使用 Flask 框架添加多个AI模型的API进行对话
1. 概述
该应用是一个基于 Flask 框架的 AI 模型 API 管理系统，允许用户添加、删除不同 AI 模型（如 DeepSeek、阿里云、智谱、百度、科大讯飞等）的 API 密钥，并通过这些配置好的 API 与相应的 AI 模型进行交互，获取回复。应用包含后端的 Flask 服务和前端的 HTML 页面及 JavaScript 脚本。
2. 后端代码说明
2.1 依赖库导入
python
from flask import Flask, request, render_template, jsonify
import requests
Flask：用于构建 Web 应用的轻量级框架。request：用于处理 HTTP 请求，获取请求中的数据。render_template：用于渲染 HTML 模板。jsonify：用于将 Python 对象转换为 JSON 格式并作为 HTTP 响应返回。requests：用于发送 HTTP 请求，与外部 API 进行交互。
2.2 应用初始化
python
app = Flask(__name__)
创建一个 Flask 应用实例，__name__参数用于指定应用的名称。
2.3 API 存储字典
python
# 存储用户配置的API
apis = {
"deepseek": None,
"aliyun": None,
"zhipu": None,
"baidu": None,
"iflytek": None
}
定义一个字典apis，用于存储不同 AI 模型的 API 密钥，初始值均为None。
2.4 路由函数
- 首页路由：
python
@app.route('/')
def index():
return render_template('index.html', apis=apis)
- 当用户访问根路径时，渲染
index.html模板，并将apis字典传递给模板，以便在页面上显示和操作。
- 添加 API 路由：
python
@app.route('/add_api', methods=['POST'])
def add_api():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
api_key = data.get('api_key')
if not model or not api_key:
return jsonify({"status": "error", "message": "Missing required parameters"}), 400
if model in apis:
apis[model] = api_key
return jsonify({"status": "success", "message": f"{model} API added successfully!"})
else:
return jsonify({"status": "error", "message": "Invalid model specified."}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
- 处理
POST请求，从请求中获取 JSON 数据，提取model和api_key。 - 检查数据的完整性，若缺少必要参数或模型不合法，则返回相应的错误信息。
- 若模型存在于
apis字典中，则将对应的 API 密钥存入字典，并返回成功消息；否则返回错误消息。 - 若发生异常，返回异常信息和 500 状态码。
- 删除 API 路由：
python
@app.route('/remove_api', methods=['POST'])
def remove_api():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
if not model:
return jsonify({"status": "error", "message": "Missing model parameter"}), 400
if model in apis:
apis[model] = None
return jsonify({"status": "success", "message": f"{model} API removed successfully!"})
else:
return jsonify({"status": "error", "message": "Invalid model specified."}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
- 处理
POST请求，从请求中获取 JSON 数据，提取model。 - 检查数据的完整性，若缺少模型参数或模型不合法，则返回相应的错误信息。
- 若模型存在于
apis字典中，则将其 API 密钥设置为None，并返回成功消息；否则返回错误消息。 - 若发生异常，返回异常信息和 500 状态码。
- 获取响应路由：
python
@app.route('/get_response', methods=['POST'])
def get_response():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
prompt = data.get('prompt')
if not model or not prompt:
return jsonify({"status": "error", "message": "Missing required parameters"}), 400
if model in apis and apis[model]:
try:
# 这里根据不同的模型调用相应的API
if model == "deepseek":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "deepseek-chat",
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.7
}
response = requests.post(
"https://api.deepseek.com/v1/chat/completions",
headers=headers,
json=payload
)
elif model == "aliyun":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "bailian",
"input": {
"messages": [{"role": "user", "content": prompt}]
}
}
response = requests.post(
"https://bailian.aliyuncs.com/v2/app/completions",
headers=headers,
json=payload
)
elif model == "zhipu":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "chatglm_turbo",
"messages": [{"role": "user", "content": prompt}]
}
response = requests.post(
"https://open.bigmodel.cn/api/paas/v3/model-api/chatglm_turbo/invoke",
headers=headers,
json=payload
)
elif model == "baidu":
headers = {
"Content-Type": "application/json",
"Accept": "application/json"
}
payload = {
"messages": [{"role": "user", "content": prompt}]
}
response = requests.post(
f"https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions?access_token={apis[model]}",
headers=headers,
json=payload
)
elif model == "iflytek":
headers = {
"Content-Type": "application/json",
