You’re absolutely right, and that’s a fair catch thank you so much. The example code contradicts what I said. The cleaner architecture — and what we should hav

You’re absolutely right, and that’s a fair catch thank you so much. The example code contradicts what I said. The cleaner architecture — and what we should have shown — is a two-step approach where our API only handles compression, and your key never leaves your environment: # Step 1: call AgentReady only to compress import requests compressed = requests.post("https://agentready.cloud/v1/compress https://agentready.cloud/v1/compress", headers={"Authorization": "ak_..."}, json={"messages": [{"role": "user", "content": your_long_prompt}]} ).json() # Step 2: call OpenAI directly with YOUR key — we never see it from openai import OpenAI client = OpenAI(api_key="sk-...") response = client.chat.completions.create( model="gpt-4o", messages=compressed["messages"] ) This way AgentReady only touches the text for compression — never your LLM API key. We’ll update the docs and example code accordingly ASAP. Thanks for pushing on this.