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Переход с OpenRouter API на OpenAI API.

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Kirill Kirilenko 2026-06-14 19:52:45 +03:00
parent 5b9f5cd1d6
commit ef1e2e8a3e
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6
AGENTS.md
View file

@ -4,7 +4,7 @@
Это движок чат-бота для мессенджеров VK и Telegram, написанный на Python 3.
Движок поддерживает некоторые полезные функции для групповых чатов (правила, приветствие новичков, статистика сообщений, вычисление молчунов и др.).
В движок интегрирован модуль ИИ: пользователи могут общаться с ботом в личных сообщениях, а также в групповых чатах, если упомянут его.
Модуль ИИ использует API OpenRouter для генерации ответов, а также API fal.ai и Replicate для генерации изображений.
Модуль ИИ использует OpenAI-совместимый API для генерации ответов, а также API Replicate для генерации изображений.
## Архитектура проекта
@ -48,7 +48,7 @@ vk_chat_bot/
## Основные технологии
- **Асинхронность:** asyncio
- **ИИ:** OpenRouter (Grok 4.1 Fast), fal.ai (Seedream 4.5) для обычных изображений, Replicate (Nova Anime XL) для генерации изображений в стиле аниме.
- **ИИ:** OpenAI-compatible API для вызова LLM, Replicate для генерации изображений.
- **Telegram:** aiogram 3.x
- **VK:** vkbottle
- **СУБД:** MariaDB (через pyodbc)
@ -78,7 +78,7 @@ python -m vk -c vk.json
Основной класс, обрабатывающий:
- `get_group_chat_reply()` - генерация ответа в групповом чате
- `get_private_chat_reply()` - генерация ответа в личном чате
- `_generate_reply()` - вызов LLM через OpenRouter
- `_generate_reply()` - вызов LLM через OpenAI
- `_process_tool_calls()` - обработка вызова функций
### Обработчики сообщений и событий мессенджера (handlers)

6
ai/__init__.py
View file

@ -1,3 +1,5 @@
from typing import Optional
import ai.agent
from database import BasicDatabase
@ -8,11 +10,11 @@ Agent = ai.agent.AiAgent
agent_instance: ai.agent.AiAgent
def create_ai_agent(openrouter_token: str, openrouter_model: str,
def create_ai_agent(openai_url: Optional[str], openai_token: str, openai_model: str,
replicate_token: str, tavily_token: str,
db: BasicDatabase, platform: str):
global agent_instance
agent_instance = ai.agent.AiAgent(openrouter_token, openrouter_model,
agent_instance = ai.agent.AiAgent(openai_url, openai_token, openai_model,
replicate_token, tavily_token,
db, platform)

