JOJO
0f4cf1078a
This commit bundles a coordinated fix set across frontend and backend runtime flows:\n\n1) Markdown table overflow UX\n- Wrap rendered markdown tables in a dedicated horizontal-scroll container.\n- Preserve wrapper attributes through sanitize so styles always apply.\n- Keep page-level horizontal scroll disabled while allowing in-container table scroll.\n- Improve table container visual consistency (border/radius/shadow/scrollbar behavior).\n\n2) Code block horizontal jitter\n- Adjust code/pre scrollbar gutter and box model handling to remove left-right jump.\n\n3) Execution mode auto-fallback sync + toast behavior\n- Add expiry-driven frontend sync timer for direct->sandbox fallback state refresh.\n- Ensure permission/execution UI state updates at expiry time.\n- Keep fallback warning toast persistent but avoid false-positive toasts when simply switching to sandbox conversations.\n- Trigger fallback toast only when a real direct-expiry transition is detected.\n\n4) Runtime guidance/notify display consistency\n- Unify live polling rendering behavior with history replay behavior.\n- Restore real-time display of guidance/notify/sub-agent/background-command messages.\n- Keep runtime_mode_notice hidden only in idle state as requested.\n\n5) Backend runtime notice emission policy\n- Suppress runtime mode notice insertion when no task is running (idle path).\n- Preserve notice injection when task is actively running.\n\n6) Tool-call ordering safety for injected completion notices\n- Delay inline sub-agent/background-command completion message insertion until all parallel tool calls in the same assistant turn are finished.\n- Prevent invalid assistant/tool_call ordering that causes provider 400 errors for missing tool_call_id responses.\n\n7) Left panel scrolling behavior\n- Enable vertical scrolling for project files / todo / sub-agent / background-command panels.\n- Hide panel scrollbars while preserving scroll capability.\n\n8) Tavily multi-key selection support\n- Introduce config/search.py with selectable env variable name for Tavily key resolution.\n- Keep existing AGENT_TAVILY_API_KEY naming compatible.\n- Export search config through config package.\n\n9) Dedicated conversation-title model config\n- Add AGENT_TITLE_API_BASE_URL / AGENT_TITLE_API_KEY / AGENT_TITLE_MODEL_ID.\n- Route title generation calls to these dedicated credentials/model with fallback defaults.\n\n10) Supporting updates\n- Update .env.example to document new Tavily and title-generation env vars.\n- Include current custom model profile tweak (kimi-k2.6).\n\nValidated with:\n- npm run build\n- python3 -m py_compile (affected backend/config modules)\n- python3 -m unittest test.test_server_refactor_smoke
1294 lines
58 KiB
Python
1294 lines
58 KiB
Python
from __future__ import annotations
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import asyncio
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import json
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import time
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from pathlib import Path
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from typing import Optional, Dict, Any, List
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from .utils_common import debug_log, brief_log
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from .state import MONITOR_FILE_TOOLS, MONITOR_MEMORY_TOOLS, MONITOR_SNAPSHOT_CHAR_LIMIT, MONITOR_MEMORY_ENTRY_LIMIT
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from .state import tool_approval_manager
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from .monitor import cache_monitor_snapshot
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from .security import compact_web_search_result
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from .chat_flow_helpers import detect_tool_failure
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from .chat_flow_runner_helpers import resolve_monitor_path, resolve_monitor_memory, capture_monitor_snapshot
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from utils.tool_result_formatter import (
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extract_mcp_content_for_context,
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format_tool_result_for_context,
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)
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from utils.context_manager import AUTO_SHALLOW_PLACEHOLDER
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from config import TOOL_CALL_COOLDOWN
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from modules.personalization_manager import load_personalization_config, resolve_context_compression_settings
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from modules.auto_approval_service import run_auto_approval
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from .deep_compression import run_deep_compression
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def _format_numbered_lines(lines: List[str], start_line_no: int) -> List[Dict[str, Any]]:
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return [
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{
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"line_no": start_line_no + idx,
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"content": line.rstrip("\n"),
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}
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for idx, line in enumerate(lines)
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]
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def _build_tool_approval_preview(web_terminal, function_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]:
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args = arguments or {}
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preview: Dict[str, Any] = {
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"type": function_name,
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"tool_name": function_name,
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"arguments": args,
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}
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if function_name == "edit_file":
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file_path = args.get("file_path")
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old_string = args.get("old_string")
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new_string = args.get("new_string")
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replace_all_provided = "replace_all" in args
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replace_all = args.get("replace_all") if replace_all_provided else None
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preview["file_path"] = file_path
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preview["replace_all"] = replace_all
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if not file_path:
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preview["summary"] = "缺少 file_path"
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return preview
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if old_string is None or new_string is None:
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preview["summary"] = "缺少 old_string/new_string"
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return preview
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if not replace_all_provided:
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preview["summary"] = "缺少 replace_all（必须显式传入 true 或 false）"
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return preview
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if not isinstance(replace_all, bool):
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preview["summary"] = "replace_all 必须是 true 或 false"
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return preview
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old_text = str(old_string or "")
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short_old_text_notice = len(old_text.splitlines()) < 3
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if short_old_text_notice:
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preview["notice"] = "提示：old_string 少于3行，允许继续执行；需要批量替换的场景可以单行或不足一行"
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try:
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valid, err, full_path = web_terminal.file_manager._validate_path(str(file_path))
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if not valid or full_path is None:
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preview["summary"] = err or "路径校验失败"
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return preview
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resolved_path = str(Path(full_path))
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preview["resolved_path"] = resolved_path
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if not full_path.exists() or not full_path.is_file():
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preview["summary"] = "目标文件不存在，无法生成上下文预览"
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return preview
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content = full_path.read_text(encoding="utf-8", errors="ignore")
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new_text = str(new_string or "")
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old_lines = old_text.splitlines()
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new_lines = new_text.splitlines()
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idx = content.find(old_text) if old_text else -1
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if idx >= 0:
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prefix = content[:idx]
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start_line_no = prefix.count("\n") + 1
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end_line_no = start_line_no + max(1, len(old_lines)) - 1
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all_lines = content.splitlines()
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before_start = max(1, start_line_no - 3)
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before = all_lines[before_start - 1:start_line_no - 1]
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after_end = min(len(all_lines), end_line_no + 3)
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after = all_lines[end_line_no:after_end]
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preview["edit_context"] = {
