Claude Code (Cloud Compute)Claude Code is an AI-driven command-line coding tool developed by Anthropic. It provides a terminal interface for interacting with Claude and supports AI-assisted development workflows such as code generation, debugging, refactoring, and technical guidance.
Platform Support
Platform / OS
Support
K1 Buildroot
No
K1 OpenHarmony
No
K1 Bianbu LXQT/GNOME
Yes
K3 Buildroot
No
K3 OpenHarmony
No
K3 Bianbu LXQT/GNOME
Yes
1. Installation
1.1 Install npm
[b]
sudo apt install npm
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1.2 Install Claude Code
[b]
sudo npm i -g @anthropic-ai/claude-code@2.1.112
[/b]If access to the default npm registry is restricted, install from a mirror registry instead.
sudo npm i --registry=https://registry.npmmirror.com -g @anthropic-ai/claude-code@2.1.112
Note: Version 2.1.112 is the currently supported release. Do not install a later version.
Verify the installation:
claude --version
If a version number is returned, Claude Code has been installed successfully.
2. Configuration
2.1 Set Environment VariablesAfter obtaining the provider URL and API key, add them to ~/.bashrc as follows:
cat >> ~/.bashrc << 'EOF'
export ANTHROPIC_BASE_URL="Provider URL"
export ANTHROPIC_AUTH_TOKEN="Generated API key"
EOF
source ~/.bashrc
2.2 Configure Automatic API Key Approval
[b]
(cat ~/.claude.json 2>/dev/null || echo 'null') | jq --arg key "${ANTHROPIC_API_KEY: -20}" '(. // {}) | .customApiKeyResponses.approved |= ([.[]?, $key] | unique)' > ~/.claude.json.tmp && mv ~/.claude.json.tmp ~/.claude.json
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3. Basic UsageStart an interactive Claude Code session:
claude
The startup screen appears below.
Example greeting using the Say Hello prompt:
Use /model to switch models.
During an interactive session, Claude Code can help with:
- Answering programming questions
- Generating and optimizing code
- Debugging and refactoring existing code
- Providing technical recommendations and best practices
Enter /exit to end the session.
4. Example WorkflowThis example demonstrates Claude Code generating and debugging an ONNX Runtime image-classification program.
- Enter the following request:
Write a program that calls ONNX Runtime, downloads and uses the ResNet50 model for image classification, and displays the classification result.
Claude Code starts analyzing the request and generating the program.
- Claude Code completes the implementation and provides the execution steps.
- Run the program. If an exception occurs, Claude Code analyzes the error and applies a fix.
- After the fix, the program runs successfully.
- The program can also be executed manually and produces the expected result.
5. Connecting to On-Device AI: Basic TrialClaude Code can also connect to a local on-device inference service for basic experimentation. This section is optional and serves as a simple local trial.
5.1 Set Environment Variables
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cat >> ~/.bashrc << 'EOF'
export ANTHROPIC_BASE_URL="http://localhost:8080"
export ANTHROPIC_AUTH_TOKEN="llama"
EOF
source ~/.bashrc
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5.2 Configure Automatic API Key Approval
[b]
(cat ~/.claude.json 2>/dev/null || echo 'null') | jq --arg key "${ANTHROPIC_API_KEY: -20}" '(. // {}) | .customApiKeyResponses.approved |= ([.[]?, $key] | unique)' > ~/.claude.json.tmp && mv ~/.claude.json.tmp ~/.claude.json
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5.3 Start llama-server
[b]
llama-server -m Qwen2.5-0.5B-Instruct-Q4_0.gguf -t 8 --host 127.0.0.1 --port 8080 --ctx-size 153600 --n-gpu-layers 0 --batch-size 512 --metrics --no-mmap
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Note: Claude Code uses a long input context, so --ctx-size must be set high enough. This example uses 153600 because 15360 is not sufficient for this scenario.
5.4 Run Claude CodeStart Claude Code with the local model and run a simple greeting test.
claude --model qwen2.5:0.5b
The initial greeting may take longer because the model prefill can exceed 17,000 tokens.
Subsequent algorithm-generation tasks are noticeably faster, but output quality may still be constrained by the compact local model.
