
Building Blocks and Orchestration of LLM enabled Tasks: Ideas and Case Study with Python Instructor and Instruct Easy
🚀 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!
Lieu
meet.google.com/oav-khuh-nwg
Default Venue
123 Main St, Default City
Détails
Durée : 2h
Tags : Python LLMs Agents Human in the loop ReAct (Reason + Act) Self-Refine Flow Engineering Natural language processing Text generation Information retrieval