"X-Appid": "your_app_id", # 需要替换为实际AppID
"X-CurTime": str(int(time.time())),
"X-Param": json.dumps({"scene": "main"}),
"X-CheckSum": "" # 需要计算校验和
}
payload = {
"text": prompt
}
response = requests.post(
"https://api.xfyun.cn/v1/aiui/v1/text",
headers=headers,
json=payload
)
if response.status_code == 200:
response_data = response.json()
# 根据不同API的响应格式提取回复
if model == "deepseek":
reply = response_data['choices'][0]['message']['content']
elif model == "aliyun":
reply = response_data['output']['text']
elif model == "zhipu":
reply = response_data['data']['choices'][0]['content']
elif model == "baidu":
reply = response_data['result']
elif model == "iflytek":
reply = response_data['data'][0]['content']
return jsonify({
"status": "success",
"response": reply,
"model": model
})
else:
return jsonify({
"status": "error",
"message": f"API call failed with status code {response.status_code}",
"response_text": response.text,
"request_payload": payload # 添加请求负载用于调试
}), response.status_code
except requests.exceptions.RequestException as e:
return jsonify({
"status": "error",
"message": f"Network error: {str(e)}"
}), 500
except Exception as e:
return jsonify({
"status": "error",
"message": str(e),
"error_type": type(e).__name__
}), 500
else:
return jsonify({
"status": "error",
"message": "API not configured or invalid model."
}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
- 处理
POST请求，从请求中获取 JSON 数据，提取model和prompt。 - 检查数据的完整性，若缺少必要参数或模型未配置 API 密钥，则返回相应的错误信息。
- 根据不同的模型，构造相应的请求头和请求负载，发送
POST请求到对应的 API 端点。 - 若 API 调用成功（状态码为 200），根据不同模型的响应格式提取回复内容，并返回成功消息；否则返回错误消息，包括状态码、响应文本和请求负载（用于调试）。
- 若发生网络错误或其他异常，返回相应的错误信息和状态码。
2.5 应用运行
python
if __name__ == '__main__':
app.run(debug=True)
当脚本直接运行时，启动 Flask 应用，并设置debug模式为True，以便在开发过程中查看错误信息和自动重新加载应用。
3. 前端代码说明
3.1 HTML 结构
- 头部部分：
html
AI Model API Manager
- 设置页面的字符编码、视口等基本信息。
- 引入 Bootstrap 的 CSS 样式表，用于页面布局和样式。
- 自定义一些 CSS 样式，用于聊天窗口、消息显示、错误消息显示等。
- 主体部分：
html
AI Model API Manager
API Management
Chat with AI
- 页面主体部分使用 Bootstrap 的栅格系统布局。
- 左侧部分用于 API 管理，包含添加 API 和移除 API 的表单，表单中包含模型选择和 API 密钥输入框。
- 右侧部分用于与 AI 聊天，包含聊天窗口和发送请求的表单，表单中包含模型选择和提示输入框。
3.2 JavaScript 脚本
- 添加 API 功能：
javascript
document.getElementById('addApiForm').addEventListener('submit', function(e) {
e.preventDefault();
const model = document.getElementById('addModel').value;
const apiKey = document.getElementById('api_key').value;
fetch('/add_api', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: model,
api_key: apiKey
})
})
.then(response => {
if (!response.ok) {
return response.json().then(err => { throw err; });
}
return response.json();
})
.then(data => {
alert(data.message);
document.getElementById('api_key').value = '';
})
.catch(error => {
alert(`Error: ${error.message || 'Failed to add API'}`);
});
});
- 监听添加 API 表单的提交事件，阻止表单的默认提交行为。
- 获取用户选择的模型和输入的 API 密钥。
- 使用
fetch发送POST请求到/add_api端点，传递模型和 API 密钥的 JSON 数据。 - 处理响应，若响应失败，抛出错误；若成功，显示提示信息并清空 API 密钥输入框；若发生异常，显示错误提示。
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app.py代码
from flask import Flask, request, render_template, jsonify
import requests
app = Flask(__name__)
# 存储用户配置的API
apis = {
"deepseek": None,
"aliyun": None,
"zhipu": None,
"baidu": None,
"iflytek": None
}
@app.route('/')
def index():
return render_template('index.html', apis=apis)
@app.route('/add_api', methods=['POST'])
def add_api():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
api_key = data.get('api_key')
if not model or not api_key:
return jsonify({"status": "error", "message": "Missing required parameters"}), 400
if model in apis:
apis[model] = api_key
return jsonify({"status": "success", "message": f"{model} API added successfully!"})
else:
return jsonify({"status": "error", "message": "Invalid model specified."}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
