Python使用Flask结合DeepSeek开发

news2025/3/29 3:48:02

一、背景

我之前关于DeepSeek使用ollama部署的文章大家可以把DeepSeek大模型部署起来。那么ollama还提供了可以调用对应部署模型的API接口。我们可以基于这些接口，做自己的二次开发。使用python+flask+ollama就可以进行模型对话调用。并且前端采用SSE的技术，后端向前端推送推理结果进行展示，可以实现属于自己的大模型对话产品。

二、代码实现

1、ollama运行deepseek-r1:1.5b模型

docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

docker exec -it ollama ollama run deepseek-r1:1.5b

2、python+flask代码

import json

from flask import Flask, request, Response
from ollama import Client

app = Flask(__name__)

# ollama客户端
ollma_url = "http://localhost:11434"   # localhost可以换成你部署ollama主机的ip、远程ip
ollama_client = Client(host=ollma_url )
# 模型名称
model_name = "deepseek-r1:1.5b"


@app.route('/stream', methods=['POST', 'GET'])
def post_example():
    def generate():
        try:
            # 调用ollama客户端，传入模型名称、提问信息
            response_generator = ollama_client.generate(model_name, prompt=question, stream=True)
            for part in response_generator:
                response_text = part.response
                # 按照 SSE 规范格式化数据
                data = f"data: {json.dumps({'response': response_text})}\n\n"
                print(data)
                yield data
        except Exception as e:
            error_data = f"data: {json.dumps({'error': str(e)})}\n\n"
            yield error_data
    # 接收问题, 调用模型, 使用SSE推送推理结果给前端
    question = request.args.get('question')
    resp = Response(generate(), mimetype='text/event-stream')
    # 设置响应头
    resp.headers['Cache-Control'] = 'no-cache'
    resp.headers['Connection'] = 'keep-alive'
    resp.headers['Access-Control-Allow-Origin'] = '*'

    return resp


if __name__ == '__main__':
    app.run(debug=True, port=8080)

3、前端代码

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Ask Ollama via SSE</title>
</head>

<body>
    <input type="text" id="questionInput" placeholder="请输入你的问题">
    <button id="askButton">提问</button>
    <pre id="answerContainer"></p>

    <script>
        const questionInput = document.getElementById('questionInput');
        const askButton = document.getElementById('askButton');
        const answerContainer = document.getElementById('answerContainer');

        askButton.addEventListener('click', async () => {
            const question = questionInput.value;
            if (!question) {
                alert('请输入问题');
                return;
            }

            const eventSource = new EventSource(`http://localhost:8080/stream?question=${encodeURIComponent(question)}`);

            eventSource.onmessage = function (event) {
                const data = JSON.parse(event.data);
                const response = data.response;
                if (response) {
                    const p = document.createElement('span');
                    p.textContent = response;
                    answerContainer.appendChild(p);
                }
            };

            eventSource.onerror = function (error) {
                console.error('EventSource failed:', error);
                eventSource.close();
            };
        });
    </script>
</body>

</html>