401 lines
24 KiB
Python
401 lines
24 KiB
Python
"""
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===============================================================================
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FILE: modules/web_api/llm/agent.py
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PROJECT: SCUD Orion AI (Unified Architecture)
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MODULE: web_api / llm (Core Agent & Function Calling Dispatcher)
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ROLE: Главный оркестратор взаимодействия с Ollama LLM (Qwen 2.5), разбор вызовов
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инструментов (Function Calling), интеграция с декларативным реестром
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действий SQLite (tool_action_registry), детерминированный Fast-Path
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для подтверждений, динамические кнопки и автоочистка эфемерных сообщений.
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===============================================================================
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"""
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# --- [SECTION 1: SYSTEM PATHS & IMPORTS] --- # ANCHOR[SYS_IMPORTS]
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import os
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import sys
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import json
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import urllib.request
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import urllib.error
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import logging
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import re
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from typing import List, Dict, Any, Tuple, Optional
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# Импорт фасада базы данных
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from .db_tools import (
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db_get_active_system_prompt,
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db_add_system_prompt,
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db_get_tool_action,
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db_get_tasks,
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db_update_task_status,
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db_delete_task,
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db_add_task,
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db_get_rules,
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db_set_session_state,
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db_get_session_state,
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db_get_snapshots,
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db_delete_snapshots,
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db_clear_session_state,
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db_get_current_server_time,
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db_save_chat_message,
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db_get_chat_history,
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db_purge_ephemeral_messages,
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db_get_stats,
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db_get_anomalies,
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db_get_session_states,
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db_get_reference
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)
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from .schemas import TOOLS_SCHEMA
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from .core.calendar_utils import get_dynamic_calendar_context, parse_relative_date_ru
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from .core.tool_injector import clean_raw_tool_tags, clean_output, inject_tools_if_needed
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# --- [SECTION 2: LOGGING CONFIGURATION] --- # ANCHOR[LOGGING_CONFIG]
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logger = logging.getLogger("SCUD_AGENT")
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logger.setLevel(logging.INFO)
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logger.propagate = False
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if not logger.handlers:
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handler = logging.StreamHandler(sys.stdout)
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formatter = logging.Formatter("%(asctime)s [%(levelname)s] [%(name)s] %(message)s")
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handler.setFormatter(formatter)
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logger.addHandler(handler)
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OLLAMA_URL = "http://192.168.11.3:11434/api/chat"
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TEXT_MODEL = "qwen2.5:14b"
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VISION_MODEL = "qwen2.5vl:7b-q8_0"
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# --- [SECTION 3: MAIN CHAT PROCESSING PIPELINE] --- # ANCHOR[CHAT_PROCESSOR]
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def process_chat_message(
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user_id: int,
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user_message: str,
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file_context: str = "",
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image_b64: Optional[str] = None,
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chat_history: List[Dict[str, Any]] = None,
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session_id: str = "web_session_main"
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) -> Tuple[str, List[Dict[str, Any]], Optional[Dict[str, Any]]]:
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"""
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Главный конвейер обработки входящего сообщения:
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1. Fast-Path перехват подтверждений/отмен при активном session_state.
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2. Перехват завершения работы ('нет, закончить настройку') с автоочисткой эфемерных сообщений.
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3. Формирование системного контекста и вызов Ollama.
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4. Выполнение вызванного Tool и опрос Data-Driven реестра действий.
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5. Возврат кортежа: (reply_text, chat_history, action_metadata).
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"""
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logger.info(f"Получено сообщение от user_id={user_id}, session_id={session_id}: {user_message}")
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# 3.1. Обогащение текста вложением (при наличии)
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full_user_content = user_message
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if file_context:
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full_user_content = f"{user_message}\n\n[СОДЕРЖИМОЕ ПРИКРЕПЛЕННОГО ФАЙЛА]:\n{file_context}"
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session_state = db_get_session_state(session_id)
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user_msg_clean = user_message.lower().strip(" .!?:;")
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# --- [FAST-PATH 1: ПЕРЕХВАТ ЗАВЕРШЕНИЯ НАСТРОЙКИ С ОЧИСТКОЙ ЭФЕМЕРНОЙ ПАМЯТИ] ---
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if user_msg_clean in ["нет, спасибо", "нет, закончить настройку", "закончить настройку", "завершить", "нет"]:
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db_clear_session_state(session_id)
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deleted_count = db_purge_ephemeral_messages(session_id)
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logger.info(f"🧹 Завершена работа с инструментом. Удалено эфемерных сообщений: {deleted_count}")
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reply_text = "Хорошо. Настройка завершена, контекст диалога чист. Чем я могу помочь дальше?"