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"before": _format_numbered_lines(before, before_start),
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"old": _format_numbered_lines(old_lines or [""], start_line_no),
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"new": _format_numbered_lines(new_lines or [""], start_line_no),
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"after": _format_numbered_lines(after, end_line_no + 1),
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"old_start_line": start_line_no,
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"old_end_line": end_line_no,
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}
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mode_text = "全部匹配" if replace_all is True else "首个匹配"
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preview["summary"] = f"编辑 {file_path} 第 {start_line_no}-{end_line_no} 行（{mode_text}）"
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else:
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preview["edit_context"] = {
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"before": [],
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"old": _format_numbered_lines(old_lines or [""], 1),
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"new": _format_numbered_lines(new_lines or [""], 1),
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"after": [],
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"old_start_line": None,
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"old_end_line": None,
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}
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preview["summary"] = "未在文件中定位到 old_string，显示原始替换内容"
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if short_old_text_notice:
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preview["summary"] = f"{preview['summary']}（old_string 少于3行，已告知并继续）"
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except Exception as exc:
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preview["summary"] = f"生成编辑预览失败: {exc}"
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return preview
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if function_name in {"run_command", "terminal_input"}:
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preview["command"] = args.get("command")
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preview["summary"] = f"执行命令: {args.get('command') or ''}"
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return preview
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if function_name in {"run_python", "runpython"}:
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code = str(args.get("code") or "")
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timeout = args.get("timeout")
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preview["code"] = code
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preview["timeout"] = timeout
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# 兼容前端已有 command 展示分支
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preview["command"] = code
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preview["summary"] = f"执行 Python 代码（timeout={timeout if timeout is not None else '未提供'}s）"
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return preview
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if function_name in {"create_file", "create_folder", "delete_file"}:
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preview["path"] = args.get("path")
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preview["summary"] = f"{function_name}: {args.get('path') or ''}"
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return preview
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if function_name == "rename_file":
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preview["old_path"] = args.get("old_path")
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preview["new_path"] = args.get("new_path")
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preview["summary"] = f"rename_file: {args.get('old_path') or ''} -> {args.get('new_path') or ''}"
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return preview
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if function_name == "write_file":
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content = str(args.get("content") or "")
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preview["file_path"] = args.get("file_path")
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preview["append"] = bool(args.get("append", False))
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preview["content_preview"] = content
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preview["content_length"] = len(content)
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preview["summary"] = f"write_file: {args.get('file_path') or ''} ({'append' if preview['append'] else 'overwrite'})"
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return preview
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return preview
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def _is_permission_denied_result(result_data: Dict[str, Any]) -> bool:
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if not isinstance(result_data, dict):
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return False
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if result_data.get("success") is True:
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return False
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fragments: List[str] = []
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for key in ("error", "message", "output"):
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value = result_data.get(key)
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if isinstance(value, str) and value.strip():
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fragments.append(value.lower())
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joined = "\n".join(fragments)
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if not joined:
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return False
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markers = (
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"operation not permitted",
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"permission denied",
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"权限不足",
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"无权限",
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"不允许",
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"access denied",
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)
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return any(marker in joined for marker in markers)
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def _inject_runtime_mode_notice(
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*,
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web_terminal,
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messages: List[Dict[str, Any]],
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content: str,
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sender=None,
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conversation_id: Optional[str] = None,
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) -> None:
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if not isinstance(content, str) or not content.strip():
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return
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text = content.strip()
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metadata = {
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"runtime_guidance": True,
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"runtime_guidance_original": text,
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"runtime_mode_notice": True,
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"message_source": "notify",
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}
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try:
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web_terminal.context_manager.add_conversation(
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"user",
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text,
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metadata=metadata,
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)
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except Exception:
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pass
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messages.append(
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{
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"role": "user",
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"content": text,
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"metadata": metadata,
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}
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)
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if callable(sender):
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try:
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sender(
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"user_message",
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{
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"message": text,
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"conversation_id": conversation_id,
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"runtime_guidance": True,
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"runtime_guidance_original": text,
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"message_source": "notify",
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},
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)
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except Exception:
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pass
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def _format_rejected_tool_text(reason: str) -> str:
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clean_reason = str(reason or "").strip() or "未提供"
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return f"工具调用被拒绝\n原因：{clean_reason}"
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async def _wait_for_tool_approval(*, approval_id: str, username: str, timeout_seconds: float = 3600.0) -> Dict[str, Any]:
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started = time.time()
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while True:
