Building Blocks and Orchestration of LLM enabled Tasks: Ideas and Case Study with Python Instructor and Instruct Easy

Building Blocks and Orchestration of LLM enabled Tasks: Ideas and Case Study with Python Instructor and Instruct Easy

The Ubuntu TechHive (Abidjan, Côte d'Ivoire)
Passado Online Python Domain Specific Langugages (DSLs) LLMs AI Agents Human in the loop ReAct (Reason + Act) Self-Refine Flow Engineering Natural language processing Text generation Information retrieval

🚀 Join us for an insightful Ubuntu TechHive meetup where we'll explore the building blocks and orchestration of LLM-enabled tasks using Python! This session is perfect for those looking to understand the integration of AI and automation in real-world applications.

🎯 Agenda:

  • Introduction: Overview of LLM-enabled tasks and their significance.
  • Case Study: Detailed case study using Python Instructor and Instruct Easy.
  • Building Blocks: Learn about Python Domain Specific Languages (DSLs) and their similarities to Lego blocks.
  • Automation and Orchestration: Discover techniques for data extraction, text generation, and information retrieval.
  • Tech Stack: Dive into the tech stack including FastAPI app, ZeroMQ for work distribution, Server Sent Events (SSE), Docker, AWS, and Cloud Computing.

📍 Who Should Attend?

  • Developers interested in AI and automation.
  • Tech enthusiasts looking to expand their knowledge in Python and workflow orchestration.

👋 We look forward to seeing you there and exploring the fascinating world of LLM-enabled tasks together!

Localização

Detalhes

Duração: 2h minutos

Organizado por chiefkemist, Aziz