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"""
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idea库蓝图 - 使用 Coze API 分析数据字段的 Flask 蓝图
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"""
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from flask import Blueprint, render_template, request, jsonify, session as flask_session
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import os
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import sys
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from cozepy import Coze, TokenAuth, Message, ChatStatus, MessageContentType
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from cozepy import COZE_CN_BASE_URL
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import json
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# 创建蓝图
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idea_house_bp = Blueprint('idea_house', __name__, url_prefix='/idea-house')
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@idea_house_bp.route('/')
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def idea_house():
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"""idea库页面"""
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return render_template('idea_house.html')
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@idea_house_bp.route('/api/process-fields', methods=['POST'])
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def process_fields():
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"""使用 Coze API 处理选定的数据字段"""
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try:
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# 从请求获取选定的字段
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data = request.get_json()
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selected_fields = data.get('selected_fields', {})
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coze_api_token = data.get('coze_api_token')
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workflow_id = data.get('workflow_id')
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dataset_description = data.get('dataset_description', '')
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print("=" * 60)
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print("🚀 COZE API 请求已启动")
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print("=" * 60)
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print(f"📋 选定字段数量: {len(selected_fields)}")
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print(f"🔑 API 令牌 (最后10位): ...{coze_api_token[-10:] if coze_api_token else '无'}")
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print(f"⚙️ 工作流 ID: {workflow_id}")
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print("=" * 60)
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if not selected_fields:
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print("❌ 错误: 未选择任何字段")
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return jsonify({'error': '未选择任何字段'}), 400
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if not coze_api_token:
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print("❌ 错误: 需要 Coze API 令牌")
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return jsonify({'error': '需要 Coze API 令牌'}), 400
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if not workflow_id:
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print("❌ 错误: 需要工作流 ID")
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return jsonify({'error': '需要工作流 ID'}), 400
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# 从选定字段准备输入字符串
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# 格式: "字段ID (描述, 单位)"
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input_lines = []
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for field_id, description in selected_fields.items():
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input_lines.append(f"{field_id} ({description})")
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input_string = "\n".join(input_lines)
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# 如果数据集描述可用，则附加
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if dataset_description:
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input_string = f"数据集描述: {dataset_description}\n\n选定字段:\n{input_string}"
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print("📤 准备 COZE API 请求:")
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print(f" 输入字符串: {input_string[:100]}..." if len(input_string) > 100 else f" 输入字符串: {input_string}")
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# 设置 Coze API
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coze_api_base = COZE_CN_BASE_URL
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print(f"🌐 使用 Coze API 基础 URL: {coze_api_base}")
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# 初始化 Coze 客户端
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print("🔧 初始化 Coze 客户端...")
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coze = Coze(auth=TokenAuth(token=coze_api_token), base_url=coze_api_base)
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# 准备参数
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parameters = {
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"input": input_string
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}
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print("📊 请求参数:")
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print(f" {json.dumps(parameters, indent=2)}")
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# 使用重试调用工作流
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workflow_result = None
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error_message = None
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print("🔄 开始带重试的工作流执行...")
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for attempt in range(3):
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try:
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print(f" 尝试 {attempt + 1}/3: 调用 Coze 工作流...")
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workflow = coze.workflows.runs.create(
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workflow_id=workflow_id,
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parameters=parameters
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)
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workflow_result = workflow
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print(f" ✅ 尝试 {attempt + 1} 成功!")
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print(f" 📥 工作流响应类型: {type(workflow_result)}")
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if hasattr(workflow_result, 'data'):
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print(f" 📥 响应数据长度: {len(str(workflow_result.data)) if workflow_result.data else 0}")
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break
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except Exception as e:
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error_message = f"尝试 {attempt + 1} 失败，错误: {str(e)}"
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print(f" ❌ {error_message}")
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continue
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if workflow_result is None:
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print("💥 所有重试后工作流执行失败")
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print(f" 最后错误: {error_message}")
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return jsonify({
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'error': '3次尝试后运行工作流失败',
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'details': error_message
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}), 500
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print("✅ 工作流执行成功")
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print("🔍 处理工作流结果...")