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row = tool_approval_manager.get(approval_id)
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if not row:
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return {"decision": "rejected", "reason": "审批请求不存在"}
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if row.get("username") != username:
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return {"decision": "rejected", "reason": "审批请求用户不匹配"}
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status = row.get("status")
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if status in {"approved", "rejected"}:
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return {"decision": status, "item": row}
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if (time.time() - started) >= timeout_seconds:
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return {"decision": "rejected", "reason": "审批超时"}
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await asyncio.sleep(0.2)
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async def execute_tool_calls(*, web_terminal, tool_calls, sender, messages, client_sid: str, username: str, iteration: int, conversation_id: Optional[str], last_tool_call_time: float, process_sub_agent_updates, process_background_command_updates, maybe_mark_failure_from_message, mark_force_thinking, get_stop_flag, clear_stop_flag, workspace=None):
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previous_tool_loop_active = getattr(web_terminal, "_tool_loop_active", False)
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web_terminal._tool_loop_active = True
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allowed_tool_names = set()
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try:
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defined_tools = web_terminal.define_tools() or []
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for tool in defined_tools:
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name = ((tool or {}).get("function") or {}).get("name")
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if isinstance(name, str) and name:
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allowed_tool_names.add(name)
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except Exception as exc:
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debug_log(f"构建工具白名单失败（降级继续）: {exc}")
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recent_tool_actions = list(getattr(web_terminal, "_recent_tool_actions", []) or [])
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# 执行每个工具
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pending_runtime_mode_notices: List[str] = []
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last_completed_tool_call_id: Optional[str] = None
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for tool_call in tool_calls:
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# 检查停止标志
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client_stop_info = get_stop_flag(client_sid, username)
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if client_stop_info:
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stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
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if stop_requested:
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debug_log("在工具调用过程中检测到停止状态")
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tool_call_id = tool_call.get("id")
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function_name = tool_call.get("function", {}).get("name")
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# 通知前端该工具已被取消，避免界面卡住
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sender('update_action', {
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'preparing_id': tool_call_id,
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'status': 'cancelled',
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'result': {
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"success": False,
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"status": "cancelled",
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"message": "命令执行被用户取消",
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"tool": function_name
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}
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})
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# 在消息列表中记录取消结果，防止重新加载时仍显示运行中
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if tool_call_id:
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call_id,
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"name": function_name,
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"content": "命令执行被用户取消",
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"metadata": {"status": "cancelled"}
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})
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sender('task_stopped', {
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'message': '命令执行被用户取消',
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'reason': 'user_stop'
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})
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clear_stop_flag(client_sid, username)
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web_terminal._tool_loop_active = previous_tool_loop_active
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return {"stopped": True, "last_tool_call_time": last_tool_call_time}
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# 工具调用间隔控制
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current_time = time.time()
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if last_tool_call_time > 0:
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elapsed = current_time - last_tool_call_time
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if elapsed < TOOL_CALL_COOLDOWN:
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await asyncio.sleep(TOOL_CALL_COOLDOWN - elapsed)
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last_tool_call_time = time.time()
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function_name = tool_call["function"]["name"]
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arguments_str = tool_call["function"]["arguments"]
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tool_call_id = tool_call["id"]
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debug_log(f"准备解析JSON，工具: {function_name}, 参数长度: {len(arguments_str)}")
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debug_log(f"JSON参数前200字符: {arguments_str[:200]}")
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debug_log(f"JSON参数后200字符: {arguments_str[-200:]}")
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# 使用改进的参数解析方法
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if hasattr(web_terminal, 'api_client') and hasattr(web_terminal.api_client, '_safe_tool_arguments_parse'):
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success, arguments, error_msg = web_terminal.api_client._safe_tool_arguments_parse(arguments_str, function_name)
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if not success:
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debug_log(f"安全解析失败: {error_msg}")
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error_text = f'工具参数解析失败: {error_msg}'
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error_payload = {
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"success": False,
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"error": error_text,
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"error_type": "parameter_format_error",
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"tool_name": function_name,
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"tool_call_id": tool_call_id,
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"message": error_text
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}
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sender('error', {'message': error_text})
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sender('update_action', {
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'preparing_id': tool_call_id,
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'status': 'completed',
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'result': error_payload,
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'message': error_text
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})
|
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error_content = json.dumps(error_payload, ensure_ascii=False)
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web_terminal.context_manager.add_conversation(
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"tool",
|
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error_content,
|
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tool_call_id=tool_call_id,
|
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name=function_name
|
||
)
|
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messages.append({
|
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"role": "tool",
|
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"tool_call_id": tool_call_id,
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"name": function_name,
|
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"content": error_content
|
||
})
|
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continue
|
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debug_log(f"使用安全解析成功，参数键: {list(arguments.keys())}")
|
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else:
|
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# 回退到带有基本修复逻辑的解析
|
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try:
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arguments = json.loads(arguments_str) if arguments_str.strip() else {}
|
||
debug_log(f"直接JSON解析成功，参数键: {list(arguments.keys())}")
|
||
except json.JSONDecodeError as e:
|
||
debug_log(f"原始JSON解析失败: {e}")
|
||
# 尝试基本的JSON修复
|
||
repaired_str = arguments_str.strip()
|
||
repair_attempts = []
|
||
|
||
# 修复1: 未闭合字符串
|
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if repaired_str.count('"') % 2 == 1:
|
||
repaired_str += '"'
|
||
repair_attempts.append("添加闭合引号")
|
||
|
||
# 修复2: 未闭合JSON对象
|
||
if repaired_str.startswith('{') and not repaired_str.rstrip().endswith('}'):
|
||
repaired_str = repaired_str.rstrip() + '}'
|
||
repair_attempts.append("添加闭合括号")
|
||
|
||
# 修复3: 截断的JSON（移除不完整的最后一个键值对）
|
||
if not repair_attempts: # 如果前面的修复都没用上
|
||
