63 lines
3.4 KiB
Python
63 lines
3.4 KiB
Python
import pandas as pd
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from AgentProxy import AgentProxy
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# Here you need to replace the API Key and API Secret with your，I provide a test key and secret here
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api_key = '25bda2c39c0f8ca0'
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api_secret = 'e0008b9b9727cb8ceea5a132dbe62495'
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assistant_id = "66bb09a84673b57506fe7bbd"
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agent = AgentProxy(assistant_id, api_key, api_secret)
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# Prospecting
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# Evaluation
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# Qualification
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# Bidding / Negotiating
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# Contract Review
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# Closed Won
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# Cancel
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# Closed Lost
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sales_stages = ["Prospecting", "Evaluation", "Qualification", "Bidding / Negotiating", "Contract Review", "Closed Won", "Cancel", "Closed Lost"]
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prompt = "某公司销售阶段分为如下几个定义，你能告诉我什么信息 "+ str(sales_stages)
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print(prompt)
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# print(agent.send_message(prompt))
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sales_stage_definition = '''
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1. **Prospecting（潜在客户开发）**：这一阶段涉及识别和开发潜在客户。销售人员通过各种渠道（如电话、电子邮件、社交媒体等）寻找潜在买家。
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2. **Evaluation（评估）**：在评估阶段，销售团队会评估潜在客户的需求，确定他们是否与公司的产品或服务相匹配。同时，潜在客户也在评估不同的供应商。
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3. **Qualification（资格认定）**：这一阶段的目标是确定潜在客户是否具有成为合格销售机会的潜力。这通常涉及对客户的预算、需求、决策过程和时间线等进行评估。
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4. **Bidding / Negotiating（投标/谈判）**：在这个阶段，销售人员会向客户提交正式的报价或提案，并进行必要的谈判，以达成最终的销售协议。
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5. **Contract Review（合同审查）**：一旦谈判完成，双方将审查合同条款，确保所有细节都得到妥善处理，并准备好签署。
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6. **Closed Won（成功关闭）**：这是销售流程的最终目标，表示交易已经成功完成，客户已经购买了产品或服务。
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7. **Cancel（取消）**：在某些情况下，交易可能会在过程的任何阶段取消。这可能是因为客户改变了主意，或者发现产品或服务不再符合他们的需求。
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8. **Closed Lost（失败关闭）**：如果销售机会没有成功，它将被标记为“失败关闭”。这可能是因为竞争、价格问题或客户需求的改变等原因。'''
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# Read the Excel file
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df = pd.read_excel('output_top20.xlsx')
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# Iterate over each row in the DataFrame
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for index, row in df.iterrows():
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# Extract the information from the column "当前详细状态及Close节奏"
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try:
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detailed_status = row['当前详细状态及Close节奏']
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print(f"Processing row {index}")
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detailed_current_stage = row['Sales stage']
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prompt = f"某公司当前销售定义为 {sales_stage_definition}, 当前销售阶段为 {detailed_current_stage}, 销售人员填写的销售动作日志为: {detailed_status} , 请分析当前销售阶段以及销售动作日志，判断其销售动作是否支持将销售阶段转化到当前阶段{detailed_current_stage}，给出判断结果及销售阶段分析报告"
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analysis_result = agent.send_message(prompt)
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print(analysis_result)
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df.at[index, '分析结果'] = analysis_result # Directly update the DataFrame
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except Exception as e:
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print(f"Error processing row {index}: {e}")
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df.at[index, '分析结果'] = f"Error: {e}" # Log the error in the DataFrame
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df.to_excel('analysis_result.xlsx', index=False)
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