parent
ca7aaaf850
commit
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@ -1,25 +1,82 @@
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#
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# LLM Worker #1
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# REQUEST --> RESPONSE
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#
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import asyncio
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from AgenticInterfaces.KafkaClient import KafkaClient
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import json
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from aiokafka import AIOKafkaConsumer, AIOKafkaProducer
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from datetime import datetime
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "NousResearch/Meta-Llama-3.1-8B"
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request_topic = "request_llm_topic"
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response_topic = "response_llm_topic"
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bootstrap_servers = "kafka:9092"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float32, # Использование float32 для CPU
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device_map=None # Явное указание, что модель не будет использовать GPU
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)
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def modify_text(text):
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return text[::-1]
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model.to("cpu")
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async def process_message(message):
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modified_text = modify_text(message["text"])
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response_message = {"text": modified_text}
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await kafka_client.send_message(response_message)
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inputs = tokenizer(message['text'], return_tensors="pt").to("cpu")
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=50, # Максимальное количество генерируемых токенов
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do_sample=True, # Включение сэмплирования
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top_p=0.95, # Параметр nucleus sampling
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top_k=50 # Параметр top-k sampling
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)
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generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
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processed_message = {
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"answer": generated_text,
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"track_uuid": message["track_uuid"],
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"processed_timestamp": datetime.utcnow().isoformat()
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}
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return processed_message
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async def start_consumer_producer():
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consumer = AIOKafkaConsumer(
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'request_llm_topic',
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bootstrap_servers='kafka:9092',
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group_id="processing_group"
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)
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producer = AIOKafkaProducer(bootstrap_servers='kafka:9092')
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await consumer.start()
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await producer.start()
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async def main():
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global kafka_client
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kafka_client = KafkaClient(topic=request_topic, bootstrap_servers=bootstrap_servers, group_id="my-group")
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await kafka_client.start()
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try:
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await kafka_client.consume_messages(process_message)
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async for msg in consumer:
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message = json.loads(msg.value.decode('utf-8'))
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# Обработка сообщения
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processed_message = await process_message(message)
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# Сериализация обработанного сообщения
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processed_message_json = json.dumps(processed_message).encode('utf-8')
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# Отправка обработанного сообщения в новый топик response_llm_topic
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await producer.send_and_wait("response_llm_topic", processed_message_json)
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print(f"Processed and sent message with UUID: {processed_message['track_uuid']}")
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finally:
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await kafka_client.stop()
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await consumer.stop()
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await producer.stop()
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async def main():
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await start_consumer_producer()
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asyncio.run(main())
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if __name__ == "__main__":
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asyncio.run(main())
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@ -1 +1,6 @@
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fastapi
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uvicorn
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aiokafka
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websockets
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torch
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transformers
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@ -0,0 +1,8 @@
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// const ws = new WebSocket("ws://localhost:7781/ws");
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const ws = new WebSocket("ws://192.168.0.100:7781/ws");
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ws.onmessage = function(event) {
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const messages = document.getElementById('messages');
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const message = document.createElement('div');
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message.textContent = event.data;
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messages.appendChild(message);
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};
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@ -0,0 +1,101 @@
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#
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# SHOW RESPONSE
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#
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import asyncio
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import json
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import random
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from fastapi import FastAPI, WebSocket, WebSocketDisconnect
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from fastapi.responses import HTMLResponse
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from aiokafka import AIOKafkaConsumer
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from fastapi.staticfiles import StaticFiles
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app = FastAPI()
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app.mount("/static", StaticFiles(directory="static"), name="static")
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class ConnectionManager:
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def __init__(self):
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self.active_connections: list[WebSocket] = []
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async def connect(self, websocket: WebSocket):
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await websocket.accept()
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self.active_connections.append(websocket)
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def disconnect(self, websocket: WebSocket):
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if websocket in self.active_connections:
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self.active_connections.remove(websocket)
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async def send_message(self, message: str):
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for connection in self.active_connections:
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try:
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await connection.send_text(message)
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except WebSocketDisconnect:
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self.disconnect(connection)
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manager = ConnectionManager()
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# HTML для тестирования WebSocket
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html = """
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<!DOCTYPE html>
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<html>
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<head>
