# srai-chat
A chat library frontend for srai services.
## installation
```
pip install srai-chat
```
## environment
requires the following environment variables set \
```
"TELEGRAM_ROOT_ID": ""
"TELEGRAM_TOKEN": ""
"OPENAI_API_KEY": ""
"MONGODB_CONNECTION_STRING": "
"MONGODB_DATABASE_NAME": ""
```
## usage example
```
import os
from srai_chat.skill.mode_chat_gpt import ModeChatGpt
from srai_chat.skill.skill_image_tag import SkillImageTag
from srai_chat.skill.skill_mode_tools import SkillModeTools
def initialize_default() -> "ContextManager":
context = ContextManager()
ContextManager._instance = context
telegram_token = os.environ["TELEGRAM_TOKEN"]
telegram_root_id = int(os.environ["TELEGRAM_ROOT_ID"])
openai_api_key = os.environ["OPENAI_API_KEY"]
connection_string = os.environ["MONGODB_CONNECTION_STRING"]
database_name = os.environ["MONGODB_DATABASE_NAME"]
from srai_chat.service.service_chat_telegram import ServiceChatTelegram
from srai_chat.service.service_openai_chat_gpt import ServiceOpenaiChatGpt
from srai_chat.service.service_persistency_mongo import ServicePersistencyMongo
from srai_chat.service.service_sceduling import ServiceSceduling
context.service_chat = ServiceChatTelegram(context, telegram_token, telegram_root_id)
context.service_persistency = ServicePersistencyMongo(context, connection_string, database_name)
context.service_openai_chat_gpt = ServiceOpenaiChatGpt(context, openai_api_key)
context.service_sceduling = ServiceSceduling(context)
return context
if __name__ == "__main__":
from srai_chat.service.context_manager import ContextManager
context_manager = initialize_default()
# initialize services
# ServiceSceduling.initialize(bot)
context_manager.initialize()
context_manager.service_chat.register_skill(SkillImageTag())
context_manager.service_chat.register_skill(SkillModeTools())
context_manager.service_chat.register_mode(ModeChatGpt())
context_manager.service_chat.mode_default = context_manager.service_chat.dict_mode["ModeChatGpt"]
# start services
context_manager.start()
```
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