enhance SSE parsing, add stream error/truncation detection, fix tool_call fallback extraction

llmcore.py

@@ -78,6 +78,7 @@ class SiderLLMSession:
 def _parse_claude_sse(resp_lines):
     """Parse Anthropic SSE stream. Yields text chunks, returns list[content_block]."""
     content_blocks = []; current_block = None; tool_json_buf = ""
+    stop_reason = None; got_message_stop = False
     for line in resp_lines:
         if not line: continue
         line = line.decode('utf-8') if isinstance(line, bytes) else line
@@ -85,7 +86,9 @@ def _parse_claude_sse(resp_lines):
         data_str = line[5:].lstrip()
         if data_str == "[DONE]": break
         try: evt = json.loads(data_str)
-        except: continue
+        except Exception as e:
+            print(f"[SSE] JSON parse error: {e}, line: {data_str[:200]}")
+            continue
         evt_type = evt.get("type", "")
         if evt_type == "message_start":
             usage = evt.get("message", {}).get("usage", {})
@@ -111,6 +114,25 @@ def _parse_claude_sse(resp_lines):
                     except: current_block["input"] = {"_raw": tool_json_buf}
                 content_blocks.append(current_block)
                 current_block = None
+        elif evt_type == "message_delta":
+            delta = evt.get("delta", {})
+            stop_reason = delta.get("stop_reason", stop_reason)
+            out_usage = evt.get("usage", {})
+            out_tokens = out_usage.get("output_tokens", 0)
+            if out_tokens: print(f"[Output] tokens={out_tokens} stop_reason={stop_reason}")
+        elif evt_type == "message_stop": got_message_stop = True
+        elif evt_type == "error":
+            err = evt.get("error", {})
+            emsg = err.get("message", str(err)) if isinstance(err, dict) else str(err)
+            print(f"[SSE ERROR] {emsg}")
+            yield f"\n\n[SSE Error: {emsg}]"
+            break
+    if not got_message_stop and not stop_reason:
+        print("[WARN] SSE stream ended without message_stop - possible network interruption")
+        yield "\n\n[!!! 流异常中断，未收到完整响应 !!!]"
+    elif stop_reason == "max_tokens":
+        print(f"[WARN] Response truncated: max_tokens")
+        yield "\n\n[!!! Response truncated: max_tokens !!!]"
     return content_blocks
 
 def _parse_openai_sse(resp_lines, api_mode="chat_completions"):
@@ -557,7 +579,19 @@ class NativeOAISession:
         text_parts = [b["text"] for b in content_blocks if b.get("type") == "text"]
         content = "\n".join(text_parts).strip()
         tool_calls = [MockToolCall(b["name"], b.get("input", {}), id=b.get("id", "")) for b in content_blocks if b.get("type") == "tool_use"]
-        return MockResponse("", content, tool_calls, str(content_blocks))
+        if len(tool_calls) == 0 and content.endswith('}]') and '[{"type":"tool_use"' in content:
+            try:
+                idx = content.index('[{"type":"tool_use"')
+                raw = json.loads(content[idx:])
+                tool_calls = [MockToolCall(b["name"], b.get("input", {}), id=b.get("id", "")) for b in raw if b.get("type") == "tool_use"]
+                content = content[:idx].strip()
+            except: pass
+        think_pattern = r"<thinking>(.*?)</thinking>"; thinking = ''
+        think_match = re.search(think_pattern, content, re.DOTALL)
+        if think_match:
+            thinking = think_match.group(1).strip()
+            content = re.sub(think_pattern, "", content, flags=re.DOTALL)
+        return MockResponse(thinking, content, tool_calls, str(content_blocks))
 
 
 class NativeClaudeSession:
@@ -712,8 +746,7 @@ class ToolClient:
 """
         if self.auto_save_tokens and self.last_tools == tools_json:
             tool_instruction = "\n### 工具库状态：持续有效（code_run/file_read等），**可正常调用**。调用协议沿用。\n"
-        else:
-            self.total_cd_tokens = 0
+        else: self.total_cd_tokens = 0
         self.last_tools = tools_json
         return tool_instruction
 
@@ -843,7 +876,6 @@ class NativeToolClient:
 每次回复请遵循：
 1. 在 <thinking></thinking> 标签中先分析现状和策略
 2. 在 <summary></summary> 中输出极简单行（<30字）物理快照：上次结果新信息+本次意图。此内容进入长期工作记忆。
-3. 如需调用工具，直接使用工具调用能力，然后结束回复。
 """.strip()
     def __init__(self, backend):
         self.backend = backend