feat(ui): gemini-style top-anchored scroll, centered chat layout and task drawer sync (closes #49)
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"""
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===============================================================================
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FILE: modules/ai_engine/agent.py
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PROJECT: SCUD Orion AI (Unified Architecture)
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MODULE: modules / ai_engine
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ROLE: Лаконичный нативный оркестратор Function Calling, диспетчер handlers
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и менеджер свободных диалогов (Topic Drift).
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AI-CONTEXT-ANCHORS:
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- ANCHOR[AGENT_PIPELINE_ENTRY]: Главная точка входа process_chat_message.
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===============================================================================
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"""
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import sys
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import json
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import logging
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from typing import List, Dict, Any, Tuple, Optional
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from modules.web_api.llm.schemas import TOOLS_SCHEMA
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from modules.web_api.llm.core.ollama_client import call_ollama_chat
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from modules.web_api.llm.core.fast_path import handle_fast_path_intercept
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from modules.web_api.llm.core.tool_injector import clean_raw_tool_tags, clean_output, inject_tools_if_needed
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from modules.web_api.llm.core.context_manager import mark_last_user_message_ephemeral, close_tool_session_and_cleanup
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from modules.web_api.llm.db.db_chat import db_save_chat_message, db_get_chat_history, db_purge_ephemeral_messages
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from modules.web_api.llm.db.db_prompts import (
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db_get_session_state, db_clear_session_state, db_set_session_state,
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db_get_stats, db_get_anomalies, db_get_reference
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)
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from services.knowledge.service import get_rules
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from .context_builder import build_agent_system_context
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from .handlers.task_handler import handle_tasks_call
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from .handlers.prompt_handler import handle_prompt_call
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from .handlers.snapshot_handler import handle_snapshots_call
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logger = logging.getLogger("AI_AGENT")
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logger.setLevel(logging.INFO)
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# ANCHOR[AGENT_PIPELINE_ENTRY]
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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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"""Главный конвейер обработки сообщений чата."""
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logger.info(f"Сообщение от user_id={user_id}, session_id={session_id}: {user_message}")
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session_state = db_get_session_state(session_id)
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if not session_state:
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db_purge_ephemeral_messages(session_id)
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full_user_content = f"{user_message}\n\n[СОДЕРЖИМОЕ ПРИКРЕПЛЕННОГО ФАЙЛА]:\n{file_context}" if file_context else user_message
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# 1. Быстрый Fast-Path перехват кнопок подтверждения
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fast_path_res = handle_fast_path_intercept(session_id, user_message, full_user_content, session_state)
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if fast_path_res:
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return fast_path_res
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db_save_chat_message(session_id, "user", full_user_content, is_ephemeral=0)
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db_history = db_get_chat_history(session_id, limit=20)
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system_prompt = build_agent_system_context(user_id, session_state)
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user_msg_obj = {"role": "user", "content": full_user_content}
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try:
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if image_b64:
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user_msg_obj["images"] = [image_b64]
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messages = [{"role": "system", "content": "Строгий модуль OCR. Перепиши весь текст буква в букву."}, user_msg_obj]
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msg = call_ollama_chat(messages, is_vision=True)
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else:
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clean_history = [dict(m) for m in db_history]
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for m in clean_history: m.pop("images", None)
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messages = [{"role": "system", "content": system_prompt}] + clean_history + [user_msg_obj]
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msg = call_ollama_chat(messages, tools=TOOLS_SCHEMA, is_vision=False)
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raw_reply = msg.get("content", "")
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tool_calls = msg.get("tool_calls", [])
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# 2. Гибридный семантический классификатор намерений (Fallback Safety Net)
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tool_calls = inject_tools_if_needed(user_message, raw_reply, tool_calls)
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# 3. Исполнение инструментов через изолированные handlers
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if tool_calls:
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tool = tool_calls[0]
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fn_name = tool["function"]["name"]
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fn_args = tool["function"].get("arguments", {})
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if isinstance(fn_args, str):
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try: fn_args = json.loads(fn_args)
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except Exception: fn_args = {}
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logger.info(f"Вызов инструмента: {fn_name} с аргументами: {fn_args}")
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close_tool_session_and_cleanup(session_id, close_reason=f"ACTIVATE_{fn_name}")
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mark_last_user_message_ephemeral(session_id)
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state_data = session_state.get("data_json") or {} if session_state else {}
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if fn_name in ["db_get_tasks", "db_tasks_edit", "db_add_task", "db_update_task_status", "db_delete_task"]:
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return handle_tasks_call(fn_name, fn_args, user_id, session_id)
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elif fn_name in ["db_get_system_prompt", "db_prompt_node_edit"]:
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return handle_prompt_call(fn_name, fn_args, session_id)
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elif fn_name in ["db_get_snapshots", "db_delete_snapshots"]:
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return handle_snapshots_call(fn_name, fn_args, session_id, user_message, state_data)
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elif fn_name == "db_get_rules":
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res_str = json.dumps(get_rules(), ensure_ascii=False)
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elif fn_name == "db_get_stats":
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res_str = json.dumps(db_get_stats(), ensure_ascii=False)
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elif fn_name == "db_get_anomalies":
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res_str = 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_reference":
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res_str = json.dumps(db_get_reference(category=fn_args.get("category")), ensure_ascii=False)
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else:
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res_str = "{}"
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messages.append(msg)
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messages.append({"role": "tool", "content": res_str})
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sec_msg = call_ollama_chat(messages, is_vision=False)
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final_content = clean_raw_tool_tags(clean_output(sec_msg.get("content", ""))) or "Запрос выполнен."
