mirror of
https://github.com/DrizzleTime/Foxel.git
synced 2026-05-07 07:22:58 +08:00
a727e77341
* feat: Implement AI Agent with tool processing capabilities - Added tools for listing and running processors in the agent. - Created data models for agent chat requests and tool calls. - Developed API integration for agent chat and streaming responses. - Built the AI Agent widget with a user interface for interaction. - Styled the agent components for better user experience. * feat: 增强 AI 助手工具功能，添加文件操作和搜索功能，更新界面显示 * feat: 更新 AI 助手组件 * feat: 更新 AiAgentWidget 组件样式，调整背景和边距以提升界面一致性
449 lines
20 KiB
Python
449 lines
20 KiB
Python
import asyncio
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import json
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import uuid
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from typing import Any, Dict, List, Optional, Tuple
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import httpx
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from fastapi import HTTPException
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from domain.agent.tools import get_tool, openai_tools, tool_result_to_content
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from domain.agent.types import AgentChatRequest, PendingToolCall
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from domain.ai.inference import MissingModelError, chat_completion, chat_completion_stream
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from domain.ai.service import AIProviderService
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from domain.auth.types import User
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def _normalize_path(p: Optional[str]) -> Optional[str]:
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if not p:
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return None
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s = str(p).strip()
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if not s:
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return None
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s = s.replace("\\", "/")
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if not s.startswith("/"):
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s = "/" + s
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s = s.rstrip("/") or "/"
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return s
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def _build_system_prompt(current_path: Optional[str]) -> str:
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lines = [
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"你是 Foxel 的 AI 助手。",
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"你可以通过工具对文件/目录进行查询、读写、移动、复制、删除，以及运行处理器（processor）。",
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"",
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"可用工具：",
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"- vfs_list_dir：浏览目录（列出 entries + pagination）。",
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"- vfs_stat：查看文件/目录信息。",
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"- vfs_read_text：读取文本文件内容（不支持二进制）。",
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"- vfs_search：搜索文件（vector/filename）。",
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"- vfs_write_text：写入文本文件内容（覆盖）。",
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"- vfs_mkdir：创建目录。",
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"- vfs_delete：删除文件或目录。",
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"- vfs_move：移动路径。",
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"- vfs_copy：复制路径。",
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"- vfs_rename：重命名路径。",
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"- processors_list：获取可用处理器列表（含 type/name/config_schema/produces_file/supports_directory）。",
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"- processors_run：运行处理器处理文件或目录（会返回 task_id 或 task_ids）。",
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"",
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"规则：",
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"1) 读操作（vfs_list_dir/vfs_stat/vfs_read_text/vfs_search）可直接调用工具。",
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"2) 写/改/删操作（vfs_write_text/vfs_mkdir/vfs_delete/vfs_move/vfs_copy/vfs_rename/processors_run）默认需要用户确认；只有在开启自动执行时才应直接执行。",
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"3) 用户未给出明确路径时先追问；若提供了“当前文件管理目录”，可以基于它把相对描述补全为绝对路径（以 / 开头）。",
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"4) 修改文件内容：先读取（vfs_read_text）→给出改动点→确认后再写入（vfs_write_text）。",
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"5) processors_run 返回任务 id 后，说明任务已提交，可在任务队列查看进度。",
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"6) 回答保持简洁中文。",
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]
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if current_path:
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lines.append("")
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lines.append(f"当前文件管理目录：{current_path}")
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return "\n".join(lines)
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def _ensure_tool_call_ids(message: Dict[str, Any]) -> Dict[str, Any]:
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tool_calls = message.get("tool_calls")
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if not isinstance(tool_calls, list):
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return message
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changed = False
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for idx, call in enumerate(tool_calls):
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if not isinstance(call, dict):
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continue
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call_id = call.get("id")
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if isinstance(call_id, str) and call_id.strip():
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continue
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call["id"] = f"call_{idx}"
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changed = True
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if changed:
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message["tool_calls"] = tool_calls
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return message
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def _extract_pending(tool_call: Dict[str, Any], requires_confirmation: bool) -> PendingToolCall:
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call_id = str(tool_call.get("id") or "")
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fn = tool_call.get("function") or {}
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name = str((fn.get("name") if isinstance(fn, dict) else None) or "")
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raw_args = fn.get("arguments") if isinstance(fn, dict) else None
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arguments: Dict[str, Any] = {}
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if isinstance(raw_args, str) and raw_args.strip():
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try:
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parsed = json.loads(raw_args)
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if isinstance(parsed, dict):
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arguments = parsed
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except json.JSONDecodeError:
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arguments = {}
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return PendingToolCall(
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id=call_id,
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name=name,
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arguments=arguments,
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requires_confirmation=requires_confirmation,