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=0)
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return reply_text, db_get_chat_history(session_id), None
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# --- [FAST-PATH 2: ПЕРЕХВАТ ПОДТВЕРЖДЕНИЯ / ОТМЕНЫ ПРЕВЬЮ ПРОМПТА] ---
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if session_state and session_state.get("state_type") == "PROMPT_PREVIEW":
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if user_msg_clean in ["подтверждаю", "подтвердить", "да", "сохранить", "применить", "ок", "хорошо"]:
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db_add_system_prompt("main_agent", session_state.get("pending_data", ""))
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db_clear_session_state(session_id)
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action_cfg = db_get_tool_action("db_confirm_prompt_preview")
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reply_text = action_cfg["success_template"] if action_cfg else "✅ Системный промпт успешно сохранен и применен в базе данных."
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if action_cfg and action_cfg.get("follow_up_question"):
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reply_text += f"\n\n{action_cfg['follow_up_question']}"
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db_save_chat_message(session_id, "user", full_user_content, is_ephemeral=1)
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=1)
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return reply_text, db_get_chat_history(session_id), {
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"type": action_cfg.get("action_type") if action_cfg else "FOLLOW_UP_ACTION",
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"buttons": action_cfg.get("buttons", []) if action_cfg else []
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}
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elif user_msg_clean in ["отмена", "отменить", "отклонить", "назад", "стоп"]:
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db_clear_session_state(session_id)
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action_cfg = db_get_tool_action("db_cancel_prompt_preview")
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reply_text = action_cfg["success_template"] if action_cfg else "❌ Изменения системного промпта отменены."
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if action_cfg and action_cfg.get("follow_up_question"):
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reply_text += f"\n\n{action_cfg['follow_up_question']}"
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db_save_chat_message(session_id, "user", full_user_content, is_ephemeral=1)
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=1)
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return reply_text, db_get_chat_history(session_id), {
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"type": action_cfg.get("action_type") if action_cfg else "FOLLOW_UP_ACTION",
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"buttons": action_cfg.get("buttons", []) if action_cfg else []
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}
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# 3.2. Сохраняем входящее сообщение в историю диалога
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is_user_ephemeral = 1 if session_state else 0
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db_save_chat_message(session_id, "user", full_user_content, is_ephemeral=is_user_ephemeral)
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# 3.3. Извлекаем полную актуальную историю для передачи в LLM
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db_history = db_get_chat_history(session_id, limit=20)
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dynamic_prompt_text = db_get_active_system_prompt()
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calendar_context = get_dynamic_calendar_context()
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user_info = f"Пользователь ID={user_id}" if user_id != 0 else "Гость"
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system_prompt_content = (
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f"Ты — интеллектуальный ассистент SCUD Orion AI. "
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f"Ты управляешь задачами, аналитикой СКУД и системными настройками с помощью инструментов (tools).\n\n"
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f"[ОКРУЖЕНИЕ]\n"
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f"- Пользователь: {user_info}\n"
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f"- {calendar_context}\n\n"
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f"[ПРАВИЛА ИСПОЛЬЗОВАНИЯ ИНСТРУМЕНТОВ]\n"
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f"1. Для любых изменений системного промпта (добавить, удалить, изменить пункт) ВСЕГДА вызывай функцию db_preview_prompt_merge(prompt_text=...).\n"
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f"2. Для просмотра системного промпта ВСЕГДА вызывай db_get_system_prompt().\n"
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f"3. Для просмотра задач ВСЕГДА вызывай db_get_tasks().\n"
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f"4. Никогда не симулируй выполнение функций в виде обычного текста. Если требуется действие — сразу вызывай соответствующий инструмент.\n\n"
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f"[ПРИМЕРЫ ВЫЗОВА ИНСТРУМЕНТОВ]:\n"
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f"- Пользователь: 'добавь пункт 3.4. Работать от сюда и до заката.' -> Вызов: db_preview_prompt_merge(prompt_text='3.4. Работать от сюда и до заката.')\n"
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f"- Пользователь: 'удали пункт 3.4' -> Вызов: db_preview_prompt_merge(prompt_text='3.4')\n"
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f"- Пользователь: 'покажи системный промпт' -> Вызов: db_get_system_prompt()\n"