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db_save_chat_message(session_id, "assistant", final_content, is_ephemeral=0)
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return final_content, db_get_chat_history(session_id), None
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# 4. Обычный содержательный диалог и управление Topic Drift
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final_reply = clean_raw_tool_tags(clean_output(raw_reply)) or "Запрос обработан."
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for artifact in ["почемучка,", "почемучка!", "почемучка?", "почемучка", "почемучто,", "почемучто", "почему-то"]:
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if final_reply.lower().startswith(artifact):
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final_reply = final_reply[len(artifact):].lstrip(",.!?:; -")
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action_payload = None
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# Обработка ответа "нет / спасибо" в режиме открытого инструмента
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if session_state and any(kw in user_message.lower() for kw in ["нет", "спасибо", "не надо", "готово", "хватит"]):
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close_tool_session_and_cleanup(session_id, close_reason="USER_DISMISSED_TOOL")
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db_save_chat_message(session_id, "assistant", final_reply, is_ephemeral=0)
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return final_reply, db_get_chat_history(session_id), None
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# Инкремент счётчика шагов в сторону от инструмента (Topic Drift)
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if session_state and session_state.get("state_type") in ["PROMPT_FOLLOWUP", "PROMPT_PREVIEW", "SNAPSHOTS_VIEW"]:
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state_type = session_state.get("state_type")
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state_data = session_state.get("data_json") or {}
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if not isinstance(state_data, dict):
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state_data = {}
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idle_turns = state_data.get("idle_turns", 0) + 1
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state_data["idle_turns"] = idle_turns
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if idle_turns >= 4:
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# 4-й шаг не по теме: бесшумно закрываем сессию и вычищаем эфемерные карточки
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close_tool_session_and_cleanup(session_id, close_reason="TOPIC_DRIFT_TIMEOUT")
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elif idle_turns == 3:
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# 3-й шаг: выводим вежливое напоминание с кнопками
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tool_label = "системным промптом" if "PROMPT" in state_type else "снапшотами СКУД"
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guard_question = f"Желаете продолжить работу с {tool_label}?"
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final_reply += f"\n\n💡 *Напоминание:* {guard_question}"
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action_payload = {
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"type": "FOLLOW_UP_ACTION",
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"buttons": [
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{"label": "Показать снова", "value": "покажи системный промпт" if "PROMPT" in state_type else "покажи снапшоты", "style": "primary"},
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{"label": "Завершить", "value": "нет, спасибо", "style": "secondary"}
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]
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}
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db_set_session_state(session_id, state_type, state_data)
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else:
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# 1-й и 2-й шаг: фиксируем обновленный счётчик
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db_set_session_state(session_id, state_type, state_data)
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is_ephem_reply = 1 if "актуальный системный промпт:" in final_reply.lower() else 0
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db_save_chat_message(session_id, "assistant", final_reply, is_ephemeral=is_ephem_reply)
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return final_reply, db_get_chat_history(session_id), action_payload
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except Exception as ex:
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logger.exception(f"Ошибка в агенте: {ex}")
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return f"Внутренняя ошибка сервера: {ex}", db_get_chat_history(session_id), None
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