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We engage GLM-5's cognitive mode to witness its internal reasoning process streamed in real-time via the reasoning_content field prior to the conclusive response. We then construct a sequential dialogue where we inquire about Python lists versus tuples, probe further about NamedTuples, and demand a practical illustration with type annotations, all while the model preserves complete contextual awareness throughout the exchange. We monitor the expanding message count and token consumption with each subsequent interaction.

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