In this 2 hour workshop, we will build an AI research agent that can search for research papers, summarize them, and answer questions on topics based on past research. We will use MongoDB as the agent's memory provider and knowledge store, open-source LLMs as the agent’s “brain”, and LangChain to orchestrate the end-to-end agentic workflow.
Attendees will be provided with all the resources required to successfully execute the hands-on portions of the workshop, including a GitHub repository consisting of notebook templates with pseudocode. Attendees will replace the pseudocode with their own code during the workshop.
For this workshop, attendees will need basic to intermediate knowledge of Python, and a laptop with the latest version of Python installed.
The preferred environment for running the labs is Google Colab, but for those who would prefer a local setup, instructions can be found here: https://mongodb-developer.github.io/ai-agents-lab/docs/dev-env/dev-setup#local-setup
Recorded live in San Francisco at the AI Engineer World's Fair. See the full schedule of talks at https://www.ai.engineer/worldsfair/2024/schedule & join us at the AI Engineer World's Fair in 2025! Get your tickets today at https://ai.engineer/2025
About Apoorva
Apoorva is a Data Scientist turned Developer Advocate, with 6 years of experience applying Machine Learning to problems in Cybersecurity, including phishing detection, malware protection, and entity behavior analytics. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications via written content and workshops.