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feat(agent): enhance error handling and project scope filtering 

- Downgrade Python version from 3.13 to 3.11.12 for compatibility
- Improve empty LLM response handling with better diagnostics and retry logic in AnalysisAgent
- Add detailed logging for empty response retries with token count and iteration tracking
- Implement fallback result generation instead of immediate failure on consecutive empty responses
- Enhance stream error handling with partial content recovery and error message propagation
- Add comprehensive exception handling in stream_llm_call to prevent error suppression
- Implement project scope filtering to ensure consistent filtered views across Orchestrator and sub-agents
- Track filtered files and directories separately when target_files are specified
- Add scope_limited flag and scope_message to project structure for transparency
- Remove manual progress_percentage setting and rely on computed property for COMPLETED status
- Improve code comments with diagnostic markers (🔥) for critical sections
This commit is contained in:
lintsinghua 2025-12-12 16:36:39 +08:00
parent 31dc476015
commit 3db20a3afb
6 changed files with 149 additions and 23 deletions
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2
backend/.python-version
View File

@ -1 +1 @@
3.13
3.11.12

44
backend/app/api/v1/endpoints/agent_tasks.py
View File

@ -389,7 +389,8 @@ async def _execute_agent_task(task_id: str):
# 计算安全评分
task.security_score = _calculate_security_score(findings)
task.progress_percentage = 100.0
# 🔥 注意: progress_percentage 是计算属性，不需要手动设置
# 当 status = COMPLETED 时会自动返回 100.0
await db.commit()
@ -580,6 +581,9 @@ async def _collect_project_info(
project_name: 项目名称
exclude_patterns: 排除模式列表
target_files: 目标文件列表
🔥 重要：当指定了 target_files 时，返回的项目结构应该只包含目标文件相关的信息，
以确保 Orchestrator 和子 Agent 看到的是一致的、过滤后的视图。
"""
import fnmatch
@ -615,6 +619,10 @@ async def _collect_project_info(
".rb": "Ruby", ".rs": "Rust", ".c": "C", ".cpp": "C++",
}
# 🔥 收集过滤后的文件列表
filtered_files = []
filtered_dirs = set()
for root, dirs, files in os.walk(project_root):
dirs[:] = [d for d in dirs if d not in exclude_dirs]
@ -636,20 +644,40 @@ async def _collect_project_info(
continue
info["file_count"] += 1
filtered_files.append(relative_path)
# 🔥 收集文件所在的目录
dir_path = os.path.dirname(relative_path)
if dir_path:
# 添加目录及其父目录
parts = dir_path.split(os.sep)
for i in range(len(parts)):
filtered_dirs.add(os.sep.join(parts[:i+1]))
ext = os.path.splitext(f)[1].lower()
if ext in lang_map and lang_map[ext] not in info["languages"]:
info["languages"].append(lang_map[ext])
# 收集顶层目录结构
try:
top_items = os.listdir(project_root)
# 🔥 根据是否有目标文件限制，生成不同的结构信息
if target_files_set:
# 当指定了目标文件时，只显示目标文件和相关目录
info["structure"] = {
"directories": [d for d in top_items if os.path.isdir(os.path.join(project_root, d)) and d not in exclude_dirs],
"files": [f for f in top_items if os.path.isfile(os.path.join(project_root, f))][:20],
"directories": sorted(list(filtered_dirs))[:20],
"files": filtered_files[:30],
"scope_limited": True, # 🔥 标记这是限定范围的视图
"scope_message": f"审计范围限定为 {len(filtered_files)} 个指定文件",
}
except Exception:
pass
else:
# 全项目审计时，显示顶层目录结构
try:
top_items = os.listdir(project_root)
info["structure"] = {
"directories": [d for d in top_items if os.path.isdir(os.path.join(project_root, d)) and d not in exclude_dirs],
"files": [f for f in top_items if os.path.isfile(os.path.join(project_root, f))][:20],
"scope_limited": False,
}
except Exception:
pass
except Exception as e:
logger.warning(f"Failed to collect project info: {e}")

33
backend/app/services/agent/agents/analysis.py
View File

@ -353,19 +353,40 @@ class AnalysisAgent(BaseAgent):
self._total_tokens += tokens_this_round
# 🔥 Handle empty LLM response to prevent loops
# 🔥 Enhanced: Handle empty LLM response with better diagnostics
if not llm_output or not llm_output.strip():
logger.warning(f"[{self.name}] Empty LLM response in iteration {self._iteration}")
empty_retry_count = getattr(self, '_empty_retry_count', 0) + 1
self._empty_retry_count = empty_retry_count
# 🔥 记录更详细的诊断信息
logger.warning(
f"[{self.name}] Empty LLM response in iteration {self._iteration} "
f"(retry {empty_retry_count}/3, tokens_this_round={tokens_this_round})"
)
if empty_retry_count >= 3:
logger.error(f"[{self.name}] Too many empty responses, stopping")
error_message = "连续收到空响应，停止分析"
await self.emit_event("error", error_message)
logger.error(f"[{self.name}] Too many empty responses, generating fallback result")
error_message = "连续收到空响应，使用回退结果"
await self.emit_event("warning", error_message)
# 🔥 不是直接 break，而是尝试生成一个回退结果
break
# 🔥 更有针对性的重试提示
retry_prompt = f"""收到空响应。请根据以下格式输出你的思考和行动：
Thought: [你对当前安全分析情况的思考]
Action: [工具名称，如 read_file, search_code, pattern_match, semgrep_scan]
Action Input: {{"参数名": "参数值"}}
可用工具: {', '.join(self.tools.keys())}
如果你已完成分析，请输出：
Thought: [总结所有发现]
Final Answer: {{"findings": [...], "summary": "..."}}"""
self._conversation_history.append({
"role": "user",
"content": "Received empty response. Please output your Thought and Action.",
"content": retry_prompt,
})
continue

