From 64ac579c2aeccc16776eaf0f017604ca059d7ecc Mon Sep 17 00:00:00 2001
From: panyy <yf_pan.yuanyin@unisinsight.com>
Date: Thu, 25 Jun 2026 09:39:25 +0800
Subject: [PATCH] =?UTF-8?q?feat(=E6=80=9D=E7=BB=B4=E5=AF=BC=E5=9B=BE?=
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---
 mineru/cli/fast_api.py | 51 ++++++++++++++++++++++++++++++++++++------
 1 file changed, 44 insertions(+), 7 deletions(-)

diff --git a/mineru/cli/fast_api.py b/mineru/cli/fast_api.py
index 3a822b8..58a32b7 100644
--- a/mineru/cli/fast_api.py
+++ b/mineru/cli/fast_api.py
@@ -367,14 +367,37 @@ class MindmapOrganizeRequest(BaseModel):
     prompt: Optional[str] = None
 
 
-def _extract_json_object(text: str) -> str:
-    content = text.strip()
+def _extract_json_object(text: Optional[str]) -> str:
+    content = (text or "").strip()
     if content.startswith("```"):
         content = re.sub(r"^```(?:json|markdown|md)?\s*", "", content, flags=re.IGNORECASE)
         content = re.sub(r"\s*```$", "", content)
     return content.strip()
 
 
+def _extract_llm_message_content(message: dict) -> str:
+    content = message.get("content")
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts = []
+        for item in content:
+            if isinstance(item, str):
+                parts.append(item)
+            elif isinstance(item, dict):
+                text = item.get("text") or item.get("content")
+                if isinstance(text, str):
+                    parts.append(text)
+        if parts:
+            return "\n".join(parts)
+
+    for key in ("reasoning_content", "reasoning", "output_text", "text"):
+        value = message.get(key)
+        if isinstance(value, str) and value.strip():
+            return value
+    return ""
+
+
 DEFAULT_MINDMAP_ORGANIZE_PROMPT = """你是文档结构整理助手。请基于用户提供的 Markdown 生成适合思维导图展示的 Markdown。
 
 要求：
@@ -551,14 +574,28 @@ def _call_mindmap_llm(markdown: str, mode: str = "smart", custom_prompt: Optiona
     except Exception as exc:
         raise RuntimeError(f"智能整理模型请求失败: {exc}") from exc
 
-    message = result.get("choices", [{}])[0].get("message", {})
-    content = message.get("content", "")
+    choices = result.get("choices") or []
+    choice = choices[0] if choices else {}
+    message = choice.get("message") or {}
+    finish_reason = choice.get("finish_reason")
+    usage = result.get("usage")
+    content = _extract_llm_message_content(message)
+    if not content:
+        logger.warning(
+            "Mindmap LLM returned empty content task_id={} role={} finish_reason={} usage={} message_keys={}",
+            task_id or "-", request_role, finish_reason, usage, list(message.keys())
+        )
+        raise RuntimeError(f"智能整理模型返回空内容，finish_reason={finish_reason}")
     organized = _extract_json_object(content)
     if not organized:
-        raise RuntimeError("智能整理模型未返回有效内容")
+        logger.warning(
+            "Mindmap LLM returned invalid organized content task_id={} role={} finish_reason={} usage={}",
+            task_id or "-", request_role, finish_reason, usage
+        )
+        raise RuntimeError(f"智能整理模型未返回有效内容，finish_reason={finish_reason}")
     logger.info(
-        "Mindmap LLM request completed task_id={} role={} output_chars={} output_tokens_est={}",
-        task_id or "-", request_role, len(organized), _estimate_tokens(organized)
+        "Mindmap LLM request completed task_id={} role={} finish_reason={} usage={} output_chars={} output_tokens_est={}",
+        task_id or "-", request_role, finish_reason, usage, len(organized), _estimate_tokens(organized)
     )
     return organized