2.2.18 — Feature Added

Context Compression automatically summarizes conversation history using a smaller, cost-efficient model before sending requests to your primary model. This significantly reduces input token costs while preserving conversation context.

Highlights

• Up to 78% token savings on long multi-turn conversations
• Three compression strategies to balance quality vs. savings:
• conservative — compresses after 8+ turns (minimal context loss)
• on — compresses after 6+ turns (balanced)
• aggressive — compresses after 3+ turns (maximum savings)
• All endpoints supported:
• POST /v1/chat/completions
• POST /v1/messages
• POST /v1/responses

How to Enable

Option 1: API Key Dashboard (Zero Code Changes)

Go to API Key Management → Edit your API key → Enable Context Compression and select your preferred strategy. All requests using that key will automatically apply compression.

Option 2: Per-Request via Request Body

  {
    "model": "gpt-4.1",
    "messages": [...],
    "compression": {
      "enabled": true,
      "strategy": "on",
      "model": "gpt-4.1-mini"
    }
  }

Option 3: Per-Request via HTTP Headers

X-Context-Compression: on X-Compression-Model: gpt-4.1-mini

SDK Support

Compression examples are now available for all supported SDKs:

• Python SDK (OpenAI, Anthropic, Responses API)
• TypeScript / Vercel AI SDK (@apertis/ai-sdk-provider)
• LangChain (via default_headers)
• LlamaIndex (via additional_kwargs)
• LiteLLM (via extra_headers)

Priority

Request body params > HTTP headers > API key defaults. Per-request settings always override key-level defaults.

See more on **Documentation**