Build an AI Research Agent: Apoorva Joshi
Oct 25, 2024 · 27:33
In this workshop, Apoorva Joshi, an AI Developer Advocate at MongoDB, teaches how to build an AI research agent using MongoDB as the memory provider and knowledge store, open-source LLMs from Fireworks AI (Fire Function V1) as the agent’s brain, and LangChain to orchestrate the workflow. The agent searches for research papers, summarizes them, and answers questions based on past research, using tools like ArXivLoader and a MongoDB vector store. Joshi explains key agent concepts—planning with chain of thought and react patterns, short-term and long-term memory, and tool creation—then guides attendees through hands-on sections to build the agent step by step. Attendees learn to create agent tools, implement reasoning with react, and add short-term memory persisted to MongoDB. The workshop emphasizes that agents enable complex, multi-step tasks through iterative reasoning, tool use, and memory, trading higher cost and latency for improved accuracy.