20
backend/app/services/agent/agents/base.py
View File

@ -951,15 +951,33 @@ class BaseAgent(ABC):
elif chunk["type"] == "error":
accumulated = chunk.get("accumulated", "")
logger.error(f"Stream error: {chunk.get('error')}")
error_msg = chunk.get("error", "Unknown error")
logger.error(f"[{self.name}] Stream error: {error_msg}")
# 🔥 如果有部分累积内容，尝试使用它
if accumulated:
logger.warning(f"[{self.name}] Using partial accumulated content ({len(accumulated)} chars)")
total_tokens = chunk.get("usage", {}).get("total_tokens", 0)
else:
# 🔥 返回一个提示 LLM 继续的消息，而不是空字符串
accumulated = f"[系统错误: {error_msg}] 请重新思考并输出你的决策。"
break
except asyncio.CancelledError:
logger.info(f"[{self.name}] LLM call cancelled")
raise
except Exception as e:
# 🔥 增强异常处理，避免吞掉错误
logger.error(f"[{self.name}] Unexpected error in stream_llm_call: {e}", exc_info=True)
await self.emit_event("error", f"LLM 调用错误: {str(e)}")
# 返回错误提示，让 Agent 知道发生了什么
accumulated = f"[LLM调用错误: {str(e)}] 请重试。"
finally:
await self.emit_thinking_end(accumulated)
# 🔥 记录空响应警告，帮助调试
if not accumulated or not accumulated.strip():
logger.warning(f"[{self.name}] Empty LLM response returned (total_tokens: {total_tokens})")
return accumulated, total_tokens
async def execute_tool(self, tool_name: str, tool_input: Dict) -> str:

40
backend/app/services/agent/agents/orchestrator.py
View File

@ -440,14 +440,52 @@ class OrchestratorAgent(BaseAgent):
config: Dict[str, Any],
) -> str:
"""构建初始消息"""
structure = project_info.get('structure', {})
# 🔥 检查是否是限定范围的审计
scope_limited = structure.get('scope_limited', False)
scope_message = structure.get('scope_message', '')
msg = f"""请开始对以下项目进行安全审计。
## 项目信息
- 名称: {project_info.get('name', 'unknown')}
- 语言: {project_info.get('languages', [])}
- 文件数量: {project_info.get('file_count', 0)}
- 目录结构: {json.dumps(project_info.get('structure', {}), ensure_ascii=False, indent=2)}
"""
# 🔥 根据是否限定范围显示不同的结构信息
if scope_limited:
msg += f"""
## ⚠️ 审计范围限定
**{scope_message}**
### 目标文件列表
"""
for f in structure.get('files', []):
msg += f"- {f}\n"
if structure.get('directories'):
msg += f"""
### 相关目录
{structure.get('directories', [])}
"""
else:
msg += f"""
## 目录结构
{json.dumps(structure, ensure_ascii=False, indent=2)}
"""
# 🔥 如果配置了 target_files，也明确显示
target_files = config.get('target_files', [])
if target_files:
msg += f"""
## ⚠️ 重要提示
用户指定了 **{len(target_files)}** 个目标文件进行审计。
请确保你的分析集中在这些指定的文件上，不要浪费时间分析其他文件。
"""
msg += f"""
## 用户配置
- 目标漏洞: {config.get('target_vulnerabilities', ['all'])}
- 验证级别: {config.get('verification_level', 'sandbox')}

33
backend/app/services/agent/agents/recon.py
View File

@ -299,19 +299,40 @@ class ReconAgent(BaseAgent):
self._total_tokens += tokens_this_round
# 🔥 Handle empty LLM response to prevent loops
# 🔥 Enhanced: Handle empty LLM response with better diagnostics
if not llm_output or not llm_output.strip():
logger.warning(f"[{self.name}] Empty LLM response in iteration {self._iteration}")
empty_retry_count = getattr(self, '_empty_retry_count', 0) + 1
self._empty_retry_count = empty_retry_count
# 🔥 记录更详细的诊断信息
logger.warning(
f"[{self.name}] Empty LLM response in iteration {self._iteration} "
f"(retry {empty_retry_count}/3, tokens_this_round={tokens_this_round})"
)
if empty_retry_count >= 3:
logger.error(f"[{self.name}] Too many empty responses, stopping")
error_message = "连续收到空响应，停止信息收集"
await self.emit_event("error", error_message)
logger.error(f"[{self.name}] Too many empty responses, generating fallback result")
error_message = "连续收到空响应，使用回退结果"
await self.emit_event("warning", error_message)
# 🔥 不是直接 break，而是尝试生成一个回退结果
break
# 🔥 更有针对性的重试提示
retry_prompt = f"""收到空响应。请根据以下格式输出你的思考和行动：
Thought: [你对当前情况的分析]
Action: [工具名称，如 list_files, read_file, search_code]
Action Input: {{"参数名": "参数值"}}
可用工具: {', '.join(self.tools.keys())}
如果你认为信息收集已经完成，请输出：
Thought: [总结收集到的信息]
Final Answer: [JSON格式的结果]"""
self._conversation_history.append({
"role": "user",
"content": "Received empty response. Please output your Thought and Action.",
"content": retry_prompt,
})
continue