Objective and Focus
The workshop will be a walkthrough on how to create and implement your own (Agentic RAG) LLM for customer service. We will create a system around the LLM that takes a prompt from the customer and decides whether it can answer the response or if it has to forward the customer to staff. It will also incorporate a vector database of information from the “company” that will facilitate it in answering any questions.
Structure and Content
- Open Google Collab
- Import requirements (pip install torch, transformers)
- Download the open source LLM (seq2seq)
- Set up an agentic workflow
- Create the router (Decides if the prompt can be answered or not)
- Create the responder (Writes the actual response with RAG)
- Implement RAG (Retrieval Augmented Generation) to retrieve relevant information regarding the prompt and feed it into the model
- DONE!!!
Style and Approach
Interactive and practical, with a focus on hands-on learning.
Target Audience
This workshop is designed for:
- AI Enthusiasts: Individuals curious about the inner workings of AI agents and their real-world applications.
- Developers and Engineers: Those interested in building AI-driven systems or exploring the mechanics behind conversational and task-oriented AI agents.
- Researchers and Students: Aspiring or experienced researchers eager to deepen their understanding of AI agent architectures and implementations.
- Product Designers and Managers: Professionals seeking insights into how AI agents can enhance user experiences and streamline processes.
Required Preparations
- A laptop
- Wifi connection
- Web browser
- Basic python knowledge and/or tech savviness
Host Information
Shariq Sayied Ali is the Chief Technological Officer and co-founder of M10 AI. At 19, Shariq is a distinguished alumnus and teaching assistant at Chalmers University of Technology. With seven years of programming experience Shariq is already an experienced developer and a rising star in the AI field. He has led numerous workshops and guided participants in implementing state-of-the-art AI models. His dedication to studying and applying the latest research ensures he remains at the forefront of advancements in artificial intelligence.
