OpenAI introduces Assistant API for AI assistants, lagging behind LangChain in natural language processing
From Towards Data Science: 2024-06-18 15:43:15
Since OpenAI has introduced the Assistant API and new features showcasing an agent-like architecture, users can now build AI assistants within their own applications. The Assistants API currently supports three types of tools: Code Interpreter, File Search, and Function calling. However, advancements still lag behind LangChain, which offers greater flexibility in processing natural language input and executing context-based actions.
The interaction with the Assistant API can be seen as a loop where given a user input, an LLM is called to determine whether to provide a response or take specific actions. If the LLM’s decision suffices, the loop ends; if an action leads to a new observation, the LLM is called again, and the loop restarts.
Despite the advantages, documentation for the API might be lacking, especially with custom function calls and building apps with frameworks like Streamlit. This blog post aims to guide users through building an AI assistant using the OpenAI Assistant API with custom function calls and a Streamlit interface for effective use of the API.
An example demonstrated in the post is creating an AI assistant capable of calculating tax based on given revenue. LangChain users may implement this by creating an agent with a “tax computation” tool that includes necessary computation steps and a prompt for adequate response. The process with the OpenAI Assistant API is slightly different, requiring specific code and tools.
Users can follow steps to define a function that computes tax based on given revenue, develop a tool using this function, and create an assistant that can access this tool for tax computation. The tax computation tool is designed as a toy example for demonstration purposes and should not be used for actual tax calculations.
Read more at Towards Data Science: Creating an Assistant with OpenAI Assistant API and Streamlit | by Shuyang Xiang | Jun, 2024