This is the third post in the series where we explore the OpenAI Assistants API. In this post, we will be looking at the code interpreter tool which allows us to upload files to the Assistants API and write python code against them. This is very powerful for scenarios where you have to do data analysis on csv or Microsoft Excel files and generate charts and reports on them.
See the following posts for the entire series:
Working with the OpenAI Assistants: Create a simple assistant
Working with the OpenAI Assistants: Using file search
Working with the OpenAI Assistants: Chat with Excel files using code interpreter (this post)
Working with OpenAI Assistants: Using code interpreter to generate charts
The Retrieval Augmented Generation (RAG) pattern, which was discussed in previous posts, works great for text based files like Microsoft Word and PDF documents. However, when it comes to structured data files like csv or excel, it comes out short. An this where the Code Interpreter tool can come in very handy. It can repetitively run python code on documents until it is confident that the user's question has been answered.
So in this post, let's see how we can query an excel file with the code interpreter tool. The excel file we will be querying will contain details of customers like their name and the licenses purchased of a fictional product by them:
To upload and analyse documents using the Code interpreter, we have to use the following moving pieces:
- First, we need to upload files using the Open AI File client
- Then, we need to connect the uploaded file to the Code Interpreter tool in either an assistant or a thread which would enable the assistant to answer questions based on the document.
As you can see the code interpreter tool takes a few passes at the data. It tries to understand the document before answering the question. This is a really powerful feature and the possibilities are endless!
Hope this helps.
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