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)
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def _find_last_assistant_tool_calls(messages: List[Dict[str, Any]]) -> Tuple[int, Dict[str, Any]]:
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for idx in range(len(messages) - 1, -1, -1):
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msg = messages[idx]
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if not isinstance(msg, dict):
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continue
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if msg.get("role") != "assistant":
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continue
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tool_calls = msg.get("tool_calls")
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if isinstance(tool_calls, list) and tool_calls:
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return idx, msg
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raise HTTPException(status_code=400, detail="没有可确认的待执行操作")
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def _existing_tool_result_ids(messages: List[Dict[str, Any]]) -> set[str]:
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ids: set[str] = set()
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for msg in messages:
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if not isinstance(msg, dict):
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continue
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if msg.get("role") != "tool":
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continue
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tool_call_id = msg.get("tool_call_id")
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if isinstance(tool_call_id, str) and tool_call_id.strip():
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ids.add(tool_call_id)
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return ids
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async def _choose_chat_ability() -> str:
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tools_model = await AIProviderService.get_default_model("tools")
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return "tools" if tools_model else "chat"
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def _sse(event: str, data: Any) -> bytes:
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payload = json.dumps(data, ensure_ascii=False, separators=(",", ":"))
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return f"event: {event}\ndata: {payload}\n\n".encode("utf-8")
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class AgentService:
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@classmethod
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async def chat(cls, req: AgentChatRequest, user: Optional[User]) -> Dict[str, Any]:
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history: List[Dict[str, Any]] = list(req.messages or [])
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current_path = _normalize_path(req.context.current_path if req.context else None)
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system_prompt = _build_system_prompt(current_path)
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internal_messages: List[Dict[str, Any]] = [{"role": "system", "content": system_prompt}] + history
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new_messages: List[Dict[str, Any]] = []
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pending: List[PendingToolCall] = []
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approved_ids = {i for i in (req.approved_tool_call_ids or []) if isinstance(i, str) and i.strip()}
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rejected_ids = {i for i in (req.rejected_tool_call_ids or []) if isinstance(i, str) and i.strip()}
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if approved_ids or rejected_ids:
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_, last_call_msg = _find_last_assistant_tool_calls(internal_messages)
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last_call_msg = _ensure_tool_call_ids(last_call_msg)
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tool_calls = last_call_msg.get("tool_calls") or []
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call_map: Dict[str, Dict[str, Any]] = {
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str(c.get("id")): c
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for c in tool_calls
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if isinstance(c, dict) and isinstance(c.get("id"), str)
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}
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existing_ids = _existing_tool_result_ids(internal_messages)
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for call_id in approved_ids | rejected_ids:
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if call_id in existing_ids:
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continue
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tool_call = call_map.get(call_id)
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if not tool_call:
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continue
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fn = tool_call.get("function") or {}
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name = fn.get("name") if isinstance(fn, dict) else None
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args_raw = fn.get("arguments") if isinstance(fn, dict) else None
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args: Dict[str, Any] = {}
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if isinstance(args_raw, str) and args_raw.strip():
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try:
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parsed = json.loads(args_raw)
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if isinstance(parsed, dict):
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args = parsed
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except json.JSONDecodeError:
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args = {}
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spec = get_tool(str(name or ""))
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if call_id in rejected_ids:
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content = tool_result_to_content({"canceled": True, "reason": "user_rejected"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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continue
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if not spec:
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content = tool_result_to_content({"error": f"unknown_tool: {name}"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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continue
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try:
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result = await spec.handler(args)
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content = tool_result_to_content(result)
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except Exception as exc: # noqa: BLE001
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content = tool_result_to_content({"error": str(exc)})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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tools_schema = openai_tools()
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ability = await _choose_chat_ability()
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max_loops = 4
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for _ in range(max_loops):
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try:
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assistant = await chat_completion(
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internal_messages,
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ability=ability,