260
ai/agent.py
View file

@ -2,14 +2,20 @@ import datetime
import json
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple, Union
from typing import List, Optional, Tuple, cast, Dict, Any
from openrouter import OpenRouter, RetryConfig
from openrouter.components import ChatAssistantMessage, ChatAssistantMessageTypedDict, \
ChatToolCall, ChatResult, ChatSystemMessageTypedDict, ChatMessagesTypedDict, ChatAssistantMessageContent
from openrouter.errors import ResponseValidationError, OpenRouterError
from openrouter.utils import BackoffStrategy
from openai import AsyncOpenAI, omit
from openai.types.chat import (
ChatCompletionMessage,
ChatCompletionMessageParam,
ChatCompletionUserMessageParam,
ChatCompletionAssistantMessageParam,
ChatCompletionSystemMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionFunctionToolParam,
ChatCompletionMessageToolCallUnion,
ChatCompletionMessageFunctionToolCall
)
import ai.tool
from database import BasicDatabase
@ -17,8 +23,11 @@ from database import BasicDatabase
from ai.utils import *
from ai.tools import *
OPENAI_DEFAULT_URL = "https://openrouter.ai/api/v1"
OPENROUTER_X_TITLE = "TG/VK Chat Bot"
OPENROUTER_HTTP_REFERER = "https://ultracoder.org"
OPENROUTER_HTTP_REFERER = "https://kiriru.cc"
OPENROUTER_CATEGORIES = "general-chat,roleplay"
GROUP_CHAT_MAX_MESSAGES = 40
PRIVATE_CHAT_MAX_MESSAGES = 40
@ -34,37 +43,70 @@ class Message:
message_id: Optional[int] = None
class ChatContextManager:
def __init__(self, db: BasicDatabase, bot_id: int, chat_id: int,
system_prompt: ChatCompletionSystemMessageParam, max_messages: int):
self.db = db
self.bot_id = bot_id
self.chat_id = chat_id
self.max_messages = max_messages
self.context: List[ChatCompletionMessageParam] = [system_prompt]
for message in self.db.context_get_messages(bot_id, chat_id):
# noinspection PyTypeChecker
self.context.append(message)
self.pending_messages: List[ChatCompletionMessageParam] = []
self.pending_messages_ids: List[Optional[int]] = []
def add_user_message(self, message: Message):
self._add_pending_message(_serialize_user_message(message.text, message.image), message.message_id)
def add_assistant_message(self, message: ChatCompletionMessage):
self._add_pending_message(_serialize_assistant_message(message), None)
def add_tool_message(self, message: ChatCompletionToolMessageParam):
self._add_pending_message(message, None)
def get_current_context(self):
return self.context
def commit(self):
for i, message in enumerate(self.pending_messages):
self.db.context_add_message(self.bot_id, self.chat_id, message["role"], message=dict(message),
message_id=self.pending_messages_ids[i], max_messages=self.max_messages)
def _add_pending_message(self, message: ChatCompletionMessageParam, message_id: Optional[int] = None):
self.pending_messages.append(message)
self.pending_messages_ids.append(message_id)
self.context.append(message)
class AiAgent:
def __init__(self,
openrouter_token: str, openrouter_model: str,
openai_url: Optional[str], openai_token: str, openai_model: str,
replicate_token: str, tavily_token: str,
db: BasicDatabase,
platform: str):
retry_config = RetryConfig(strategy="backoff",
backoff=BackoffStrategy(
initial_interval=2000, max_interval=8000, exponent=2, max_elapsed_time=14000),
retry_connection_errors=True)
self.db = db
self.openrouter_model = openrouter_model
self.openai_model = openai_model
self.platform = platform
self._load_prompts()
self.client_openrouter = OpenRouter(api_key=openrouter_token,
x_open_router_title=OPENROUTER_X_TITLE,
http_referer=OPENROUTER_HTTP_REFERER,
retry_config=retry_config)
self.client = AsyncOpenAI(
base_url=openai_url if openai_url is not None else OPENAI_DEFAULT_URL,
api_key=openai_token
)
# Создание наборов инструментов
self.toolsets: list[ai.tool.ToolSet] = []
self.toolsets.append(
ImageGenerationToolSet(replicate_token=replicate_token)
)
self.toolsets.append(ImageGenerationToolSet(replicate_token=replicate_token))
self.toolsets.append(TavilySearchToolSet(tavily_token=tavily_token))
# Сбор всех инструментов
self.tools: list[ai.tool.Tool] = []
self.tools_descriptions: list = []
self.tools_descriptions: list[ChatCompletionFunctionToolParam] = []
for toolset in self.toolsets:
self.tools.extend(toolset.functions)
self.tools_descriptions.extend(toolset.get_all_tools_description())
@ -106,48 +148,44 @@ class AiAgent:
async def _handle_chat_reply(self, bot_id: int, chat_id: int,
message: Message, forwarded_messages: List[Message],
