diff --git a/robowaiter/algos/MemGPT_simple/__init__.py b/robowaiter/algos/MemGPT_simple/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/robowaiter/llm_client/MemGPT_simple/agent.py b/robowaiter/algos/MemGPT_simple/agent.py similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/agent.py rename to robowaiter/algos/MemGPT_simple/agent.py diff --git a/robowaiter/llm_client/MemGPT_simple/functions.py b/robowaiter/algos/MemGPT_simple/functions.py similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/functions.py rename to robowaiter/algos/MemGPT_simple/functions.py diff --git a/robowaiter/llm_client/MemGPT_simple/humans/customer.txt b/robowaiter/algos/MemGPT_simple/humans/customer.txt similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/humans/customer.txt rename to robowaiter/algos/MemGPT_simple/humans/customer.txt diff --git a/robowaiter/llm_client/MemGPT_simple/main.py b/robowaiter/algos/MemGPT_simple/main.py similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/main.py rename to robowaiter/algos/MemGPT_simple/main.py diff --git a/robowaiter/llm_client/MemGPT_simple/memory.py b/robowaiter/algos/MemGPT_simple/memory.py similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/memory.py rename to robowaiter/algos/MemGPT_simple/memory.py diff --git a/robowaiter/llm_client/MemGPT_simple/personas/robowaiter.txt b/robowaiter/algos/MemGPT_simple/personas/robowaiter.txt similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/personas/robowaiter.txt rename to robowaiter/algos/MemGPT_simple/personas/robowaiter.txt diff --git a/robowaiter/llm_client/MemGPT_simple/system/memgpt_chs.txt b/robowaiter/algos/MemGPT_simple/system/memgpt_chs.txt similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/system/memgpt_chs.txt rename to robowaiter/algos/MemGPT_simple/system/memgpt_chs.txt diff --git a/robowaiter/llm_client/MemGPT_simple/system/system_gpt3.5.txt b/robowaiter/algos/MemGPT_simple/system/system_gpt3.5.txt similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/system/system_gpt3.5.txt rename to robowaiter/algos/MemGPT_simple/system/system_gpt3.5.txt diff --git a/robowaiter/llm_client/MemGPT_simple/utils.py b/robowaiter/algos/MemGPT_simple/utils.py similarity index 100% rename from robowaiter/llm_client/MemGPT_simple/utils.py rename to robowaiter/algos/MemGPT_simple/utils.py diff --git a/robowaiter/algos/retrieval/README.md b/robowaiter/algos/retrieval/README.md new file mode 100644 index 0000000..d4df828 --- /dev/null +++ b/robowaiter/algos/retrieval/README.md @@ -0,0 +1,6 @@ +# 安装环境 +```python +pip3 install torch torchvision torchaudio +conda install -c conda-forge faiss +pip install src +``` diff --git a/robowaiter/algos/retrieval/retrieval_lm/__init__.py b/robowaiter/algos/retrieval/retrieval_lm/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/robowaiter/algos/retrieval/retrieval_lm/fix_questions.jsonl b/robowaiter/algos/retrieval/retrieval_lm/fix_questions.jsonl new file mode 100644 index 0000000..2241464 --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/fix_questions.jsonl @@ -0,0 +1,41 @@ +{"id": 0, "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}"} +{"id": 1, "title": "感谢，这些够啦，你去忙吧。", "text": "{'answer': 'ok, 有需要您再找我。', 'function': None}"} +{"id": 2, "title": "做一杯咖啡", "text": "{'answer': '好的，我马上做咖啡', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,CoffeeTable)\"}'}"} +{"id": 3, "title": "不用了。", "text": "{'answer': '好的，您有需要再跟我说', 'function': 'stop_serve', 'args': '{}'}"} +{"id": 4, "title": "来一号桌", "text": "{'answer': '好的，我马上来一号桌', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,Table1)\"}'}"} +{"id": 5, "title": "早上好呀，我想找个能晒太阳的地方。", "text": "{'answer': '您右手边就有能晒太阳的位置呢。', 'function': None}"} +{"id": 6, "title": "可以带我过去嘛？", "text": "{'answer': '当然，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable1)\"}'}"} +{"id": 7, "title": "嘿，RoboWaiter，过来一下！", "text": "{'answer': '我在来的路上啦，请稍等噢！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable6)\"}'}"} +{"id": 8, "title": "你们这有什么饮料嘛？", "text": "{'answer': '我们咖啡厅提供各种口味咖啡，水，冰红茶，酸奶等饮品，还提供点心蛋糕等甜品。您想点什么？', 'function': None}"} +{"id": 9, "title": "来杯卡布奇诺吧。", "text": "{'answer': 'ok，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,BrightTable6)\"}'}"} +{"id": 10, "title": "我昨天保温杯好像落在你们咖啡厅了，你看到了吗？", "text": "{'answer': '是的，我有印象，保温杯在大厅的2号桌子上。', 'function': 'get_object_info', 'args': '{\"obj\":\"保温杯\"}'}"} +{"id": 11, "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}"} +{"id": 12, "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}"} +{"id": 13, "title": "你可以帮我拿来吗，我在前门的桌子前等你。", "text": "{'answer': '当然，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(VacuumCup,Table1)\"}'}"} +{"id": 14, "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}"} +{"id": 15, "title": "大厅的桌子好啊，快带我去呀！", "text": "{'answer': '好的好的，请跟我来。', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,WaterTable)\"}'}"} +{"id": 16, "title": "我想来杯水，帮我孩子拿个酸奶吧。", "text": "{'answer': 'ok，没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Water,WaterTable),On(Yogurt,WaterTable)\"}'}"} +{"id": 17, "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}"} +{"id": 18, "title": "好热呀！太阳也好大！", "text": "{'answer': '抱歉，我这就去开空调和关窗帘。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(AC,On),Is(Curtain,Off)\"}'}"} +{"id": 19, "title": "下班啦！别忘了打扫卫生。", "text": "{'answer': '收到！下班啦！', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(Floor,Clean),Is(Table1,Clean),Is(Chairs,Clean),Is(AC,Off),Is(HallLight,Off),Is(TubeLight,Off),Is(Curtain,Off)\"}'}"} +{"id": 20, "title": "请问洗手间在哪里？", "text": "{'answer': '洗手间在这附近', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}"} +{"id": 21, "title": "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Chips,WaterTable),On(NFCJuice,WaterTable)\"}'}"} +{"id": 22, "title": "给我来份薯片和果汁，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)\"}'}"} +{"id": 23, "title": "好热呀，想开空调，想要温度调低点！", "text": "{'answer': '抱歉，我马上去开空调并调低空调温度。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(ACTemperature,Down)\"}'}"} +{"id": 24, "title": "请问哪里有空位啊？", "text": "{'answer': '现在有不少空位呢，请问您有什么要求嘛？', 'function': None}"} +{"id": 25, "title": "我想坐高脚凳子。", "text": "{'answer': '没问题，大厅里就有这样的位置呢！', 'function': None}"} +{"id": 26, "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}"} +{"id": 27, "title": "可以关筒灯和关窗帘吗？", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(TubeLight,Off),Is(Curtain,Off)\"}'}"} +{"id": 28, "title": "给我来杯咖啡，哦对，再倒一杯水。", "text": "{'answer': '速速就好，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Water,WaterTable),On(Coffee,WaterTable)\"}'}"} +{"id": 29, "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}"} +{"id": 30, "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}"} +{"id": 31, "title": "你好呀，你们这有啥好吃的？", "text": "{'answer': '我们咖啡厅有咖啡，还有饮料和点心蛋糕呢？您想点什么不？', 'function': None}"} +{"id": 32, "title": "听起来都好甜呀，我女朋友爱吃水果。", "text": "{'answer': '没问题，我们也提供草莓、橘子和苹果等水果呢。', 'function': None}"} +{"id": 33, "title": "你们这人可真多。", "text": "{'answer': '目前还有空位呢，你们可以坐下来一起品尝水果呢？', 'function': 'get_object_info', 'args': '{\"obj\":\"空位\"}'}"} +{"id": 34, "title": "我女朋友怕晒，有空余的阴凉位置嘛？", "text": "{'answer': '我查询完毕，阴凉位置有两个。