Client Feedback Processing with AI Agents Using CrewAI
There are a number of blog posts out there on how to use crewAI to create personal assistants like blog post creating AIs. My motivation to write another one was to show how ai agents can be implemented to improve existing data processing software. In this made-up scenario, we are running a big e-learning platform and users are constantly submitting messages through our feedback form. Each message needs to be reviewed, and a decision must be made about what action should be taken. The possible actions include:/
As a task that requires understanding of human language and simple decision making skills, this seems to be an obvious choice for AI!
An AI agent is a piece of software built around a large language model (LLM) that can act autonomously - make decisions, perform tasks, and use tools. Essentially, it's like a mini version of ChatGPT that you can integrate directly into your code, giving it access to a variety of tools. These tools can scrape the web, read from databases, parse Excel files, or perform virtually any function you can think of. By combining decision making capabilities with external tools, these agents can automate a wide range of tasks.
CrewAI is a python framework build on top of langchain that makes it very simple to define those agents, their tasks and tools and have them work together in a crew. A crew can consist of a single agent processing a single task or of multiple agents working together and even delegating work to each other.
.jpg)
