---
title: "Qwen Code CLI"
description: "This tutorial shows you how to integrate the Qwen Code CLI with LiteLLM Proxy, allowing you to route requests through LiteLLM's unified interface."
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/litellm-qwen-code-cli
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:30:39.342Z
license: CC-BY-4.0
attribution: "Qwen Code CLI — Claudary (https://claudary.paisolsolutions.com/skills/litellm-qwen-code-cli)"
---
# Qwen Code CLI
This tutorial shows you how to integrate the Qwen Code CLI with LiteLLM Proxy, allowing you to route requests through LiteLLM's unified interface.
## Overview
# Qwen Code CLI
This tutorial shows you how to integrate the Qwen Code CLI with LiteLLM Proxy, allowing you to route requests through LiteLLM's unified interface.
:::info
This integration is supported from LiteLLM v1.73.3-nightly and above.
:::
## Benefits of using qwen-code with LiteLLM
When you use qwen-code with LiteLLM you get the following benefits:
**Developer Benefits:**
- Universal Model Access: Use any LiteLLM supported model (Anthropic, OpenAI, Vertex AI, Bedrock, etc.) through the qwen-code interface.
- Higher Rate Limits & Reliability: Load balance across multiple models and providers to avoid hitting individual provider limits, with fallbacks to ensure you get responses even if one provider fails.
**Proxy Admin Benefits:**
- Centralized Management: Control access to all models through a single LiteLLM proxy instance without giving your developers API Keys to each provider.
- Budget Controls: Set spending limits and track costs across all qwen-code usage.
## Prerequisites
Before you begin, ensure you have:
- Node.js and npm installed on your system
- A running LiteLLM Proxy instance
- A valid LiteLLM Proxy API key
- Git installed for cloning the repository
## Quick Start Guide
### Step 1: Install Qwen Code CLI
Clone the Qwen Code CLI repository and navigate to the project directory:
```bash
npm install -g @qwen-code/qwen-code
```
### Step 2: Configure Qwen Code CLI for LiteLLM Proxy
Configure the Qwen Code CLI to point to your LiteLLM Proxy instance by setting the required environment variables:
```bash
export OPENAI_BASE_URL="http://localhost:4000"
export OPENAI_API_KEY=sk-1234567890
export OPENAI_MODEL="your-configured-model"
```
**Note:** Replace the values with your actual LiteLLM Proxy configuration:
- `OPENAI_BASE_URL`: The URL where your LiteLLM Proxy is running
- `OPENAI_API_KEY`: Your LiteLLM Proxy API key
- `OPENAI_MODEL`: The model you want to use (configured in your LiteLLM proxy)
### Step 3: Build and Start Qwen Code CLI
Build the project and start the CLI:
```bash
qwen
```
### Step 4: Test the Integration
Once the CLI is running, you can send test requests. These requests will be automatically routed through LiteLLM Proxy to the configured Qwen model.
The CLI will now use LiteLLM Proxy as the backend, giving you access to LiteLLM's features like:
- Request/response logging
- Rate limiting
- Cost tracking
- Model routing and fallbacks
## Advanced
### Use Anthropic, OpenAI, Bedrock, etc. models on qwen-code
In order to use non-qwen models on qwen-code, you need to set a `model_group_alias` in the LiteLLM Proxy config. This tells LiteLLM that requests with model = `qwen-code` should be routed to your desired model from any provider.
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Route `qwen-code` requests to Claude Sonnet:
```yaml showLineNumbers title="proxy_config.yaml"
model_list:
- model_name: claude-sonnet-4-20250514
litellm_params:
model: anthropic/claude-3-5-sonnet-20241022
api_key: os.environ/ANTHROPIC_API_KEY
router_settings:
model_group_alias: {"qwen-code": "claude-sonnet-4-20250514"}
```
Route `qwen-code` requests to GPT-4o:
```yaml showLineNumbers title="proxy_config.yaml"
model_list:
- model_name: gpt-4o-model
litellm_params:
model: gpt-4o
api_key: os.environ/OPENAI_API_KEY
router_settings:
model_group_alias: {"qwen-code": "gpt-4o-model"}
```
Route `qwen-code` requests to Claude on Bedrock:
```yaml showLineNumbers title="proxy_config.yaml"
model_list:
- model_name: bedrock-claude
litellm_params:
model: bedrock/anthropic.claude-haiku-4-5-20251001:0
aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
aws_region_name: us-east-1
router_settings:
model_group_alias: {"qwen-code": "bedrock-claude"}
```
All deployments with model_name=`anthropic-claude` will be load balanced. In this example we load balance between Anthropic and Bedrock.
```yaml showLineNumbers title="proxy_config.yaml"
model_list:
- model_name: anthropic-claude
litellm_params:
model: anthropic/claude-3-5-sonnet-20241022
api_key: os.environ/ANTHROPIC_API_KEY
- model_name: anthropic-claude
litellm_params:
model: bedrock/anthropic.claude-haiku-4-5-20251001:0
aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
aws_region_name: us-east-1
router_settings:
model_group_alias: {"qwen-code": "anthropic-claude"}
```
With this configuration, when you use `qwen-code` in the CLI, LiteLLM will automatically route your requests to the configured provider(s) with load balancing and fallbacks.
## Troubleshooting
If you encounter issues:
1. **Connection errors**: Verify that your LiteLLM Proxy is running and accessible at the configured `OPENAI_BASE_URL`
2. **Authentication errors**: Ensure your `OPENAI_API_KEY` is valid and has the necessary permissions
3. **Build failures**: Make sure all dependencies are installed with `npm install`
---
Source: [Claudary](https://claudary.paisolsolutions.com/skills/litellm-qwen-code-cli) · https://claudary.paisolsolutions.com