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How to Connect to GPT-5.6 API: Selecting Sol, Terra, Luna and Configuring Inference Parameters
GPT-5.6 comes in three variants—Sol, Terra, and Luna—all supporting a 1.05M token context window and up to 128K output tokens; integration only requires changing the base_url, reasoning depth is controlled via reasoning.effort, and long-context tests verify whether a channel is downgraded.
How to Integrate Agent APIs: Four Verification Points from Framework Configuration to Tool Calling
AI Agents rely on the underlying model's native tool calling for multi-turn reasoning; when integrating OpenAI-compatible APIs, verify four key points: passthrough support for tools parameters, complete long-context retention, clear rate limits, and state tracking after tool returns.
How to Integrate a Streaming Output API: SSE Parsing, Token Usage, and Proxy Buffering Troubleshooting
Starting from a working curl command, this guide explains the SSE message structure of streaming output APIs, the empty choices and cross-packet issues easily missed during parsing, how to get token usage with stream_options, the troubleshooting order for reverse proxy buffering that causes one-shot output, and how to abort upstream requests when the client disconnects.
How to Design AI API Retries: What to Retry, How Long to Back Off, and What to Do When a Stream Breaks
Split LLM call errors into retryable transient failures and deterministic failures that retrying won't fix, with parameter choices for Retry-After priority and jittered exponential backoff, plus handling for three common traps: stream interruptions, nested SDK retries, and tool-call side effects.
How to Handle AI API Rate Limiting: From 429 Headers to Backoff Retries and Traffic Isolation
When a large model API returns 429, check the response headers and error code before deciding on a retry strategy: honor Retry-After when present, and stop immediately if quota is exhausted. This article covers four dimensions of rate limiting, how to use six remaining-quota headers, an exponential backoff skeleton with jitter, and architectural mitigations like token buckets, tighter max_tokens, and per-key isolation.