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tools=tools_schema,
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tool_choice="auto",
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timeout=60.0,
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)
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except MissingModelError as exc:
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raise HTTPException(status_code=400, detail=str(exc)) from exc
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except httpx.HTTPStatusError as exc:
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raise HTTPException(status_code=502, detail=f"对话请求失败: {exc}") from exc
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except httpx.RequestError as exc:
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raise HTTPException(status_code=502, detail=f"对话请求异常: {exc}") from exc
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assistant = _ensure_tool_call_ids(assistant)
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internal_messages.append(assistant)
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new_messages.append(assistant)
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tool_calls = assistant.get("tool_calls")
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if not isinstance(tool_calls, list) or not tool_calls:
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break
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pending = []
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for call in tool_calls:
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if not isinstance(call, dict):
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continue
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call_id = str(call.get("id") or "")
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fn = call.get("function") or {}
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name = fn.get("name") if isinstance(fn, dict) else None
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args_raw = fn.get("arguments") if isinstance(fn, dict) else None
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args: Dict[str, Any] = {}
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if isinstance(args_raw, str) and args_raw.strip():
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try:
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parsed = json.loads(args_raw)
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if isinstance(parsed, dict):
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args = parsed
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except json.JSONDecodeError:
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args = {}
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spec = get_tool(str(name or ""))
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if not spec:
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content = tool_result_to_content({"error": f"unknown_tool: {name}"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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continue
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if spec.requires_confirmation and not req.auto_execute:
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pending.append(_extract_pending(call, True))
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continue
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try:
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result = await spec.handler(args)
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content = tool_result_to_content(result)
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except Exception as exc: # noqa: BLE001
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content = tool_result_to_content({"error": str(exc)})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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if pending:
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break
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payload: Dict[str, Any] = {"messages": new_messages}
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if pending:
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payload["pending_tool_calls"] = [p.model_dump() for p in pending]
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return payload
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@classmethod
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async def chat_stream(cls, req: AgentChatRequest, user: Optional[User]):
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history: List[Dict[str, Any]] = list(req.messages or [])
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current_path = _normalize_path(req.context.current_path if req.context else None)
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system_prompt = _build_system_prompt(current_path)
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internal_messages: List[Dict[str, Any]] = [{"role": "system", "content": system_prompt}] + history
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new_messages: List[Dict[str, Any]] = []
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pending: List[PendingToolCall] = []
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approved_ids = {i for i in (req.approved_tool_call_ids or []) if isinstance(i, str) and i.strip()}
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rejected_ids = {i for i in (req.rejected_tool_call_ids or []) if isinstance(i, str) and i.strip()}
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try:
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if approved_ids or rejected_ids:
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_, last_call_msg = _find_last_assistant_tool_calls(internal_messages)
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last_call_msg = _ensure_tool_call_ids(last_call_msg)
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tool_calls = last_call_msg.get("tool_calls") or []
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call_map: Dict[str, Dict[str, Any]] = {
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str(c.get("id")): c
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for c in tool_calls
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if isinstance(c, dict) and isinstance(c.get("id"), str)
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}
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existing_ids = _existing_tool_result_ids(internal_messages)
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for call_id in approved_ids | rejected_ids:
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if call_id in existing_ids:
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continue
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tool_call = call_map.get(call_id)
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if not tool_call:
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continue
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fn = tool_call.get("function") or {}
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name = fn.get("name") if isinstance(fn, dict) else None
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args_raw = fn.get("arguments") if isinstance(fn, dict) else None
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args: Dict[str, Any] = {}
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if isinstance(args_raw, str) and args_raw.strip():
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try:
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parsed = json.loads(args_raw)
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if isinstance(parsed, dict):
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args = parsed
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except json.JSONDecodeError:
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args = {}
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spec = get_tool(str(name or ""))
