steer, pause and resume long tasks.
+Completion judged by task-appropriate evidence such as tests, builds and diffs.
+Same agent and sessions across TUI, desktop and web; bring your own models.
+Research-backed (Paper2Code) and MIT licensed.
03

Trade-offs

!The project has evolved quickly from a research prototype into a full agent; check that guides you follow match the current version.
!Long autonomous runs can consume many model calls; set budgets and permissions.
!Requires Python 3.12+ and a shared local background service, which adds setup compared with a single CLI binary.
04

Compatibility

Python
Python Runtime
Verified via docs
Command Line Interface
Native CLI
Verified via docs
Web Interface
Native Web UI
Verified via docs
05

Quick start

1
$ uv tool install --python 3.12 deepcode-hku
06

Use cases

↳Accelerating algorithm reproduction and scientific software engineering for researchers.
↳Rapid prototyping and development of front-end and back-end web applications from text descriptions.
↳Automating repetitive coding tasks and integrating into CI/CD pipelines for professional developers.
07

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Stats
GitHub Stars★ 16.7k
Last commit1d ago
StatusActive
LicenseMIT
CategoryCode Assistant
Trend (30d)
+0.6k↑ 4.8%
Links
Documentation↗Discussion↗Issues↗Releases↗

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