I see a lot of job openings about training a chatbot with the company's data so that it will be able to answer the questions of the company's employees, customers, or clients. I thought at first that training a chatbot would require a lot of computing power and a substantial amount of data. Then, I came across the Chainlet, Langchainin, and OpenAI libraries for Python purely by accident. A video appeared on my YouTube watch list, and I accidentally clicked on it. I was surprised to discover that such libraries exist. I've already forgotten the title of that video because upon learning about the capabilities of Chainlet, I immediately searched YouTube for tutorials, and yes, there are tons of them. I also browsed the Chainlet website. While the information there is very basic, one particular example caught my attention: Document QA. You can check it out here. All I did was copy the code, insert my OpenAI API, and run it. I obtained the ebook in TXT format from https://www.gutenberg.org.
To be honest, it didn't run immediately. I encountered several errors. One notable error I encountered was the version of SQLite3. I was using Python 3.8, and the built-in SQLite3 version is 3.14, which is not compatible with the version being used by Chainlet. I did some research and found out that SQLite3 is not upgradable on Windows 10. I would have to upgrade to version Python 3.10 because it uses SQLite3 version 3.10. However, I didn't want to upgrade to version 3.10 because my Machine Learning projects are only compatible with 3.8. I had to install 3.10 and run the program in a virtual environment. I used Pipenv, reinstalled all the libraries, and finally, it worked! Take a look at the screenshots below:
Inital Screen:
It answered several of m questions:
I also noticed that it lacks chat memory; perhaps that's another interesting topic to explore. But with all those huge topics to explore, I hope there will be tutorials, documentations and sample code snippets for developers to be able to learn how to use chainlet easily.
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