Awesome Deep Research

An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.

No fortress, purely open ground. OpenManus is Coming.

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

Get started with building Fullstack Agents using Gemini 2.5 and LangGraph

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

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted.

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.

Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.

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.

"Your Fully-Automated Personal AI Assistant"

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

An Open-Source AI Writing Project.

🔥🔥COLM 2026🔥🔥 CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch. Works with Claude Code, Codex, Cursor, OpenCode, Kiro, and more.

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

No description.

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

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.