Building Simple and Efficient Chatbots Step-by-Step

Description

In this code demonstration, we're leveraging the LangChain Framework to build a sophisticated chatbot. We'll start by setting up the necessary environment and dependencies. Then, we'll dive into implementing LLM and RAG techniques to enhance the chatbot's responses, ensuring accuracy and engagement. Throughout the code, we'll explore efficient prompts and strategies to streamline the conversation flow. By the end, you'll have a comprehensive understanding of how to leverage advanced techniques to develop a powerful and intelligent chatbot solution.

Getting Started

Dependencies

• Azure OpenAI Service
• Python 3.9.12

Executing Program

1. Clone the git repository.
2. Create a .env file to store the following environment variables:
   • OPENAI_API_KEY
   • BASE_URL
   • Deployment names for the EMBEDDING_MODEL and CHAT_MODEL.
3. Ensure that all files are located in the same folder.

These steps should help users effectively set up and run the program.