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e759ad4a1b
- Settings → Models: inline API key, frosted drawer, dark-mode polish, provider icons, i18n sweep - WeChat Work channel: rebuild HttpClient on reconnect, dedup failure signals, route auth_succeed errcode!=0 through failure handler - Channel framework: per-adapter error isolation, QR auth SPI, health indicators - Agent: patch cross-turn assistants for DeepSeek thinking-mode - GitHub: bilingual issue templates with required fields
56 lines
2.2 KiB
Java
56 lines
2.2 KiB
Java
package vip.mate.channel;
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import org.springframework.stereotype.Component;
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/**
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* Single source of truth for "is this assistant reply actually an error
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* surface?" used across the channel layer.
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*
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* <p>Why this matters: an LLM-side 400 (DashScope's "Bad request, please
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* check input", DeepSeek thinking-mode "reasoning_content must be passed
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* back", Anthropic "does not support assistant message prefill") is rendered
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* as a normal-looking assistant string by {@code NodeStreamingChatHelper}.
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* If that string is persisted with {@code status='completed'}, the next
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* turn's history feeds it back to the LLM as a real assistant turn and the
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* 400 self-replicates indefinitely.
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*
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* <p>The fix has two layers:
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* <ol>
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* <li>This classifier flips the persisted status to {@code 'error'} so
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* {@code BaseAgent.sanitizeForLlm} filters it from history.</li>
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* <li>The "[错误] " content prefix kept on disk is the legacy backup
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* filter — both work together.</li>
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* </ol>
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*
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* <p>Heuristics are kept in sync with the error-message templates emitted
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* by {@code NodeStreamingChatHelper.buildErrorResultWithType} and friends.
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* Adding a new error template there means adding the matching probe here.
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*/
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@Component
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public class ChannelErrorClassifier {
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/**
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* @return {@code true} if the reply text matches one of the known
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* LLM-side error surfaces and should NOT be treated as a real
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* assistant turn for memory / history purposes.
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*/
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public boolean isErrorReply(String reply) {
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if (reply == null || reply.isBlank()) {
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return false;
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}
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return reply.startsWith("[错误] ")
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|| reply.contains("Bad request:")
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|| reply.contains("LLM 调用失败:")
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|| reply.contains("LLM 调用超时")
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|| reply.contains("LLM 调用被中断")
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|| reply.contains("Prompt 过长:")
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|| reply.contains("认证失败:")
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|| reply.contains("LLM 返回空响应");
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}
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/** Map a classification result to the {@code mate_message.status} value. */
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public String statusFor(String reply) {
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return isErrorReply(reply) ? "error" : "completed";
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}
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}
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