在tool_api_multi_round.py中可以进行多轮对话

robowaiter/llm_client/tool_api.py

@@ -32,6 +32,7 @@ functions = get_tools()
 def run_conversation(query: str, stream=False,  max_retry=5):
     params = dict(model="chatglm3", messages=[{"role": "user", "content": query}], stream=stream)
     params["functions"] = functions
+    print(params)
     response = get_response(**params)
 
     for _ in range(max_retry):

robowaiter/llm_client/tool_api_multi_round.py

@@ -0,0 +1,78 @@
+import json
+
+import openai
+from colorama import init, Fore
+from loguru import logger
+import json
+from robowaiter.llm_client.tool_register import get_tools, dispatch_tool
+import requests
+import json
+
+import urllib3
+init(autoreset=True)
+
+########################################
+#   该文件实现了与大模型的通信以及工具调用
+########################################
+
+# 忽略https的安全性警告
+urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
+
+base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
+
+def get_response(**kwargs):
+    data = kwargs
+
+    response = requests.post(f"{base_url}/v1/chat/completions", json=data, stream=data["stream"], verify=False)
+    decoded_line = response.json()
+    return decoded_line
+
+functions = get_tools()
+
+
+
+
+if __name__ == "__main__":
+    question = input("\n顾客：")
+    data_memory = [{
+            "role": "system",
+            "content": "你是RoboWaiter,一个由HPCL团队开发的机器人服务员，你在咖啡厅工作。接受顾客的指令并调用工具函数来完成各种服务任务。",
+        },]
+    n = 1
+    max_retry = 5
+    params = dict(model="RoboWaiter",messages=data_memory, stream=False)
+    params["functions"] = functions
+
+    while question != 'end':
+        user_dict = {"role": "user", "content": question}
+        params["messages"].append(user_dict)
+
+        # print(data_memory)
+        response = get_response(**params)
+        for _ in range(max_retry):
+            if response["choices"][0]["message"].get("function_call"):
+                function_call = response["choices"][0]["message"]["function_call"]
+                logger.info(f"Function Call Response: {function_call}")
+
+                function_args = json.loads(function_call["arguments"])
+                tool_response = dispatch_tool(function_call["name"], function_args)
+                logger.info(f"Tool Call Response: {tool_response}")
+
+                return_message = response["choices"][0]["message"]
+                params["messages"].append(return_message)
+                t = {
+                        "role": "function",
+                        "name": function_call["name"],
+                        "content": tool_response,  # 调用函数返回结果
+                    }
+                params["messages"].append(t)
+                response = get_response(**params)
+
+            else:
+                return_message = response["choices"][0]["message"]
+                reply = return_message["content"]
+                params["messages"].append(return_message)
+                logger.info(f"Final Reply: \n{reply}")
+                break
+
+        question = input("\n顾客：")

robowaiter/llm_client/tool_api_test.py

@@ -0,0 +1,74 @@
+import json
+
+import openai
+from colorama import init, Fore
+from loguru import logger
+import json
+from robowaiter.llm_client.tool_register import get_tools, dispatch_tool
+import requests
+import json
+
+import urllib3
+init(autoreset=True)
+
+########################################
+#   该文件实现了与大模型的通信以及工具调用
+########################################
+
+# 忽略https的安全性警告
+urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
+
+base_url = "https://45.125.46.134:25344" # 本地部署的地址,或者使用你访问模型的API地址
+
+def get_response(**kwargs):
+    data = kwargs
+
+    response = requests.post(f"{base_url}/v1/chat/completions", json=data, stream=data["stream"], verify=False)
+    decoded_line = response.json()
+    return decoded_line
+
+functions = get_tools()
+
+def run_conversation(query: str, stream=False,  max_retry=5):
+    params = dict(model="chatglm3", messages=[{"role": "user", "content": query}], stream=stream)
+    params["functions"] = functions
+    response = get_response(**params)
+
+    for _ in range(max_retry):
+        if response["choices"][0]["message"].get("function_call"):
+            function_call = response["choices"][0]["message"]["function_call"]
+            logger.info(f"Function Call Response: {function_call}")
+            if "sub_task" in function_call["name"]:
+                return {
+                    "Answer": "好的",
+                    "Goal": json.loads(function_call["arguments"])["goal"]
+                }
+
+            function_args = json.loads(function_call["arguments"])
+            tool_response = dispatch_tool(function_call["name"], function_args)
+            logger.info(f"Tool Call Response: {tool_response}")
+
+            params["messages"].append(response["choices"][0]["message"])
+            params["messages"].append(
+                {
+                    "role": "function",
+                    "name": function_call["name"],
+                    "content": tool_response,  # 调用函数返回结果
+                }
+            )
+        else:
+            reply = response["choices"][0]["message"]["content"]
+            return {
+                "Answer": reply,
+                "Goal": None
+            }
+            logger.info(f"Final Reply: \n{reply}")
+            return
+
+        response = get_response(**params)
+
+
+
+if __name__ == "__main__":
+    query = "可以带我去吗"
+    print(run_conversation(query, stream=False))