在你们右侧往里走，就有适合你们二位的沙发呢。', 'function': 'get_object_info', 'args': '{\"obj\":\"阴凉空位\"}'}"} +{"id": 35, "title": "那还不错。", "text": "{'answer': '是的，那边安静，不会晒到太阳呢。', 'function': None}"} +{"id": 36, "title": "我们还想一起下下棋,切磋切磋。", "text": "{'answer': '我们这有两份军棋呢,在大厅的三号桌上。', 'function': 'get_object_info', 'args': '{\"obj\":\"棋\"}'}"} +{"id": 37, "title": "请问洗手间在哪呢？", "text": "{'answer': '在后门，你们的左侧往里走就是了呢。', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}"} +{"id": 38, "title": "我带着孩子呢，想要宽敞亮堂的地方。", "text": "{'answer': '好的，我明白了，那么我们推荐您到大厅的桌子，那里的空间比较宽敞，环境也比较明亮，适合带着孩子一起用餐。', 'function': None}"} +{"id": 39, "title": "冰红茶", "text": "{'answer': '好的', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Softdrink,Bar)\"}'}"} +{"id": 40, "title": "水杯", "text": "{'answer': '好的', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Glass,Bar)\"}'}"} diff --git a/robowaiter/algos/retrieval/retrieval_lm/fix_questions.txt b/robowaiter/algos/retrieval/retrieval_lm/fix_questions.txt new file mode 100644 index 0000000..9b2196a --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/fix_questions.txt @@ -0,0 +1,240 @@ +你好 +您好，我是这家咖啡厅的服务员，请问您要点什么？ + + +感谢，这些够啦，你去忙吧。 +ok, 有需要您再找我。 + + +做一杯咖啡 +好的，我马上做咖啡 +create_sub_task +{"goal":"On(Coffee,CoffeeTable)"} + +不用了。 +好的，您有需要再跟我说 +stop_serve +{} + +来一号桌 +好的，我马上来一号桌 +create_sub_task +{"goal":"At(Robot,Table1)"} + + +早上好呀，我想找个能晒太阳的地方。 +您右手边就有能晒太阳的位置呢。 + + +可以带我过去嘛？ +当然，请跟我来！ +create_sub_task +{"goal":"At(Robot,BrightTable1)"} + + +嘿，RoboWaiter，过来一下！ +我在来的路上啦，请稍等噢！ +create_sub_task +{"goal":"At(Robot,BrightTable6)"} + + +你们这有什么饮料嘛？ +我们咖啡厅提供各种口味咖啡，水，冰红茶，酸奶等饮品，还提供点心蛋糕等甜品。您想点什么？ + + +来杯卡布奇诺吧。 +ok，请稍等！ +create_sub_task +{"goal":"On(Coffee,BrightTable6)"} + + + + +我昨天保温杯好像落在你们咖啡厅了，你看到了吗？ +是的，我有印象，保温杯在大厅的2号桌子上。 +get_object_info +{"obj":"保温杯"} + + +给我来份午餐套餐。 +本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？ + +打包吧，快点！ +请稍等，马上就好！ +create_sub_task +{"goal":"On(Dessert,Bar),On(Coffee,Bar)"} + + +你可以帮我拿来吗，我在前门的桌子前等你。 +当然，请稍等！ +create_sub_task +{"goal":"On(VacuumCup,Table1)"} + +麻烦啦！ +没事儿，为您服务是我的荣幸！ + +大厅的桌子好啊，快带我去呀！ +好的好的，请跟我来。 +create_sub_task +{"goal":"At(Robot,WaterTable)"} + + +我想来杯水，帮我孩子拿个酸奶吧。 +ok，没问题，请稍等！ +create_sub_task +{"goal":"On(Water,WaterTable),On(Yogurt,WaterTable)"} + +来杯酸奶吧。 +好的没问题，请稍等！ +create_sub_task +{"goal":"On(Yogurt,WaterTable)"} + + +好热呀！太阳也好大！ +抱歉，我这就去开空调和关窗帘。 +create_sub_task +{"goal":"Is(AC,On),Is(Curtain,Off)"} + + +下班啦！别忘了打扫卫生。 +收到！下班啦！ +create_sub_task +{"goal":"Is(Floor,Clean),Is(Table1,Clean),Is(Chairs,Clean),Is(AC,Off),Is(HallLight,Off),Is(TubeLight,Off),Is(Curtain,Off)"} + + +请问洗手间在哪里？ +洗手间在这附近 +get_object_info +{"obj":"洗手间"} + + + +给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。 +好的，请稍等。 +create_sub_task +{"goal":"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)"} + + +给我来份薯片和果汁，我坐在对面的桌子那儿。 +好的，请稍等。 +create_sub_task +{"goal":"On(Chips,WaterTable),On(NFCJuice,WaterTable)"} + +给我来份薯片和果汁，我坐在对面的水杯桌那儿。 +好的，请稍等。 +create_sub_task +{"goal":"On(Chips,WaterTable),On(NFCJuice,WaterTable)"} + +好热呀，想开空调，想要温度调低点！ +抱歉，我马上去开空调并调低空调温度。 +create_sub_task +{"goal":"Is(ACTemperature,Down)"} + +请问哪里有空位啊？ +现在有不少空位呢，请问您有什么要求嘛？ + +我想坐高脚凳子。 +没问题，大厅里就有这样的位置呢！ +get_object_info +{"obj":"高脚凳子的空位"} + + +你带我去吧。 +OK，请跟我来！ +create_sub_task +{"goal":"At(Robot,BrightTable5)"} + + +可以关筒灯和关窗帘吗？ +好的，请稍等。 +create_sub_task +{"goal":"Is(TubeLight,Off),Is(Curtain,Off)"} + + +给我来杯咖啡，哦对，再倒一杯水。 +速速就好，请稍等！ +create_sub_task +{"goal":"On(Water,WaterTable),On(Coffee,WaterTable)"} + + +我想来份点心和酸奶。 +稍等片刻噢~ +create_sub_task +{"goal":"On(Yogurt,Bar),On(Dessert,Bar)"} + +酸奶。 +稍等片刻噢~ +create_sub_task +{"goal":"On(Yogurt,Bar)"} + + + +你好呀，你们这有啥好吃的？ +我们咖啡厅有咖啡，还有饮料和点心蛋糕呢？您想点什么不？ +get_object_info +{"obj":"饮料,水果,点心"} + + +听起来都好甜呀，我女朋友爱吃水果。 +没问题，我们也提供草莓、橘子和苹果等水果呢。 + + +你们这人可真多。 +目前还有空位呢，你们可以坐下来一起品尝水果呢？ +get_object_info +{"obj":"空位"} + +我女朋友怕晒，有空余的阴凉位置嘛？ +我查询完毕，阴凉位置有两个。在你们右侧往里走，就有适合你们二位的沙发呢。 +get_object_info +{"obj":"阴凉空位"} + +那还不错。 +是的，那边安静，不会晒到太阳呢。 + +我们还想一起下下棋,切磋切磋。 +我们这有两份军棋呢,在大厅的三号桌上。 +get_object_info +{"obj":"棋"} + +请问洗手间在哪呢？ +在后门，你们的左侧往里走就是了呢。 +get_object_info +{"obj":"洗手间"} + +我带着孩子呢，想要宽敞亮堂的地方。 +好的，我明白了，那么我们推荐您到大厅的桌子，那里的空间比较宽敞，环境也比较明亮，适合带着孩子一起用餐。 + + +冰红茶 +好的 +create_sub_task +{"goal":"On(Softdrink,Bar)"} + + +水杯 +好的 +create_sub_task +{"goal":"On(Water,Bar)"} + +点心 +好的 +create_sub_task +{"goal":"On(Dessert,Bar)"} + +酸奶 +好的 +create_sub_task +{"goal":"On(Yogurt,Bar)"} + + +做一杯咖啡 +好的，我马上做咖啡 +create_sub_task +{"goal":"On(Coffee,CoffeeTable)"} + + +把盒装冰红茶放到水桌 +好的 +create_sub_task +{"goal":"On(Softdrink,WaterTable)"} \ No newline at end of file diff --git a/robowaiter/algos/retrieval/retrieval_lm/fix_questions_test.jsonl b/robowaiter/algos/retrieval/retrieval_lm/fix_questions_test.jsonl new file mode 100644 index 0000000..ec75be3 --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/fix_questions_test.jsonl @@ -0,0 +1,41 @@ +{"id": 0, "question": "你好"} +{"id": 1, "question": "感谢，这些够啦，你去忙吧。"} +{"id": 2, "question": "做一杯咖啡"} +{"id": 3, "question": "不用了。"} +{"id": 4, "question": "来一号桌"} +{"id": 5, "question": "早上好呀，我想找个能晒太阳的地方。"} +{"id": 6, "question": "可以带我过去嘛？"} +{"id": 7, "question": "嘿，RoboWaiter，过来一下！"} +{"id": 8, "question": "你们这有什么饮料嘛？"} +{"id": 9, "question": "来杯卡布奇诺吧。"} +{"id": 10, "question": "我昨天保温杯好像落在你们咖啡厅了，你看到了吗？"} +{"id": 11, "question": "给我来份午餐套餐。"} +{"id": 12, "question": "打包吧，快点！"} +{"id": 13, "question": "你可以帮我拿来吗，我在前门的桌子前等你。"} +{"id": 14, "question": "麻烦啦！"} +{"id": 15, "question": "大厅的桌子好啊，快带我去呀！"} +{"id": 16, "question": "我想来杯水，帮我孩子拿个酸奶吧。"} +{"id": 17, "question": "来杯酸奶吧。"} +{"id": 18, "question": "好热呀！太阳也好大！"} +{"id": 19, "question": "下班啦！别忘了打扫卫生。"} +{"id": 20, "question": "请问洗手间在哪里？"} +{"id": 21, "question": "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。"} +{"id": 22, "question": "给我来份薯片和果汁，我坐在对面的桌子那儿。"} +{"id": 23, "question": "好热呀，想开空调，想要温度调低点！"} +{"id": 24, "question": "请问哪里有空位啊？"} +{"id": 25, "question": "我想坐高脚凳子。"} +{"id": 26, "question": "你带我去吧。"} +{"id": 27, "question": "可以关筒灯和关窗帘吗？"} +{"id": 28, "question": "给我来杯咖啡，哦对，再倒一杯水。"} +{"id": 29, "question": "我想来份点心和酸奶。"} +{"id": 30, "question": "酸奶。"} +{"id": 31, "question": "你好呀，你们这有啥好吃的？"} +{"id": 32, "question": "听起来都好甜呀，我女朋友爱吃水果。"} +{"id": 33, "question": "你们这人可真多。"} +{"id": 34, "question": "我女朋友怕晒，有空余的阴凉位置嘛？"} +{"id": 35, "question": "那还不错。"} +{"id": 36, "question": "我们还想一起下下棋,切磋切磋。"} +{"id": 37, "question": "请问洗手间在哪呢？"} +{"id": 38, "question": "我带着孩子呢，想要宽敞亮堂的地方。"} +{"id": 39, "question": "冰红茶"} +{"id": 40, "question": "水杯"} diff --git a/robowaiter/algos/retrieval/retrieval_lm/question2jsonl.py b/robowaiter/algos/retrieval/retrieval_lm/question2jsonl.py new file mode 100644 index 0000000..755af93 --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/question2jsonl.py @@ -0,0 +1,59 @@ +import time + +import openai +from colorama import init, Fore +from loguru import logger +from robowaiter.llm_client.tool_register import get_tools, dispatch_tool +import requests +import json +from collections import deque +import re +import jsonlines + + +def question2jsonl(file_path, output_path): + with open(file_path, 'r', encoding="utf-8") as f: + lines = f.read().strip() + + sections = re.split(r'\n\s*\n', lines) + with jsonlines.open(output_path, "w") as file_jsonl: + k = 0 + + for s in sections: + x = s.strip().splitlines() + if len(x) == 2: + answer_dict = { + "answer": x[1], + "function": None + } + else: + answer_dict = { + "answer": x[1], + "function": x[2], + "args": x[3] + } + + item_dict = {"id": k, 'title': x[0], 'text': str(answer_dict)} + file_jsonl.write(item_dict) + k += 1 + +def question2jsonl_test(file_path, output_path): + with open(file_path, 'r', encoding="utf-8") as f: + lines = f.read().strip() + + sections = re.split(r'\n\s*\n', lines) + with jsonlines.open(output_path, "w") as file_jsonl: + k = 0 + + for s in sections: + x = s.strip().splitlines() + + item_dict = {"id": k, 'question': x[0]} + file_jsonl.write(item_dict) + k += 1 + + +if __name__ == '__main__': + file_path = "fix_questions.txt" + output_path = "fix_questions.jsonl" + question2jsonl(file_path,output_path) \ No newline at end of file diff --git a/robowaiter/algos/retrieval/retrieval_lm/retr_result/fix_questions_test.jsonl b/robowaiter/algos/retrieval/retrieval_lm/retr_result/fix_questions_test.jsonl new file mode 100644 index 0000000..969f899 --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/retr_result/fix_questions_test.jsonl @@ -0,0 +1,41 @@ +{"id": 0, "question": "你好", "ctxs": [{"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "2.1162708"}, {"id": "39", "title": "冰红茶", "text": "{'answer': '好的', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Softdrink,Bar)\"}'}", "score": "1.9018158"}, {"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.7684793"}]} +{"id": 1, "question": "感谢，这些够啦，你去忙吧。", "ctxs": [{"id": "1", "title": "感谢，这些够啦，你去忙吧。", "text": "{'answer': 'ok, 有需要您再找我。', 'function': None}", "score": "1.9322114"}, {"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "1.913708"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "1.886067"}]} +{"id": 2, "question": "做一杯咖啡", "ctxs": [{"id": "4", "title": "来一号桌", "text": "{'answer': '好的，我马上来一号桌', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,Table1)\"}'}", "score": "1.8168783"}, {"id": "2", "title": "做一杯咖啡", "text": "{'answer': '好的，我马上做咖啡', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,CoffeeTable)\"}'}", "score": "1.78474"}, {"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "1.4285033"}]} +{"id": 3, "question": "不用了。", "ctxs": [{"id": "3", "title": "不用了。", "text": "{'answer': '好的，您有需要再跟我说', 'function': 'stop_serve', 'args': '{}'}", "score": "2.3739111"}, {"id": "35", "title": "那还不错。", "text": "{'answer': '是的，那边安静，不会晒到太阳呢。', 'function': None}", "score": "2.3256633"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.1746387"}]} +{"id": 4, "question": "来一号桌", "ctxs": [{"id": "4", "title": "来一号桌", "text": "{'answer': '好的，我马上来一号桌', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,Table1)\"}'}", "score": "1.879482"}, {"id": "2", "title": "做一杯咖啡", "text": "{'answer': '好的，我马上做咖啡', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,CoffeeTable)\"}'}", "score": "1.8168783"}, {"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "1.5156002"}]} +{"id": 5, "question": "早上好呀，我想找个能晒太阳的地方。", "ctxs": [{"id": "5", "title": "早上好呀，我想找个能晒太阳的地方。", "text": "{'answer': '您右手边就有能晒太阳的位置呢。', 'function': None}", "score": "2.0365968"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "1.93718"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "1.9365059"}]} +{"id": 6, "question": "可以带我过去嘛？", "ctxs": [{"id": "6", "title": "可以带我过去嘛？", "text": "{'answer': '当然，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable1)\"}'}", "score": "1.8335087"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "1.810061"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "1.8016064"}]} +{"id": 7, "question": "嘿，RoboWaiter，过来一下！", "ctxs": [{"id": "7", "title": "嘿，RoboWaiter，过来一下！", "text": "{'answer': '我在来的路上啦，请稍等噢！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable6)\"}'}", "score": "2.259178"}, {"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.4411571"}, {"id": "35", "title": "那还不错。", "text": "{'answer': '是的，那边安静，不会晒到太阳呢。', 'function': None}", "score": "1.3609219"}]} +{"id": 8, "question": "你们这有什么饮料嘛？", "ctxs": [{"id": "8", "title": "你们这有什么饮料嘛？", "text": "{'answer': '我们咖啡厅提供各种口味咖啡，水，冰红茶，酸奶等饮品，还提供点心蛋糕等甜品。您想点什么？', 'function': None}", "score": "1.629295"}, {"id": "24", "title": "请问哪里有空位啊？", "text": "{'answer': '现在有不少空位呢，请问您有什么要求嘛？', 'function': None}", "score": "1.4364586"}, {"id": "6", "title": "可以带我过去嘛？", "text": "{'answer': '当然，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable1)\"}'}", "score": "1.4195945"}]} +{"id": 9, "question": "来杯卡布奇诺吧。", "ctxs": [{"id": "9", "title": "来杯卡布奇诺吧。", "text": "{'answer': 'ok，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,BrightTable6)\"}'}", "score": "2.2569346"}, {"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "2.2550735"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.114133"}]} +{"id": 10, "question": "我昨天保温杯好像落在你们咖啡厅了，你看到了吗？", "ctxs": [{"id": "10", "title": "我昨天保温杯好像落在你们咖啡厅了，你看到了吗？", "text": "{'answer': '是的，我有印象，保温杯在大厅的2号桌子上。', 'function': 'get_object_info', 'args': '{\"obj\":\"保温杯\"}'}", "score": "1.8863823"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "1.6723425"}, {"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "1.6531497"}]} +{"id": 11, "question": "给我来份午餐套餐。", "ctxs": [{"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.4523244"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.4017403"}, {"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "2.294158"}]} +{"id": 12, "question": "打包吧，快点！", "ctxs": [{"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.9456723"}, {"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.7008219"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "1.6680572"}]} +{"id": 13, "question": "你可以帮我拿来吗，我在前门的桌子前等你。", "ctxs": [{"id": "13", "title": "你可以帮我拿来吗，我在前门的桌子前等你。", "text": "{'answer': '当然，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(VacuumCup,Table1)\"}'}", "score": "2.107453"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.027741"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.0193963"}]} +{"id": 14, "question": "麻烦啦！", "ctxs": [{"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.943545"}, {"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "1.7684793"}, {"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.7008219"}]} +{"id": 15, "question": "大厅的桌子好啊，快带我去呀！", "ctxs": [{"id": "15", "title": "大厅的桌子好啊，快带我去呀！", "text": "{'answer': '好的好的，请跟我来。', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,WaterTable)\"}'}", "score": "2.0067687"}, {"id": "22", "title": "给我来份薯片和果汁，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)\"}'}", "score": "1.7625781"}, {"id": "21", "title": "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Chips,WaterTable),On(NFCJuice,WaterTable)\"}'}", "score": "1.7411622"}]} +{"id": 16, "question": "我想来杯水，帮我孩子拿个酸奶吧。", "ctxs": [{"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.0797672"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.066708"}, {"id": "16", "title": "我想来杯水，帮我孩子拿个酸奶吧。", "text": "{'answer': 'ok，没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Water,WaterTable),On(Yogurt,WaterTable)\"}'}", "score": "2.0554054"}]} +{"id": 17, "question": "来杯酸奶吧。", "ctxs": [{"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "2.3097181"}, {"id": "9", "title": "来杯卡布奇诺吧。", "text": "{'answer': 'ok，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,BrightTable6)\"}'}", "score": "2.2550735"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.2482162"}]} +{"id": 18, "question": "好热呀！太阳也好大！", "ctxs": [{"id": "18", "title": "好热呀！太阳也好大！", "text": "{'answer': '抱歉，我这就去开空调和关窗帘。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(AC,On),Is(Curtain,Off)\"}'}", "score": "2.1915846"}, {"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.6174916"}, {"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.4927042"}]} +{"id": 19, "question": "下班啦！