last_comma = repaired_str.rfind(',')
|
||
if last_comma > 0:
|
||
repaired_str = repaired_str[:last_comma] + '}'
|
||
repair_attempts.append("移除不完整的键值对")
|
||
|
||
# 尝试解析修复后的JSON
|
||
try:
|
||
arguments = json.loads(repaired_str)
|
||
debug_log(f"JSON修复成功: {', '.join(repair_attempts)}")
|
||
debug_log(f"修复后参数键: {list(arguments.keys())}")
|
||
except json.JSONDecodeError as repair_error:
|
||
debug_log(f"JSON修复也失败: {repair_error}")
|
||
debug_log(f"修复尝试: {repair_attempts}")
|
||
debug_log(f"修复后内容前100字符: {repaired_str[:100]}")
|
||
error_text = f'工具参数解析失败: {e}'
|
||
error_payload = {
|
||
"success": False,
|
||
"error": error_text,
|
||
"error_type": "parameter_format_error",
|
||
"tool_name": function_name,
|
||
"tool_call_id": tool_call_id,
|
||
"message": error_text
|
||
}
|
||
sender('error', {'message': error_text})
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'completed',
|
||
'result': error_payload,
|
||
'message': error_text
|
||
})
|
||
error_content = json.dumps(error_payload, ensure_ascii=False)
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
error_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name
|
||
)
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": error_content
|
||
})
|
||
continue
|
||
|
||
# 严格校验：只允许执行当前回合明确下发给模型的工具。
|
||
# 某些模型会“幻觉”调用未下发工具（如 view_image），必须在执行层拦截。
|
||
if allowed_tool_names and function_name not in allowed_tool_names:
|
||
if function_name == "view_image" and "vlm_analyze" in allowed_tool_names:
|
||
if not arguments.get("prompt"):
|
||
arguments["prompt"] = "请详细分析这张图片的内容，包括关键文字、主体对象与场景信息。"
|
||
debug_log(
|
||
"工具名自动纠正: view_image -> vlm_analyze (模型未获授权 view_image)"
|
||
)
|
||
function_name = "vlm_analyze"
|
||
else:
|
||
denied_message = (
|
||
f"工具 {function_name} 不在当前模型可用工具列表中，已拒绝执行。"
|
||
)
|
||
denied_payload = {
|
||
"success": False,
|
||
"status": "denied",
|
||
"code": "tool_not_allowed",
|
||
"tool": function_name,
|
||
"message": denied_message,
|
||
}
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'completed',
|
||
'result': denied_payload,
|
||
'message': denied_message,
|
||
'conversation_id': conversation_id
|
||
})
|
||
denied_content = json.dumps(denied_payload, ensure_ascii=False)
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
denied_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name
|
||
)
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": denied_content
|
||
})
|
||
continue
|
||
|
||
debug_log(f"执行工具: {function_name} (ID: {tool_call_id})")
|
||
previous_tool_actions = list(recent_tool_actions)
|
||
recent_tool_actions.append({
|
||
"tool_name": function_name,
|
||
"arguments": arguments,
|
||
})
|
||
recent_tool_actions = recent_tool_actions[-3:]
|
||
setattr(web_terminal, "_recent_tool_actions", list(recent_tool_actions))
|
||
|
||
permission_eval = web_terminal.evaluate_tool_permission(function_name, arguments)
|
||
if not permission_eval.get("allowed", True):
|
||
denied_message = permission_eval.get("message") or "当前权限模式不允许执行该工具。"
|
||
denied_payload = {
|
||
"success": False,
|
||
"status": "denied",
|
||
"code": permission_eval.get("code") or "permission_denied",
|
||
"tool": function_name,
|
||
"mode": permission_eval.get("mode"),
|
||
"message": denied_message,
|
||
}
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'completed',
|
||
'result': denied_payload,
|
||
'message': denied_message,
|
||
'conversation_id': conversation_id
|
||
})
|
||
denied_content = json.dumps(denied_payload, ensure_ascii=False)
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
denied_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name
|
||
)
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": denied_content
|
||
})
|
||
continue
|
||
|
||
if permission_eval.get("requires_approval"):
|
||
approval_preview = _build_tool_approval_preview(web_terminal, function_name, arguments)
|
||
approval_item = tool_approval_manager.create_request(
|
||
username=username,
|
||
conversation_id=conversation_id,
|
||
task_id=getattr(web_terminal, "task_id", None),
|
||
tool_call_id=tool_call_id,
|
||
tool_name=function_name,
|
||
arguments=arguments,
|
||
preview=approval_preview,
|
||
)
|
||
sender('tool_approval_required', {
|
||
'approval': approval_item,
|
||
'conversation_id': conversation_id,
|
||
})
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'awaiting_approval',
|
||
'result': {
|
||
"success": False,
|
||
"status": "awaiting_approval",
|
||
"approval_id": approval_item.get("approval_id"),
|
||
"message": "等待用户审批"
|
||
},
|
||
'message': '等待用户审批',
|
||
'conversation_id': conversation_id
|
||
})
|
||
wait_result = None
|
||
permission_mode = str(permission_eval.get("mode") or "")
|
||
if permission_mode == "auto_approval":
|
||
approval_id = approval_item.get("approval_id")
|
||
wait_result = await run_auto_approval(
|
||
web_terminal=web_terminal,
|
||
username=username,
|
||
approval_id=approval_id,
|
||
conversation_id=conversation_id,
|
||
recent_tool_actions=previous_tool_actions,
|
||
function_name=function_name,
|
||
arguments=arguments,
|
||
risk_markers=permission_eval.get("risk_markers") if isinstance(permission_eval, dict) else None,
|
||
sender=sender,
|
||
)
|
||
else:
|
||
wait_result = await _wait_for_tool_approval(
|
||
approval_id=approval_item.get("approval_id"),
|
||
username=username,
|
||
)
|
||
sender('tool_approval_resolved', {
|
||
'approval_id': approval_item.get("approval_id"),
|
||
'decision': wait_result.get("decision"),
|
||
'reason': ((wait_result.get("item") or {}).get("reason") or wait_result.get("reason")),
|
||
'conversation_id': conversation_id,
|
||
})
|
||
if wait_result.get("decision") != "approved":
|
||
reject_message = "操作被用户拒绝"
|
||
if wait_result.get("reason") == "审批超时":
|
||
reject_message = "审批超时，操作未执行"
|
||
reason = ((wait_result.get("item") or {}).get("reason") or wait_result.get("reason") or "").strip()
|
||
if reason:
|
||
reject_message = f"{reject_message}：{reason}"
|
||
reject_payload = {
|
||
"success": False,
|
||
"status": "rejected",
|
||
"code": "approval_rejected",
|
||
"tool": function_name,
|
||
"message": reject_message,
|
||
"approval_id": approval_item.get("approval_id"),
|
||
}
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'completed',
|
||
'result': reject_payload,
|
||
'message': reject_message,
|
||
'conversation_id': conversation_id
|
||
})
|
||
reject_content = _format_rejected_tool_text(reason or reject_message)
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
reject_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name
|
||
)
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": reject_content
|
||
})
|
||
if permission_mode != "auto_approval":
|
||
web_terminal._tool_loop_active = previous_tool_loop_active
|
||
return {
|
||
"stopped": False,
|
||
"approval_rejected": True,
|
||
"approval_message": reject_message,
|
||
"last_tool_call_time": last_tool_call_time
|
||
}
|
||
continue
|
||
|
||
# 发送工具开始事件
|
||
tool_display_id = f"tool_{iteration}_{function_name}_{time.time()}"
|
||
monitor_snapshot = None
|
||
snapshot_path = None
|
||
memory_snapshot_type = None
|
||
if function_name in MONITOR_FILE_TOOLS:
|
||
snapshot_path = resolve_monitor_path(arguments)
|
||
monitor_snapshot = capture_monitor_snapshot(web_terminal.file_manager, snapshot_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
|
||
if monitor_snapshot:
|
||
cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
|
||
elif function_name in MONITOR_MEMORY_TOOLS:
|
||
memory_snapshot_type = (arguments.get('memory_type') or 'main').lower()
|
||
before_entries = None
|
||
try:
|
||
before_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_snapshot_type), MONITOR_MEMORY_ENTRY_LIMIT)
|
||
except Exception as exc:
|
||
debug_log(f"[MonitorSnapshot] 读取记忆失败: {memory_snapshot_type} ({exc})")
|
||
if before_entries is not None:
|
||
monitor_snapshot = {
|
||
'memory_type': memory_snapshot_type,
|
||
'entries': before_entries
|
||
}
|
||
cache_monitor_snapshot(tool_display_id, 'before', monitor_snapshot)
|
||
|
||
sender('tool_start', {
|
||
'id': tool_display_id,
|
||
'name': function_name,
|
||
'arguments': arguments,
|
||
'preparing_id': tool_call_id,
|
||
'monitor_snapshot': monitor_snapshot,
|
||
'conversation_id': conversation_id
|
||
})
|
||
brief_log(f"调用了工具: {function_name}")
|
||
|
||
await asyncio.sleep(0.3)
|
||
start_time = time.time()
|
||
|
||
# 执行工具，同时监听停止标志
|
||
debug_log(f"[停止检测] 开始执行工具: {function_name}")
|
||
tool_task = asyncio.create_task(web_terminal.handle_tool_call(function_name, arguments))
|
||
tool_result = None
|
||
tool_cancelled = False
|
||
|
||
# 在工具执行期间持续检查停止标志
|
||
check_count = 0
|
||
while not tool_task.done():
|
||
await asyncio.sleep(0.1) # 每100ms检查一次
|
||
check_count += 1
|
||
client_stop_info = get_stop_flag(client_sid, username)
|
||
if client_stop_info:
|
||
stop_requested = client_stop_info.get('stop', False) if isinstance(client_stop_info, dict) else client_stop_info
|
||
if stop_requested:
|
||
debug_log(f"[停止检测] 工具执行过程中检测到停止请求(检查次数:{check_count})，立即取消工具")
|
||
tool_task.cancel()
|
||
tool_cancelled = True
|
||
break
|
||
|
||
debug_log(f"[停止检测] 工具执行完成，cancelled={tool_cancelled}, 检查次数={check_count}")
|
||
|
||
# 获取工具结果或处理取消
|
||
if tool_cancelled:
|
||
try:
|
||
await tool_task
|
||
except asyncio.CancelledError:
|
||
debug_log("[停止检测] 工具任务已被取消(CancelledError)")
|
||
except Exception as e:
|
||
debug_log(f"[停止检测] 工具任务取消时发生异常: {e}")
|
||
|
||
# 返回取消消息
|
||
tool_result = json.dumps({
|
||
"success": False,
|
||
"status": "cancelled",
|
||
"message": "命令执行被用户取消"
|
||
}, ensure_ascii=False)
|
||
|
||
debug_log("[停止检测] 发送取消通知到前端")
|
||
# 通知前端工具被取消
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'cancelled',
|
||
'result': {
|
||
"success": False,
|
||
"status": "cancelled",
|
||
"message": "命令执行被用户取消",
|
||
"tool": function_name
|
||
}
|
||
})
|
||
|
||
# 记录取消结果到消息历史
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": "命令执行被用户取消",
|
||
"metadata": {"status": "cancelled"}
|
||
})
|
||
|
||
# 保存取消结果
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
"命令执行被用户取消",
|
||
tool_call_id=tool_call_id,
|
||
name=function_name,
|
||
metadata={"status": "cancelled"}
|
||
)
|
||
debug_log("[停止检测] 取消结果已保存到对话历史")
|
||
|
||
# 发送停止事件并清除标志
|
||
sender('task_stopped', {
|
||
'message': '命令执行被用户取消',
|
||
'reason': 'user_stop'
|
||
})
|
||
clear_stop_flag(client_sid, username)
|
||
debug_log("[停止检测] 返回stopped=True")
|
||
web_terminal._tool_loop_active = previous_tool_loop_active
|
||
return {"stopped": True, "last_tool_call_time": last_tool_call_time}
|
||
else:
|
||
tool_result = await tool_task
|
||
debug_log(f"工具结果: {tool_result[:200]}...")
