Connect Coding Agents to WaveSpeedAI LLM

Use this guide when you want a coding assistant or developer agent to run through WaveSpeedAI LLM using an OpenAI-compatible endpoint. It covers Claude Code, OpenAI Codex, OpenClaw, and other custom model clients.

Recommended Mental Model

Most coding tools are built around one provider. WaveSpeedAI LLM is usually easiest to test when the tool supports an OpenAI-compatible custom provider:

Coding tool
  -> Custom OpenAI-compatible provider
  -> https://llm.wavespeed.ai/v1
  -> Selected WaveSpeedAI model

Claude Code, OpenAI Codex, OpenClaw, or Custom OpenAI?

Universal OpenAI-Compatible Settings

Verify the Backend First

Before configuring an agent, confirm your key and model work with a small API call.

curl --fail-with-body --connect-timeout 10 --max-time 120 \
  https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -d '{
    "model": "deepseek/deepseek-v4-flash",
    "messages": [
      {
        "role": "user",
        "content": "Reply with one sentence confirming you are ready for coding tasks."
      }
    ]
  }'

Verify Current Availability

Model availability changes over time. Confirm the model ID in the LLM Playground, then make the small request above before configuring an agent.

After the endpoint check passes, run a read-only prompt in your coding tool to confirm the selected provider, model, and project permissions before asking it to edit files.

For long coding sessions, keep project instructions, tool definitions, and repository context stable so the selected upstream model has a better chance of reusing cached prompt prefixes. See Prompt Caching for HTTP examples and cache-hit troubleshooting.

Before a Long Coding Session

Run a small prompt first:

Reply with one sentence confirming which model you are.

This helps confirm the agent is using the intended provider, key, and model before it starts reading or editing a large codebase.

Model Selection Tips

Claude Code

Claude Code uses Anthropic-style client settings. WaveSpeedAI exposes the compatible POST /v1/messages endpoint directly, so no additional gateway is required.

Claude Code
  -> https://llm.wavespeed.ai/v1/messages

Set the WaveSpeedAI values in the shell that launches Claude Code:

export ANTHROPIC_BASE_URL="https://llm.wavespeed.ai"
export ANTHROPIC_AUTH_TOKEN="YOUR_WAVESPEED_API_KEY"
export ANTHROPIC_MODEL="deepseek/deepseek-v4-flash"
claude

Windows PowerShell:

$env:ANTHROPIC_BASE_URL = "https://llm.wavespeed.ai"
$env:ANTHROPIC_AUTH_TOKEN = "YOUR_WAVESPEED_API_KEY"
$env:ANTHROPIC_MODEL = "deepseek/deepseek-v4-flash"
claude

If your Claude Code setup loads environment variables from ~/.claude/settings.json, add the WaveSpeedAI values under env.

{
  "env": {
    "DISABLE_AUTOUPDATER": "1",
    "ANTHROPIC_BASE_URL": "https://llm.wavespeed.ai",
    "ANTHROPIC_AUTH_TOKEN": "YOUR_WAVESPEED_API_KEY",
    "ANTHROPIC_MODEL": "deepseek/deepseek-v4-flash"
  }
}

Set ANTHROPIC_MODEL to the model name accepted by your Claude Code runtime. Use the WaveSpeedAI model ID when your setup passes model names through, or use the local alias that maps to a WaveSpeedAI model upstream.

OpenAI Codex

For Codex clients that support custom OpenAI-compatible providers, configure WaveSpeedAI as the provider and use a tested WaveSpeedAI model ID.

model = "deepseek/deepseek-v4-flash"
model_provider = "wavespeed"
 
[model_providers.wavespeed]
name = "WaveSpeedAI LLM"
base_url = "https://llm.wavespeed.ai/v1"
env_key = "WAVESPEED_API_KEY"
wire_api = "responses"

Then launch Codex with your WaveSpeedAI key in the environment:

export WAVESPEED_API_KEY="YOUR_WAVESPEED_API_KEY"
codex

Windows PowerShell:

$env:WAVESPEED_API_KEY = "YOUR_WAVESPEED_API_KEY"
codex

This configuration uses WaveSpeedAI’s POST /v1/responses route. If your Codex version uses different config field names, adapt the surrounding configuration while keeping the base URL, API key environment variable, and available model ID.

After configuring Codex, start with a read-only prompt such as:

Summarize this repository in three bullets. Do not edit files.

OpenClaw

For OpenClaw setups with custom OpenAI-compatible providers, add WaveSpeedAI as a provider and test a small prompt first.

{
  agents: {
    defaults: {
      model: { primary: "wavespeed/deepseek/deepseek-v4-flash" },
    },
  },
  models: {
    mode: "merge",
    providers: {
      wavespeed: {
        baseUrl: "https://llm.wavespeed.ai/v1",
        apiKey: "${WAVESPEED_API_KEY}",
        api: "openai-completions",
        models: [
          {
            id: "deepseek/deepseek-v4-flash",
            name: "DeepSeek V4 Flash via WaveSpeedAI",
            input: ["text"],
          }
        ],
      },
    },
  },
}

If your OpenClaw version uses a different provider config shape, keep the same base URL, API key, and model IDs while adapting the surrounding fields to that version.

After selecting the provider in OpenClaw, start with a read-only prompt before asking it to modify a project.

Troubleshooting