Chatbot Lessons

Interesting Read

GenAI Customer Care Project Now Saving $4M/yr for Car Insurance Firm, Jerry

Key Lessons

• Leverage Large Language Models (LLMs) to create a chatbot 
• Open AI GPT-4 for complex queries
• Open AI GPT-3.5 for initial sorting
• Dataset - Messages are captured from chat and SMS through Twilio and stored on Jerry's servers
• Routing Agent - Route based on requests - "Payments," "Policy," and "Opt-out" agents
• Webhook / API - Handlebars to insert data from their database into the chatbot's responses

Key Learning's

• Prompt engineering
• Rapid iteration
• Investment in testing
• Version control

Webhooks in Python with Flask

Webhook

How to Create a Webhook in Python

Python Flask Webhook Receiver

Drawback of LLM

• Exposes your corporate data to the provider of your LLM 
• LLMs have been shown to suffer from “hallucinations

Quick Lessons

• FAQ from Cache
• VectorDB for queries where answers can be located in docs
• Intent recognition and call APIs based on OrderNumber#
• Knowledge Graph if we have some meta data loaded
• If all attempt fails LLM answer
• Add guard rails wherever possible

Ref - Link

Dialogflow Notes Link

Keep Exploring!!!!