is_group_chat: bool, max_messages: int) -> Tuple[Message, bool]:
# 1. Подготовка текста сообщения (префикс)
context_manager = ChatContextManager(
db=self.db, bot_id=bot_id, chat_id=chat_id, max_messages=max_messages,
system_prompt=self._construct_system_prompt(is_group_chat, bot_id, chat_id)
)
# Добавление нового сообщения пользователя
if is_group_chat:
message.text = _add_message_prefix(message.text, message.user_name)
else:
message.text = _add_message_prefix(message.text)
context_manager.add_user_message(message)
# 2. Сбор контекста из БД
context = self._get_chat_context(is_group_chat=is_group_chat, bot_id=bot_id, chat_id=chat_id)
context.append(_serialize_message(role="user", text=message.text, image=message.image))
# 3. Обработка пересланных сообщений
# Добавление пересланных сообщений
for fwd_message in forwarded_messages:
message_text = '<Цитируемое сообщение от {}>'.format(fwd_message.user_name)
if fwd_message.text is not None:
message_text += '\n' + fwd_message.text
fwd_message.text = message_text
context.append(_serialize_message(role="user", text=fwd_message.text, image=fwd_message.image))
context_manager.add_user_message(fwd_message)
# 4. Генерация ответа с поддержкой инструментов
# Генерация ответа с поддержкой инструментов
try:
response = await self._generate_reply(bot_id, chat_id, context=context, allow_tools=True)
context.append(_serialize_assistant_message(response))
ai_response: Optional[ChatAssistantMessageContent] = response.content
response = await self._generate_reply(bot_id, chat_id, context=context_manager.get_current_context(),
allow_tools=True)
context_manager.add_assistant_message(response)
ai_response: Optional[str] = response.content
tools_artifacts = {}
while response.tool_calls is not None:
tools_artifacts = await self._process_tool_calls(tool_calls=response.tool_calls, context=context)
response = await self._generate_reply(bot_id, chat_id, context=context, allow_tools=True)
context.append(_serialize_assistant_message(response))
while response.tool_calls is not None and len(response.tool_calls) > 0:
tools_artifacts = await self._process_tool_calls(tool_calls=response.tool_calls,
context_manager=context_manager)
response = await self._generate_reply(bot_id, chat_id, context=context_manager.get_current_context(),
allow_tools=True)
context_manager.add_assistant_message(response)
ai_response = response.content
# 5. Сохранение истории в БД
self.db.context_add_message(bot_id, chat_id, role="user", text=message.text, image=message.image,
message_id=message.message_id, max_messages=max_messages)
for fwd_message in forwarded_messages:
self.db.context_add_message(bot_id, chat_id,
role="user", text=fwd_message.text, image=fwd_message.image,
message_id=fwd_message.message_id, max_messages=max_messages)
self.db.context_add_message(bot_id, chat_id,
role="assistant", text=ai_response,
image=tools_artifacts.get("generated_image"),
message_id=None, max_messages=max_messages)
# Сохранение обновленного контекста в БД
context_manager.commit()
return Message(text=ai_response, image=tools_artifacts.get("generated_image"),
image_hires=tools_artifacts.get("generated_image_hires")), True
@ -159,15 +197,8 @@ class AiAgent:
print(f"Ошибка выполнения запроса к ИИ: {e}")
return Message(text=f"Извините, при обработке запроса произошла ошибка:\n{e}"), False
def _get_chat_context(self, is_group_chat: bool, bot_id: int, chat_id: int) -> List[ChatMessagesTypedDict]:
context: List[ChatMessagesTypedDict] = [
self._construct_system_prompt(is_group_chat=is_group_chat, bot_id=bot_id, chat_id=chat_id)
]
for message in self.db.context_get_messages(bot_id, chat_id):
context.append(_serialize_message(message["role"], message["text"], message["image"]))
return context
def _construct_system_prompt(self, is_group_chat: bool, bot_id: int, chat_id: int) -> ChatSystemMessageTypedDict:
def _construct_system_prompt(self, is_group_chat: bool, bot_id: int, chat_id: int) \
-> ChatCompletionSystemMessageParam:
prompt = self.system_prompt_group_chat if is_group_chat else self.system_prompt_private_chat
prompt = prompt.replace('{platform}', 'Telegram' if self.platform == 'tg' else 'VK')
@ -188,19 +219,26 @@ class AiAgent:
return {"role": "system", "content": prompt}
async def _generate_reply(self, bot_id: int, chat_id: int,
context: List[ChatMessagesTypedDict], allow_tools: bool = False) -> ChatAssistantMessage:
response = await self._async_chat_completion_request(
