Tutorial Membuat RAG (Retrieval-Augmented Generation) API dengan Python FastAPI dan Open LLMs
An exclusive technical tutorial webinar on building Retrieval-Augmented Generation (RAG) APIs using Python FastAPI and Open Large Language Models. Provided comprehensive guidance on integrating modern AI capabilities into practical applications for innovative development solutions.
Invite Me to SpeakTalk Overview
Delivered an exclusive technical tutorial for the Meetap Software Engineer Community on building cutting-edge RAG APIs. As a mentor for Meetap Chapter Tangerang, provided comprehensive guidance on combining retrieval systems with large language models using Python FastAPI. The session focused on practical implementation strategies for developers looking to integrate modern AI capabilities into their applications.
Target Audience
Software developers, AI enthusiasts, and engineers interested in building intelligent applications with modern LLM technology
Topics Covered
- Fundamentals of Retrieval-Augmented Generation (RAG) architecture
- Building robust APIs with Python FastAPI framework
- Integration techniques for Open Large Language Models
- Implementing document retrieval and context augmentation
- Performance optimization for AI-powered applications
- Best practices for production-ready RAG systems
Key Takeaways
- Understanding RAG architecture and its practical applications
- Building scalable APIs with Python FastAPI for AI workloads
- Integrating and optimizing Open Source Large Language Models
- Implementing efficient document retrieval and context management
- Performance considerations for production AI applications
- Future trends and opportunities in AI-powered development
Impact & Results
Empowered the Indonesian developer community with cutting-edge AI development skills. The tutorial provided practical knowledge for building intelligent applications, contributing to the advancement of AI adoption and innovation in the local tech ecosystem.