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# 处理结果
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try:
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# 尝试从工作流数据中提取输出
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if hasattr(workflow_result, 'data') and workflow_result.data:
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print(" 📊 找到工作流数据，正在处理...")
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# 如果是字符串，尝试评估数据
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try:
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result_data = eval(workflow_result.data) if isinstance(workflow_result.data, str) else workflow_result.data
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output = result_data.get('output', '')
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print(f" 📄 提取的输出长度: {len(str(output))}")
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except:
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# 如果评估失败，按原样使用数据
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output = str(workflow_result.data)
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print(f" 📄 使用原始数据作为输出 (长度: {len(output)})")
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else:
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output = "工作流未返回数据"
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print(" ⚠️ 工作流未返回数据")
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print("=" * 60)
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print("🎉 COZE API 请求成功完成")
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print(f"📊 最终输出预览: {str(output)[:150]}..." if len(str(output)) > 150 else f"📊 最终输出: {str(output)}")
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print("=" * 60)
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return jsonify({
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'success': True,
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'output': output,
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'parameters': parameters,
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'selected_fields': selected_fields
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})
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except Exception as parse_error:
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print(f"💥 解析工作流结果错误: {str(parse_error)}")
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print(f" 原始 workflow.data: {workflow_result.data if hasattr(workflow_result, 'data') else '无数据属性'}")
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return jsonify({
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'error': '解析工作流结果时出错',
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'details': str(parse_error),
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'raw_data': str(workflow_result.data) if hasattr(workflow_result, 'data') else None
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}), 500
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except Exception as e:
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print(f"💥 处理字段错误: {str(e)}")
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print("=" * 60)
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return jsonify({'error': str(e)}), 500
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@idea_house_bp.route('/api/get-datafields-proxy', methods=['GET'])
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def get_datafields_proxy():
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"""代理端点，从主应用的 BRAIN API 端点获取数据字段"""
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try:
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from flask import current_app
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# 使用测试客户端发出内部请求
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with current_app.test_client() as client:
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# 从原始请求复制头部
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headers = {
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'Session-ID': request.headers.get('Session-ID') or flask_session.get('brain_session_id')
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}
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# 复制查询参数
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params = request.args.to_dict()
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# 向主应用的数据字段端点发出内部请求
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response = client.get('/api/datafields', headers=headers, query_string=params)
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# 返回响应数据和状态
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return response.get_json(), response.status_code
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except Exception as e:
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print(f"数据字段代理错误: {str(e)}")
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return jsonify({'error': str(e)}), 500
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@idea_house_bp.route('/api/get-dataset-description', methods=['GET'])
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def get_dataset_description():
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"""代理端点，从主应用的 BRAIN API 端点获取数据集描述"""
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print("\n" + "="*60)
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print("🔍 数据集描述代理端点被调用")
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print("="*60)
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try:
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from flask import current_app
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# 使用测试客户端发出内部请求
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with current_app.test_client() as client:
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# 从原始请求复制头部
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headers = {
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'Session-ID': request.headers.get('Session-ID') or flask_session.get('brain_session_id')
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}
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# 复制查询参数
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params = request.args.to_dict()
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print(f"📊 代理请求参数: {params}")
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print(f"📌 会话 ID: {headers.get('Session-ID')}")
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# 向主应用的数据集描述端点发出内部请求
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response = client.get('/api/dataset-description', headers=headers, query_string=params)
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print(f"📥 代理响应状态: {response.status_code}")
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# 返回响应数据和状态
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return response.get_json(), response.status_code
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except Exception as e:
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print(f"💥 数据集描述代理错误: {str(e)}")
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print("="*60 + "\n")
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return jsonify({'error': str(e)}), 500 |
