We build a practical GLM-5.2 workflow using its hosted, OpenAI-compatible API instead of running the model locally. We set up multiple providers, load the API key securely, and create a reusable chat wrapper. We then test thinking-effort control, streamed reasoning, function calling, a tool-using agent, structured JSON output, and long-context retrieval. We close with token and cost accounting so every demo stays measurable.
The post GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrieval appeared first on MarkTechPost.
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