Part of my series: AI & ChatGPT
Using AI can save tons of time. Increases your productivity exponentially. However public AI Bots tools do not allow you to use your own data at scale, being limited to uploading a single document (typically a limited sized txt or PDF)
If you are looking to take advantage of your own data to help users chat / interact in a natural language to get answers, then you can create your own chatbot without having to create your own language model (LLM). It is a good way to understand how AI can be customized for you own use case.
The steps are fairly straight forward:
- Choose the core LLM you want to use
- (you can use the OpenAI LLM API)
- Add your own data source ( Pick or create a location with your source files)
- Once uploaded you will need to “index” your documents.
- (Please note that your data is NOT going back to the LLM (Model). You are not training that model, you are using that model to index your data!)
- Fine Tune the model which is basically adjusting the tone, limit responses, and things like that.
- Create the end-user front-end
- You can use HTML/WebApp or integrate into your own application using API calls.
Best explanation videos I have seen on this topic are:
- Create Chatbot With Custom Data Using Azure OpenAI – YouTube
- Create Your Own ChatGPT with PDF Data in 5 Minutes (LangChain Tutorial) – YouTube
- How to Build an AI Document Chatbot in 10 Minutes – YouTube
In machine learning, fine-tuning is the process of optimizing a model for a specific dataset. This can be done by adjusting the model’s parameters, such as the learning rate or the number of hidden layers.
A few examples from YouTube:
- Azure OpenAI BYOD: ChatGPT with Your Own Data! – YouTube
- Build a Chatbot in 15 minutes (Python & Bubble.io no code) – YouTube
- How to Build a Custom Knowledge ChatGPT Clone in 5 Minutes – YouTube
- Fine-tuning Llama 2 on Your Own Dataset | Train an LLM for Your Use Case with QLoRA on a Single GPU – YouTube
- Using ChatGPT with YOUR OWN Data. This is magical. (LangChain OpenAI API) – YouTube
- AutoGen FULL Tutorial with Python (Step-By-Step) 🤯 Build AI Agent Teams! – YouTube
BUilding using tools: