The Langchain project is a customer support application leveraging Large Language Models (LLMs) to enhance the customer service experience. Customer support is pivotal in any business, serving as a direct channel for users to seek assistance, resolve issues, and gain valuable information. In this project, we harness the power of LLMs to streamline and optimize the customer support process.
Large Language Models (LLMs) have emerged as a game-changing technology in natural language processing. They can understand, process, and generate human-like text, enabling applications to engage in complex conversations with users. In customer support, LLMs play a crucial role by providing intelligent, context-aware responses, thereby significantly improving the efficiency and effectiveness of customer interactions.
The Langchain project is a multi-agent customer support application powered by LLM. It utilizes a script to greet users, employs a PDF knowledge base to answer queries, and connects to a user database for additional information. If an issue cannot be resolved through chat, it provides a "Submit Ticket" button. The app also includes two additional LLM agents for audio transcription and summarization. It simulates a user's phone call during the chat, where the MP3 of the call is uploaded into the system. The app uses LLM to translate the call into text and summarize the call, adding the information to the ticket.
The Langchain project aims to leverage Large Language Models (LLMs) to enhance customer support interactions by providing intelligent, context-aware responses. It seeks to seamlessly integrate LLM technology with databases, PDF knowledge bases, and audio processing agents, creating a comprehensive customer support application.
The project utilizes diverse datasets, including user interaction logs, PDF knowledge bases, and user information stored in databases for demonstration purposes.