model=self.openrouter_model,
messages=context,
tools=self.tools_descriptions if allow_tools else None,
tool_choice="auto" if allow_tools else None,
max_tokens=MAX_OUTPUT_TOKENS,
user=f'{self.platform}_{bot_id}_{chat_id}'
)
return self._filter_response(response.choices[0].message)
context: List[ChatCompletionMessageParam], allow_tools: bool = False) \
-> ChatCompletionMessage:
async def _process_tool_calls(self, tool_calls: List[ChatToolCall],
context: List[ChatMessagesTypedDict]) -> dict:
response = await self.client.chat.completions.create(
model=self.openai_model,
messages=context,
tools=self.tools_descriptions if allow_tools else omit,
tool_choice="auto" if allow_tools else omit,
max_tokens=MAX_OUTPUT_TOKENS,
user=f'{self.platform}_{bot_id}_{chat_id}',
extra_headers={
"HTTP-Referer": OPENROUTER_HTTP_REFERER,
"X-OpenRouter-Title": OPENROUTER_X_TITLE,
"X-OpenRouter-Categories": OPENROUTER_CATEGORIES
}
)
return response.choices[0].message
async def _process_tool_calls(self, tool_calls: List[ChatCompletionMessageToolCallUnion],
context_manager: ChatContextManager) -> Dict[str, Any]:
artifacts = {}
if tool_calls is None:
return artifacts
@ -208,50 +246,24 @@ class AiAgent:
tools_map = {tool.name: tool for tool in self.tools}
for tool_call in tool_calls:
tool_name = tool_call.function.name
tool_args = json.loads(tool_call.function.arguments)
if tool_call.type != "function":
continue
func_call = cast(ChatCompletionMessageFunctionToolCall, tool_call)
tool_name = func_call.function.name
tool_args = json.loads(func_call.function.arguments)
if tool_name in tools_map:
tool = tools_map[tool_name]
# Вызов инструмента с передачей artifacts
tool_result = await tool.execute(tool_args, artifacts)
context.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": tool_result
})
context_manager.add_tool_message(
ChatCompletionToolMessageParam(role="tool", tool_call_id=tool_call.id, content=tool_result)
)
return artifacts
async def _async_chat_completion_request(self, **kwargs) -> ChatResult:
try:
# noinspection PyTypeChecker
return await self.client_openrouter.chat.send_async(**kwargs)
except ResponseValidationError as e:
# Костыль для OpenRouter SDK:
# https://github.com/OpenRouterTeam/python-sdk/issues/44
body = json.loads(e.body)
if "error" in body:
try:
raw_response = json.loads(body["error"]["metadata"]["raw"])
message = str(raw_response["error"]["message"])
e = RuntimeError(message)
except Exception:
pass
raise e
except OpenRouterError as e:
if e.message == "Provider returned error":
body = json.loads(e.body)
try:
raw_response = json.loads(body["error"]["metadata"]["raw"])
message = str(raw_response["error"]["message"])
e = RuntimeError(message)
except Exception:
pass
raise e
# TODO: удалить
@staticmethod
def _filter_response(response: ChatAssistantMessage) -> ChatAssistantMessage:
def _filter_response(response: ChatCompletionMessage) -> ChatCompletionMessage:
text = str(response.content)
text = text.replace("<image>", "")
response.content = text
@ -270,27 +282,19 @@ def _add_message_prefix(text: Optional[str], username: Optional[str] = None) ->
return f"{prefix}: {text}" if text is not None else f"{prefix}:"
def _serialize_message(role: str, text: Optional[str], image: Optional[bytes]) -> dict:
return {"role": role, "content": serialize_message_content(text, image)}
def _serialize_assistant_message(message: ChatAssistantMessage) -> ChatAssistantMessageTypedDict:
# noinspection PyTypeChecker
return _remove_none_recursive(message.model_dump(by_alias=True))
def _remove_none_recursive(data: Union[Dict, List, Any]) -> Union[Dict, List, Any]:
if isinstance(data, dict):
return {
k: _remove_none_recursive(v)
for k, v in data.items()
if v is not None
}
elif isinstance(data, list):
return [
_remove_none_recursive(item)
for item in data
if item is not None
]
def _serialize_user_message(text: Optional[str], image: Optional[bytes]) -> ChatCompletionUserMessageParam:
if image is None:
if text is not None:
content = text
else:
raise ValueError("Either text or image must be provided")
else:
return data
content = []
if text is not None:
content.append({"type": "text", "text": text})
content.append({"type": "image_url", "image_url": {"url": encode_image(image), "detail": "high"}})
return {"role": "user", "content": content}
def _serialize_assistant_message(message: ChatCompletionMessage) -> ChatCompletionAssistantMessageParam:
return message.model_dump(exclude_none=True)