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f"- Пользователь: 'покажи мои задачи' -> Вызов: db_get_tasks()\n\n"
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f"[ТЕКУЩИЙ АКТИВНЫЙ СИСТЕМНЫЙ ПРОМПТ]:\n{dynamic_prompt_text}"
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)
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llm_options = {
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"num_predict": 8192,
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"num_ctx": 8192,
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"temperature": 0.1,
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"repeat_penalty": 1.1,
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"presence_penalty": 0.5,
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"top_p": 0.9
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}
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user_msg_object = {"role": "user", "content": full_user_content}
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# --- [SECTION 4: ROUTING & OLLAMA PAYLOAD] --- # ANCHOR[PAYLOAD_BUILD]
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if image_b64:
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user_msg_object["images"] = [image_b64]
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messages = [
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{"role": "system", "content": "Ты — строгий модуль OCR. Перепиши весь текст с изображения буква в букву без отсебятины."},
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user_msg_object
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]
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payload = {"model": VISION_MODEL, "messages": messages, "stream": False, "options": llm_options}
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else:
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clean_db_history = [dict(m) for m in db_history]
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for m in clean_db_history:
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m.pop("images", None)
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messages = [{"role": "system", "content": system_prompt_content}] + clean_db_history + [user_msg_object]
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payload = {"model": TEXT_MODEL, "messages": messages, "tools": TOOLS_SCHEMA, "stream": False, "options": llm_options}
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# --- [SECTION 5: EXECUTION & TOOL ROUTING] --- # ANCHOR[TOOL_ROUTER]
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try:
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req = urllib.request.Request(
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OLLAMA_URL,
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data=json.dumps(payload).encode("utf-8"),
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headers={"Content-Type": "application/json"}
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)
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with urllib.request.urlopen(req) as response:
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res_data = json.loads(response.read().decode("utf-8"))
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msg = res_data.get("message", {})
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tool_calls = msg.get("tool_calls", [])
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raw_text_content = msg.get("content", "")
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#tool_calls = inject_tools_if_needed(user_message, raw_text_content, tool_calls)
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if tool_calls:
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logger.info(f"Ответ от Ollama получен. Tool calls: True (кол-во: {len(tool_calls)})")
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messages.append(msg)
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for tool in tool_calls:
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fn_name = tool["function"]["name"]
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fn_args = tool["function"].get("arguments", {})
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logger.info(f"🚀 Вызов функции (Tool): {fn_name} с аргументами: {fn_args}")
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tool_result_content = ""
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action_cfg = db_get_tool_action(fn_name)
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if fn_name == "db_confirm_prompt_preview":
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if session_state and session_state.get("state_type") == "PROMPT_PREVIEW":
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db_add_system_prompt("main_agent", session_state.get("pending_data", ""))
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db_clear_session_state(session_id)
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if action_cfg and action_cfg.get("bypass_llm"):
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reply_text = action_cfg["success_template"]
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if action_cfg.get("follow_up_question"):
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reply_text += f"\n\n{action_cfg['follow_up_question']}"
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is_eph = action_cfg.get("is_ephemeral", 1)
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=is_eph)
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return reply_text, db_get_chat_history(session_id), {
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"type": action_cfg.get("action_type"),
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"buttons": action_cfg.get("buttons", [])
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}
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tool_result_content = json.dumps({"status": "success"}, ensure_ascii=False)
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else:
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err_reply = "⚠️ Нет активного превью для подтверждения."