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if call_id in rejected_ids:
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content = tool_result_to_content({"canceled": True, "reason": "user_rejected"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
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continue
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if not spec:
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content = tool_result_to_content({"error": f"unknown_tool: {name}"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
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continue
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yield _sse("tool_start", {"tool_call_id": call_id, "name": spec.name})
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try:
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result = await spec.handler(args)
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content = tool_result_to_content(result)
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except Exception as exc: # noqa: BLE001
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content = tool_result_to_content({"error": str(exc)})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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yield _sse("tool_end", {"tool_call_id": call_id, "name": spec.name, "message": tool_msg})
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tools_schema = openai_tools()
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ability = await _choose_chat_ability()
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max_loops = 4
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for _ in range(max_loops):
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assistant_event_id = uuid.uuid4().hex
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yield _sse("assistant_start", {"id": assistant_event_id})
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assistant_message: Dict[str, Any] | None = None
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try:
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async for event in chat_completion_stream(
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internal_messages,
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ability=ability,
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tools=tools_schema,
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tool_choice="auto",
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timeout=60.0,
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):
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if event.get("type") == "delta":
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delta = event.get("delta")
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if isinstance(delta, str) and delta:
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yield _sse("assistant_delta", {"id": assistant_event_id, "delta": delta})
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elif event.get("type") == "message":
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msg = event.get("message")
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if isinstance(msg, dict):
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assistant_message = msg
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except MissingModelError as exc:
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raise HTTPException(status_code=400, detail=str(exc)) from exc
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except httpx.HTTPStatusError as exc:
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raise HTTPException(status_code=502, detail=f"对话请求失败: {exc}") from exc
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except httpx.RequestError as exc:
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raise HTTPException(status_code=502, detail=f"对话请求异常: {exc}") from exc
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if not assistant_message:
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assistant_message = {"role": "assistant", "content": ""}
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assistant_message = _ensure_tool_call_ids(assistant_message)
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internal_messages.append(assistant_message)
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new_messages.append(assistant_message)
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yield _sse("assistant_end", {"id": assistant_event_id, "message": assistant_message})
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tool_calls = assistant_message.get("tool_calls")
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if not isinstance(tool_calls, list) or not tool_calls:
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break
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pending = []
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for call in tool_calls:
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if not isinstance(call, dict):
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continue
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call_id = str(call.get("id") or "")
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fn = call.get("function") or {}
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name = fn.get("name") if isinstance(fn, dict) else None
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args_raw = fn.get("arguments") if isinstance(fn, dict) else None
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args: Dict[str, Any] = {}
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if isinstance(args_raw, str) and args_raw.strip():
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try:
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parsed = json.loads(args_raw)
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if isinstance(parsed, dict):
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args = parsed
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except json.JSONDecodeError:
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args = {}
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spec = get_tool(str(name or ""))
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if not spec:
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content = tool_result_to_content({"error": f"unknown_tool: {name}"})
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tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
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internal_messages.append(tool_msg)
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new_messages.append(tool_msg)
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yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
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continue
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if spec.requires_confirmation and not req.auto_execute:
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pending.append(_extract_pending(call, True))
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continue
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yield _sse("tool_start", {"tool_call_id": call_id, "name": spec.name})
|
||
try:
|
||
result = await spec.handler(args)
|
||
content = tool_result_to_content(result)
|
||
except Exception as exc: # noqa: BLE001
|
||
content = tool_result_to_content({"error": str(exc)})
|
||
tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
|
||
internal_messages.append(tool_msg)
|
||
new_messages.append(tool_msg)
|
||
yield _sse("tool_end", {"tool_call_id": call_id, "name": spec.name, "message": tool_msg})
|
||
|
||
if pending:
|
||
yield _sse("pending", {"pending_tool_calls": [p.model_dump() for p in pending]})
|
||
break
|
||
|
||
payload: Dict[str, Any] = {"messages": new_messages}
|
||
if pending:
|
||
payload["pending_tool_calls"] = [p.model_dump() for p in pending]
|
||
yield _sse("done", payload)
|
||
|
||
except asyncio.CancelledError:
|
||
return
|