百度大模型开源
本地启动手册
安装依赖：
python -m pip install paddlepaddle-gpu==3.1.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/python -m pip install fastdeploy-gpu -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-gpu-80_90/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simpleapt install libgomp1
启动 API
python -m fastdeploy.entrypoints.openai.api_server \--model baidu/ERNIE-4.5-0.3B-Paddle \--port 8180 \--metrics-port 8181 \--engine-worker-queue-port 8182 \--max-model-len 32768 \--max-num-seqs 32
大概等待10分钟左右
测试 Python 代码
import requests
import jsonurl = "http://127.0.0.1:8180/v1/chat/completions"
headers = {"Content-Type": "application/json"}data = {"model": "baidu/ERNIE-4.5-0.3B-PT","messages": [{"role": "user", "content": "我是仕宇2050，你帮我写一个Python函数判断字符串是否为回文串"}],"temperature": 0.7
}response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json()["choices"][0]["message"]["content"])
模型开源地址：https://ai.gitcode.com/theme/1939325484087291906
视频演示： 全网同名 #JavaPub #仕宇2050
循环对话的python代码
import requests
import jsondef chat():url = "http://127.0.0.1:8180/v1/chat/completions"headers = {"Content-Type": "application/json"}model = "baidu/ERNIE-4.5-0.3B-PT"# 保存对话历史messages = []print("开始对话吧！（输入 'exit' 或 'quit' 退出）")while True:user_input = input("\n你：")if user_input.lower() in {"exit", "quit"}:print("结束对话。")break# 添加用户消息到对话历史messages.append({"role": "user", "content": user_input})# 构建请求体data = {"model": model,"messages": messages}try:response = requests.post(url, headers=headers, data=json.dumps(data))response.raise_for_status()result = response.json()if "choices" in result and len(result["choices"]) > 0:ai_message = result["choices"][0]["message"]["content"]print("AI：", ai_message)# 将AI的回复加入对话历史messages.append({"role": "assistant", "content": ai_message})else:print("AI 没有返回内容。")except requests.exceptions.RequestException as e:print(f"请求错误: {e}")except json.JSONDecodeError:print(f"JSON解析错误，响应内容: {response.text}")except Exception as e:print(f"发生错误: {e}")if __name__ == "__main__":chat()
