Cortex.cpp

Documentation - API Reference - Changelog - Bug reports - Discord

⚠️ Cortex.cpp is currently in active development. This outlines the intended behavior of Cortex, which may not yet be fully implemented in the codebase.

Overview

Cortex.cpp is a Local AI engine that is used to run and customize LLMs. Cortex can be deployed as a standalone server, or integrated into apps like Jan.ai.

Cortex.cpp is a multi-engine that uses llama.cpp as the default engine but also supports the following:

• llamacpp
• onnx
• tensorrt-llm

Installation

This Local Installer packages all required dependencies, so that you don’t need an internet connection during the installation process.

Alternatively, Cortex is available with a Network Installer which downloads the necessary dependencies from the internet during the installation.

Stable

Windows:

cortex-local-installer.exe

MacOS:

cortex-local-installer.pkg

Linux:

cortex-local-installer.deb

Download the installer and run the following command in terminal:

    sudo apt install ./cortex-local-installer.deb
    # or
    sudo apt install ./cortex-network-installer.deb

The binary will be installed in the /usr/bin/ directory.

Usage

After installation, you can run Cortex.cpp from the command line by typing cortex --help. For Beta preview, you can run cortex-beta --help.

Built-in Model Library

Cortex.cpp supports various models available on the Cortex Hub. Once downloaded, all model source files will be stored in ~\cortexcpp\models.

Example models:

Model	llama.cpp :gguf	TensorRT :tensorrt	ONNXRuntime :onnx	Command
llama3.1	✅		✅	cortex run llama3.1:gguf
llama3	✅	✅	✅	cortex run llama3
mistral	✅	✅	✅	cortex run mistral
qwen2	✅			cortex run qwen2:7b-gguf
codestral	✅			cortex run codestral:22b-gguf
command-r	✅			cortex run command-r:35b-gguf
gemma	✅		✅	cortex run gemma
mixtral	✅			cortex run mixtral:7x8b-gguf
openhermes-2.5	✅	✅	✅	cortex run openhermes-2.5
phi3 (medium)	✅		✅	cortex run phi3:medium
phi3 (mini)	✅		✅	cortex run phi3:mini
tinyllama	✅			cortex run tinyllama:1b-gguf

Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 14B models, and 32 GB to run the 32B models.

Cortex.cpp CLI Commands

For complete details on CLI commands, please refer to our CLI documentation.

REST API

Cortex.cpp includes a REST API accessible at localhost:39281. For a complete list of endpoints and their usage, visit our API documentation.

Advanced Installation

Local Installer: Beta & Nightly Versions

Beta is an early preview for new versions of Cortex. It is for users who want to try new features early - we appreciate your feedback.

Nightly is our development version of Cortex. It is released every night and may contain bugs and experimental features.

Version Type	Windows	MacOS	Linux
Stable (Recommended)	cortex-local-installer.exe	cortex-local-installer.pkg	cortex-local-installer.deb
Beta (Preview)	cortex-local-installer.exe	cortex-local-installer.pkg	cortex-local-installer.deb
Nightly Build (Experimental)	cortex-local-installer.exe	cortex-local-installer.pkg	cortex-local-installer.deb

Network Installer

Cortex.cpp is available with a Network Installer, which is a smaller installer but requires internet connection during installation to download the necessary dependencies.

Version Type	Windows	MacOS	Linux
Stable (Recommended)	cortex-network-installer.exe	cortex-network-installer.pkg	cortex-network-installer.deb
Beta (Preview)	cortex-network-installer.exe	cortex-network-installer.pkg	cortex-network-installer.deb
Nightly Build (Experimental)	cortex-network-installer.exe	cortex-network-installer.pkg	cortex-network-installer.deb

Build from Source

Windows

1. Clone the Cortex.cpp repository here.
2. Navigate to the engine > vcpkg folder.
3. Configure the vpkg:

cd vcpkg
./bootstrap-vcpkg.bat
vcpkg install

4. Build the Cortex.cpp inside the build folder:

mkdir build
cd build
cmake .. -DBUILD_SHARED_LIBS=OFF -DCMAKE_TOOLCHAIN_FILE=path_to_vcpkg_folder/vcpkg/scripts/buildsystems/vcpkg.cmake -DVCPKG_TARGET_TRIPLET=x64-windows-static

5. Use Visual Studio with the C++ development kit to build the project using the files generated in the build folder.
6. Verify that Cortex.cpp is installed correctly by getting help information.

# Get the help information
cortex -h

MacOS

1. Clone the Cortex.cpp repository here.
2. Navigate to the engine > vcpkg folder.
3. Configure the vpkg:

cd vcpkg
./bootstrap-vcpkg.sh
vcpkg install

4. Build the Cortex.cpp inside the build folder:

mkdir build
cd build
cmake .. -DCMAKE_TOOLCHAIN_FILE=path_to_vcpkg_folder/vcpkg/scripts/buildsystems/vcpkg.cmake
make -j4

5. Use Visual Studio with the C++ development kit to build the project using the files generated in the build folder.
6. Verify that Cortex.cpp is installed correctly by getting help information.

# Get the help information
cortex -h

Linux

1. Clone the Cortex.cpp repository here.
2. Navigate to the engine > vcpkg folder.
3. Configure the vpkg:

cd vcpkg
./bootstrap-vcpkg.sh
vcpkg install

4. Build the Cortex.cpp inside the build folder:

mkdir build
cd build
cmake .. -DCMAKE_TOOLCHAIN_FILE=path_to_vcpkg_folder/vcpkg/scripts/buildsystems/vcpkg.cmake
make -j4

5. Use Visual Studio with the C++ development kit to build the project using the files generated in the build folder.
6. Verify that Cortex.cpp is installed correctly by getting help information.

# Get help
cortex

Uninstallation

Windows

1. Open the Windows Control Panel.
2. Navigate to Add or Remove Programs.
3. Search for cortexcpp and double click to uninstall. (for beta and nightly builds, search for cortexcpp-beta and cortexcpp-nightly respectively)

MacOs

Run the uninstaller script:

sudo sh cortex-uninstall.sh

For MacOS, there is a uninstaller script comes with the binary and added to the /usr/local/bin/ directory. The script is named cortex-uninstall.sh for stable builds, cortex-beta-uninstall.sh for beta builds and cortex-nightly-uninstall.sh for nightly builds.

Linux

# For stable builds
sudo apt remove cortexcpp

Contact Support

• For support, please file a GitHub ticket.
• For questions, join our Discord here.
• For long-form inquiries, please email hello@jan.ai.