{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/bdb2c251b80e4a39ab2dd156f3e15193\" frameborder=\"0\" width=\"1110\" height=\"832\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":832,"width":1110,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":832,"thumbnail_width":1110,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/bdb2c251b80e4a39ab2dd156f3e15193-edc88cd9881e7e82.gif","duration":244.6702,"title":"Exploring a Life Sciences Research AI Agent with Crew AI and Ory","description":"In this video, I demonstrate a Streamlit app that utilizes a crew of agents built with the Crew AI framework, leveraging an Ory endpoint powered by the latest open-source GPT model with 120 billion parameters. The app is specifically designed for life sciences research, enabling users to query and retrieve detailed reports from the PubMed data source. I walk through the process of submitting a technical query and showcase the comprehensive report generated by the AI agent, which includes summaries, research landscapes, and references. I encourage you to explore the app and check the blog post for more details and code. Stay tuned for future sessions where I will dive deeper into the agent-building process."}