腾讯云DeepSeek API对接微信小程序完全指南

import os
import logging
from flask import Flask, request, jsonify
from flask_cors import CORS
from openai import OpenAI
from typing import Dict, Any

# 初始化Flask应用
app = Flask(__name__)
CORS(app)  # 启用跨域支持

# 配置日志记录
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# 环境变量配置
OPENAI_CONFIG = {
    "api_key": os.getenv("OPENAI_API_KEY", "sk-pXLyNnk8bdl8zkmFkBIi7KBRiaLTATlmGsr8QfTwek7Zawfk"),
    "base_url": os.getenv("OPENAI_BASE_URL", "https://api.lkeap.cloud.tencent.com/v1")
}

# 初始化OpenAI客户端
client = OpenAI(**OPENAI_CONFIG)


def validate_request(data: Dict[str, Any]) -> tuple:
    """请求参数验证"""
    if not data.get('content'):
        logger.warning("Missing content parameter")
        return False, "Content parameter is required"

    if len(data['content']) > 1000:
        logger.warning("Content length exceeds limit")
        return False, "Content exceeds maximum length of 1000 characters"

    return True, ""


def process_stream_response(stream) -> dict:
    """处理流式响应数据"""
    result = {"reasoning_content": "", "answer_content": ""}

    for chunk in stream:
        if not chunk.choices:
            continue

        delta = chunk.choices[0].delta

        # 使用getattr安全获取属性
        if reasoning := getattr(delta, 'reasoningcontent', None):
            result["reasoning_content"] += reasoning

        if content := getattr(delta, 'content', None):
            result["answer_content"] += content

    return result


@app.route('/deepseekapi', methods=['POST'])
def generate_content():
    """
    处理生成请求
    ---
    parameters:
      - name: body
        in: body
        required: true
        schema:
          type: object
          properties:
            content:
              type: string
    responses:
      200:
        description: 生成结果
      400:
        description: 无效请求
      500:
        description: 服务器错误
    """
    # 请求验证
    data = request.get_json()
    print(data)
    is_valid, message = validate_request(data)
    if not is_valid:
        return jsonify({"error": message}), 400

    try:
        # 创建流式请求
        stream = client.chat.completions.create(
            model="deepseek-r1",
            messages=[{"role": "user", "content": data['content']}],
            stream=True,
            temperature=0.7,  # 添加生成参数
            max_tokens=1000
        )

        # 处理流式响应
        processed_data = process_stream_response(stream)

        # 结果后处理
        processed_data["answer_content"] = processed_data["answer_content"].strip()

        return jsonify(processed_data)

    except Exception as e:
        logger.error(f"API请求失败: {str(e)}", exc_info=True)
        return jsonify({"error": "服务暂时不可用，请稍后再试"}), 500


if __name__ == "__main__":
    app.run(
        host=os.getenv("FLASK_HOST", "0.0.0.0"),
        port=int(os.getenv("FLASK_PORT", 5001)),
        debug=os.getenv("FLASK_DEBUG", "false").lower() == "true"
    )

curl --location --request POST 'http://192.168.31.134:5001/deepseekapi' \
--header 'User-Agent: Apifox/1.0.0 (https://apifox.com)' \
--header 'Content-Type: application/json' \
--header 'Accept: */*' \
--header 'Host: 192.168.31.134:5001' \
--header 'Connection: keep-alive' \
--data-raw '{
   content: "请根据以下内容生成500字小红书种草文案：↵关键词：三亚,海边,游泳,拍照↵"
}'

<template>
    <view class="content">
        <!--   <view class="upload-section">
            <uv-upload
                :fileList="fileList"
                @afterRead="afterRead"
                @delete="deletePic"
                :maxCount="1"
                name="1"
            ></uv-upload>
        </view> -->
        <view class="txtArea">
            <uv-textarea
                v-model="textArea"
                placeholder="请输入关键词,以逗号隔开"
                :height="150"
                :border="'surround'"
                :count="true"
                :maxlength="500"
            ></uv-textarea>
        </view>
        <view class="type-section">
            <uv-radio-group
                v-model="typeValue"
                placement="row"
                @change="handleChangeType"
                :wrap="false"
            >
                <uv-radio
                    v-for="(item, index) in typeOptions"
                    :key="index"
                    :name="item.value"
                    :label="item.text"
                ></uv-radio>
            </uv-radio-group>
        </view>

        <view class="button-section">
            <uv-button
                type="primary"
                text="开始生成"
                @click="startGenerate"
            ></uv-button>
            <uv-button type="info" text="重置" @click="resetForm"></uv-button>
        </view>

        <view class="result-section">
            <uv-loading-icon
                v-if="loading"
                text="文案生成中..."
                mode="circle"
                size="28"
            ></uv-loading-icon>
            <uv-text v-if="resultText" :text="resultText"></uv-text>
        </view>
    </view>
</template>

     startGenerate() {
            // 1. 判断用户是否上传图片或输入关键词
            if (!this.textArea) {
                uni.showToast({
                    title: "请输入关键词",
                    icon: "none",
                });
                return;
            }

            // 2. 配置prompt提示词
            let prompt = `请根据以下内容生成500字${this.typeText}文案：\n`;

            // 添加关键词内容
            if (this.textArea) {
                prompt += `关键词：${this.textArea}\n`;
            }

            // 添加图片信息
            // if (this.fileList.length > 0) {
            //     prompt += `${this.fileList[0].url}\n`;
            // }

            // 3. 设置加载状态
            this.loading = true;

            // 4. 接口调用
            request({
                url: "/deepseekapi",
                method: "POST",
                data: {
                    content: prompt,
                },
            })
                .then((res) => {
                    console.log("生成成功:", res);
                    this.loading = false;
                    this.resultText =
                        res.answer_content || "文案生成失败,请稍后重试...";
                })
                .catch((err) => {
                    console.error("生成失败:", err);
                    this.loading = false;
                });
        },