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.
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Open-Source Model: IntelliCodeEx leverages an open-source model to provide code explanations, ensuring transparency and accessibility.
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Quantized Model Implementation: To optimize resource usage, the tool utilizes a quantized model, reducing memory and processing requirements.
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Chatbot Implementation: An interactive chatbot is integrated into the tool, allowing users to receive code explanations through a conversational interface.
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Data Security: IntelliCodeEx prioritizes data security, ensuring that sensitive information is handled with utmost care and follows best practices for secure data handling.
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On-Premise Solution: The tool offers an on-premise deployment option, providing control and privacy over your code explanations within your own infrastructure.
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Low Cost: It is cost-effective, offering efficient code explanations without incurring significant expenses.
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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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Llama-2 7B GGML 4-bit Quantized Model: This variant uses a 4-bit quantized version of the Llama-2 7B GGML model.
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Llama-2 7B Original Model with Self-Quantization Options: This variant offers the original Llama-2 7B model and includes options for self-quantization.
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Clone the repository:
git clone https://github.com/sanket98a/IntelliCodeEx.git
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Install the required dependencies:
pip install -r requirements.txt
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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.