阅丞集团API服务接口

import requests import json API_URL = "https://ycceo.com/API/endpoint.php" API_KEY = "您的API密钥" headers = { "Content-Type": "application/json", "Authorization": f"Bearer {API_KEY}" } # 构建对话历史 messages = [ { "role": "system", "content": "你是一个有用的AI助手，请用Markdown格式回复用户的问题。" }, { "role": "user", "content": "你好，请介绍一下Python编程语言的主要特点" }, { "role": "assistant", "content": "# Python主要特点\n\n1. **简单易学**\n - 语法清晰简洁\n - 适合初学者入门\n\n2. **面向对象**\n - 支持面向对象编程\n - 类和对象的概念清晰\n\n3. **丰富的库**\n - 拥有庞大的第三方库生态系统\n - 涵盖Web开发、数据分析、人工智能等领域" }, { "role": "user", "content": "那Python在数据科学方面有什么优势？" } ] data = { "messages": messages, "model": "YueCheng-Lite", "stream": False } try: response = requests.post(API_URL, headers=headers, json=data, timeout=30) print(f"状态码: {response.status_code}") result = response.json() if result.get('success'): print("AI回复 (Markdown格式):") print(result.get('answer')) # 完整的对话历史（包含新的回复） print("\n完整对话历史:") for msg in result.get('messages', []): print(f"{msg['role']}: {msg['content'][:100]}...") else: print(f"错误: {result.get('error')}") except Exception as e: print(f"请求失败: {e}") 复制代码

{ "success": true, "answer": "## Python在数据科学的优势\n\nPython在数据科学领域具有以下主要优势：\n\n### 1. 强大的数据处理库\n- **Pandas**: 数据清洗和分析\n- **NumPy**: 数值计算\n- **SciPy**: 科学计算\n\n### 2. 机器学习和深度学习\n- **Scikit-learn**: 传统机器学习\n- **TensorFlow/PyTorch**: 深度学习框架\n\n### 3. 数据可视化\n- **Matplotlib**: 基础绘图\n- **Seaborn**: 统计可视化\n- **Plotly**: 交互式图表", "model": "YueCheng-Lite", "messages": [ {"role": "system", "content": "你是一个有用的AI助手，请用Markdown格式回复用户的问题。"}, {"role": "user", "content": "你好，请介绍一下Python编程语言的主要特点"}, {"role": "assistant", "content": "# Python主要特点\n\n1. **简单易学**\n - 语法清晰简洁\n - 适合初学者入门\n\n2. **面向对象**\n - 支持面向对象编程\n - 类和对象的概念清晰\n\n3. **丰富的库**\n - 拥有庞大的第三方库生态系统\n - 涵盖Web开发、数据分析、人工智能等领域"}, {"role": "user", "content": "那Python在数据科学方面有什么优势？"}, {"role": "assistant", "content": "## Python在数据科学的优势\n\nPython在数据科学领域具有以下主要优势：\n\n### 1. 强大的数据处理库\n- **Pandas**: 数据清洗和分析\n- **NumPy**: 数值计算\n- **SciPy**: 科学计算\n\n### 2. 机器学习和深度学习\n- **Scikit-learn**: 传统机器学习\n- **TensorFlow/PyTorch**: 深度学习框架\n\n### 3. 数据可视化\n- **Matplotlib**: 基础绘图\n- **Seaborn**: 统计可视化\n- **Plotly**: 交互式图表"} ] } 复制代码

import requests import json API_URL = "https://ycceo.com/API/endpoint.php" API_KEY = "您的API密钥" headers = { "Content-Type": "application/json", "Authorization": f"Bearer {API_KEY}" } data = { "model": "YueCheng-Lite", "prompt": "请用Markdown格式写一篇关于人工智能的短文，包含标题、段落和列表", "stream": True } try: response = requests.post( API_URL, headers=headers, json=data, stream=True, timeout=60 ) print("流式响应开始 (Markdown格式):") full_response = "" for line in response.iter_lines(): if line: decoded_line = line.decode('utf-8') if decoded_line.startswith('data: '): data_str = decoded_line[6:] # 移除 "data: " 前缀 if data_str.strip() == '[DONE]': print("\n\n流式响应结束") break try: data_obj = json.loads(data_str) if 'choices' in data_obj and len(data_obj['choices']) > 0: delta = data_obj['choices'][0].get('delta', {}) if 'content' in delta: content = delta['content'] print(content, end='', flush=True) full_response += content except json.JSONDecodeError: continue print(f"\n\n完整响应内容:\n{full_response}") except Exception as e: print(f"流式请求失败: {e}") 复制代码

data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"#"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":" 人"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"工"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"智"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"能"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"的"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"未"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{"content":"来"},"finish_reason":null}]} data: {"id":"chatcmpl-xxx","object":"chat.completion.chunk","created":1700000000,"model":"deepseek-v4-flash","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]} data: [DONE] 复制代码