|
||
|
||
execution_time = time.time() - start_time
|
||
if execution_time < 1.5:
|
||
await asyncio.sleep(1.5 - execution_time)
|
||
|
||
# 更新工具状态
|
||
result_data = {}
|
||
try:
|
||
result_data = json.loads(tool_result)
|
||
except:
|
||
result_data = {'output': tool_result}
|
||
|
||
# 批准模式下 run_command 采用“先只读执行，触发权限拒绝后再审批并单次可写重试”。
|
||
if (
|
||
function_name == "run_command"
|
||
and permission_eval.get("mode") in {"approval", "auto_approval"}
|
||
and not bool(arguments.get("_approval_write_granted", False))
|
||
and _is_permission_denied_result(result_data)
|
||
):
|
||
approval_preview = _build_tool_approval_preview(web_terminal, function_name, arguments)
|
||
approval_item = tool_approval_manager.create_request(
|
||
username=username,
|
||
conversation_id=conversation_id,
|
||
task_id=getattr(web_terminal, "task_id", None),
|
||
tool_call_id=tool_call_id,
|
||
tool_name=function_name,
|
||
arguments=arguments,
|
||
preview=approval_preview,
|
||
)
|
||
sender('tool_approval_required', {
|
||
'approval': approval_item,
|
||
'conversation_id': conversation_id,
|
||
})
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'awaiting_approval',
|
||
'result': {
|
||
"success": False,
|
||
"status": "awaiting_approval",
|
||
"approval_id": approval_item.get("approval_id"),
|
||
"message": "检测到写权限受限，等待用户审批后重试"
|
||
},
|
||
'message': '检测到写权限受限，等待用户审批',
|
||
'conversation_id': conversation_id
|
||
})
|
||
wait_result = None
|
||
permission_mode = str(permission_eval.get("mode") or "")
|
||
if permission_mode == "auto_approval":
|
||
approval_id = approval_item.get("approval_id")
|
||
wait_result = await run_auto_approval(
|
||
web_terminal=web_terminal,
|
||
username=username,
|
||
approval_id=approval_id,
|
||
conversation_id=conversation_id,
|
||
recent_tool_actions=previous_tool_actions,
|
||
function_name=function_name,
|
||
arguments=arguments,
|
||
risk_markers=permission_eval.get("risk_markers") if isinstance(permission_eval, dict) else None,
|
||
sender=sender,
|
||
)
|
||
else:
|
||
wait_result = await _wait_for_tool_approval(
|
||
approval_id=approval_item.get("approval_id"),
|
||
username=username,
|
||
)
|
||
sender('tool_approval_resolved', {
|
||
'approval_id': approval_item.get("approval_id"),
|
||
'decision': wait_result.get("decision"),
|
||
'reason': ((wait_result.get("item") or {}).get("reason") or wait_result.get("reason")),
|
||
'conversation_id': conversation_id,
|
||
})
|
||
if wait_result.get("decision") != "approved":
|
||
reject_message = "操作被用户拒绝"
|
||
if wait_result.get("reason") == "审批超时":
|
||
reject_message = "审批超时，操作未执行"
|
||
reason = ((wait_result.get("item") or {}).get("reason") or wait_result.get("reason") or "").strip()
|
||
if reason:
|
||
reject_message = f"{reject_message}：{reason}"
|
||
reject_payload = {
|
||
"success": False,
|
||
"status": "rejected",
|
||
"code": "approval_rejected",
|
||
"tool": function_name,
|
||
"message": reject_message,
|
||
"approval_id": approval_item.get("approval_id"),
|
||
}
|
||
sender('update_action', {
|
||
'preparing_id': tool_call_id,
|
||
'status': 'completed',
|
||
'result': reject_payload,
|
||
'message': reject_message,
|
||
'conversation_id': conversation_id
|
||
})
|
||
reject_content = _format_rejected_tool_text(reason or reject_message)
|
||
web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
reject_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name
|
||
)
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": reject_content
|
||
})
|
||
if permission_mode == "approval":
|
||
web_terminal._tool_loop_active = previous_tool_loop_active
|
||
return {
|
||
"stopped": False,
|
||
"approval_rejected": True,
|
||
"approval_message": reject_message,
|
||
"last_tool_call_time": last_tool_call_time
|
||
}
|
||
continue
|
||
|
||
retry_arguments = dict(arguments or {})
|
||
retry_arguments["_approval_write_granted"] = True
|
||
retry_tool_result = await web_terminal.handle_tool_call(function_name, retry_arguments)
|
||
try:
|
||
result_data = json.loads(retry_tool_result)
|
||
tool_result = retry_tool_result
|
||
except Exception:
|
||
result_data = {"output": retry_tool_result}
|
||
tool_result = retry_tool_result
|
||
|
||
tool_failed = detect_tool_failure(result_data)
|
||
|
||
action_status = 'completed'
|
||
action_message = None
|
||
awaiting_flag = False
|
||
|
||
if function_name in {"write_file", "edit_file"}:
|
||
diff_path = result_data.get("path") or arguments.get("file_path")
|
||
summary = result_data.get("summary") or result_data.get("message")
|
||
if summary:
|
||
action_message = summary
|
||
debug_log(f"{function_name} 执行完成: {summary or '无摘要'}")
|
||
|
||
if function_name == "wait_sub_agent":
|
||
system_msg = result_data.get("system_message")
|
||
if system_msg:
|
||
messages.append({
|
||
"role": "system",
|
||
"content": system_msg
|
||
})
|
||
sender('system_message', {
|
||
'content': system_msg,
|
||
'inline': False
|
||
})
|
||
maybe_mark_failure_from_message(web_terminal, system_msg)
|
||
if function_name == "sleep":
|
||
try:
|
||
if isinstance(result_data, dict) and result_data.get("mode") == "wait_sub_agent_ids":
|
||
