docker chatgpt-mqttapi代码

作为AI语言模型，我无法提供实际的代码。但是，以下是编写ChatGPT-MQTT API的一般步骤：

1. 安装Docker和MQTT broker
2. 创建Docker镜像并将ChatGPT模型添加到镜像中
3. 编写Python代码，使用paho-mqtt库与MQTT broker进行通信
4. 在代码中解析接收到的消息，使用ChatGPT模型生成回应
5. 将回应发送回MQTT broker

以下是可能的Python代码示例：

import paho.mqtt.client as mqtt
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load ChatGPT model and tokenizer
model_name = "microsoft/DialoGPT-large"
model = AutoModelForCausalLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Define MQTT client and connect to broker
client = mqtt.Client()
client.connect("localhost", 1883, 60)

# Define MQTT topics
request_topic = "chat/request"
response_topic = "chat/response"

# Define callback for receiving messages
def on_message(client, userdata, message):
    # Decode message payload
    input_text = message.payload.decode()

    # Generate response using ChatGPT model
    input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors="pt")
    response_ids = model.generate(input_ids, max_length=50, pad_token_id=tokenizer.eos_token_id)
    response_text = tokenizer.decode(response_ids.squeeze(), skip_special_tokens=True)

    # Publish response to MQTT broker
    client.publish(response_topic, response_text)

# Subscribe to request topic and start MQTT client loop
client.subscribe(request_topic)
client.on_message = on_message
client.loop_forever()