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DeepResearch

Alibaba-NLP/DeepResearch

Tongyi Deep Research, the Leading Open-source Deep Research Agent

GraphCanon updated today · GitHub synced today · 41 views this month

20k stars1.5k forksLast push 5mo Python Apache-2.0

Decision brief

DeepResearch is an open-source AI research agent specialized for information-seeking tasks, built with Python and licensed under Apache-2.0.

Good fit when

  • When you need a tool backed by Alibaba’s ecosystem that offers a robust environment for conducting deep research using AI techniques.
  • For environments where the use of leading open-source technology from reputable sources is a priority.

Avoid when

  • Avoid DeepResearch if you require specialized features that are not covered under its deep research and information-seeking scope.
  • Do not use this tool if your project necessitates proprietary solutions, as the open-source nature might be a constraint in such scenarios.

Observed Jul 11, 2026 · Source: enrich:decision_facts

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Maintenance and security

Full trust report
Maintenance
Slowing (172d since push)
As of today
Provenance
Not a fork · Organization account
As of today
Security (OSV)
104 low (104 low)
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install DeepResearch
PyPI

How it fits your stack(9)

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Relationship graph

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Similar tools

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

An open-source AI research agent for information-seeking tasks.

Capability facts

Languages
python

Source: github.language · Aug 19, 2026

Categories

Graph entities

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 19, 2026)

pip install -r requirements.txt
Source link

Tags

README

Quick Start

This guide provides instructions for setting up the environment and running inference scripts located in the inference folder.


2. Installation

Install the required dependencies:

pip install -r requirements.txt

For agents

This page has a .md twin and JSON over the API.

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