10
ai/tool.py
View file

@ -2,7 +2,7 @@ from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Any, Dict, List, Optional
from openrouter.components import ChatToolMessageContentTypedDict, ChatFunctionToolFunctionTypedDict
from openai.types.chat import ChatCompletionFunctionToolParam
class Tool(ABC):
@ -26,7 +26,7 @@ class Tool(ABC):
"""Описание параметров функции"""
pass
def to_dict(self) -> ChatFunctionToolFunctionTypedDict:
def to_dict(self) -> ChatCompletionFunctionToolParam:
"""JSON-представление инструмента для OpenRouter"""
return {
"type": "function",
@ -38,7 +38,7 @@ class Tool(ABC):
}
@abstractmethod
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> List[ChatToolMessageContentTypedDict]:
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> str:
"""Вызов функции.
:param args: Параметры из JSON
:param artifacts: Словарь для хранения артефактов
@ -61,6 +61,6 @@ class ToolSet:
"""Поиск инструмента по имени"""
return next((t for t in self.functions if t.name == name), None)
def get_all_tools_description(self) -> List[ChatFunctionToolFunctionTypedDict]:
def get_all_tools_description(self) -> List[ChatCompletionFunctionToolParam]:
"""Получить JSON-описание всех инструментов"""
return [tool.to_dict() for tool in self.functions]
return [function.to_dict() for function in self.functions]

23
ai/tools/image_generation/generate_image.py
View file

@ -1,6 +1,5 @@
from typing import Any, Dict, List
from typing import Any, Dict
from openrouter.components import ChatToolMessageContentTypedDict
from replicate import Client as ReplicateClient
from ai.tool import Tool
@ -12,15 +11,15 @@ REPLICATE_MODEL = "bytedance/seedream-4.5"
class GenerateImageTool(Tool):
def __init__(self, replicate_token: str):
self._client = ReplicateClient(api_token=replicate_token)
@property
def name(self) -> str:
return "generate_image"
@property
def description(self) -> str:
return "Генерация изображения по описанию"
@property
def parameters(self) -> Dict[str, Any]:
return {
@ -39,12 +38,12 @@ class GenerateImageTool(Tool):
},
"required": ["prompt"]
}
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> List[ChatToolMessageContentTypedDict]:
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> str:
prompt = args.get("prompt", "")
aspect_ratio = args.get("aspect_ratio", "4:3")
print(f"Генерация изображения {aspect_ratio}: {prompt}")
arguments = {
"prompt": prompt,
"aspect_ratio": aspect_ratio,
@ -55,11 +54,7 @@ class GenerateImageTool(Tool):
outputs: Any = await self._client.async_run(REPLICATE_MODEL, input=arguments)
artifacts["generated_image_hires"] = await outputs[0].aread()
artifacts["generated_image"] = compress_image(artifacts["generated_image_hires"], 1280)
return serialize_message_content(
text="Изображение сгенерировано и будет показано пользователю.",
image=None
)
return "Изображение сгенерировано и будет показано пользователю."
except Exception as e:
print(f"Ошибка генерации изображения: {e}")
return serialize_message_content(text=f"Не удалось сгенерировать изображение: {e}")
return f"Не удалось сгенерировать изображение: {e}"