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db_save_chat_message(session_id, "assistant", err_reply, is_ephemeral=1)
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return err_reply, db_get_chat_history(session_id), None
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elif fn_name == "db_cancel_prompt_preview":
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db_clear_session_state(session_id)
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if action_cfg and action_cfg.get("bypass_llm"):
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reply_text = action_cfg["success_template"]
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if action_cfg.get("follow_up_question"):
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reply_text += f"\n\n{action_cfg['follow_up_question']}"
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is_eph = action_cfg.get("is_ephemeral", 1)
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=is_eph)
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return reply_text, db_get_chat_history(session_id), {
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"type": action_cfg.get("action_type"),
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"buttons": action_cfg.get("buttons", [])
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}
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tool_result_content = json.dumps({"status": "cancelled"}, ensure_ascii=False)
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elif fn_name == "db_get_snapshots":
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snapshots_res = db_get_snapshots(session_id=session_id, date_str=fn_args.get("date_str"), original_user_message=user_message)
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tool_result_content = json.dumps(snapshots_res, ensure_ascii=False)
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elif fn_name == "db_get_current_server_time":
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tool_result_content = json.dumps(db_get_current_server_time(), ensure_ascii=False)
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elif fn_name == "db_get_tasks":
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tool_result_content = json.dumps(db_get_tasks(user_id), ensure_ascii=False)
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elif fn_name in ["db_get_system_prompt", "db_get_system_prompts"]:
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tool_result_content = json.dumps({"system_prompt": db_get_active_system_prompt()}, ensure_ascii=False)
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elif fn_name == "db_get_stats":
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tool_result_content = json.dumps(db_get_stats(), ensure_ascii=False)
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elif fn_name == "db_get_anomalies":
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tool_result_content = json.dumps(db_get_anomalies(limit=fn_args.get("limit", 100), date_str=fn_args.get("date_str")), ensure_ascii=False)
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elif fn_name == "db_get_session_states":
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tool_result_content = json.dumps(db_get_session_states(), ensure_ascii=False)
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elif fn_name == "db_delete_snapshots":
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res = db_delete_snapshots(snapshot_id=fn_args.get("snapshot_id"), day_str=fn_args.get("day_str"))
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if action_cfg and action_cfg.get("bypass_llm"):
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reply_text = action_cfg["success_template"]
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if action_cfg.get("follow_up_question"):
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reply_text += f"\n\n{action_cfg['follow_up_question']}"
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is_eph = action_cfg.get("is_ephemeral", 1)
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db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=is_eph)
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return reply_text, db_get_chat_history(session_id), {
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"type": action_cfg.get("action_type"),
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"buttons": action_cfg.get("buttons", [])
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}
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tool_result_content = json.dumps(res, ensure_ascii=False)
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elif fn_name == "db_get_reference":
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tool_result_content = json.dumps(db_get_reference(category=fn_args.get("category")), ensure_ascii=False)
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# --- [SECTION 6: PROMPT MERGE & PREVIEW ENGINE] --- # ANCHOR[PROMPT_MERGE_LOGIC]
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elif fn_name == "db_preview_prompt_merge":
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proposed_text = fn_args.get("prompt_text") or fn_args.get("proposed_prompt") or ""
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if isinstance(fn_args, str):
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proposed_text = fn_args
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current_prompt = db_get_active_system_prompt()
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user_msg_lower = user_message.lower()
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# 1. ОБРАБОТКА УДАЛЕНИЯ ПУНКТА
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if any(w in user_msg_lower for w in ["удали", "стереть", "убрать", "вырежи", "удалить"]):
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target_num_match = re.search(r'\d+(\.\d+)*', user_message)
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target_num = target_num_match.group(0) if target_num_match else ""
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lines = current_prompt.splitlines()
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if target_num:
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new_lines = [line for line in lines if not line.strip().startswith(f"{target_num}.")]
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else:
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new_lines = lines
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proposed_text = "\n".join(new_lines)
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# 2. ОБРАБОТКА ДОБАВЛЕНИЯ / ИЗМЕНЕНИЯ ПУНКТА
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elif proposed_text:
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if len(proposed_text) < 500:
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clean_item = proposed_text.strip()
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for prefix in ["добавь пункт", "добавить пункт", "вставь пункт", "добавь"]:
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if prefix in clean_item.lower():
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clean_item = re.sub(prefix, "", clean_item, flags=re.IGNORECASE).strip(" .:")
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lines = current_prompt.splitlines()
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new_lines = []
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inserted = False
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for line in lines:
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new_lines.append(line)
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if "3.3." in line and not inserted:
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item_str = clean_item if re.match(r'^\d+\.\d+\.', clean_item) else f"3.4. {clean_item}"
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new_lines.append(f" {item_str}")
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inserted = True
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if not inserted:
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new_lines.append(f" {clean_item}")
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proposed_text = "\n".join(new_lines)
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db_set_session_state(session_id, "PROMPT_PREVIEW", proposed_text)
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preview_reply = (
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f"Ваше изменение успешно предпросмотрено. Полный обновленный системный промпт теперь выглядит так:\n\n"
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f"{proposed_text}\n\n"
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f"Для применения изменений подтвердите действие («подтверждаю») или отмените («отмена»)."
