This is an AI Research Assistant that uses an agentic approach to conduct research automatically. The project leverages LangChain's agent framework to create an intelligent system that can analyze research queries, strategically select appropriate tools, and execute multi-step research workflows without manual intervention.
Agentic Approach: Instead of following pre-programmed steps, the AI agent makes autonomous decisions about which tools to use and in what sequence based on the research query. For example, if you ask about "recent developments in renewable energy," the agent might first use the search tool for current information, then the Wikipedia tool for background context, and finally the save tool to store the findings.
Tool Usage: The system integrates three core research tools - a web search tool for real-time information gathering, a Wikipedia tool for encyclopedic knowledge and background research, and a file-saving tool for organizing and storing research outputs. The agent intelligently orchestrates these tools, often using them in combination to provide comprehensive research results that include summaries, verified sources, and transparent documentation of the research methodology used.
This creates a hands-off research experience where users simply input their query and receive structured, professional research outputs without needing to manually search, cross-reference, or organize information themselves.