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<title>WebSocket Test</title>
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</head>
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<body>
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<h1>WebSocket Test</h1>
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<div id="messages"></div>
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<script src="/static/websocket.js"></script>
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</body>
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</html>
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"""
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@app.get("/")
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async def get():
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return HTMLResponse(html)
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@app.websocket("/ws")
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async def websocket_endpoint(websocket: WebSocket):
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await manager.connect(websocket)
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try:
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while True:
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await asyncio.sleep(1) # Задержка для поддержания соединения
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except WebSocketDisconnect:
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manager.disconnect(websocket)
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async def consume_kafka_and_forward():
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consumer = AIOKafkaConsumer(
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'response_llm_topic',
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bootstrap_servers='kafka:9092',
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group_id="websocket_group"
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)
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await consumer.start()
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try:
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async for message in consumer:
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message_value = json.loads(message.value.decode('utf-8'))
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answer = message_value["answer"]
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json_message = {"answer": answer}
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# Сериализация данных в JSON
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message_json = json.dumps(json_message).encode('utf-8')
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# Отправляем сообщение ws
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await manager.send_message(message_json.decode('utf-8'))
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finally:
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await consumer.stop()
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@app.on_event("startup")
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async def startup_event():
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asyncio.create_task(consume_kafka_and_forward())
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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@ -0,0 +1,63 @@
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#
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# SEND REQUEST
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#
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import asyncio
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import uuid
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import json
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import random
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import base64
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from aiokafka import AIOKafkaProducer
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from datetime import datetime
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producer = None
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async def init_kafka_producer():
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global producer
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if producer is None:
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producer = AIOKafkaProducer(bootstrap_servers='kafka:9092', max_request_size=10485760)
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for _ in range(5):
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try:
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print(f"Producing message {_}")
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await producer.start()
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break
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except Exception as e:
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print(f"Kafka connection error, retrying in 5 seconds: {e}")
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await asyncio.sleep(5)
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async def stop_kafka_producer():
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global producer
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if producer is not None:
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await producer.stop()
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producer = None
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async def send_random_data():
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try:
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timestamp = datetime.utcnow().isoformat()
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frame_uuid = str(uuid.uuid4())
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MESSAGE = "Hello World!"
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message = {
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"text": MESSAGE,
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"track_uuid": frame_uuid,
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"timestamp": timestamp,
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}
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message_json = json.dumps(message).encode('utf-8')
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await producer.send_and_wait("request_llm_topic", message_json)
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print(f"Sent message with UUID: {frame_uuid}")
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except Exception as e:
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print(f"Error sending message to Kafka: {e}")
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async def main():
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await init_kafka_producer()
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try:
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while True:
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await send_random_data()
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await asyncio.sleep(1)
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finally:
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await stop_kafka_producer()
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asyncio.run(main())
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@ -1,19 +0,0 @@
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import asyncio
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from AgenticInterfaces.KafkaClient import KafkaClient
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bootstrap_servers = "kafka:9092"
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request_topic = "request_llm_topic"
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async def send_periodic_messages():
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kafka_client = KafkaClient(topic=request_topic, bootstrap_servers=bootstrap_servers)
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await kafka_client.start()
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try:
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while True:
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message = {"text": "Пример сообщения"}
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await kafka_client.send_message(message)
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await asyncio.sleep(5)
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finally:
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await kafka_client.stop()
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asyncio.run(send_periodic_messages())
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@ -1,19 +0,0 @@
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import asyncio
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from AgenticInterfaces.KafkaClient import KafkaClient
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bootstrap_servers = "kafka:9092"
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response_topic = "response_llm_topic"
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async def print_received_messages(message):
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print("Получено сообщение:", message["text"])
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async def receive_messages():
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kafka_client = KafkaClient(topic=response_topic, bootstrap_servers=bootstrap_servers, group_id="response-group")
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await kafka_client.start()
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try:
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await kafka_client.consume_messages(print_received_messages)
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finally:
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await kafka_client.stop()
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asyncio.run(receive_messages())
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Reference in new issue