waited_task_ids = result_data.get("waited_task_ids") or []
|
||
if not hasattr(web_terminal, "_announced_sub_agent_tasks"):
|
||
web_terminal._announced_sub_agent_tasks = set()
|
||
for tid in waited_task_ids:
|
||
if tid:
|
||
web_terminal._announced_sub_agent_tasks.add(str(tid))
|
||
except Exception:
|
||
pass
|
||
monitor_snapshot_after = None
|
||
if function_name in MONITOR_FILE_TOOLS:
|
||
result_path = None
|
||
if isinstance(result_data, dict):
|
||
result_path = resolve_monitor_path(result_data)
|
||
if not result_path:
|
||
candidate_path = result_data.get('path')
|
||
if isinstance(candidate_path, str) and candidate_path.strip():
|
||
result_path = candidate_path.strip()
|
||
if not result_path:
|
||
result_path = resolve_monitor_path(arguments, snapshot_path) or snapshot_path
|
||
monitor_snapshot_after = capture_monitor_snapshot(web_terminal.file_manager, result_path, MONITOR_SNAPSHOT_CHAR_LIMIT, debug_log)
|
||
elif function_name in MONITOR_MEMORY_TOOLS:
|
||
memory_after_type = str(
|
||
arguments.get('memory_type')
|
||
or (isinstance(result_data, dict) and result_data.get('memory_type'))
|
||
or memory_snapshot_type
|
||
or 'main'
|
||
).lower()
|
||
after_entries = None
|
||
try:
|
||
after_entries = resolve_monitor_memory(web_terminal.memory_manager._read_entries(memory_after_type), MONITOR_MEMORY_ENTRY_LIMIT)
|
||
except Exception as exc:
|
||
debug_log(f"[MonitorSnapshot] 读取记忆失败(after): {memory_after_type} ({exc})")
|
||
if after_entries is not None:
|
||
monitor_snapshot_after = {
|
||
'memory_type': memory_after_type,
|
||
'entries': after_entries
|
||
}
|
||
|
||
mcp_parsed = None
|
||
update_result_data = result_data
|
||
if isinstance(function_name, str) and function_name.startswith("mcp__") and isinstance(result_data, dict):
|
||
try:
|
||
mcp_parsed = extract_mcp_content_for_context(result_data)
|
||
update_result_data = mcp_parsed.get("sanitized_payload") or result_data
|
||
except Exception:
|
||
mcp_parsed = None
|
||
update_result_data = result_data
|
||
|
||
update_payload = {
|
||
'id': tool_display_id,
|
||
'status': action_status,
|
||
'result': update_result_data,
|
||
'preparing_id': tool_call_id,
|
||
'conversation_id': conversation_id
|
||
}
|
||
if action_message:
|
||
update_payload['message'] = action_message
|
||
if awaiting_flag:
|
||
update_payload['awaiting_content'] = True
|
||
if monitor_snapshot_after:
|
||
update_payload['monitor_snapshot_after'] = monitor_snapshot_after
|
||
cache_monitor_snapshot(tool_display_id, 'after', monitor_snapshot_after)
|
||
|
||
sender('update_action', update_payload)
|
||
|
||
if function_name in ['create_file', 'delete_file', 'rename_file', 'create_folder']:
|
||
if not web_terminal.context_manager._is_host_mode_without_safety():
|
||
structure = web_terminal.context_manager.get_project_structure()
|
||
sender('file_tree_update', structure)
|
||
|
||
# ===== 增量保存：立即保存工具结果 =====
|
||
metadata_payload = None
|
||
tool_images = None
|
||
tool_videos = None
|
||
tool_media_refs = None
|
||
if isinstance(result_data, dict):
|
||
if isinstance(function_name, str) and function_name.startswith("mcp__"):
|
||
if not isinstance(mcp_parsed, dict):
|
||
mcp_parsed = extract_mcp_content_for_context(result_data)
|
||
tool_result_content = (
|
||
mcp_parsed.get("text")
|
||
or format_tool_result_for_context(function_name, result_data, tool_result)
|
||
)
|
||
mcp_media_items = mcp_parsed.get("media_items") or []
|
||
if mcp_media_items:
|
||
tool_media_refs = []
|
||
for item in mcp_media_items:
|
||
if not isinstance(item, dict):
|
||
continue
|
||
tool_media_refs.append(
|
||
{
|
||
"kind": item.get("kind"),
|
||
"mime_type": item.get("mime_type"),
|
||
"data_base64": item.get("data_base64"),
|
||
"source": "mcp_content",
|
||
"item_type": item.get("item_type"),
|
||
"label": item.get("label"),
|
||
"name": item.get("name"),
|
||
"title": item.get("title"),
|
||
"uri": item.get("uri"),
|
||
"url": item.get("url"),
|
||
"index": item.get("index"),
|
||
}
|
||
)
|
||
metadata_payload = {
|
||
"tool_payload": mcp_parsed.get("sanitized_payload") or result_data
|
||
}
|
||
else:
|
||
# 特殊处理 web_search：保留可供前端渲染的精简结构，以便历史记录复现搜索结果
|
||
if function_name == "web_search":
|
||
try:
|
||
tool_result_content = json.dumps(compact_web_search_result(result_data), ensure_ascii=False)
|
||
except Exception:
|
||
tool_result_content = tool_result
|
||
else:
|
||
tool_result_content = format_tool_result_for_context(function_name, result_data, tool_result)
|
||
metadata_payload = {"tool_payload": result_data}
|
||
else:
|
||
tool_result_content = tool_result
|
||
tool_message_content = tool_result_content
|
||
|
||
# view_image: 将图片直接附加到 tool 结果中（不再插入 user 消息）
|
||
if function_name == "view_image" and getattr(web_terminal, "pending_image_view", None):
|
||
inj = web_terminal.pending_image_view
|
||
web_terminal.pending_image_view = None
|
||
if (
|
||
not tool_failed
|
||
and isinstance(result_data, dict)
|
||
and result_data.get("success") is not False
|
||
):
|
||
img_path = inj.get("path") if isinstance(inj, dict) else None
|
||
if img_path:
|
||
tool_images = [img_path]
|
||
if metadata_payload is None:
|
||
metadata_payload = {}
|
||
metadata_payload["tool_image_path"] = img_path
|
||
sender('system_message', {
|
||
'content': f'系统已记录图片路径（不再附带二进制数据）: {img_path}'
|
||
})
|
||
|
||
# view_video: 将视频直接附加到 tool 结果中（不再插入 user 消息）
|
||
if function_name == "view_video" and getattr(web_terminal, "pending_video_view", None):
|
||
inj = web_terminal.pending_video_view
|
||
web_terminal.pending_video_view = None
|
||
if (
|
||
not tool_failed
|
||
and isinstance(result_data, dict)
|
||
and result_data.get("success") is not False
|
||
):
|
||
video_path = inj.get("path") if isinstance(inj, dict) else None
|
||
if video_path:
|
||
tool_videos = [video_path]
|
||
if metadata_payload is None:
|
||
metadata_payload = {}
|
||
metadata_payload["tool_video_path"] = video_path
|
||
sender('system_message', {
|
||
'content': f'系统已记录视频路径（不再附带二进制数据）: {video_path}'
|
||
})
|
||
|
||
# 立即保存工具结果
|
||
saved_tool_message = web_terminal.context_manager.add_conversation(
|
||
"tool",
|
||
tool_result_content,
|
||
tool_call_id=tool_call_id,
|
||
name=function_name,
|
||
metadata=metadata_payload,
|
||
images=tool_images,
|
||
videos=tool_videos,
|
||
media_refs=tool_media_refs,
|
||
)
|
||
saved_media_refs = []
|
||
if isinstance(saved_tool_message, dict):
|
||
saved_media_refs = saved_tool_message.get("media_refs") or []
|
||
|
||
# 将工具结果即时组装为多模态消息，确保同一轮 tool loop 的下一次模型请求能真正看到媒体
|
||
if tool_images or tool_videos or saved_media_refs:
|
||
try:
|
||
tool_message_content = web_terminal.context_manager._build_content_with_images(
|
||
str(tool_result_content or ""),
|
||
tool_images or [],
|
||
tool_videos or [],
|
||
media_refs=saved_media_refs,
|
||
)
|
||
except Exception:
|
||
tool_message_content = tool_result_content
|
||
try:
|
||
workspace_data_dir = getattr(workspace, "data_dir", None) if workspace else None
|
||
personal_config = load_personalization_config(workspace_data_dir) if workspace_data_dir else {}
|
||
except Exception:
|
||
personal_config = {}
|
||
compression_settings = resolve_context_compression_settings(personal_config)
|
||
auto_shallow_enabled = bool(personal_config.get("auto_shallow_compress_enabled", False))
|
||
auto_deep_enabled = bool(personal_config.get("auto_deep_compress_enabled", False))
|
||
compressed_count = 0
|
||
try:
|
||
compressed_count = int(
|
||
web_terminal.context_manager.on_tool_call_finished(
|
||
function_name,
|
||
enable_shallow=auto_shallow_enabled,
|
||
shallow_trigger_tokens=compression_settings["shallow_trigger_tokens"],
|
||
deep_trigger_tokens=compression_settings["deep_trigger_tokens"],
|
||
shallow_batch_size=compression_settings["shallow_max_replace_per_round"],
|
||
shallow_keep_recent_tools=compression_settings["shallow_keep_recent_tools"],
|
||
shallow_trigger_tool_calls_interval=compression_settings["shallow_trigger_tool_calls_interval"],
|
||
shallow_keep_user_turn_tools=compression_settings.get("shallow_keep_user_turn_tools", 3),
|
||
) or 0
|
||
)
|
||
except Exception as exc:
|
||
debug_log(f"[ContextCompression] 工具后浅压缩检测失败: {exc}")
|
||
if compressed_count > 0:
|
||
sender('shallow_compression', {
|
||
"conversation_id": conversation_id,
|
||
"compressed_count": compressed_count,
|
||
"keep_recent_tools": compression_settings["shallow_keep_recent_tools"],
|
||
"keep_user_turn_tools": compression_settings.get("shallow_keep_user_turn_tools", 3),
|
||
})
|
||
# 关键修复：同一轮工具循环里，API 继续调用使用的是本地 messages（不是每次重建上下文），
|
||
# 因此需要把已打标的旧 tool 结果同步替换为占位符，避免日志看起来“弹窗触发但请求未替换”。
|
||
if auto_shallow_enabled and messages:
|
||
try:
|
||
marked_keys = set()
|
||
for item in (web_terminal.context_manager.conversation_history or []):
|
||
if not isinstance(item, dict) or item.get("role") != "tool":
|
||
continue
|
||
item_meta = item.get("metadata") or {}
|
||
if not item_meta.get("auto_shallow_compacted"):
|
||
continue
|
||
marked_keys.add((str(item.get("tool_call_id") or ""), str(item.get("name") or "")))
|
||
|
||
if marked_keys:
|
||
replaced_in_loop = 0
|
||
for msg in messages:
|
||
if not isinstance(msg, dict) or msg.get("role") != "tool":
|
||
continue
|
||
key = (str(msg.get("tool_call_id") or ""), str(msg.get("name") or ""))
|
||
if key in marked_keys and msg.get("content") != AUTO_SHALLOW_PLACEHOLDER:
|
||
msg["content"] = AUTO_SHALLOW_PLACEHOLDER
|
||
replaced_in_loop += 1
|
||
if replaced_in_loop > 0:
|
||
debug_log(f"[ContextCompression] 同步替换本轮 messages 中已压缩 tool 结果: {replaced_in_loop}")
|
||
except Exception as exc:
|
||
debug_log(f"[ContextCompression] 同步替换本轮 messages 失败: {exc}")
|
||
debug_log(f"💾 增量保存：工具结果 {function_name}")
|
||
if function_name != "wait_sub_agent":
|
||
system_message = result_data.get("system_message") if isinstance(result_data, dict) else None
|
||
if system_message:
|
||
web_terminal._record_sub_agent_message(system_message, result_data.get("task_id"), inline=False)
|
||
maybe_mark_failure_from_message(web_terminal, system_message)
|
||
|
||
# 自动深层压缩（工具调用后触发）
|
||
current_context_tokens = web_terminal.context_manager.get_current_context_tokens(conversation_id)
|
||
if (
|
||
auto_deep_enabled
|
||
and current_context_tokens > compression_settings["deep_trigger_tokens"]
|
||
