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"""
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Idea House Blueprint - Flask Blueprint for analyzing data fields using Coze API
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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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# Create blueprint
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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 house page"""
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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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"""Process selected data fields using Coze API"""
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try:
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# Get the selected fields from request
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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 REQUEST INITIATED")
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print("=" * 60)
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print(f"📋 Selected Fields Count: {len(selected_fields)}")
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print(f"🔑 API Token (last 10 chars): ...{coze_api_token[-10:] if coze_api_token else 'None'}")
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print(f"⚙️ Workflow ID: {workflow_id}")
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print("=" * 60)
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if not selected_fields:
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print("❌ ERROR: No fields selected")
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return jsonify({'error': 'No fields selected'}), 400
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if not coze_api_token:
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print("❌ ERROR: Coze API token is required")
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return jsonify({'error': 'Coze API token is required'}), 400
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if not workflow_id:
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print("❌ ERROR: Workflow ID is required")
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return jsonify({'error': 'Workflow ID is required'}), 400
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# Prepare the input string from selected fields
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# Format: "field_id (description, unit)"
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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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# Append dataset description if available
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if dataset_description:
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input_string = f"Dataset Description: {dataset_description}\n\nSelected Fields:\n{input_string}"
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print("📤 PREPARING COZE API REQUEST:")
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print(f" Input String: {input_string[:100]}..." if len(input_string) > 100 else f" Input String: {input_string}")
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# Setup Coze API
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coze_api_base = COZE_CN_BASE_URL
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print(f"🌐 Using Coze API Base URL: {coze_api_base}")
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# Initialize Coze client
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print("🔧 Initializing Coze client...")
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coze = Coze(auth=TokenAuth(token=coze_api_token), base_url=coze_api_base)
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# Prepare parameters
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parameters = {
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"input": input_string
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}
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print("📊 Request Parameters:")
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print(f" {json.dumps(parameters, indent=2)}")
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# Call the workflow with retries
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workflow_result = None
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error_message = None
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print("🔄 Starting workflow execution with retries...")
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for attempt in range(3):
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try:
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print(f" Attempt {attempt + 1}/3: Calling Coze workflow...")
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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" ✅ Attempt {attempt + 1} succeeded!")
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print(f" 📥 Workflow Response Type: {type(workflow_result)}")
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if hasattr(workflow_result, 'data'):
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print(f" 📥 Response Data Length: {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"Attempt {attempt + 1} failed with error: {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("💥 WORKFLOW EXECUTION FAILED AFTER ALL RETRIES")
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print(f" Last Error: {error_message}")
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return jsonify({
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'error': 'Failed to run workflow after 3 attempts',
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'details': error_message
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}), 500
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print("✅ WORKFLOW EXECUTION SUCCESSFUL")
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print("🔍 Processing workflow result...")
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# Process the result
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try:
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# Try to extract output from workflow data
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if hasattr(workflow_result, 'data') and workflow_result.data:
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print(" 📊 Workflow data found, processing...")
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# Try to evaluate the data if it's a string
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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" 📄 Extracted output length: {len(str(output))}")
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except:
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# If eval fails, use the data as is
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output = str(workflow_result.data)
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print(f" 📄 Using raw data as output (length: {len(output)})")
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else:
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output = "No data returned from the workflow"
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print(" ⚠️ No data returned from workflow")
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print("=" * 60)
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print("🎉 COZE API REQUEST COMPLETED SUCCESSFULLY")
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print(f"📊 Final Output Preview: {str(output)[:150]}..." if len(str(output)) > 150 else f"📊 Final Output: {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"💥 ERROR PARSING WORKFLOW RESULT: {str(parse_error)}")
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print(f" Raw workflow.data: {workflow_result.data if hasattr(workflow_result, 'data') else 'No data attribute'}")
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return jsonify({
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'error': 'Error parsing workflow result',
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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"💥 PROCESS FIELDS ERROR: {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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"""Proxy endpoint to get data fields from main app's BRAIN API endpoint"""
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try:
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from flask import current_app
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# Use the test client to make an internal request
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with current_app.test_client() as client:
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# Copy headers from the original request
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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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# Copy query parameters
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params = request.args.to_dict()
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# Make internal request to the main app's datafields endpoint
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response = client.get('/api/datafields', headers=headers, query_string=params)
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# Return the response data and status
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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"Datafields proxy error: {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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"""Proxy endpoint to get dataset description from main app's BRAIN API endpoint"""
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print("\n" + "="*60)
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print("🔍 DATASET DESCRIPTION PROXY ENDPOINT CALLED")
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print("="*60)
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try:
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from flask import current_app
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# Use the test client to make an internal request
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with current_app.test_client() as client:
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# Copy headers from the original request
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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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# Copy query parameters
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params = request.args.to_dict()
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print(f"📊 Proxying request with params: {params}")
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print(f"📌 Session ID: {headers.get('Session-ID')}")
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# Make internal request to the main app's dataset description endpoint
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response = client.get('/api/dataset-description', headers=headers, query_string=params)
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print(f"📥 Proxy response status: {response.status_code}")
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# Return the response data and status
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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"💥 Dataset description proxy error: {str(e)}")
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print("="*60 + "\n")
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return jsonify({'error': str(e)}), 500 |
