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.

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

"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.

"Your Fully-Automated Personal AI Assistant"

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Salesforce Enterprise Deep Research

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.

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

[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

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

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

No description.

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.

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