TIGER-AI-Lab/OpenResearcher

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1211 stars · 118 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenResearcher is a fully open-source pipeline for synthesizing long-horizon deep research trajectories using LLM agents with retrieval and web browsing. It includes agent code, training code, a released dataset, and a trained model for building deep research assistants.

Use cases

• generate deep research trajectories for LLM training
• build an open-source deep research agent
• synthesize long-horizon research datasets with web retrieval
• train a model to do multi-step research with search
• reproduce deep research pipelines without closed APIs
• evaluate agents on long-form research tasks

When to choose

• you need an open pipeline for generating research agent training data
• you want to train or fine-tune an LLM for deep research tasks
• you need a self-hosted alternative to proprietary deep research tools
• you want to study or extend long-horizon agent trajectories with retrieval

When to avoid

• you need a polished end-user research assistant UI rather than a research pipeline
• you lack GPU resources for training or running large models
• you need a project with a permissive license - no license is specified
• your task is simple single-shot question answering without multi-step research

Facets

framework · maturity active

agent-framework rag llm-inference search-engine machine-learning llm-training artificial-intelligence large-language-models python self-hosted deep-research trajectory-synthesis open-source-pipeline research-agent dataset-generation web-search-agent ai-agents retrieval-augmented-generation natural-language-processing linux docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="TIGER-AI-Lab/OpenResearcher")