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fix(agent): clamp DashScope max_tokens to the provider's 8192 ceiling

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matevip 2026-05-19 16:53:06 +08:00
parent 3d643f909d
commit b0d9bde664
1 changed files with 22 additions and 1 deletions
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23
mateclaw-server/src/main/java/vip/mate/agent/graph/node/ReasoningNode.java
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@ -71,6 +71,17 @@ public class ReasoningNode implements NodeAction {
*/
private static final int DEFAULT_MAX_OUTPUT_TOKENS = 16384;
/**
* DashScope's native chat API caps {@code max_tokens} at 8192 and returns a
* 400 {@code InvalidParameter} ("Range of max_tokens should be [1, 8192]")
* for anything larger. The failover layer misclassifies that 400 as
* "model not found" and silently switches to a different provider, so the
* per-call ceiling must be clamped to this value for DashScope-backed
* models — keeping {@link #DEFAULT_MAX_OUTPUT_TOKENS} for every other
* provider that does accept the larger budget.
*/
private static final int DASHSCOPE_MAX_OUTPUT_TOKENS = 8192;
/**
* Hermes-agent style enforcement clause appended to every ReasoningNode
* system prompt. Treats narration ("I will now …") as a protocol violation
@ -768,9 +779,19 @@ public class ReasoningNode implements NodeAction {
// 始终使用 OpenAiChatOptions（而非 ToolCallingChatOptions），
// 因为 ToolCallingChatOptions 会丢失 OpenAI 特有参数（streamUsage 等），
// 导致 Kimi 等 OpenAI 兼容 API 响应异常或提前截断。
// DashScope rejects max_tokens above its 8192 ceiling with a 400 that
// the failover layer misreads as "model not found"; clamp so a
// DashScope-backed model never overflows the provider limit.
int effectiveMaxTokens = maxOutputTokens;
if (chatModel instanceof com.alibaba.cloud.ai.dashscope.chat.DashScopeChatModel
&& effectiveMaxTokens > DASHSCOPE_MAX_OUTPUT_TOKENS) {
log.debug("[ReasoningNode] Clamping max_tokens {} -> {} for DashScope-backed model",
effectiveMaxTokens, DASHSCOPE_MAX_OUTPUT_TOKENS);
effectiveMaxTokens = DASHSCOPE_MAX_OUTPUT_TOKENS;
}
OpenAiChatOptions.Builder oaiBuilder = OpenAiChatOptions.builder()
.toolCallbacks(toolCallbacks)
.maxTokens(maxOutputTokens);
.maxTokens(effectiveMaxTokens);
if (StringUtils.hasText(effectiveReasoning)) {
oaiBuilder.reasoningEffort(effectiveReasoning);
}