别忘了打扫卫生。", "ctxs": [{"id": "19", "title": "下班啦！别忘了打扫卫生。", "text": "{'answer': '收到！下班啦！', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(Floor,Clean),Is(Table1,Clean),Is(Chairs,Clean),Is(AC,Off),Is(HallLight,Off),Is(TubeLight,Off),Is(Curtain,Off)\"}'}", "score": "2.1349034"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.0114217"}, {"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "1.9978157"}]} +{"id": 20, "question": "请问洗手间在哪里？", "ctxs": [{"id": "20", "title": "请问洗手间在哪里？", "text": "{'answer': '洗手间在这附近', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}", "score": "2.035435"}, {"id": "24", "title": "请问哪里有空位啊？", "text": "{'answer': '现在有不少空位呢，请问您有什么要求嘛？', 'function': None}", "score": "1.8009094"}, {"id": "37", "title": "请问洗手间在哪呢？", "text": "{'answer': '在后门，你们的左侧往里走就是了呢。', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}", "score": "1.6338948"}]} +{"id": 21, "question": "给我来杯酸奶和冰红茶，我坐在对面的桌子那儿。", "ctxs": [{"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "2.0604768"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.0411088"}, {"id": "22", "title": "给我来份薯片和果汁，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)\"}'}", "score": "2.0308568"}]} +{"id": 22, "question": "给我来份薯片和果汁，我坐在对面的桌子那儿。", "ctxs": [{"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "2.060318"}, {"id": "22", "title": "给我来份薯片和果汁，我坐在对面的桌子那儿。", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(BottledDrink,WaterTable),On(Yogurt,WaterTable)\"}'}", "score": "2.0375805"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.033156"}]} +{"id": 23, "question": "好热呀，想开空调，想要温度调低点！", "ctxs": [{"id": "23", "title": "好热呀，想开空调，想要温度调低点！", "text": "{'answer': '抱歉，我马上去开空调并调低空调温度。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(ACTemperature,Down)\"}'}", "score": "1.7416465"}, {"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.6216934"}, {"id": "15", "title": "大厅的桌子好啊，快带我去呀！", "text": "{'answer': '好的好的，请跟我来。', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,WaterTable)\"}'}", "score": "1.4971969"}]} +{"id": 24, "question": "请问哪里有空位啊？", "ctxs": [{"id": "24", "title": "请问哪里有空位啊？", "text": "{'answer': '现在有不少空位呢，请问您有什么要求嘛？', 'function': None}", "score": "2.1733356"}, {"id": "20", "title": "请问洗手间在哪里？", "text": "{'answer': '洗手间在这附近', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}", "score": "1.8009094"}, {"id": "23", "title": "好热呀，想开空调，想要温度调低点！", "text": "{'answer': '抱歉，我马上去开空调并调低空调温度。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(ACTemperature,Down)\"}'}", "score": "1.4684138"}]} +{"id": 25, "question": "我想坐高脚凳子。", "ctxs": [{"id": "25", "title": "我想坐高脚凳子。", "text": "{'answer': '没问题，大厅里就有这样的位置呢！', 'function': None}", "score": "2.4146953"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.239801"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.2386413"}]} +{"id": 26, "question": "你带我去吧。", "ctxs": [{"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.4195614"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.4017403"}, {"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "2.2611532"}]} +{"id": 27, "question": "可以关筒灯和关窗帘吗？", "ctxs": [{"id": "27", "title": "可以关筒灯和关窗帘吗？", "text": "{'answer': '好的，请稍等。', 'function': 'create_sub_task', 'args': '{\"goal\":\"Is(TubeLight,Off),Is(Curtain,Off)\"}'}", "score": "1.7811872"}, {"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "1.4139738"}, {"id": "8", "title": "你们这有什么饮料嘛？", "text": "{'answer': '我们咖啡厅提供各种口味咖啡，水，冰红茶，酸奶等饮品，还提供点心蛋糕等甜品。您想点什么？', 'function': None}", "score": "1.3538787"}]} +{"id": 28, "question": "给我来杯咖啡，哦对，再倒一杯水。", "ctxs": [{"id": "28", "title": "给我来杯咖啡，哦对，再倒一杯水。", "text": "{'answer': '速速就好，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Water,WaterTable),On(Coffee,WaterTable)\"}'}", "score": "2.0709205"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.0688043"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.0623634"}]} +{"id": 29, "question": "我想来份点心和酸奶。", "ctxs": [{"id": "29", "title": "我想来份点心和酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar),On(Dessert,Bar)\"}'}", "score": "2.432145"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.294158"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.2611532"}]} +{"id": 30, "question": "酸奶。", "ctxs": [{"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.4139419"}, {"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "2.2482162"}, {"id": "35", "title": "那还不错。", "text": "{'answer': '是的，那边安静，不会晒到太阳呢。', 'function': None}", "score": "2.2257895"}]} +{"id": 31, "question": "你好呀，你们这有啥好吃的？", "ctxs": [{"id": "31", "title": "你好呀，你们这有啥好吃的？", "text": "{'answer': '我们咖啡厅有咖啡，还有饮料和点心蛋糕呢？您想点什么不？', 'function': None}", "score": "1.7358209"}, {"id": "15", "title": "大厅的桌子好啊，快带我去呀！", "text": "{'answer': '好的好的，请跟我来。', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,WaterTable)\"}'}", "score": "1.6412368"}, {"id": "12", "title": "打包吧，快点！", "text": "{'answer': '请稍等，马上就好！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Dessert,Bar),On(Coffee,Bar)\"}'}", "score": "1.5643499"}]} +{"id": 32, "question": "听起来都好甜呀，我女朋友爱吃水果。", "ctxs": [{"id": "32", "title": "听起来都好甜呀，我女朋友爱吃水果。", "text": "{'answer': '没问题，我们也提供草莓、橘子和苹果等水果呢。', 'function': None}", "score": "2.3256402"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "1.9134985"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "1.9034417"}]} +{"id": 33, "question": "你们这人可真多。", "ctxs": [{"id": "33", "title": "你们这人可真多。", "text": "{'answer': '目前还有空位呢，你们可以坐下来一起品尝水果呢？', 'function': 'get_object_info', 'args': '{\"obj\":\"空位\"}'}", "score": "2.453949"}, {"id": "17", "title": "来杯酸奶吧。", "text": "{'answer': '好的没问题，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,WaterTable)\"}'}", "score": "2.0001283"}, {"id": "9", "title": "来杯卡布奇诺吧。", "text": "{'answer': 'ok，请稍等！', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Coffee,BrightTable6)\"}'}", "score": "1.9580796"}]} +{"id": 34, "question": "我女朋友怕晒，有空余的阴凉位置嘛？", "ctxs": [{"id": "34", "title": "我女朋友怕晒，有空余的阴凉位置嘛？", "text": "{'answer': '我查询完毕，阴凉位置有两个。在你们右侧往里走，就有适合你们二位的沙发呢。', 'function': 'get_object_info', 'args': '{\"obj\":\"阴凉空位\"}'}", "score": "1.9651799"}, {"id": "32", "title": "听起来都好甜呀，我女朋友爱吃水果。", "text": "{'answer': '没问题，我们也提供草莓、橘子和苹果等水果呢。', 'function': None}", "score": "1.7868259"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "1.6948454"}]} +{"id": 35, "question": "那还不错。", "ctxs": [{"id": "35", "title": "那还不错。", "text": "{'answer': '是的，那边安静，不会晒到太阳呢。', 'function': None}", "score": "2.355879"}, {"id": "3", "title": "不用了。", "text": "{'answer': '好的，您有需要再跟我说', 'function': 'stop_serve', 'args': '{}'}", "score": "2.3256633"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "2.2257895"}]} +{"id": 36, "question": "我们还想一起下下棋,切磋切磋。", "ctxs": [{"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "2.2116985"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "2.184878"}, {"id": "36", "title": "我们还想一起下下棋,切磋切磋。", "text": "{'answer': '我们这有两份军棋呢,在大厅的三号桌上。', 'function': 'get_object_info', 'args': '{\"obj\":\"棋\"}'}", "score": "2.1775815"}]} +{"id": 37, "question": "请问洗手间在哪呢？", "ctxs": [{"id": "37", "title": "请问洗手间在哪呢？", "text": "{'answer': '在后门，你们的左侧往里走就是了呢。', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}", "score": "1.6928627"}, {"id": "20", "title": "请问洗手间在哪里？", "text": "{'answer': '洗手间在这附近', 'function': 'get_object_info', 'args': '{\"obj\":\"洗手间\"}'}", "score": "1.6338948"}, {"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.413432"}]} +{"id": 