and not web_terminal.context_manager.is_compression_in_progress()
|
||
):
|
||
web_terminal.context_manager._set_meta_flag("is_ultra_long_conversation", True)
|
||
sender('compression_state', {
|
||
"conversation_id": conversation_id,
|
||
"in_progress": True,
|
||
"mode": "auto",
|
||
"stage": "queued"
|
||
})
|
||
deep_result = await run_deep_compression(
|
||
web_terminal=web_terminal,
|
||
workspace=workspace,
|
||
conversation_id=conversation_id,
|
||
mode="auto",
|
||
sender=sender,
|
||
)
|
||
if not deep_result.get("success"):
|
||
sender('error', {
|
||
"message": deep_result.get("error") or "自动深层压缩失败",
|
||
"conversation_id": conversation_id,
|
||
})
|
||
web_terminal._tool_loop_active = previous_tool_loop_active
|
||
return {
|
||
"stopped": False,
|
||
"deep_compressed": True,
|
||
"deep_result": deep_result,
|
||
"last_tool_call_time": last_tool_call_time
|
||
}
|
||
|
||
# 添加到消息历史（用于API继续对话）
|
||
messages.append({
|
||
"role": "tool",
|
||
"tool_call_id": tool_call_id,
|
||
"name": function_name,
|
||
"content": tool_message_content
|
||
})
|
||
last_completed_tool_call_id = tool_call_id
|
||
|
||
if not pending_runtime_mode_notices:
|
||
try:
|
||
if hasattr(web_terminal, "apply_pending_runtime_mode_changes"):
|
||
pending_runtime_mode_notices = list(web_terminal.apply_pending_runtime_mode_changes() or [])
|
||
except Exception as exc:
|
||
debug_log(f"[RuntimeMode] 应用挂起模式变更失败: {exc}")
|
||
|
||
await asyncio.sleep(0.2)
|
||
|
||
if tool_failed:
|
||
mark_force_thinking(web_terminal, reason=f"{function_name}_failed")
|
||
|
||
# 子智能体/后台指令完成通知：必须等待同一轮全部 tool_call 都完成后再注入，
|
||
# 避免在 assistant.tool_calls 与未完成的 tool 结果之间插入 system 消息导致 API 报错。
|
||
if last_completed_tool_call_id:
|
||
debug_log(
|
||
f"[SubAgent] after all tools finished -> poll updates inline after_tool_call_id={last_completed_tool_call_id}"
|
||
)
|
||
await process_sub_agent_updates(
|
||
messages=messages,
|
||
inline=True,
|
||
after_tool_call_id=last_completed_tool_call_id,
|
||
web_terminal=web_terminal,
|
||
sender=sender,
|
||
debug_log=debug_log,
|
||
maybe_mark_failure_from_message=maybe_mark_failure_from_message,
|
||
)
|
||
debug_log(
|
||
"[BgCmdDebug] after all tools finished -> poll background command updates "
|
||
f"inline after_tool_call_id={last_completed_tool_call_id}"
|
||
)
|
||
await process_background_command_updates(
|
||
messages=messages,
|
||
inline=True,
|
||
after_tool_call_id=last_completed_tool_call_id,
|
||
web_terminal=web_terminal,
|
||
sender=sender,
|
||
debug_log=debug_log,
|
||
maybe_mark_failure_from_message=maybe_mark_failure_from_message,
|
||
)
|
||
|
||
# 运行期模式通知：必须等待同一轮全部 tool_call 都完成后再注入，
|
||
# 避免在 assistant.tool_calls 与对应 tool 消息之间插入 system 消息导致 API 报错。
|
||
if pending_runtime_mode_notices:
|
||
for notice in pending_runtime_mode_notices:
|
||
_inject_runtime_mode_notice(
|
||
web_terminal=web_terminal,
|
||
messages=messages,
|
||
content=notice,
|
||
sender=sender,
|
||
conversation_id=conversation_id,
|
||
)
|
||
|
||
# 运行期“引导对话”：需要等待同一轮全部工具执行结束后再注入，
|
||
# 避免一轮内并行/多工具调用时过早插入。
|
||
try:
|
||
from .tasks import task_manager
|
||
|
||
runtime_guidance_items = task_manager.consume_runtime_guidance_for_injection(
|
||
username=username, task_id=client_sid
|
||
)
|
||
except Exception as exc:
|
||
runtime_guidance_items = []
|
||
debug_log(f"[RuntimeGuidance] 读取引导队列失败: {exc}")
|
||
|
||
if runtime_guidance_items:
|
||
injected_count = 0
|
||
for raw_item in runtime_guidance_items:
|
||
runtime_guidance_source = "guidance"
|
||
if isinstance(raw_item, dict):
|
||
runtime_guidance_text = str(raw_item.get("text") or "").strip()
|
||
runtime_guidance_source = (
|
||
str(raw_item.get("source") or "guidance").strip().lower()
|
||
or "guidance"
|
||
)
|
||
else:
|
||
runtime_guidance_text = str(raw_item or "").strip()
|
||
if runtime_guidance_source not in {"guidance", "notify", "user", "presend", "sub_agent", "background_command"}:
|
||
runtime_guidance_source = "guidance"
|
||
if not runtime_guidance_text:
|
||
continue
|
||
runtime_guidance_meta = {
|
||
"runtime_guidance": True,
|
||
"runtime_guidance_original": runtime_guidance_text,
|
||
"message_source": runtime_guidance_source,
|
||
}
|
||
try:
|
||
web_terminal.context_manager.add_conversation(
|
||
"user",
|
||
runtime_guidance_text,
|
||
metadata=runtime_guidance_meta,
|
||
)
|
||
except Exception as exc:
|
||
debug_log(f"[RuntimeGuidance] 持久化引导消息失败: {exc}")
|
||
messages.append(
|
||
{
|
||
"role": "user",
|
||
"content": runtime_guidance_text,
|
||
"metadata": runtime_guidance_meta,
|
||
}
|
||
)
|
||
sender(
|
||
"user_message",
|
||
{
|
||
"message": runtime_guidance_text,
|
||
"conversation_id": conversation_id,
|
||
"runtime_guidance": True,
|
||
"runtime_guidance_original": runtime_guidance_text,
|
||
"message_source": runtime_guidance_source,
|
||
},
|
||
)
|
||
injected_count += 1
|
||
if injected_count:
|
||
debug_log(
|
||
"[RuntimeGuidance] 已在工具结果批次结束后批量注入引导/通知 "
|
||
f"task_id={client_sid} count={injected_count}"
|
||
)
|
||
|
||
web_terminal._tool_loop_active = previous_tool_loop_active
|
||
return {"stopped": False, "last_tool_call_time": last_tool_call_time}
|