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fix(middleware): repair dangling tool-call history after loop interru… (#2035)

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* fix(middleware): repair dangling tool-call history after loop interruption (#2029)

* docs(backend): fix middleware chain ordering

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Co-authored-by: luoxiao6645 <luoxiao6645@gmail.com>
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2026-04-12 19:11:22 +08:00
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@@ -658,6 +658,8 @@ This is the difference between a chatbot with tool access and an agent with an a
**Summarization**: Within a session, DeerFlow manages context aggressively — summarizing completed sub-tasks, offloading intermediate results to the filesystem, compressing what's no longer immediately relevant. This lets it stay sharp across long, multi-step tasks without blowing the context window.
**Strict Tool-Call Recovery**: When a provider or middleware interrupts a tool-call loop, DeerFlow now strips provider-level raw tool-call metadata on forced-stop assistant messages and injects placeholder tool results for dangling calls before the next model invocation. This keeps OpenAI-compatible reasoning models that strictly validate `tool_call_id` sequences from failing with malformed history errors.
### Long-Term Memory
Most agents forget everything the moment a conversation ends. DeerFlow remembers.