Project manifest. Part of Catalyst Ecosystem:
- Alchemy - Experiments logging & visualization
- Catalyst - Accelerated Deep Learning Research and Development
- Reaction - Convenient Deep Learning models serving
Common installation:
pip install -U reaction
consumer.py:
import asyncio
from typing import List, Any
from reaction.rpc import RabbitRPC
class rpc(RabbitRPC):
URL = "amqp://user:password@host"
@rpc()
def sync_square(*values) -> List[float]:
return [v ** 2 for v in values]
@rpc()
async def async_square(*values) -> List[float]:
await asyncio.sleep(1)
return [v ** 2 for v in values]
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.create_task(sync_square.consume())
loop.create_task(async_square.consume())
loop.run_forever()
client.py:
import asyncio
from consumer import sync_square, async_square
if __name__ == "__main__":
loop = asyncio.get_event_loop()
x = loop.run_until_complete(sync_square.call(2, 3))
y = loop.run_until_complete(async_square.call(4, 5, 6))
print(x) # 4, 9
print(y) # 16, 25, 36
loop.close()
- Register telegram bot, achieve token
cd example && TG_TOKEN="telegram bot token goes here" docker-compose up --force-recreate --build
- RabbitMQ web ui: http://127.0.0.1:15672/#/
- user: admin
- password: j8XfG9ZDT5ZZrWTzw62q
- Docs (you can submit requests from web ui): http://127.0.0.1:8000/docs#/
- Redoc: http://127.0.0.1:8000/redoc
- Telegram bot is ready to classify ants & bees, you have to send files "as a photo" or "as a file"
Install async telegram client first:
$ pip install aiotg
Then create your bot:
tgbot.py
from consumer import async_square
from aiotg import Bot, Chat
bot = Bot(api_token="telegram bot token goes here")
@bot.command("/start")
async def start(chat: Chat, match):
return chat.reply("Send me /square command with one float argument")
@bot.command(r"/square (.+)")
async def square_command(chat: Chat, match):
val = match.group(1)
try:
val = float(val)
square = await async_square.call(val)
resp = f"Square for {val} is {square}"
except:
resp = "Invalid number"
return chat.reply(resp)
bot.run()