38, "question": "我带着孩子呢，想要宽敞亮堂的地方。", "ctxs": [{"id": "38", "title": "我带着孩子呢，想要宽敞亮堂的地方。", "text": "{'answer': '好的，我明白了，那么我们推荐您到大厅的桌子，那里的空间比较宽敞，环境也比较明亮，适合带着孩子一起用餐。', 'function': None}", "score": "2.1044755"}, {"id": "11", "title": "给我来份午餐套餐。", "text": "{'answer': '本店的午餐套餐包括咖啡和点心，请问您是打包还是堂食？', 'function': None}", "score": "1.9571061"}, {"id": "26", "title": "你带我去吧。", "text": "{'answer': 'OK，请跟我来！', 'function': 'create_sub_task', 'args': '{\"goal\":\"At(Robot,BrightTable5)\"}'}", "score": "1.9560921"}]} +{"id": 39, "question": "冰红茶", "ctxs": [{"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "1.9018158"}, {"id": "39", "title": "冰红茶", "text": "{'answer': '好的', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Softdrink,Bar)\"}'}", "score": "1.8260775"}, {"id": "14", "title": "麻烦啦！", "text": "{'answer': '没事儿，为您服务是我的荣幸！', 'function': None}", "score": "1.6870449"}]} +{"id": 40, "question": "水杯", "ctxs": [{"id": "40", "title": "水杯", "text": "{'answer': '好的', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Glass,Bar)\"}'}", "score": "2.177751"}, {"id": "0", "title": "你好", "text": "{'answer': '您好，我是这家咖啡厅的服务员，请问您要点什么？', 'function': None}", "score": "1.4147856"}, {"id": "30", "title": "酸奶。", "text": "{'answer': '稍等片刻噢~', 'function': 'create_sub_task', 'args': '{\"goal\":\"On(Yogurt,Bar)\"}'}", "score": "1.3056059"}]} diff --git a/robowaiter/algos/retrieval/retrieval_lm/retrieval.py b/robowaiter/algos/retrieval/retrieval_lm/retrieval.py new file mode 100644 index 0000000..ca5ad0f --- /dev/null +++ b/robowaiter/algos/retrieval/retrieval_lm/retrieval.py @@ -0,0 +1,274 @@ +# Copyright (c) Facebook, Inc. and its affiliates. +# All rights reserved. +# +# This source code is licensed under the license found in the +# LICENSE file in the root directory of this source tree. + +import os +import argparse +import csv +import json +import logging +import pickle +import time +import glob +from pathlib import Path + +import numpy as np +import torch +import transformers + +import robowaiter.algos.retrieval.retrieval_lm.src.index +import robowaiter.algos.retrieval.retrieval_lm.src.contriever +import robowaiter.algos.retrieval.retrieval_lm.src.utils +import robowaiter.algos.retrieval.retrieval_lm.src.slurm +import robowaiter.algos.retrieval.retrieval_lm.src.data +from robowaiter.algos.retrieval.retrieval_lm.src.evaluation import calculate_matches +import robowaiter.algos.retrieval.retrieval_lm.src.normalize_text +from robowaiter.algos.retrieval.retrieval_lm import src + + +os.environ["TOKENIZERS_PARALLELISM"] = "true" + + +def embed_queries(args, queries, model, tokenizer): + model.eval() + embeddings, batch_question = [], [] + with torch.no_grad(): + + for k, q in enumerate(queries): + if args.lowercase: + q = q.lower() + if args.normalize_text: + q = src.normalize_text.normalize(q) + batch_question.append(q) + + if len(batch_question) == args.per_gpu_batch_size or k == len(queries) - 1: + + encoded_batch = tokenizer.batch_encode_plus( + batch_question, + return_tensors="pt", + max_length=args.question_maxlength, + padding=True, + truncation=True, + ) + encoded_batch = {k: v for k, v in encoded_batch.items()} + output = model(**encoded_batch) + embeddings.append(output.cpu()) + + batch_question = [] + + embeddings = torch.cat(embeddings, dim=0) + print(f"Questions embeddings shape: {embeddings.size()}") + + return embeddings.numpy() + + +def index_encoded_data(index, embedding_files, indexing_batch_size): + allids = [] + allembeddings = np.array([]) + for i, file_path in enumerate(embedding_files): + print(f"Loading file {file_path}") + with open(file_path, "rb") as fin: + ids, embeddings = pickle.load(fin) + + allembeddings = np.vstack((allembeddings, embeddings)) if allembeddings.size else embeddings + allids.extend(ids) + while allembeddings.shape[0] > indexing_batch_size: + allembeddings, allids = add_embeddings(index, allembeddings, allids, indexing_batch_size) + + while allembeddings.shape[0] > 0: + allembeddings, allids = add_embeddings(index, allembeddings, allids, indexing_batch_size) + + print("Data indexing completed.") + + +def add_embeddings(index, embeddings, ids, indexing_batch_size): + end_idx = min(indexing_batch_size, embeddings.shape[0]) + ids_toadd = ids[:end_idx] + embeddings_toadd = embeddings[:end_idx] + ids = ids[end_idx:] + embeddings = embeddings[end_idx:] + index.index_data(ids_toadd, embeddings_toadd) + return embeddings, ids + + +def validate(data, workers_num): + match_stats = calculate_matches(data, workers_num) + top_k_hits = match_stats.top_k_hits + + print("Validation results: top k documents hits %s", top_k_hits) + top_k_hits = [v / len(data) for v in top_k_hits] + message = "" + for k in [5, 10, 20, 100]: + if k <= len(top_k_hits): + message += f"R@{k}: {top_k_hits[k-1]} " + print(message) + return match_stats.questions_doc_hits + + +def add_passages(data, passages, top_passages_and_scores): + # add passages to original data + merged_data = [] + assert len(data) == len(top_passages_and_scores) + for i, d in enumerate(data): + results_and_scores = top_passages_and_scores[i] + docs = [passages[int(doc_id)] for doc_id in results_and_scores[0]] + scores = [str(score) for score in results_and_scores[1]] + ctxs_num = len(docs) + d["ctxs"] = [ + { + "id": results_and_scores[0][c], + "title": docs[c]["title"], + "text": docs[c]["text"], + "score": scores[c], + } + for c in range(ctxs_num) + ] + + +def add_hasanswer(data, hasanswer): + # add hasanswer to data + for i, ex in enumerate(data): + for k, d in enumerate(ex["ctxs"]): + d["hasanswer"] = hasanswer[i][k] + + +def load_data(data_path): + if data_path.endswith(".json"): + with open(data_path, "r") as fin: + data = json.load(fin) + elif data_path.endswith(".jsonl"): + data = [] + with open(data_path, "r",encoding='utf-8') as fin: + for k, example in enumerate(fin): + example = json.loads(example) + data.append(example) + return data + +parser = argparse.ArgumentParser() + +parser.add_argument( + "--data", + type=str, + default=None, + help=".json file containing question and answers, similar format to reader data", +) +parser.add_argument("--passages", type=str, default=None, help="Path to passages (.tsv file)") +parser.add_argument("--passages_embeddings", type=str, default=None, help="Glob path to encoded passages") +parser.add_argument( + "--output_dir", type=str, default=None, help="Results are written to outputdir with data suffix" +) +parser.add_argument("--n_docs", type=int, default=3, help="Number of documents to retrieve per questions") +parser.add_argument( + "--validation_workers", type=int, default=32, help="Number of parallel processes to validate results" +) +parser.add_argument("--per_gpu_batch_size", type=int, default=64, help="Batch size for question encoding") +parser.add_argument( + "--save_or_load_index", action="store_true", help="If enabled, save index and load index if it exists" +) +parser.add_argument( + "--model_name_or_path", type=str, help="path to directory containing model weights and config file" +) +parser.add_argument("--no_fp16", action="store_true", help="inference in fp32") +parser.add_argument("--question_maxlength", type=int, default=512, help="Maximum number of tokens in a question") +parser.add_argument( + "--indexing_batch_size", type=int, default=1000000, help="Batch size of the number of passages