PureCPP

PureCPP is the C++ backend for architectural code that powers the RAG system.

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📖 Documentation

For detailed installation and setup instructions, please refer to our official documentation:

🔗 PureCPP Documentation

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🚀 Contributing to PureCPP

We welcome contributions to PureCPP! If you would like to contribute, please read our contribution guide before opening an issue or submitting a pull request:

👉 Contribution Guide

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📌 Minimum Requirements

Ensure you have the following dependencies installed before building PureCPP:

• GCC/G++ 13.1
• CMake 3.22
• Conan 2
• Rust

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⚡ Quick Start with PIP

To quickly get started with PureCPP, follow the installation guide in our documentation:

📖 Setup Guide

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🔨 How to Build

The following commands execute the cleand_and_build.sh script, which performs the following actions:

• Creates the required folders for the project build.
• Runs CMake to configure and generate the build files.
• Creates the build folder, where the compiled files will be stored.
• Installs Conan dependencies, ensuring all necessary libraries and packages are available.

Build Commands:

chmod +x cleand_and_build.sh
./cleand_and_build.sh

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📥 Downloading Pre-trained Models

To use pre-trained models with PureCPP, you can download and convert them to ONNX format using the following commands:

python3 scripts/hf_model_to_onnx.py -m="dbmdz/bert-large-cased-finetuned-conll03-english" -o="bert-large-cased-finetuned-conll03-english"
python3 scripts/hf_model_to_onnx.py -m="sentence-transformers/all-MiniLM-L6-v2" -o="sentence-transformers/all-MiniLM-L6-v2"

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🦀 Rust Installation

Install Rust:

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Activate Rust Environment:

source ~/.cargo/env

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🔗 Downloading Libtorch

Libtorch is required for running PyTorch models in C++. Follow the links below for installation:

• 📖 Installing Libtorch
• 📥 Download Binaries

CPU Version Installation

libtorch_cpu_zip=libtorch-cxx11-abi-shared-with-deps-2.5.1+cpu.zip
libtorch_cpu_url=https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-2.5.1%2Bcpu.zip

wget ${libtorch_cpu_url} -O ${libtorch_cpu_zip}
mkdir -p ./libs/libtorch
unzip ${libtorch_cpu_zip} -d ./libs/libtorch
mv ./libs/libtorch/libtorch/ ./libs/libtorch/cpu

CUDA Version Installation

libtorch_cuda_zip=libtorch-cxx11-abi-shared-with-deps-2.5.1+cu124.zip
libtorch_cuda_url=https://download.pytorch.org/libtorch/cu124/libtorch-cxx11-abi-shared-with-deps-2.5.1%2Bcu124.zip

wget ${libtorch_cuda_url} -O ${libtorch_cuda_zip}
mkdir -p ./libs/libtorch
unzip ${libtorch_cuda_zip} -d ./libs/libtorch
mv ./libs/libtorch/libtorch/ ./libs/libtorch/cuda

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📌 Next Steps

Stay tuned for updates! 🚀