latekvo/ResearchChain
📦 Open Source Projectlatekvo
An autonomous AI research toolkit for complex web crawling, data extraction, and iterative knowledge base expansion.
ResearchChain is a Python-based framework engineered to streamline the research process by leveraging LLMs and automated web agents. Unlike static search tools, ResearchChain is built to be iterative; it utilizes a RAG (Retrieval-Augmented Generation) pipeline that updates its internal knowledge store with every new lookup, ensuring that the system becomes more informed over time. The architecture consists of a set of independent, specialized workers that handle distinct tasks such as crawling, parsing, and synthesizing information. It includes a React-based WebUI, providing an accessible interface for users to trigger research chains and monitor the progress of autonomous agents. By combining LangChain for orchestration and custom crawling logic, it enables users to perform deep-dive research on specific topics without manual intervention. The project is highly extensible, allowing developers to integrate custom tools or modify the worker logic to suit specific data gathering requirements.
💡Highlights
- ├─Iterative RAG knowledge expansion
- ├─Independent worker architecture
- └─Integrated React WebUI
🎯For
- ├─AI Researchers
- ├─Data Analysts
- └─Automation Engineers