indexed" +) +parser.add_argument("--projection_size", type=int, default=768) +parser.add_argument( + "--n_subquantizers", + type=int, + default=0, + help="Number of subquantizer used for vector quantization, if 0 flat index is used", +) +parser.add_argument("--n_bits", type=int, default=8, help="Number of bits per subquantizer") +parser.add_argument("--lang", nargs="+") +parser.add_argument("--dataset", type=str, default="none") +parser.add_argument("--lowercase", action="store_true", help="lowercase text before encoding") +parser.add_argument("--normalize_text", action="store_true", help="normalize text") + +args = parser.parse_args() +#src.slurm.init_distributed_mode(args) +from robowaiter.utils.basic import get_root_path +retrieval_lm_path = f'{get_root_path()}/robowaiter/algos/retrieval/retrieval_lm' +args.model_name_or_path = f"{retrieval_lm_path}/../contriever-msmarco" +args.passages_embeddings = f'{retrieval_lm_path}/robot_embeddings/*' +args.no_fp16 = True +args.passages = f"{retrieval_lm_path}/fix_questions.jsonl" + +class Retrieval(): + + def __init__(self, threshold): + print(f"Loading model from: {args.model_name_or_path}") + model, tokenizer, _ = src.contriever.load_retriever(args.model_name_or_path) + model.eval() + #model = model.cuda() + if not args.no_fp16: + model = model.half() + self.model = model + self.tokenizer = tokenizer + self.threshold = threshold + index = src.index.Indexer(args.projection_size, args.n_subquantizers, args.n_bits) + self.index = index + + # index all passages + input_paths = glob.glob(args.passages_embeddings) + input_paths = sorted(input_paths) + embeddings_dir = os.path.dirname(input_paths[0]) + index_path = os.path.join(embeddings_dir, "index.faiss") + if args.save_or_load_index and os.path.exists(index_path): + index.deserialize_from(embeddings_dir) + else: + print(f"Indexing passages from files {input_paths}") + start_time_indexing = time.time() + index_encoded_data(index, input_paths, args.indexing_batch_size) + print(f"Indexing time: {time.time()-start_time_indexing:.1f} s.") + if args.save_or_load_index: + index.serialize(embeddings_dir) + + # load passages + passages = src.data.load_passages(args.passages) + passage_id_map = {x["id"]: x for x in passages} + self.passage_id_map = passage_id_map + + def get_result(self, queries): + questions_embedding = embed_queries(args, [queries], self.model, self.tokenizer) + top_ids_and_scores = self.index.search_knn(questions_embedding, args.n_docs) + print(top_ids_and_scores) + data = [{"question":queries}] + add_passages(data, self.passage_id_map, top_ids_and_scores) + + if float(data[0]["ctxs"][0]["score"]) >= self.threshold: + result_dict = eval(data[0]["ctxs"][0]["text"]) + result_dict["question"] = queries + return result_dict + else: + return None + # data_paths = glob.glob(args.data) + # alldata = [] + # for path in data_paths: + # data = load_data(path) + # output_path = os.path.join(args.output_dir, os.path.basename(path)) + # + # queries = [ex["question"] for ex in data] + # + # # get top k results + # start_time_retrieval = time.time() + # print(f"Search time: {time.time()-start_time_retrieval:.1f} s.") + # + # add_passages(data, passage_id_map, top_ids_and_scores) + # #hasanswer = validate(data, args.validation_workers) + # #add_hasanswer(data, hasanswer) + # os.makedirs(os.path.dirname(output_path), exist_ok=True) + # with open(output_path, "w",encoding='utf-8') as fout: + # for ex in data: + # json.dump(ex, fout, ensure_ascii=False) + # fout.write("\n") + # print(f"Saved results to {output_path}") + +if __name__ == '__main__': + r = Retrieval(1.8) + print(r.get_result("来一号桌")) + print(r.get_result("去二号桌")) + print(r.get_result("去三号桌")) diff --git a/robowaiter/algos/retrieval/retrieval_lm/robot_embeddings/passages_00 b/robowaiter/algos/retrieval/retrieval_lm/robot_embeddings/passages_00 index 8fcf491..f531ebb 100644 Binary files a/robowaiter/algos/retrieval/retrieval_lm/robot_embeddings/passages_00 and b/robowaiter/algos/retrieval/retrieval_lm/robot_embeddings/passages_00 differ diff --git a/robowaiter/algos/retrieval/retrieval_lm/run_retri_All_In_One.py b/robowaiter/algos/retrieval/retrieval_lm/run_retri_All_In_One.py index 66551e8..872ca86 100644 --- a/robowaiter/algos/retrieval/retrieval_lm/run_retri_All_In_One.py +++ b/robowaiter/algos/retrieval/retrieval_lm/run_retri_All_In_One.py @@ -1,14 +1,24 @@ import os +from robowaiter.algos.retrieval.retrieval_lm.question2jsonl import question2jsonl,question2jsonl_test -path_goal_states_with_description = os.path.join('../../../behavior_tree/dataset/goal_states_with_description.jsonl') +file_path = "fix_questions.txt" +output_path = "fix_questions.jsonl" +output_test_path = "fix_questions_test.jsonl" -cmd_goal_states_with_descrip_to_train = f' .\process_json.py --passages {path_goal_states_with_description} --mode train' -cmd_goal_states_with_descrip_to_test = f" .\process_json.py --passages .\\train_robot.jsonl --mode test" -cmd_get_embedding = f" generate_passage_embeddings.py --model_name_or_path ../contriever-msmarco --passages train_robot.jsonl --output_dir robot_embeddings --shard_id 0 --num_shards 1 --per_gpu_batch_size 500 --no_fp16" -cmd_test_retri = f" passage_retrieval2.py --data test_robot.jsonl --model_name_or_path ../contriever-msmarco --passages train_robot.jsonl --passages_embeddings \"robot_embeddings/*\" --output_dir retr_result --n_docs 3 --no_fp16" +question2jsonl(file_path,output_path) +question2jsonl_test(file_path,output_test_path) -conda_path = os.path.join("C:/Users/Estrella/.conda/envs/py310/python.exe") -os.system(conda_path + cmd_goal_states_with_descrip_to_train) -os.system(conda_path + cmd_goal_states_with_descrip_to_test) -os.system(conda_path + cmd_get_embedding) -os.system(conda_path + cmd_test_retri) +# path_goal_states_with_description = os.path.join('../../../behavior_tree/dataset/goal_states_with_description.jsonl') +# +# cmd_goal_states_with_descrip_to_train = f' .\process_json.py --passages {path_goal_states_with_description} --mode train' + + +# cmd_goal_states_with_descrip_to_test = f" .\process_json.py --passages .\\train_robot.jsonl --mode test" +cmd_get_embedding = f" generate_passage_embeddings.py --model_name_or_path ../contriever-msmarco --passages {output_path} --output_dir robot_embeddings --shard_id 0 --num_shards 1 --per_gpu_batch_size 500 --no_fp16" +cmd_test_retri = f" passage_retrieval2.py --data {output_test_path} --model_name_or_path ../contriever-msmarco --passages {output_path} --passages_embeddings \"robot_embeddings/*\" --output_dir retr_result --n_docs 3 --no_fp16" + +# conda_path = os.path.join("C:/Users/Estrella/.conda/envs/py310/python.exe") +# os.system(conda_path + cmd_goal_states_with_descrip_to_train) +# os.system(conda_path + cmd_goal_states_with_descrip_to_test) +os.system("python " + cmd_get_embedding) +os.system("python " + cmd_test_retri) diff --git a/robowaiter/algos/retrieval/retrieval_lm/src/contriever.py b/robowaiter/algos/retrieval/retrieval_lm/src/contriever.py index 14b6cff..10ea129 100644 --- a/robowaiter/algos/retrieval/retrieval_lm/src/contriever.py +++ b/robowaiter/algos/retrieval/retrieval_lm/src/contriever.py @@ -5,7 +5,7 @@ import torch import transformers from transformers import BertModel, XLMRobertaModel -from src import utils +from robowaiter.algos.retrieval.retrieval_lm.src import utils class Contriever(BertModel): diff --git