29
ai/tools/image_generation/generate_image_anime.py
View file

@ -1,26 +1,25 @@
from typing import Any, Dict, List
from typing import Any, Dict
from openrouter.components import ChatToolMessageContentTypedDict
from replicate import Client as ReplicateClient
from ai.tool import Tool
from ai.utils import *
REPLICATE_MODEL = "ultracoderru/nova-anime-xl-17:8f702486aa2852a08564ede8c83a7f58e52c83f6698e7be0e061d79c113dc88b"
REPLICATE_MODEL = "kirirururu/nova-anime-xl-17:8f702486aa2852a08564ede8c83a7f58e52c83f6698e7be0e061d79c113dc88b"
class GenerateImageAnimeTool(Tool):
def __init__(self, replicate_token: str):
self._client = ReplicateClient(api_token=replicate_token)
@property
def name(self) -> str:
return "generate_image_anime"
@property
def description(self) -> str:
return "Генерация изображения в стиле аниме по описанию"
@property
def parameters(self) -> Dict[str, Any]:
return {
@ -42,12 +41,12 @@ class GenerateImageAnimeTool(Tool):
},
"required": ["prompt", "negative_prompt"]
}
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> List[ChatToolMessageContentTypedDict]:
async def execute(self, args: Dict[str, Any], artifacts: Dict[str, Any]) -> str:
prompt = args.get("prompt", "")
negative_prompt = args.get("negative_prompt", "")
aspect_ratio = args.get("aspect_ratio", "4:3")
aspect_ratio_resolution_map = {
"1:1": (1280, 1280),
"4:3": (1280, 1024),
@ -58,7 +57,7 @@ class GenerateImageAnimeTool(Tool):
}
width, height = aspect_ratio_resolution_map.get(aspect_ratio, (1280, 1024))
print(f"Генерация аниме-изображения {width}x{height}:\n+ {prompt}\n- {negative_prompt}")
arguments = {
"prompt": prompt,
"negative_prompt": negative_prompt,
@ -71,16 +70,12 @@ class GenerateImageAnimeTool(Tool):
"hires_num_inference_steps": 30,
"disable_safety_checker": True
}
try:
outputs: Any = await self._client.async_run(REPLICATE_MODEL, input=arguments)
artifacts["generated_image_hires"] = await outputs[0].aread()
artifacts["generated_image"] = compress_image(artifacts["generated_image_hires"], 1280)
return serialize_message_content(
text="Изображение сгенерировано и будет показано пользователю.",
image=None
)
return "Изображение сгенерировано и будет показано пользователю."
except Exception as e:
print(f"Ошибка генерации изображения: {e}")
return serialize_message_content(text=f"Не удалось сгенерировать изображение: {e}")
return f"Не удалось сгенерировать изображение: {e}"

28
ai/tools/web_search/tavily_search.py
View file

@ -1,24 +1,22 @@
from typing import Any, Dict, List
from typing import Any, Dict
from openrouter.components import ChatToolMessageContentTypedDict
from tavily import TavilyClient
from ai.tool import Tool
from ai.utils import *
class TavilySearchTool(Tool):
def __init__(self, tavily_token: str):
self._client = TavilyClient(api_key=tavily_token)
@property
def name(self) -> str:
return "tavily_search"
@property
def description(self) -> str:
return "Поиск информации в интернете"
@property
def parameters(self) -> Dict[str, Any]:
return {
@ -31,26 +29,26 @@ class TavilySearchTool(Tool):
},
"required": ["query"]
}
async def execute(self, args: Dict[str, Any], _artifacts: Dict[str, Any]) -> List[ChatToolMessageContentTypedDict]:
async def execute(self, args: Dict[str, Any], _artifacts: Dict[str, Any]) -> str:
query = args.get("query", "")
print(f"Веб-поиск: {query}")
try:
results = self._client.search(query=query, max_results=5)
if not results or "results" not in results:
return serialize_message_content(text="Не удалось получить результаты поиска.")
return "Не удалось получить результаты поиска."
answer_parts = []
for i, result in enumerate(results["results"], 1):
title = result.get("title", "Без названия")
url = result.get("url", "")
content = result.get("content", "")
answer_parts.append(f"{i}. {title}\n {url}\n {content}\n")
answer = "\n".join(answer_parts)
return serialize_message_content(text=f"По запросу \"{query}\" найдено:\n\n{answer}")
return f"По запросу \"{query}\" найдено:\n\n{answer}"
except Exception as e:
print(f"Ошибка веб-поиска: {e}")
return serialize_message_content(text=f"Не удалось выполнить веб-поиск: {e}")
return f"Не удалось выполнить веб-поиск: {e}"

12
ai/utils.py
View file

@ -1,16 +1,7 @@
from base64 import b64encode
from io import BytesIO
from PIL import Image
from typing import Dict, List, Optional
def serialize_message_content(text: Optional[str], image: Optional[bytes] = None) -> List[Dict]:
content = []
if text is not None:
content.append({"type": "text", "text": text})
if image is not None:
content.append({"type": "image_url", "detail": "high", "image_url": {"url": encode_image(image)}})
return content
from typing import Optional
def encode_image(image: bytes) -> str:
@ -33,7 +24,6 @@ def compress_image(image: bytes, max_side: Optional[int] = None) -> bytes:
__all__ = [
"serialize_message_content",
"compress_image",
"encode_image"
]

