Next js + FastAPI + Python implementation of realtime chat sentiment analysis with GPT-4 Omni

The video tutorial discusses building a real-time chat sentiment analysis application using Next.js, FastAPI, and Python with GPT-4 Omni. It covers three implementations - a terminal version for parallel sentiment analysis, FastAPI for real-time sentiment analysis, and Next.js for the visually appealing frontend with real-time updates on messages and sentiment.

The video tutorial discusses the implementation of a real-time chat sentiment analysis application using Next.js, FastAPI, and Python with GPT-4 Omni. The application provides instantaneous sentiment analysis every two messages, displaying the number of messages sent and the chat duration. Three implementations are covered: Next.js for the frontend, FastAPI for the API backend, and a terminal implementation for parallel sentiment analysis written to a text file.

The terminal implementation utilizes OpenAI for sentiment analysis and threading to run sentiment analysis in parallel with the chat conversation. Messages are accumulated and sentiment analysis is triggered every two messages. The FastAPI implementation provides real-time sentiment analysis for each message input by the user, updating the sentiment along with the messages and time elapsed. The terminal implementation writes sentiment analysis results to a text file, capturing the tone of the conversation and user expressions.

The Next.js implementation showcases a visually appealing user interface with responsive design. The application uses Vercel AI SDK for handling API calls and components like Avatars, Text Areas, and Buttons for user interaction. The sentiment analysis is triggered based on changes in the assistant’s response, with sentiment input set for analysis. The application displays real-time updates on the number of messages, chat duration, and sentiment analysis results if available.

The tutorial also highlights the benefits of becoming a patron, providing access to code files, courses like the THX Master Class, Streamlit Course, and FastAPI Course, along with one-on-one consultations. The Next.js implementation involves defining routes, utilizing the Vercel AI SDK for API calls, and handling message streaming and sentiment analysis. The application updates message content and sentiment analysis based on user and assistant input, with real-time updates on message count, chat duration, and sentiment data displayed on the sidebar.

Overall, the tutorial covers the implementation of a real-time chat sentiment analysis application using Next.js, FastAPI, and Python with GPT-4 Omni. It provides insights into building responsive user interfaces, handling API calls, parallel sentiment analysis, and real-time updates. The detailed walkthrough of the implementations offers valuable information for developers looking to create similar applications for their own use cases.