cj.py

import openai
import os
import time
from concurrent.futures import ThreadPoolExecutor

from openai import OpenAI
client = OpenAI(
    api_key= os.environ["gptkey"]
)
import json

def format_customer_journey(contents):
    formatted_text = ""
    for stage, details in contents.items():
       
        formatted_text += f"【 {stage} 】\n\n"
        formatted_text += f"#TA小故事#\n{details['TA小故事']}\n\n"
        formatted_text += f"#接觸點#\n{details['接觸點']}\n\n"
        formatted_text += f"#痛點#\n{details['痛點']}\n\n"
        formatted_text += f"#痛點解決方案#\n{details['痛點解決方案']}\n\n"
        formatted_text += f"#TA心情評分#\n{details['TA心情評分']}\n\n"
        formatted_text += "-----------------------------\n\n"
    return formatted_text


def generate_cj(brand_name, brand_info, product_info, cjstages_count, target_persona, target_ccs, target_info):
    with ThreadPoolExecutor(max_workers=3) as executor:
        fun_1 = executor.submit(generate_cj_stages,brand_name, brand_info, product_info, cjstages_count)
        cj_stages_str = fun_1.result()
        cj_stages = json.loads(cj_stages_str)
            
        fun_2 = executor.submit(generate_cj_contents,brand_name, brand_info, product_info, cjstages_count, target_persona, target_ccs, target_info,cj_stages["stages"])
        cj_contents_str = fun_2.result()
        cj_contents = json.loads(cj_contents_str)

#    return    cj_contents_str
    return format_customer_journey(cj_contents["contents"])


    
def generate_cj_stages(brand_name, brand_info, product_info, cjstages_count):
    print(cjstages_count)
    messages_base = [
        {"role": "system", "content": "你是一個專業的UX設計師，擅長Customer Journey Map的規劃。"},
        {"role": "user", "content": f"本次要規劃的品牌名稱如下 品牌名稱：{brand_name},品牌資訊：{brand_info},產品資訊：{product_info}"}
     ]

    cj_stages_schema ={
        "name": "customer_journey_stages",
        "description": f"請根據這個品牌的消費者消費行為，幫我列出Customer Journey Map的{cjstages_count}個階段，只要給我{cjstages_count}個階段的中文標題就好。",
        "parameters": {
            "type": "object",
            "properties": {
                "stages": {
                    "type": "array",
                    "items": {
                        "type": "string",
                        "enum": []
                    },
                    "description": f"這{cjstages_count}個階段的標題，每個階段的標題都以'階段'兩個字作為結尾。"
                }
            },"required": [
            "stages"]
        }
    }
    
    response = client.chat.completions.create(
        model='gpt-4o',
        messages= messages_base,
        functions=[
            cj_stages_schema
        ],
        function_call={"name": "customer_journey_stages"}
    )
    arguments_str = response.choices[0].message.function_call.arguments
    return arguments_str

def generate_cj_contents_schema(cj_stages):
    stage_template = {
        "type": "object",
        "properties": {
            "TA小故事": { 
                "type": "string",
                "description": "TA在這個階段發生的情境故事(150個中文字以上)"
            },
            "接觸點": { 
                "type": "string",
                "description": "品牌與TA的接觸點(3~5點)"
            },
            "痛點": { 
                "type": "string",
                "description": "TA在這個階段遭遇的痛點(30個中文字以上)"
            },
            "痛點解決方案": { 
                "type": "string",
                "description": "品牌能解決TA遇到這個痛點的方式(80個中文字以上)"
            },
            "TA心情評分": { 
                "type": "number",
                "description": "TA在這個階段發生的心情指數(1最低、5最高)",
                "minimum": 1,
                "maximum": 5
            }
        },"required": [
            "TA小故事",
            "接觸點",
            "痛點",
            "痛點解決方案",
            "TA心情評分"
        ]
    }

    stages_properties = {stage: stage_template for stage in cj_stages}
    
    cj_contents_schema = {
        "name": "customer_journey_contents",
        "description": f"請根據這個品牌的資訊、TA的資訊及每個顧客旅程階段幫我生成該階段的TA小故事、品牌與TA的接觸點、痛點、痛點解決方案及TA心情評分。",
        "parameters": {
            "type": "object",
            "properties": {
                "contents": {
                    "type": "object",
                    "properties": stages_properties,
                    "required": cj_stages,
                    "description": f"這{len(cj_stages)}個階段的TA小故事、品牌與TA的接觸點、痛點、痛點解決方案及TA心情評分"
                }
            },"required": [
            "contents"]
        }
    }

    return cj_contents_schema
    
def generate_cj_contents(brand_name, brand_info, product_info, cjstages_count, target_persona, target_ccs, target_info,cj_stages):
    print(cjstages_count)
    messages_base = [
        {"role": "system", "content": "你是一個專業的UX設計師，擅長Customer Journey Map的規劃。"},
        {"role": "user", "content": f"本次要規劃的品牌名稱如下 品牌名稱：{brand_name},品牌資訊：{brand_info},產品資訊：{product_info},TA人物誌：{target_persona},TA_CCS敘述：{target_ccs},TA人補充資訊：{target_info}"}
     ]

    
    response = client.chat.completions.create(
        model='gpt-4o',
        messages= messages_base,
        functions=[
            generate_cj_contents_schema(cj_stages)
        ],
        function_call={"name": "customer_journey_contents"}
    )
    arguments_str = response.choices[0].message.function_call.arguments
    return arguments_str