2-Langchain Series-Building Chatbot Using Paid And Open Source APIs
The video introduces the Lang Chain Series focusing on creating chatbot applications using paid and open-source APIs. It covers setting up the environment by defining essential environment variables and importing necessary libraries for the coding process. The implementation of the chatbot application for both paid and open-source LLMS is demonstrated, including instructions on calling open-source LLMS locally using AMA. The presenter showcases how to call the Lama 2 model using AMA and run the application locally, offering a practical guide for those interested in developing chatbot applications.
Table of Contents
- Introduction to Lang Chain Series
- Setting Up the Environment
- Coding the Chatbot Application
- Implementing Open Source LLMS Locally
- FAQ
Introduction to Lang Chain Series
The presenter introduces the Lang Chain Series and discusses creating chatbot applications using paid and open-source APIs. The plan for the series is outlined, focusing entirely on Lang Chain with many more practical videos to come.
Setting Up the Environment
The presenter starts coding the chatbot application by importing necessary libraries such as chat prompt template, chat open AI, string output parser, and streamlet. The process of defining prompt templates, chat prompts, and user prompts is explained. The implementation of the chatbot application for both paid and open-source LLMS is demonstrated.
Implementing Open Source LLMS Locally
Instructions on calling open-source LLMS locally using AMA (Auto Model Archive). The process involves downloading AMA, initializing AMA, and importing necessary libraries to call open-source models. The presenter demonstrates calling Lama 2 model using AMA and running the application locally.
FAQ
Q: What is Lang Chain Series?
A: The Lang Chain Series is a series focused on creating chatbot applications using paid and open-source APIs.
Q: What libraries are imported for coding the chatbot application?
A: Libraries such as chat prompt template, chat open AI, string output parser, and streamlet are imported for coding the chatbot application.
Q: What is AMA in the context of calling open-source LLMS?
A: AMA stands for Auto Model Archive and is used for calling open-source LLMS locally.
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