robowaiter/llm_client/tool_register.py

@@ -132,8 +132,13 @@ def create_sub_task(
     当需要完成具身任务（如做咖啡，拿放物体，扫地，前往某位置）时，调用该函数，根据用户的提示进行意图理解，生成子任务的目标状态集合 `goal`（以一阶逻辑的形式表示），用户意图
     做一杯咖啡,则该函数的参数为 "On(Coffee,Bar)",
     前往一号桌,则该函数的参数为 "At(Robot,Table1)",
-    打开空调,则该函数的参数为 "Is(AC,On)",。
+    前往二号桌,则该函数的参数为 "At(Robot,Table2)",
-    关空调,则该函数的参数为 "Is(AC,Off)",。
+    打开空调,则该函数的参数为 "Is(AC,On)",
+    关空调,则该函数的参数为 "Is(AC,Off)",
+    打开窗帘,则该函数的参数为 "Is(Curtain,On)",
+    关闭窗帘,则该函数的参数为 "Is(Curtain,Off)",
+    拖地,则该函数的参数为 "Is(Floor,Clean)",
+    打开大厅灯,则该函数的参数为 "Is(HallLight,On)",
     """
 
     return goal
@@ -143,9 +148,9 @@ def get_object_info(
         obj: Annotated[str, '需要获取信息的物体名称', True]
 ) -> str:
     """
-    获取场景中指定物体 `object` 在哪里，
+    获取场景中指定物体 `object` 在哪里，不涉及到具体的执行任务
-    如果`object` 是一个地点，例如洗手间，地方，则输出。
+    如果`object` 是一个地点，例如洗手间，则输出大门。
-    如果`object`是一个咖啡，则输出。
+    如果`object`是咖啡，则输出桌子，咖啡在桌子上。
     如果`object` 是空桌子，则输出一号桌
     """
     near_object = None

robowaiter/scene/tasks/Auto_tasks.py

@@ -16,8 +16,9 @@ class SceneAT(Scene):
         super().__init__(robot)
 
     def _reset(self):
-        self.add_walker(1085, 2630, 220)
+        # self.add_walker(1085, 2630, 220)
-        self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
+        # self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
+        pass
 
     def _run(self):
 

robowaiter/scene/tasks/GQA.py

@@ -22,8 +22,8 @@ class SceneGQA(Scene):
 
     def _reset(self):
         # self.clean_walker()
-        self.add_walkers()
+        # self.add_walkers([[50, 500,90]])
-
+        pass
 
         # self.walker_bubble("洗手间在哪里")
         # self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])

robowaiter/scene/tasks/Open_tasks.py

@@ -19,8 +19,7 @@ class SceneOT(Scene):
         super().__init__(robot)
         # 在这里加入场景中发生的事件
         self.event_list = [
-            # (5,self.create_chat_event("给我一杯咖啡"))  # (事件发生的时间，事件函数)
+            (5, self.create_chat_event("我有点热，能开个空调吗？")),
-            (5, self.create_chat_event("我有点热，能开个空调吗？"))  # (事件发生的时间，事件函数)
         ]
 
     def _reset(self):
@@ -30,7 +29,6 @@ class SceneOT(Scene):
         print("scene.walkers:",scene.walkers)
         cont = scene.walkers[0].name+":我有点热，能开个空调吗？"
         self.control_robot_action(0,3,cont)
-        # self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
         pass
 
     def _run(self):

robowaiter/scene/tasks/Open_tasks_test.py

@@ -18,20 +18,11 @@ class SceneOT(Scene):
         super().__init__(robot)
         # 在这里加入场景中发生的事件
         self.event_list = [
-            # (5,self.create_chat_event("做一杯咖啡")),
+            (5, self.create_chat_event("给我一杯咖啡"))
-            (5,self.create_chat_event("感觉有点冷，可以关一下空调吗")),
         ]
 
     def _reset(self):
-        scene = self.add_walkers([[50, 300, 0]])
+        pass
-        # time.sleep(2.0)
-        # print("我有点热，能开个空调吗？")
-        print("scene.walkers:",scene.walkers)
-        cont = scene.walkers[0].name+":我有点热，能开个空调吗？"
-        self.control_robot_action(0,3,cont)
-
-        # self.add_walker(1085, 2630, 220)
-        # self.control_walker([self.walker_control_generator(0, False, 100, 755, 1900, 180)])
 
 
     def _run(self):