* Add migration
continuous-integration/drone/push Build is passing

* Delete legacy from bot
* Clear old models
* Единый http клиент
* РАГ полечен
This commit is contained in:
2025-12-24 13:44:52 +03:00
parent 1ce1c23d10
commit 8bdacb4f7a
19 changed files with 200 additions and 565 deletions
+109 -116
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@@ -1,137 +1,130 @@
import aiohttp
from tg_bot.infrastructure.external.deepseek_client import DeepSeekClient
"""
RAG сервис для бота - вызывает API бэкенда
"""
from tg_bot.config.settings import settings
from tg_bot.infrastructure.http_client import create_http_session
class RAGService:
"""Сервис для работы с RAG через API бэкенда"""
def __init__(self):
self.deepseek_client = DeepSeekClient()
async def search_documents_in_collections(
self,
user_telegram_id: str,
query: str,
limit_per_collection: int = 5
) -> list[dict]:
async def get_or_create_conversation(
self,
user_telegram_id: str,
collection_id: str = None
) -> str | None:
"""Получить или создать беседу для пользователя"""
try:
async with aiohttp.ClientSession() as session:
async with create_http_session() as session:
async with session.get(
f"{settings.BACKEND_URL}/users/telegram/{user_telegram_id}"
) as user_response:
if user_response.status != 200:
return []
user_data = await user_response.json()
user_uuid = str(user_data.get("user_id"))
if not user_uuid:
return []
async with session.get(
f"{settings.BACKEND_URL}/collections/",
headers={"X-Telegram-ID": user_telegram_id}
f"{settings.BACKEND_URL}/collections/",
headers={"X-Telegram-ID": user_telegram_id}
) as collections_response:
if collections_response.status != 200:
return []
return None
collections = await collections_response.json()
all_documents = []
for collection in collections:
collection_id = collection.get("collection_id")
if not collections:
if not collection_id:
async with session.post(
f"{settings.BACKEND_URL}/collections",
json={
"name": "Основная коллекция",
"description": "Коллекция по умолчанию",
"is_public": False
},
headers={"X-Telegram-ID": user_telegram_id}
) as create_collection_response:
if create_collection_response.status in [200, 201]:
collection_data = await create_collection_response.json()
collection_id = collection_data.get("collection_id")
else:
collection_id = collection_id
else:
collection_id = collections[0].get("collection_id")
if not collection_id:
continue
try:
async with aiohttp.ClientSession() as search_session:
async with search_session.get(
f"{settings.BACKEND_URL}/documents/collection/{collection_id}",
params={"search": query, "limit": limit_per_collection},
headers={"X-Telegram-ID": user_telegram_id}
) as search_response:
if search_response.status == 200:
documents = await search_response.json()
for doc in documents:
doc["collection_name"] = collection.get("name", "Unknown")
all_documents.append(doc)
except Exception as e:
print(f"Error searching collection {collection_id}: {e}")
continue
return all_documents[:20]
return None
async with session.get(
f"{settings.BACKEND_URL}/conversations",
headers={"X-Telegram-ID": user_telegram_id}
) as conversations_response:
if conversations_response.status == 200:
conversations = await conversations_response.json()
for conv in conversations:
if conv.get("collection_id") == str(collection_id):
return conv.get("conversation_id")
async with session.post(
f"{settings.BACKEND_URL}/conversations",
json={"collection_id": str(collection_id)},
headers={"X-Telegram-ID": user_telegram_id}
) as create_conversation_response:
if create_conversation_response.status in [200, 201]:
conversation_data = await create_conversation_response.json()
return conversation_data.get("conversation_id")
return None
except Exception as e:
print(f"Error searching documents: {e}")
return []
print(f"Error getting/creating conversation: {e}")
return None
async def generate_answer_with_rag(
self,
question: str,
user_telegram_id: str
self,
question: str,
user_telegram_id: str
) -> dict:
documents = await self.search_documents_in_collections(
user_telegram_id,
question
)
context_parts = []
sources = []
for doc in documents[:5]:
title = doc.get("title", "Без названия")
content = doc.get("content", "")[:1000]
collection_name = doc.get("collection_name", "Unknown")
context_parts.append(f"Документ: {title}\nКоллекция: {collection_name}\nСодержание: {content[:500]}...")
sources.append({
"title": title,
"collection": collection_name,
"document_id": doc.get("document_id")
})
context = "\n\n".join(context_parts) if context_parts else "Релевантные документы не найдены."
system_prompt = """Ты - помощник-юрист, который отвечает на вопросы на основе предоставленных документов.
Используй информацию из документов для формирования точного и полезного ответа.
Если в документах нет информации для ответа, честно скажи об этом."""
user_prompt = f"""Контекст из документов:
{context}
Вопрос пользователя: {question}
Ответь на вопрос, используя информацию из предоставленных документов. Если информации недостаточно, укажи это."""
"""Генерирует ответ используя RAG через API бэкенда"""
try:
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
]
response = await self.deepseek_client.chat_completion(
messages=messages,
temperature=0.7,
max_tokens=2000
)
return {
"answer": response.get("content", "Failed to generate answer"),
"sources": sources,
"usage": response.get("usage", {})
}
except Exception as e:
print(f"Error generating answer: {e}")
if documents:
conversation_id = await self.get_or_create_conversation(user_telegram_id)
if not conversation_id:
return {
"answer": f"Found {len(documents)} documents but failed to generate answer",
"sources": sources[:3],
"usage": {}
}
else:
return {
"answer": "No relevant documents found",
"answer": "Не удалось создать беседу. Попробуйте позже.",
"sources": [],
"usage": {}
}
async with create_http_session() as session:
async with session.post(
f"{settings.BACKEND_URL}/rag/question",
json={
"conversation_id": str(conversation_id),
"question": question,
"top_k": 20,
"rerank_top_n": 5
},
headers={"X-Telegram-ID": user_telegram_id}
) as response:
if response.status == 200:
result = await response.json()
sources = []
for source in result.get("sources", []):
sources.append({
"title": source.get("title", "Без названия"),
"document_id": source.get("document_id"),
"chunk_id": source.get("chunk_id"),
"index": source.get("index", 0)
})
return {
"answer": result.get("answer", "Не удалось сгенерировать ответ."),
"sources": sources,
"usage": result.get("usage", {}),
"conversation_id": str(conversation_id)
}
else:
error_text = await response.text()
print(f"RAG API error: {response.status} - {error_text}")
return {
"answer": "Ошибка при генерации ответа. Попробуйте позже.",
"sources": [],
"usage": {}
}
except Exception as e:
print(f"Error generating answer with RAG: {e}")
return {
"answer": "Произошла ошибка при генерации ответа. Попробуйте позже.",
"sources": [],
"usage": {}
}