Awesome Deep Research

No fortress, purely open ground. OpenManus is Coming.

A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.

An autonomous agent that conducts deep research on any data using any LLM providers

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

"AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework"

PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.

SOTA search powered LLM

DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.

Humanity's Last Exam

"Your Fully-Automated Personal AI Assistant"

[NeurIPS 2025] 🌐 WebThinker: Empowering Large Reasoning Models with Deep Research Capability

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning & ReCall: Learning to Reason with Tool Call for LLMs via Reinforcement Learning

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

🔍 Search-o1: Agentic Search-Enhanced Large Reasoning Models [EMNLP 2025]

Salesforce Enterprise Deep Research

An Open-Source AI Writing Project.

[EMNLP'25] s3 - ⚡ Efficient & Effective Search Agent Training via RL for RAG (RLVR for Search with Minimal Data)

DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents

Scaling Deep Research via Reinforcement Learning in Real-world Environments.

R1-searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

recursive rag with r1 reasoning

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Repo for "MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability"

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Official repository for RAG-Gym

The official repo of "WebExplorer: Explore and Evolve for Training Long-Horizon Web Agents"

[NeurIPS'25 D&B] Mind2Web-2 Benchmark: Evaluating Agentic Search with Agent-as-a-Judge

[EMNLP 2025] WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning

R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning

A High-Efficiency System of Large Language Model Based Search Agents

IKEA: Reinforced Internal-External Knowledge Synergistic Reasoning for Efficient Adaptive Search Agent

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[AAAI 2026] AutoTool: Efficient Tool Selection for Large Language Model Agents

Official Implementation of "O-Researcher: An Open Ended Deep Research Model via Multi-Agent Distillation and Agentic RL"

HiPRAG (Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation) is a reinforcement learning method designed for training reasoning-and-searching interleaved LLMs with improved efficiency and reduced oversearching as well as undersearching behavior.

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WebSeer: Training Deeper Search Agents through Reinforcement Learning with Self-Reflection

Learn to resolve ambiguity for Question Answering through RL