DeepClaude is an advanced inference framework designed to harness the combined strengths of DeepSeek R1 and Claude, offering a powerful solution for reasoning, problem-solving, and code generation. By integrating DeepSeek R1’s structured thinking and logical processing with Claude’s creative and coding capabilities, it provides a seamless and efficient experience through a unified API. Built on a high-performance Rust backend, DeepClaude ensures low latency, secure key management, and full customization options. As an open-source project under the MIT License, it allows developers to self-host, contribute, and tailor it to their needs while maintaining complete control over their data and API usage.
Resource
GitHub
Link: https://github.com/getasterisk/deepclaude
Website
Link: https://deepclaude.com/
Prerequisites for Installing DeepClaude Locally
Make sure you have the following:
- GPUs: 1xRTXA6000 (for smooth execution).
- Disk Space: 100 GB free.
- RAM: 48 GB(24 Also works) but we use 48 for smooth execution
- CPU: 48 Cores(24 Also works)but we use 48 for smooth execution
Step-by-Step Process to Install DeepClaude Locally
For the purpose of this tutorial, we will use a GPU-powered Virtual Machine offered by NodeShift; however, you can replicate the same steps with any other cloud provider of your choice. NodeShift provides the most affordable Virtual Machines at a scale that meets GDPR, SOC2, and ISO27001 requirements.
Step 1: Sign Up and Set Up a NodeShift Cloud Account
Visit the NodeShift Platform and create an account. Once you’ve signed up, log into your account.
Follow the account setup process and provide the necessary details and information.
Step 2: Create a GPU Node (Virtual Machine)
GPU Nodes are NodeShift’s GPU Virtual Machines, on-demand resources equipped with diverse GPUs ranging from H100s to A100s. These GPU-powered VMs provide enhanced environmental control, allowing configuration adjustments for GPUs, CPUs, RAM, and Storage based on specific requirements.
Navigate to the menu on the left side. Select the GPU Nodes option, create a GPU Node in the Dashboard, click the Create GPU Node button, and create your first Virtual Machine deployment.
Step 3: Select a Model, Region, and Storage
In the “GPU Nodes” tab, select a GPU Model and Storage according to your needs and the geographical region where you want to launch your model.
We will use 1x RTX A6000 GPU for this tutorial to achieve the fastest performance. However, you can choose a more affordable GPU with less VRAM if that better suits your requirements.
Step 4: Select Authentication Method
There are two authentication methods available: Password and SSH Key. SSH keys are a more secure option. To create them, please refer to our official documentation.
Step 5: Choose an Image
Next, you will need to choose an image for your Virtual Machine. We will deploy DeepClaude on an NVIDIA Cuda Virtual Machine. This proprietary, closed-source parallel computing platform will allow you to install DeepClaude on your GPU Node.
After choosing the image, click the ‘Create’ button, and your Virtual Machine will be deployed.
Step 6: Virtual Machine Successfully Deployed
You will get visual confirmation that your node is up and running.
Step 7: Connect to GPUs using SSH
NodeShift GPUs can be connected to and controlled through a terminal using the SSH key provided during GPU creation.
Once your GPU Node deployment is successfully created and has reached the ‘RUNNING’ status, you can navigate to the page of your GPU Deployment Instance. Then, click the ‘Connect’ button in the top right corner.
Now open your terminal and paste the proxy SSH IP or direct SSH IP.
Next, if you want to check the GPU details, run the command below:
nvidia-smi
Step 8: Clone the Repository
Run the following command to clone the DeepClaude repository:
git clone https://github.com/getasterisk/deepclaude.git
cd deepclaude
Step 9: Install Cargo (and Rust)
Run the following command to install the Cargo (and Rust):
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
Cargo is the Rust package manager and build tool, so if you haven’t installed Rust yet, you’ll need to install it.
Then, run the following command to verify the Cargo (and Rust) version:
cargo --version
Step 10: Build the Project
Run the following command to build the project:
cargo build --release
Step 11: Create DeepSeek and Anthropic API Key
To use the DeepSeek and Anthropic API, you need to create an API key. This keys will allow you to securely access DeepSeek and Anthropic API services.
Step 12: Export DeepSeek and Anthropic API Key
Run the following command to export the DeepSeek and Anthropic API Key:
export DEEPSEEK_API_KEY="your api key"
export ANTROPIC_API_KEY="your api key"
Step 13: Run DeepClaude Server
Execute the following command to run the deepclaude server:
./target/release/deepclaude
Step 14: Check the Available Python version and Install the new version
Run the following commands to check the available Python version.
If you check the version of the python, system has Python 3.8.1 available by default. To install a higher version of Python, you’ll need to use the deadsnakes PPA.
Run the following commands to add the deadsnakes PPA:
sudo apt update
sudo apt install -y software-properties-common
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt update
Step 15: Install Python 3.11
Now, run the following command to install Python 3.11 or another desired version:
sudo apt install -y python3.11 python3.11-distutils python3.11-venv
Step 16: Update the Default Python3 Version
Now, run the following command to link the new Python version as the default python3:
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 2
sudo update-alternatives --config python3
Then, run the following command to verify that the new Python version is active:
python3 --version
Step 17: Install and Update Pip
Run the following command to install and update the pip:
python3 -m ensurepip --upgrade
python3 -m pip install --upgrade pip
Then, run the following command to check the version of pip:
pip --version
Step 18: Create Python File
Run the following command to create a python file:
touch app.py
Step 19: Play With DeepClaude
Now play with DeepClaude in Terminal.
Conclusion
DeepClaude provides a seamless and efficient way to harness the combined reasoning and creativity of DeepSeek R1 and Claude through a unified, high-performance API. With secure key management, full customization, and the ability to self-host, it offers complete control over data and usage. By following the step-by-step installation guide, you can easily set up DeepClaude on a GPU-powered virtual machine and unlock its full potential. As an open-source project under the MIT License, it welcomes contributions from developers looking to refine and expand its capabilities. Whether for problem-solving, code generation, or logical reasoning, DeepClaude delivers a robust and adaptable solution.