a/robowaiter/algos/retrieval/retrieval_lm/src/data.py b/robowaiter/algos/retrieval/retrieval_lm/src/data.py index 5938f37..ead3685 100644 --- a/robowaiter/algos/retrieval/retrieval_lm/src/data.py +++ b/robowaiter/algos/retrieval/retrieval_lm/src/data.py @@ -12,7 +12,7 @@ import logging from collections import defaultdict import torch.distributed as dist -from src import dist_utils +from robowaiter.algos.retrieval.retrieval_lm.src import dist_utils logger = logging.getLogger(__name__) diff --git a/robowaiter/algos/retrieval/retrieval_lm/src/utils.py b/robowaiter/algos/retrieval/retrieval_lm/src/utils.py index 66b9623..3ecefa2 100644 --- a/robowaiter/algos/retrieval/retrieval_lm/src/utils.py +++ b/robowaiter/algos/retrieval/retrieval_lm/src/utils.py @@ -8,7 +8,7 @@ import errno from typing import Union, Tuple, List, Dict from collections import defaultdict -from src import dist_utils +from robowaiter.algos.retrieval.retrieval_lm.src import dist_utils Number = Union[float, int] diff --git a/robowaiter/behavior_lib/_base/Behavior.py b/robowaiter/behavior_lib/_base/Behavior.py index 7051e10..5bfcff3 100644 --- a/robowaiter/behavior_lib/_base/Behavior.py +++ b/robowaiter/behavior_lib/_base/Behavior.py @@ -56,6 +56,35 @@ class Bahavior(ptree.behaviour.Behaviour): 'BrightTable6': (5, -315, 116.5), } + place_have_obj_xyz_dic = { + 'QuietTable1': (480, 1300, 70), + 'QuietTable2': (250, -240, 70), + 'BrightTable1': (230, 1200, 35), + 'BrightTable2': (65, 1000, 35), + 'BrightTable3': (-80, 850, 35), + 'BrightTable4': (-270, 520, 70), + 'BrightTable5': (-270, 420, 35) + } + place_have_obj_xyz_dic.update(place_xyz_dic) + + place_en2zh_name={ + 'Bar': "吧台", + 'Bar2': "另一侧的吧台", + 'WaterTable': "大厅的茶水桌", + 'CoffeeTable': "咖啡桌", + 'Table1': "前门的斜桌子", + 'Table2': "大厅长桌子", + 'Table3': "大厅长桌子", + 'BrightTable6': "后门靠窗边圆桌", + 'QuietTable1': "前门角落双人圆桌", + 'QuietTable2': "后门角落三人圆桌", + 'BrightTable1': "靠窗边第一个四人矮桌", + 'BrightTable2': "靠窗边第二个四人矮桌", + 'BrightTable3': "靠窗边第三个四人矮桌", + 'BrightTable4': "大厅里靠窗边长桌子", + 'BrightTable5': "大厅里靠窗边多人矮桌", + } + place_xy_yaw_dic={ 'Bar': (247.0, 520.0, 180), # (247.0, 520.0, 100.0) 'Bar2': (240.0, 40.0, 100.0), diff --git a/robowaiter/behavior_lib/act/DealChat.py b/robowaiter/behavior_lib/act/DealChat.py index 4b074bd..a0345ee 100644 --- a/robowaiter/behavior_lib/act/DealChat.py +++ b/robowaiter/behavior_lib/act/DealChat.py @@ -1,13 +1,21 @@ import py_trees as ptree from robowaiter.behavior_lib._base.Act import Act -from robowaiter.llm_client.multi_rounds import ask_llm, new_history +from robowaiter.llm_client.multi_rounds_retri import ask_llm, new_history import random from collections import deque +from translate import Translator + + +translator = Translator(to_lang="zh") +translator.from_lang = 'en' +translator.to_lang = 'zh-cn' + +import spacy +nlp = spacy.load('en_core_web_lg') +nlp_zh = spacy.load('zh_core_web_lg') -# import spacy -# nlp = spacy.load('en_core_web_lg') class History(deque): def __init__(self,scene,customer_name): @@ -29,7 +37,8 @@ class DealChat(Act): "create_sub_task": self.create_sub_task, "stop_serve": self.stop_serve, "get_object_info": self.get_object_info, - "find_location": self.find_location + # "find_location": self.find_location, + "get_number_of_objects": self.get_number_of_objects, } def _update(self) -> ptree.common.Status: @@ -63,6 +72,12 @@ class DealChat(Act): return ptree.common.Status.RUNNING + def obj_name_en2zh(self,obj): + obj = obj.replace("_", " ") + obj = translator.translate(obj) #转成中文 + print("====obj:=======",obj) + return obj + def create_sub_task(self, **args): try: goal = args['goal'] @@ -84,76 +99,179 @@ class DealChat(Act): def get_object_info(self,**args): try: obj = args['obj'] - self.function_success = True except: obj = None print("参数解析错误") + d = {"保温杯": "二号桌子"} if obj in d.keys(): result = d[obj] else: - result = "None" + result = "没有" return result - # max_similarity = 0.02 - # similar_word = None + + # 先把 obj 转成中文 + + # 写死的内容 + if obj in d.keys(): + near_object = d[obj] + near_object = f"{obj}在{near_object}附近" + obj_id = 0 + else: # 根据相似性查找物品位置 + obj = self.obj_name_en2zh(obj) + + max_similarity = 0.02 + similar_word = None + + # 场景中现有物品 + cur_things = set() + for item in self.scene.status.objects: + cur_things.add(self.scene.objname_en2zh_dic[item.name]) + # obj与现有物品进行相似度匹配 中文的匹配 + print("==========obj==========:",obj) + query_token = nlp_zh(obj) + for w in cur_things: + word_token = nlp_zh(w) + similarity = query_token.similarity(word_token) + print("similarity:", similarity, w) + if similarity > max_similarity: + max_similarity = similarity + similar_word = w + if similar_word: + 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 + # 找到距离最近的物品 + similar_word_en = self.scene.objname_zh2en_dic[similar_word] + obj_dict = self.scene.status.objects + if len(obj_dict)!=0: + + for id, obji in enumerate(obj_dict): + if obji.name == similar_word_en: + obj_info = obj_dict[id] + objx,objy,objz = obj_info.location.X, obj_info.location.Y, obj_info.location.Z + break + + # 获取离它最近的物品 + # min_dis = float('inf') + # obj_id = -1 + # near_object = None + # for id,obji in enumerate(obj_dict): + # if obji.name != similar_word_en: + # obj_info = obj_dict[id] + # dis = self.scene.getDistanc3D((obj_info.location.X, obj_info.location.Y, obj_info.location.Z),(objx,objy,objz)) + # if dis 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: - # 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 = "Door" - # - # return near_object - # - def find_location(self, **args): + # mp = list(self.scene.loc_map_en[similar_word]) + # near_location = random.choice(mp) + # return near_location + + def get_number_of_objects(self,**args): try: - location = args['obj'] + obj = args['obj'] self.function_success = True + obj = self.obj_name_en2zh(obj) except: obj = None print("参数解析错误") - d = {"保温杯": "二号桌子"} - if location in d.keys(): - result = d[obj] + # 找到最近的中文 + max_similarity = 0.02 + similar_word = None + + # obj 是中文 + # obj = translator.translate(obj) #转成中文 + # print("obj:",obj) + query_token = nlp_zh(obj) + for real_obj_name in self.scene.objname_zh2en_dic.keys(): # 在中文名字里面找 + word_token = nlp_zh(real_obj_name) + similarity = query_token.similarity(word_token) + # print("similarity:",similarity,real_obj_name) + if similarity > max_similarity: + max_similarity = similarity + similar_word = real_obj_name + if similar_word: + print("max_similarity:",max_similarity,"similar_word:",similar_word) + + count = 0 + similar_word_en = self.scene.objname_zh2en_dic[similar_word] + if similar_word_en != "Customer": + for item in self.scene.status.objects: + if item.name == similar_word_en: + count+=1 else: - result = "None" - return result - # 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.scene.all_loc_en: - # word_token = nlp(w) + count = len(self.scene.status.walkers) + + # obj 是英文 + # query_token = nlp(obj) + # for real_obj_name in self.scene.objname_en2zh_dic.keys(): # 在中文名字里面找 + # word_token = nlp(real_obj_name) # similarity = query_token.similarity(word_token) + # print("similarity:",similarity,real_obj_name) # 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 + # similar_word = real_obj_name # if similar_word: - # mp = list(self.scene.loc_map_en[similar_word]) - # near_location = random.choice(mp) - # return near_location + # print("max_similarity:",max_similarity,"similar_word:",similar_word) + return count + + def stop_serve(self,**args): customer = self.scene.state["attention"]["customer"] diff --git a/robowaiter/behavior_lib/act/DealChatNLP.py b/robowaiter/behavior_lib/act/DealChatNLP.py deleted file mode 100644 index 37045c4..0000000 --- a/robowaiter/behavior_lib/act/DealChatNLP.py +++ /dev/null @@ -1,140 +0,0 @@ -import py_trees as ptree -from robowaiter.behavior_lib._base.Act import Act - -from robowaiter.llm_client.multi_rounds import ask_llm, new_history -import random - - - -class DealChatNLP(Act): - def __init__(self): - super().