From 3e48f5a39c67eb14da62c95a219fd2d781bdb9de Mon Sep 17 00:00:00 2001
From: Netceor <45135347+Netceor@users.noreply.github.com>
Date: Sun, 19 Nov 2023 14:24:36 +0800
Subject: [PATCH] Update DealChat.py

---
 robowaiter/behavior_lib/act/DealChat.py | 123 ++++++++++++------------
 1 file changed, 61 insertions(+), 62 deletions(-)

diff --git a/robowaiter/behavior_lib/act/DealChat.py b/robowaiter/behavior_lib/act/DealChat.py
index f39cb75..02ff157 100644
--- a/robowaiter/behavior_lib/act/DealChat.py
+++ b/robowaiter/behavior_lib/act/DealChat.py
@@ -4,9 +4,8 @@ from robowaiter.behavior_lib._base.Act import Act
 from robowaiter.llm_client.multi_rounds import ask_llm, new_history
 import random
 
-import spacy
-
-nlp = spacy.load('en_core_web_lg')
+# import spacy
+# nlp = spacy.load('en_core_web_lg')
 
 
 class DealChat(Act):
@@ -63,65 +62,65 @@ class DealChat(Act):
 
         self.scene.robot.expand_sub_task_tree(goal_set)
 
-    def get_object_info(self,**args):
-        try:
-            obj = args['obj']
-
-            self.function_success = True
-        except:
-            obj = None
-            print("参数解析错误")
-
-        near_object = "None"
-
-        # 场景中现有物品
-        cur_things = set()
-        for item in self.status.objects:
-            cur_things.add(item.name)
-        # obj与现有物品进行相似度匹配
-        query_token = nlp(obj)
-        for w in self.all_loc_en:
-            word_token = nlp(w)
-            similarity = query_token.similarity(word_token)
-            if similarity > max_similarity:
-                max_similarity = similarity
-                similar_word = w
-        print("max_similarity:",max_similarity,"similar_word:",similar_word)
-
-        if similar_word:   # 存在同义词说明场景中存在该物品
-            near_object = random.choices(list(cur_things), k=5)   # 返回场景中的5个物品
-
-        if obj == "洗手间":
-            near_object = "大门"
-
-        return near_object
-
-    def find_location(self, **args):
-        try:
-            location = args['obj']
-            self.function_success = True
-        except:
-            obj = None
-            print("参数解析错误")
-
-        near_location = None
-        # 用户咨询的地点
-        query_token = nlp(location)
-        max_similarity = 0
-        similar_word = None
-        # 到自己维护的地点列表中找同义词
-        for w in self.all_loc_en:
-            word_token = nlp(w)
-            similarity = query_token.similarity(word_token)
-            if similarity > max_similarity:
-                max_similarity = similarity
-                similar_word = w
-        print("similarity:", max_similarity, "similar_word:", similar_word)
-        # 存在同义词说明客户咨询的地点有效
-        if similar_word:
-            mp = list(self.loc_map_en[similar_word])
-            near_location = random.choice(mp)
-        return near_location
+    # def get_object_info(self,**args):
+    #     try:
+    #         obj = args['obj']
+    #
+    #         self.function_success = True
+    #     except:
+    #         obj = None
+    #         print("参数解析错误")
+    #
+    #     near_object = "None"
+    #
+    #     # 场景中现有物品
+    #     cur_things = set()
+    #     for item in self.status.objects:
+    #         cur_things.add(item.name)
+    #     # obj与现有物品进行相似度匹配
+    #     query_token = nlp(obj)
+    #     for w in self.all_loc_en:
+    #         word_token = nlp(w)
+    #         similarity = query_token.similarity(word_token)
+    #         if similarity > max_similarity:
+    #             max_similarity = similarity
+    #             similar_word = w
+    #     print("max_similarity:",max_similarity,"similar_word:",similar_word)
+    #
+    #     if similar_word:   # 存在同义词说明场景中存在该物品
+    #         near_object = random.choices(list(cur_things), k=5)   # 返回场景中的5个物品
+    #
+    #     if obj == "洗手间":
+    #         near_object = "大门"
+    #
+    #     return near_object
+    #
+    # def find_location(self, **args):
+    #     try:
+    #         location = args['obj']
+    #         self.function_success = True
+    #     except:
+    #         obj = None
+    #         print("参数解析错误")
+    #
+    #     near_location = None
+    #     # 用户咨询的地点
+    #     query_token = nlp(location)
+    #     max_similarity = 0
+    #     similar_word = None
+    #     # 到自己维护的地点列表中找同义词
+    #     for w in self.all_loc_en:
+    #         word_token = nlp(w)
+    #         similarity = query_token.similarity(word_token)
+    #         if similarity > max_similarity:
+    #             max_similarity = similarity
+    #             similar_word = w
+    #     print("similarity:", max_similarity, "similar_word:", similar_word)
+    #     # 存在同义词说明客户咨询的地点有效
+    #     if similar_word:
+    #         mp = list(self.loc_map_en[similar_word])
+    #         near_location = random.choice(mp)
+    #     return near_location
 
     def stop_serve(self,**args):