In this repo, we’ll cover:
- Set up an OpenAI developer account and integrate it with Python environment.
- Utilizing the chat functionality in the OpenAI API, with and without langchain.
- Perform prompt engineering.
- Build longer conversations with GPT.
- Ideas for incorporating GPT into a data analysis or data science workflow.
We will explore electric vehicle dataset (This dataset shows the Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) that are currently registered through Washington State Department of Licensing (DOL).) Link: https://catalog.data.gov/dataset/electric-vehicle-population-data/resource/fa51be35-691f-45d2-9f3e-535877965e69
What is Open AI API and LangChain?
Open AI API — Open AI has released an API for accessing new AI models developed by OpenAI. Unlike most AI systems which are designed for one use-case, this API provides general-purpose “text in, text out” interface, allowing users to try it on virtually any English language task.
LangChain — LangChain is a framework for developing applications powered by language models. It connects a language model to sources of context (prompt instructions, content to ground its response in, etc.) and rely on a language model to reason (about how to answer based on provided context, what actions to take, etc.)