add action result analysis

analysis_action_result.py

@@ -0,0 +1,90 @@
+import re
+import pandas as pd
+from AgentProxy import AgentProxy 
+
+
+result_category_list = [
+    "完成需求确认与收集",
+    "完成技术评估与测试",
+    "完成商务谈判与合同准备",
+    "完成内部审批与预算确认",
+    "完成项目立项与采购流程",
+    "完成关系建立与维护",
+    "完成市场调研与竞争分析",
+    "完成产品推广与市场活动",
+    "完成技术支持与售后服务",
+    "完成续约与增购谈判"
+]
+
+
+df = pd.read_excel('analysis_result_action_result_top200.xlsx')
+data = []
+
+for index, row in df.iterrows():
+    text = row["行动结果"]
+    # print(text)
+    action_pattern = re.compile(r'\*\*销售动作\*\*：(.+?)\n')
+    category_pattern = re.compile(r'\*\*销售动作归类\*\*：(.+?)\n')
+    result_pattern = re.compile(r'\*\*销售动作行动结果\*\*：(.+?)\n')
+    abstract_result_pattern = re.compile(r'\*\*抽象销售动作行动结果\*\*：(.+?)\n')
+    # Find all matches
+    actions = action_pattern.findall(text)
+    categories = category_pattern.findall(text)
+    results = result_pattern.findall(text)
+    abstract_results = abstract_result_pattern.findall(text)
+    if (len(actions) == len(categories) and len(actions) == len(results) and len(actions) == len(abstract_results)):
+        print("index result compliance: true")
+    else:
+        print("index result compliance: false")
+        continue  
+
+    # Combine into a list of dictionaries
+    for action, category, result, abstract_result in zip(actions, categories, results, abstract_results):
+        data.append({
+            "action": action,
+            "action_category": category,
+            "result": result,
+            "result_category": abstract_result
+        })
+
+result_list = []
+for item in data:
+    print(item["result"])
+    result_list.append(item["result"])
+
+# prompt_abstract_result = (f"以下列表为销售动作行动结果，请分析各个结果，将其抽象、总结成通用、概括性的销售行动结果，请注意要体现出结果，比如确定了需求，达成了签约，即完成了什么任务达成了什么效果"
+#                           f"{','.join(result_list)}")
+
+api_key = '25bda2c39c0f8ca0' 
+api_secret = 'e0008b9b9727cb8ceea5a132dbe62495' 
+assistant_id = "66bb09a84673b57506fe7bbd" 
+agent = AgentProxy(assistant_id, api_key, api_secret)
+
+# res = agent.send_message(prompt_abstract_result)
+# print(res)
+
+
+statistics = {}
+for index, row in df.iterrows():
+    try:
+        text = row["当前详细状态及Close节奏"]
+        stage = row["Sales stage"]
+        if stage not in statistics:
+            statistics[stage] = 0
+        statistics[stage] += 1
+        prompt_result_analysis = (f"以下是销售行动结果列表:"
+                                  f"{','.join(result_category_list)}"
+                                  f"请分析如下销售日志，提取出其中的销售动作，并且分析该销售动作是否达成了上述定义的销售动作结果之一，如达成，请将该销售动作映射到行动结果上，如果未达成，则映射到\"未达成\"上"
+                                  f"销售日志如下：{text}"
+                                  f"输出格式如下："
+                                  f"**销售动作**:"
+                                  f"**销售动作行动结果**:"
+                                  )
+        print(prompt_result_analysis)
+        res = agent.send_message(prompt_result_analysis)
+        df.at[index, "销售动作行动结果"] = res
+        print(res)
+    except Exception as e:
+        print(f"Error processing row {index}: {e}")
+        df.at[index, "销售动作行动结果"] = f"Error: {e}"
+df.to_excel('analysis_result_action_result_stage2.xlsx')

re_test.py

@@ -97,4 +97,6 @@ if json_match:
     mapping = json.loads(json_data)
 else:
     mapping = []
-print(mapping)
+print(mapping)
+
+