Unverified50% confidenceSolutionExact time
The continuation token mechanism makes "a million tokens in a single response" engineering-feasible by splitting one ultra-long generation into multiple coherent segments, but it requires the model to maintain contextual consistency across segments.
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50%
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Long-term
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10/13/2026
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UnverifiedThe self-attention mechanism allows the model to dynamically weigh the importance of all other tokens in the sequence when processing each token, thereby capturing long-range semantic dependencies.73% similarUnverifiedContext length refers to the total number of tokens a model can accommodate in a single request, including input and output; when the upper limit is exceeded, different services handle it differently, with some returning an error directly and others silently truncating.68% similarUnverifiedThe ability to replay execution from an intermediate node is critical because LLM calls have latency and are typically billed per token, avoiding the need to re-run the entire process from the beginning each time.67% similarUnverifiedDify's Agent supports configuring a maximum number of iterations, which can prevent the model from falling into infinite loops and consuming large amounts of tokens.67% similarUnverifiedAgent 的每一轮循环都需将完整历史上下文传入 LLM，导致 token 消耗随任务复杂度呈线性乃至指数增长67% similar
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