Generative AI

Presentation

This is a Python-based project focused on explore the power of llm model and framework such as GPT4ALL and LangChain.

It includes notebooks providing an overview of the LangChain framework, querying local documents with Obsidian, and integrating with GPT4All models.

You can exploring notebooks for in-depth demonstrations of various prompt processing in Python and chatbot functionalities.

Key Components

The project's structure involves organized notebooks and locally downloaded GPT4All models.

The collection of Jupyter notebooks are organized as follows:

promptengineering
├─ models
│  ├─ model1.bin
├─ 0_LangChain_overview.ipynb 
├─ 1_LangChain_Obsidian_loader.ipynb   
├─ 2_gpt4all_overview.ipynb  
├─ 3_LangChain_gpt4all.ipynb   
├─ 4_chatbot_openai.ipynb 
├─ 5_chatbot_gpt4all.ipynb 
└─ ...

Folder models contains download locally models for gpt4all. They are loaded in notebooks by command :

model = GPT4All(model_name, model_path="models")

The following table provides an overview of the notebooks contained within this project:

Notebook Filename	Description
0_LangChain_overview.ipynb	Overview of the LangChain framework
1_LangChain_Obsidian_loader.ipynb	Querying local documents created with Obsidian
2_gpt4all_overview.ipynb	Overview of the locally-running LLM GPT4ALL
3_LangChain_gpt4all.ipynb	Example of using LangChain to interact with GPT4All models
4_chatbot_openai.ipynb	Example of chatbot using OpenAI's model
5_chatbot_gpt4all.ipynb	Example of chatbot using GPT4All model

Getting Started

To get started with this project, follow these steps :

1. Clone the Repository

git clone https://github.com/data-modelisation/prompt-engineering.git

2. Configure API keys

Optain API key for OpenAI. Insert these keys in the configuration file .env :

OPENAI_API_KEY= <obtained API key>

Optain API key for OpenAI

You can do this by following the link to generate OpenAI API key.
Additionally, you can use another link to monitor your API usage.