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](https://apertis.ai/token) → 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 ```json { "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**](https://docs.apertis.ai/api/text-generation/context-compression)