Qwen (Alibaba)

# settings.json "env" block, or your shell:
ANTHROPIC_BASE_URL=https://dashscope-intl.aliyuncs.com/compatible-mode/v1
ANTHROPIC_AUTH_TOKEN=<YOUR_API_KEY>
ANTHROPIC_MODEL=qwen-flash

# Claude Code speaks the Anthropic Messages API. Use an Anthropic-compatible
# endpoint, or an OpenAI→Anthropic proxy in front of Qwen (Alibaba).

You are being set up to use a free LLM API as your model backend.

Provider:     Qwen (Alibaba)
Base URL:     https://dashscope-intl.aliyuncs.com/compatible-mode/v1
Model:        qwen-flash
Auth:         Bearer token (OpenAI-compatible)
Key env var:  DASHSCOPE_API_KEY

Task:
1. Configure Claude Code to call the endpoint above using the OpenAI Chat Completions format.
2. Read the API key from the DASHSCOPE_API_KEY environment variable. Do NOT
   ask me to paste the key in plain text in this chat — I will set it in my env.
3. If a setting requires a base URL, use exactly: https://dashscope-intl.aliyuncs.com/compatible-mode/v1
4. Send one short test message ("ping") and report back whether the call
   succeeded, including the model name and latency.

If anything is missing (e.g. an account ID for the base URL), ask me for just
that value and nothing else.

curl https://dashscope-intl.aliyuncs.com/compatible-mode/v1/chat/completions \
  -H "Authorization: Bearer <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-flash",
    "messages": [{ "role": "user", "content": "Hello!" }]
  }'

{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "model": "qwen-flash",
  "choices": [
    {
      "index": 0,
      "message": { "role": "assistant", "content": "Hello! How can I help?" },
      "finish_reason": "stop"
    }
  ],
  "usage": { "prompt_tokens": 9, "completion_tokens": 12, "total_tokens": 21 }
}