IntelliCodeEx ^{by Sanki}

IntelliCodeEx is a code explanation tool powered by LLM (Language Model) that utilizes the open-source Llama-2 7B GGML quantized model. It's designed to provide intelligent explanations for various programming languages. This project builds a Streamlit-based user interface for the proof of concept (POC). It includes a chatbot capable of explaining code in Python, C#, JavaScript, and .NET languages.

🎉 Features

1. Open-Source Model: IntelliCodeEx leverages an open-source model to provide code explanations, ensuring transparency and accessibility.

2. Quantized Model Implementation: To optimize resource usage, the tool utilizes a quantized model, reducing memory and processing requirements.

3. Chatbot Implementation: An interactive chatbot is integrated into the tool, allowing users to receive code explanations through a conversational interface.

4. Data Security: IntelliCodeEx prioritizes data security, ensuring that sensitive information is handled with utmost care and follows best practices for secure data handling.

5. On-Premise Solution: The tool offers an on-premise deployment option, providing control and privacy over your code explanations within your own infrastructure.

6. Low Cost: It is cost-effective, offering efficient code explanations without incurring significant expenses.

7. Easy Customizability: IntelliCodeEx is designed to be easily customizable to adapt to specific requirements, making it a versatile solution for various use cases.

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🏃Variants of IntelliCodeEx

1. Llama-2 7B GGML 4-bit Quantized Model: This variant uses a 4-bit quantized version of the Llama-2 7B GGML model.

2. Llama-2 7B Original Model with Self-Quantization Options: This variant offers the original Llama-2 7B model and includes options for self-quantization.

💻 Installation

A. Llama-2 7B GGML 4-bit Quantized Model

1. Clone the repository:

   git clone https://github.com/sanket98a/IntelliCodeEx.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the following command to start the Streamlit UI:

   streamlit run app.py

This will start the IntelliCodeEx chatbot and allow you to explain code in various languages.