@app.route('/remove_api', methods=['POST'])
def remove_api():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
if not model:
return jsonify({"status": "error", "message": "Missing model parameter"}), 400
if model in apis:
apis[model] = None
return jsonify({"status": "success", "message": f"{model} API removed successfully!"})
else:
return jsonify({"status": "error", "message": "Invalid model specified."}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
@app.route('/get_response', methods=['POST'])
def get_response():
try:
data = request.get_json()
if not data:
return jsonify({"status": "error", "message": "No data provided"}), 400
model = data.get('model')
prompt = data.get('prompt')
if not model or not prompt:
return jsonify({"status": "error", "message": "Missing required parameters"}), 400
if model in apis and apis[model]:
try:
# 这里根据不同的模型调用相应的API
if model == "deepseek":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "deepseek-chat",
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.7
}
response = requests.post(
"https://api.deepseek.com/v1/chat/completions",
headers=headers,
json=payload
)
elif model == "aliyun":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "bailian",
"input": {
"messages": [{"role": "user", "content": prompt}]
}
}
response = requests.post(
"https://bailian.aliyuncs.com/v2/app/completions",
headers=headers,
json=payload
)
elif model == "zhipu":
headers = {
"Authorization": f"Bearer {apis[model]}",
"Content-Type": "application/json"
}
payload = {
"model": "chatglm_turbo",
"messages": [{"role": "user", "content": prompt}]
}
response = requests.post(
"https://open.bigmodel.cn/api/paas/v3/model-api/chatglm_turbo/invoke",
headers=headers,
json=payload
)
elif model == "baidu":
headers = {
"Content-Type": "application/json",
"Accept": "application/json"
}
payload = {
"messages": [{"role": "user", "content": prompt}]
}
response = requests.post(
f"https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions?access_token={apis[model]}",
headers=headers,
json=payload
)
elif model == "iflytek":
headers = {
"Content-Type": "application/json",
"X-Appid": "your_app_id", # 需要替换为实际AppID
"X-CurTime": str(int(time.time())),
"X-Param": json.dumps({"scene": "main"}),
"X-CheckSum": "" # 需要计算校验和
}
payload = {
"text": prompt
}
response = requests.post(
"https://api.xfyun.cn/v1/aiui/v1/text",
headers=headers,
json=payload
)
if response.status_code == 200:
response_data = response.json()
# 根据不同API的响应格式提取回复
if model == "deepseek":
reply = response_data['choices'][0]['message']['content']
elif model == "aliyun":
reply = response_data['output']['text']
elif model == "zhipu":
reply = response_data['data']['choices'][0]['content']
elif model == "baidu":
reply = response_data['result']
elif model == "iflytek":
reply = response_data['data'][0]['content']
return jsonify({
"status": "success",
"response": reply,
"model": model
})
else:
return jsonify({
"status": "error",
"message": f"API call failed with status code {response.status_code}",
"response_text": response.text,
"request_payload": payload # 添加请求负载用于调试
}), response.status_code
except requests.exceptions.RequestException as e:
return jsonify({
"status": "error",
"message": f"Network error: {str(e)}"
}), 500
except Exception as e:
return jsonify({
"status": "error",
"message": str(e),
"error_type": type(e).__name__
}), 500
else:
return jsonify({
"status": "error",
"message": "API not configured or invalid model."
}), 400
except Exception as e:
return jsonify({"status": "error", "message": str(e)}), 500
if __name__ == '__main__':
app.run(debug=True)index.html代码
AI Model API Manager
AI Model API Manager
API Management
Chat with AI