Build semantic search with MongoDB Atlas, OpenAI and PyMongo
Viraj Thakrar (~virajut) |
Description:
In the era of Big data and AI, the ability to efficiently search and retrieve information from giant datasets has become paramount. Traditional keyword-based searches aren't capable of dealing with complex data structures and unstructured texts.
With the emerging use cases of generative-AI based applications, everyone wants to create applications that serve user content driven results.
In this session, we will explore how we can build a semantic search within our primary dataset and integrate it into our application.
Two use cases that we will cover:
- How we can integrate OpenAI with our primary dataset stored on MongoDB Atlas
- How we can enable semantic search capabilities in our primary dataset and automate the whole process
Key takeaways from this session:
- How to integrate LLM into operational database
- Example of how other LLMs can be integrated
- How to use PyMongo for performing semantic search
- How to use MongoDB Atlas, a managed developer data platform
- Perform Vector Search on MongoDB Atlas (Preview)
Prerequisites:
- Basic knowledge of Python
- Basic knowledge of Database systems
- Basic knowledge of Cloud systems
- Basic knowledge of NoSQL databases
Speaker Info:
Viraj Thakrar, a software engineer, techpreneur from Ahmedabad, Gujarat: is a MongoDB Certified Developer and a MongoDB user since 8+ years. He has experience working with different tech stacks and has worked with small scale applications to large scale applications playing different roles. He has worked with different startups and teams from across the globe. He is founder of Webstring Global Services based in Ahmedabad Gujarat. He is leading a MongoDB User Group Ahmedabad with his team mate.