Files
fckbot/rag/rag_orchestrator.py
Markov Andrey 59feffc190 Update 9 files
- /rag/config_models.py
- /rag/utils/config_loader.py
- /rag/auth.py
- /rag/rag_server.py
- /rag/rag_api.py
- /rag/rag_orchestrator.py
- /rag/__init__.py
- /bots/xmpp/client.py
- /bots/rag_client.py
2026-06-30 14:27:34 +00:00

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# -*- coding: utf-8 -*-
"""
Главный оркестратор RAG-пайплайна (фасад).
Координирует работу менеджеров: HistoryManager, IntentRouter, QueryProcessor, IndexingManager.
"""
import logging
from typing import Optional, Dict, List, Any
from .services.postgres_service import PostgresService
from .services.qdrant_service import QdrantService
from .services.embedding_service import EmbeddingService
from .services.kb_service import KBService
from .services.giga_client import GigaClient
from .services.file_service import FileService
from .history_manager import HistoryManager
from .intent_router import IntentRouter
from .query_processor import QueryProcessor
from .indexing_manager import IndexingManager
from .functions.intent_classify import classify_intent
from .utils.text_utils import count_tokens
from .config_models import AppConfig
logger = logging.getLogger(__name__)
class RAGOrchestrator:
"""
Оркестратор RAG-пайплайна.
Содержит ссылки на все сервисы и менеджеры.
"""
def __init__(
self,
db: PostgresService,
qdrant: QdrantService,
embedding: EmbeddingService,
kb: KBService,
giga: GigaClient,
files: FileService,
config: AppConfig,
default_prompts: Optional[Dict[str, str]] = None
):
self.db = db
self.qdrant = qdrant
self.embedding = embedding
self.kb = kb
self.giga = giga
self.files = files
self.config = config
self.default_prompts = default_prompts or {}
# Инициализация менеджеров
self.history_manager = HistoryManager(
db=db,
giga=giga,
config=config,
default_prompts=self.default_prompts
)
self.intent_router = IntentRouter(
giga=giga,
kb=kb,
files=files,
config=config,
default_prompts=self.default_prompts
)
self.query_processor = QueryProcessor(
giga=giga,
kb=kb,
config=config,
default_prompts=self.default_prompts
)
self.indexing_manager = IndexingManager(
kb=kb,
giga=giga,
config=config,
default_prompts=self.default_prompts
)
logger.info("RAGOrchestrator инициализирован с менеджерами")
def _prepare_prompt_parts(
self,
synthesis_template: str,
system_prompt: Optional[str],
query: str,
max_total_tokens: int = 8192,
reserved_for_answer: int = 1000,
reserved_for_overhead: int = 200
) -> Dict[str, Any]:
system_tokens = count_tokens(system_prompt) if system_prompt else 0
synthesis_tokens = count_tokens(synthesis_template)
query_tokens = count_tokens(query)
prompt_tokens = system_tokens + synthesis_tokens + query_tokens
available = max_total_tokens - prompt_tokens - reserved_for_answer - reserved_for_overhead
if available < 0:
logger.warning(
f"Недостаточно токенов для истории и контекста: {available}. "
f"Увеличьте max_total_tokens или уменьшите размер промптов."
)
available = max(available, 100)
return {
"available_for_history_and_context": available,
"prompt_tokens": prompt_tokens,
"system_tokens": system_tokens,
"synthesis_tokens": synthesis_tokens,
"query_tokens": query_tokens,
}
async def process_query(
self,
query: str,
user_jid: str,
room_jid: Optional[str],
prompts: Optional[Dict[str, str]] = None,
intent_override: Optional[str] = None,
last_file_path: Optional[str] = None,
last_file_text: Optional[str] = None,
) -> Dict[str, Any]:
if prompts is None:
prompts = self.default_prompts.copy()
synthesis_template = prompts.get('synthesis', '')
if not synthesis_template:
synthesis_template = "{context}\n\n{query}\n\nОтвет:"
system_prompt = prompts.get('system', None)
max_model_tokens = self.config.max_model_tokens
reserved_for_answer = self.config.reserved_for_answer_tokens
reserved_for_overhead = self.config.reserved_for_overhead_tokens
token_info = self._prepare_prompt_parts(
synthesis_template=synthesis_template,
system_prompt=system_prompt,
query=query,
max_total_tokens=max_model_tokens,
reserved_for_answer=reserved_for_answer,
reserved_for_overhead=reserved_for_overhead
)
available_for_history_and_context = token_info["available_for_history_and_context"]
logger.debug(f"Доступно для истории и контекста: {available_for_history_and_context} токенов")
raw_history = await self.history_manager.get_history(user_jid, room_jid, limit=100)
max_history_tokens = min(available_for_history_and_context // 2, 2000)
formatted_history = await self.history_manager.compress_history_if_needed(
raw_history,
max_tokens=max_history_tokens,
prompt_template=prompts.get('hierarchical_summary', '')
)
intent = intent_override
if intent is None and self.config.enable_intent_classification:
intent_prompt = prompts.get('intent', '')
if intent_prompt:
intent = await classify_intent(
giga=self.giga,
query=query,
prompt_text=intent_prompt,
bot_config=self.config
)
else:
intent = "GENERAL"
else:
intent = intent or "GENERAL"
keywords = self.config.surgical_keywords
if any(kw in query.lower() for kw in keywords) and last_file_path:
intent = "SURGICAL"
logger.info(f"Принудительный Intent: SURGICAL (есть файл и ключевые слова)")
router_result = await self.intent_router.route(
intent=intent,
query=query,
user_jid=user_jid,
room_jid=room_jid,
prompts=prompts,
last_file_path=last_file_path,
last_file_text=last_file_text,
history=formatted_history,
system_prompt=system_prompt
)
answer = None
context = ""
sources = []
if router_result is not None:
answer = router_result.get("answer")
context = router_result.get("context", "")
sources = router_result.get("sources", [])
else:
history_tokens = sum(count_tokens(msg['content']) for msg in formatted_history)
available_for_context = available_for_history_and_context - history_tokens
available_for_context = max(available_for_context, 0)
processor_result = await self.query_processor.process(
query=query,
user_jid=user_jid,
room_jid=room_jid,
prompts=prompts,
intent=intent,
history=formatted_history,
system_prompt=system_prompt,
available_tokens_for_context=available_for_context
)
answer = processor_result.get("answer")
context = processor_result.get("context", "")
sources = processor_result.get("sources", [])
await self.history_manager.save_message(user_jid, "user", query, room_jid)
if answer:
await self.history_manager.save_message(user_jid, "assistant", answer, room_jid)
return {
"answer": answer or "⚠️ Не удалось сгенерировать ответ.",
"intent": intent,
"context": context,
"sources": sources,
"confidence": None,
"error": None
}
async def index_document(
self,
file_name: str,
file_text: str,
user_jid: str,
room_jid: Optional[str],
is_global: bool = False,
title: Optional[str] = None,
metadata: Optional[Dict] = None,
file_hash: Optional[str] = None,
update_if_exists: bool = True
) -> Dict[str, Any]:
try:
doc_id, chunk_count = await self.indexing_manager.index_document(
file_name=file_name,
file_text=file_text,
user_jid=user_jid,
room_jid=room_jid,
is_global=is_global,
title=title,
metadata=metadata,
file_hash=file_hash,
update_if_exists=update_if_exists
)
return {"doc_id": doc_id, "chunk_count": chunk_count, "error": None}
except Exception as e:
logger.error(f"Ошибка индексации документа {file_name}: {e}", exc_info=True)
return {"doc_id": None, "chunk_count": 0, "error": str(e)}