25
database.py
View file

@ -1,3 +1,4 @@
import json
from datetime import datetime
from typing import Dict, List, Optional, Any, Type
@ -161,11 +162,12 @@ class BasicDatabase:
with self.pool.acquire() as conn:
with conn.cursor() as cursor:
cursor.execute("""
SELECT role, text, image FROM contexts
SELECT message FROM contexts
WHERE bot_id = ? AND chat_id = ?
ORDER BY id
""", (bot_id, chat_id))
return cursor.fetchall()
""", (bot_id, chat_id))
result = cursor.fetchall()
return [json.loads(_to_val(str, item)) for item in result]
def context_get_count(self, bot_id: int, chat_id: int) -> int:
with self.pool.acquire() as conn:
@ -185,17 +187,14 @@ class BasicDatabase:
return _to_val(int, cursor.fetchone())
def context_add_message(self, bot_id: int, chat_id: int, role: str,
text: Optional[str], image: Optional[bytes],
message_id: Optional[int], max_messages: int):
assert (text or image)
message: Dict, message_id: Optional[int], max_messages: int):
self._context_trim(bot_id, chat_id, max_messages)
# Подготовка данных для вставки
data = {
"bot_id": bot_id, "chat_id": chat_id,
"message_id": message_id, "role": role,
"text": text, "image": image
"message": json.dumps(message, ensure_ascii=False)
}
# Формирование SQL-запроса и параметров вставки
@ -211,9 +210,13 @@ class BasicDatabase:
def context_set_last_message_id(self, bot_id: int, chat_id: int, message_id: int):
with self.pool.acquire() as conn:
with conn.cursor() as cursor:
cursor.execute(
"UPDATE contexts SET message_id = ? WHERE bot_id = ? AND chat_id = ? AND message_id IS NULL",
(message_id, bot_id, chat_id))
cursor.execute("""
UPDATE contexts
SET message_id = %s
WHERE bot_id = %s AND chat_id = %s AND message_id IS NULL
ORDER BY id DESC
LIMIT 1
""", (message_id, bot_id, chat_id))
def _context_trim(self, bot_id: int, chat_id: int, max_messages: int):
current_count = self.context_get_count(bot_id, chat_id)

2
requirements.txt
View file

@ -3,7 +3,7 @@ aiohttp~=3.13.5
vkbottle~=4.8.2
vkbottle-types~=5.199.99.20
mariadb[pool]~=2.0.0rc2
openrouter==0.9.1
openai~=2.41.1
replicate~=1.0.7
tavily~=1.1.0
pillow~=12.2.0

2
tg/__main__.py
View file

@ -24,7 +24,7 @@ async def main() -> None:
database.create_database(config['db_hostname'], config['db_user'], config['db_password'], config['db_database'])
create_ai_agent(config['openrouter_token'], config['openrouter_model'],
create_ai_agent(config.get('openai_url', None), config['openai_token'], config['openai_model'],
config['replicate_token'], config['tavily_token'],
database.DB, 'tg')

3
tg/tg_database.py
View file

@ -53,8 +53,7 @@ class TgDatabase(database.BasicDatabase):
chat_id BIGINT NOT NULL,
message_id BIGINT,
role VARCHAR(16) NOT NULL,
text VARCHAR(4000),
image MEDIUMBLOB,
message MEDIUMTEXT NOT NULL,
PRIMARY KEY (id),
CONSTRAINT fk_contexts_chats FOREIGN KEY (bot_id, chat_id) REFERENCES chats (bot_id, chat_id)
ON UPDATE CASCADE ON DELETE CASCADE

2
vk/__main__.py
View file

@ -24,7 +24,7 @@ if __name__ == '__main__':
database.create_database(config['db_hostname'], config['db_user'], config['db_password'], config['db_database'])
create_ai_agent(config['openrouter_token'], config['openrouter_model'],
create_ai_agent(config.get('openai_url', None), config['openai_token'], config['openai_model'],
config['replicate_token'], config['tavily_token'],
database.DB, 'vk')

3
vk/vk_database.py
View file

@ -56,8 +56,7 @@ class VkDatabase(database.BasicDatabase):
chat_id BIGINT NOT NULL,
message_id BIGINT,
role VARCHAR(16) NOT NULL,
text VARCHAR(4000),
image MEDIUMBLOB,
message MEDIUMTEXT NOT NULL,
PRIMARY KEY (id),
CONSTRAINT fk_contexts_chats FOREIGN KEY (bot_id, chat_id) REFERENCES chats (bot_id, chat_id)
ON UPDATE CASCADE ON DELETE CASCADE