|
||
)
|
||
db_save_chat_message(session_id, "assistant", preview_reply, is_ephemeral=1)
|
||
return clean_raw_tool_tags(preview_reply), db_get_chat_history(session_id), {
|
||
"type": "PROMPT_PREVIEW",
|
||
"buttons": [
|
||
{"label": "Подтвердить", "value": "подтверждаю", "style": "primary"},
|
||
{"label": "Отменить", "value": "отмена", "style": "danger"}
|
||
]
|
||
}
|
||
|
||
elif fn_name == "db_get_rules":
|
||
tool_result_content = json.dumps(db_get_rules(), ensure_ascii=False)
|
||
|
||
elif fn_name == "db_add_task":
|
||
res = db_add_task(user_id=user_id, module=fn_args.get("module", "general"), title=fn_args.get("title"), priority=fn_args.get("priority", "MEDIUM"), due_date=fn_args.get("due_date"))
|
||
tool_result_content = json.dumps(res, ensure_ascii=False)
|
||
|
||
elif fn_name == "db_update_task_status":
|
||
res = db_update_task_status(user_id=user_id, task_id=str(fn_args.get("task_id")), status=fn_args.get("status", "COMPLETED"), due_date=fn_args.get("due_date"))
|
||
tool_result_content = json.dumps(res, ensure_ascii=False)
|
||
|
||
elif fn_name == "db_delete_task":
|
||
res = db_delete_task(user_id=user_id, task_id=str(fn_args.get("task_id", "")).upper())
|
||
if action_cfg and action_cfg.get("bypass_llm"):
|
||
reply_text = action_cfg["success_template"]
|
||
if action_cfg.get("follow_up_question"):
|
||
reply_text += f"\n\n{action_cfg['follow_up_question']}"
|
||
is_eph = action_cfg.get("is_ephemeral", 1)
|
||
db_save_chat_message(session_id, "assistant", reply_text, is_ephemeral=is_eph)
|
||
return reply_text, db_get_chat_history(session_id), {
|
||
"type": action_cfg.get("action_type"),
|
||
"buttons": action_cfg.get("buttons", [])
|
||
}
|
||
tool_result_content = json.dumps(res, ensure_ascii=False)
|
||
|
||
messages.append({"role": "tool", "content": tool_result_content})
|
||
|
||
# --- [SECTION 7: SECONDARY LLM PASS] --- # ANCHOR[SECONDARY_PASS]
|
||
second_payload = {"model": TEXT_MODEL, "messages": messages, "stream": False, "options": llm_options}
|
||
sec_req = urllib.request.Request(OLLAMA_URL, data=json.dumps(second_payload).encode("utf-8"), headers={"Content-Type": "application/json"})
|
||
with urllib.request.urlopen(sec_req) as sec_response:
|
||
sec_res_data = json.loads(sec_response.read().decode("utf-8"))
|
||
raw_content = sec_res_data.get("message", {}).get("content", "").strip().replace("**", "")
|
||
final_content = clean_raw_tool_tags(clean_output(raw_content))
|
||
db_save_chat_message(session_id, "assistant", final_content, is_ephemeral=0)
|
||
return final_content, db_get_chat_history(session_id), None
|
||
|
||
# Если вызовов функций не было
|
||
raw_str = msg.get("content", "").strip().replace("**", "")
|
||
content_str = clean_raw_tool_tags(clean_output(raw_str))
|
||
final_reply = content_str or "Запрос обработан."
|
||
db_save_chat_message(session_id, "assistant", final_reply, is_ephemeral=0)
|
||
return final_reply, db_get_chat_history(session_id), None
|
||
|
||
except Exception as ex:
|
||
logger.exception(f"Непредвиденная ошибка: {ex}")
|
||
error_reply = f"Внутренняя ошибка сервера: {ex}"
|
||
return error_reply, db_get_chat_history(session_id), None |