Alibaba-NLP/DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
⚡ Executive Summary & Quick Facts
Authoritative SourceDeepResearch is DeepResearch is an open-source project written in Python: Tongyi Deep Research, the Leading Open-source Deep Research Agent..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), Alibaba-NLP/DeepResearch has accumulated 20,091 GitHub stars and 1,528 forks. It is written in Python, licensed under Apache-2.0, and ranks #839 globally. It is actively maintained with the latest commit recorded on Feb 27, 2026.”
| Repository | Alibaba-NLP/DeepResearch ↗ |
|---|---|
| Primary Category | agent |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 20.1K stars · ⑂ 1.5K forks · #839 globally |
| Maintenance | ● Active (Last commit: Feb 27, 2026) · 98 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 78/100 · Grade BNote: DeepResearch displays slower maintenance activity. Continuous telemetry recorded the last code commit on Feb 27, 2026 (258 days ago). Supported by 20,091 stars and 1,528 community forks, this repository holds a calculated health index of 78/100, reflecting low frequency (258 days since last push) and healthy issue cadence.
Star History
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+87
STARS · LAST 30 DAYS
3
PER DAY
#157
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +87 | +270 |
| Per day | 1 | 3 | 3 |
| Forks gained | +0 | +0 | +76 |
DeepResearch gained 87 stars in the last 30 days, about 3 a day, and now has 20.1K. It is about 2 years old and has averaged roughly 10K stars a year. It ranks #157 among Python repositories and #839 across all languages on GitHubRepo.
Trending Record
45
DAYS ON TRENDING
#244
BEST RANK
Sep 23, 2026
FIRST APPEARANCE
Active
STATUS TODAY
DeepResearch has maintained a continuous presence across global trending indexes, peaking at #244. Below is the 30-day activity profile:
💡 Overview
DeepResearch is an open-source project written in Python: Tongyi Deep Research, the Leading Open-source Deep Research Agent.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent, alibaba, artificial-intelligence. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install DeepResearch⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
DeepResearch coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with DeepResearch.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install DeepResearch using your package manager: `pip install DeepResearch`
Initialize your project workspace or configuration file for DeepResearch.
Import DeepResearch into your codebase or invoke it directly from your terminal.
Execute your test suite or run `DeepResearch --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Alibaba-NLP/DeepResearch is currently ranked #839 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
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| #839 | Alibaba-NLP/DeepResearch This Project | Python | ★ 20.1K | |
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Frequently Asked Questions
What does DeepResearch do? +
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Is DeepResearch actively maintained in 2026? +
Note: DeepResearch exhibits slower recent commit activity. The latest code push was recorded on Feb 27, 2026 (258 days ago). It holds a calculated Maintenance Health Score of 78/100 (B rating) with 20,091 stars and 98 open issues.
What language is DeepResearch written in? +
The primary language is Python. Topics include: agent, alibaba, artificial-intelligence, deep-research, deepresearch.
How many stars does DeepResearch have? +
DeepResearch has 20,091 stars and 1,528 forks on GitHub.
How does DeepResearch rank among GitHub repositories? +
With 20,091 stars, Alibaba-NLP/DeepResearch is ranked #839 globally across all repositories tracked on GitHubRepo and #157 among Python projects.
What license is DeepResearch distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