__init__() - self.chat_history = "" - self.function_success = False - self.func_map = { - "create_sub_task": self.create_sub_task, - "stop_serve": self.stop_serve, - "get_object_info": self.get_object_info, - "find_location": self.find_location - } - - def _update(self) -> ptree.common.Status: - # if self.scene.status? - name, sentence = self.scene.state['chat_list'].pop(0) - - if name == "Goal": - self.create_sub_task(goal=sentence) - return ptree.common.Status.RUNNING - - if name not in self.scene.state["chat_history"]: - self.scene.state["chat_history"][name] = new_history() - - history = self.scene.state["chat_history"][name] - self.scene.state["attention"]["customer"] = name - self.scene.state["serve_state"] = { - "last_chat_time": self.scene.time, - } - - function_call, response = ask_llm(sentence,history,func_map=self.func_map) - - - self.scene.chat_bubble(response) # 机器人输出对话 - - return ptree.common.Status.RUNNING - - - def create_sub_task(self, **args): - try: - goal = args['goal'] - - w = goal.split(")") - goal_set = set() - goal_set.add(w[0] + ")") - if len(w) > 1: - for x in w[1:]: - if x != "": - goal_set.add(x[1:] + ")") - self.function_success = True - except: - print("参数解析错误") - - self.scene.robot.expand_sub_task_tree(goal_set) - - def get_object_info(self,**args): - - import spacy - nlp = spacy.load('en_core_web_lg') - - try: - obj = args['obj'] - - self.function_success = True - except: - obj = None - print("参数解析错误") - - near_object = "None" - - max_similarity = 0.02 - similar_word = None - - # 场景中现有物品 - cur_things = set() - for item in self.scene.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 cur_things: - word_token = nlp(w) - similarity = query_token.similarity(word_token) - if similarity > max_similarity: - max_similarity = similarity - similar_word = w - if similar_word: - 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 = "Door" - - return near_object - - def find_location(self, **args): - - import spacy - nlp = spacy.load('en_core_web_lg') - - 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.scene.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.scene.loc_map_en[similar_word]) - near_location = random.choice(mp) - return near_location - - def stop_serve(self,**args): - - - return "好的" - - diff --git a/robowaiter/behavior_tree/dataset/expansion_out/output2.txt b/robowaiter/behavior_tree/dataset/expansion_out/output2.txt new file mode 100644 index 0000000..9c06989 --- /dev/null +++ b/robowaiter/behavior_tree/dataset/expansion_out/output2.txt @@ -0,0 +1,57 @@ +At(Robot,Bar) 请问您需要什么帮助吗？我就在吧台附近，能否请您自己过来呢？ +At(Robot,Bar) 请问你能去一下吧台吗？ +At(Robot,Bar) 请问你能帮我到吧台那个位置吗？ +At(Robot,WaterTable) 请问你能过来一下吗？我正在茶水桌旁。 +At(Robot,WaterTable) 请问你可以去茶水桌一下吗？ +At(Robot,WaterTable) 你能带路去茶水桌吗？ +At(Robot,CoffeeTable) 请问你可以过来一下吗？我在这张咖啡桌旁边。 +At(Robot,CoffeeTable) 请问你可以帮我一下，去一下咖啡桌吗？ +At(Robot,CoffeeTable) 请问你能帮我前往咖啡桌那个位置吗？ +At(Robot,Bar2) 您好，请问您需要什么帮助吗？我正在另一个吧台处理一些事情。 +At(Robot,Bar2) 请问你可以去一下另一个吧台吗？ +At(Robot,Bar2) 你能去另一个吧台的位置吗？ +At(Robot,Table1) 请问你能过来一下吗？我目前在第一桌，需要你的帮助。 +At(Robot,Table1) 请问你能去一下第一桌吗？ +At(Robot,Table1) 请问你能帮我到第一张桌子那个位置吗？ +At(Robot,Table2) 请问您能过来一下吗？我正在第二张桌子这里。 +At(Robot,Table2) 请问你可以去第二张桌子一下吗？ +At(Robot,Table2) 请问你能帮我前往第二桌吗？ +At(Robot,Table3) 请问你能过来一下吗？我正在第三张桌子旁。 +At(Robot,Table3) 请问你能去第三张桌子一下吗？ +At(Robot,Table3) 你能告诉我第三张桌子的位置在哪里吗？ +On(Softdrink,Bar) 您好，请问您需要我帮您把盒装冰红茶放到哪个位置呢？ +On(Softdrink,Bar) 服务员，能否帮我拿来一盒冰红茶放到吧台呢？ +On(Softdrink,WaterTable) 您好，请问您需要我帮忙将盒装冰红茶放到哪个位置吗？ +On(Softdrink,WaterTable) 服务员，能否帮我把盒装冰红茶拿到茶水桌呢？ +On(Softdrink,CoffeeTable) 请问你能把盒装冰红茶放到咖啡桌那个位置吗？ +On(Softdrink,CoffeeTable) 服务员，把盒装冰红茶拿到咖啡桌 position 好吗？ +On(Softdrink,Bar2) 请问你能把盒装冰红茶放到另一个吧台的位置吗？ +On(Softdrink,Bar2) 请问你能把盒装冰红茶拿到另一个吧台位置吗？ +On(Softdrink,Table1) 请问您能否把盒装冰红茶放在第一桌的指定位置呢？ +On(Softdrink,Table1) 请您把盒装冰红茶拿到第一桌的位置。 +On(Softdrink,Table2) 服务员，您好，请问能否帮我將這盒裝冰红茶放 到第二張桌子那個位置呢？ +On(Softdrink,Table2) 服务员，请把盒装冰红茶拿到第二张桌子的位置。 +On(Softdrink,Table3) 请问你可以把盒装冰红茶放到第三张桌子的那个位置吗？ +On(Softdrink,Table3) 请问你能把盒装冰红茶拿到第三张桌子的位置吗？ +On(BottledDrink,Bar) 您好，请问您需要我将瓶装饮料放到哪个位置呢？ +On(BottledDrink,Bar) 请把瓶装饮料拿到吧台的位置。 +On(BottledDrink,WaterTable) 请问你可以把瓶装饮料放到茶水桌那个位置吗？ +On(BottledDrink,WaterTable) 请问你能把瓶装饮料拿到茶水桌位置吗？ +On(BottledDrink,CoffeeTable) 服务员，能否把瓶装饮料放在咖啡桌那个位置呢？ +On(BottledDrink,CoffeeTable) 服务员，能否把瓶装饮料拿到咖啡桌附近呢？ +On(BottledDrink,Bar2) 请问你能把瓶装饮料放到另一个吧台的那个位置吗？ +On(BottledDrink,Bar2) 请把瓶装饮料拿到另一个吧台位置。 +On(BottledDrink,Table1) 请问您能否帮我將瓶裝飲料放至第一張桌子的那個位置呢？ +On(BottledDrink,Table1) 请问你能把瓶装饮料拿到第一桌的位置吗？ +On(BottledDrink,Table2) 请问，你可以把瓶装饮料放到第二张桌子的那个位置吗？ +On(BottledDrink,Table2) 请问你能把瓶装饮料拿到第二张桌子的位置吗？ +On(BottledDrink,Table3) 请问，你能把瓶装饮料放到第三桌的哪个位置吗？ +On(BottledDrink,Table3) 请问你能把瓶装饮料拿到第三张桌子的位置吗？ +On(Yogurt,Bar) 请问你能把酸奶放到吧台那个位置吗？ +On(Yogurt,Bar) 请问你能把酸奶拿到吧台位置吗？ +On(Yogurt,WaterTable) 请问你能把酸奶放到茶水桌那个位置吗？ +On(Yogurt,WaterTable) 服务员，请把酸奶拿到茶水桌的位置。 +On(Yogurt,CoffeeTable) 请问，你能把酸奶放在咖啡桌那个位置吗？ +On(Yogurt,CoffeeTable) 服务员，能否把酸奶拿到咖啡桌的位置呢？ +On(Yogurt,Bar2) 请问你能把酸奶放到另一个吧台的那个位置吗？ +On(Yogurt,Bar2) 请问你能把酸奶拿到另一个吧台位置吗？ diff --git a/robowaiter/behavior_tree/dataset/sentence_expansion.py b/robowaiter/behavior_tree/dataset/sentence_expansion.py index edf8e6f..5cd2be4 100644 --- a/robowaiter/behavior_tree/dataset/sentence_expansion.py +++ b/robowaiter/behavior_tree/dataset/sentence_expansion.py @@ -1,6 +1,8 @@ import os import requests import urllib3 +from tqdm import tqdm + ######################################## # 该文件实现了与大模型的简单通信 ######################################## @@ -9,23 +11,28 @@ import urllib3 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) -def single_round(question,prefix=""): +def single_round(question, prefix=""): url = "https://45.125.46.134:25344/v1/chat/completions" headers = {"Content-Type": "application/json"} data = { "model": "RoboWaiter", "messages": [ - { - "role": "system", - # "content": "你是一个机器人服务员：RoboWaiter. 你的职责是为顾客提供对话及具身服务。" - "content": "请将以下你对咖啡厅服务员说的话改写成更清晰更合理的顾客表述。" - }, - { - "role": "user", - "content": prefix + question - } + { + "role": "system", + # "content": "你是一个机器人服务员：RoboWaiter. 你的职责是为顾客提供对话及具身服务。" + "content": """ + 假设现在你是咖啡厅的一个顾客，请将以下你对咖啡厅服务员说的话改写成更清晰更合理的顾客表述。注意：句中的你指的是咖啡厅服务员，也不要说能帮我。 + 例如：麻烦你去一下吧台。可以转述成：服务员，你能去下吧台吗？ + 另一个例子：请你拿一下酸奶到吧台位置。可以转述成：服务员，拿一杯酸奶来吧台。 + + """ + }, + { + "role": "user", + "content": prefix + question + } ] - } + } response = requests.post(url, headers=headers, json=data, verify=False) @@ -37,14 +44,18 @@ def single_round(question,prefix=""): if __name__ == '__main__': - with open('goal_states_with_description.txt', 'r', encoding='utf-8') as file: + with open('./goal_states_with_description.txt', 'r', encoding='utf-8') as file: lines = file.readlines() - for line in lines: + + output_file = './expansion_out/output2.txt' + with open(output_file, 'a', encoding='utf-8') as file: + file.truncate(0) + for line in tqdm(lines): tmp = line[:-1].split('\t') - #file.write("""{"title":"%s","text":"%s"}\n""" % (tmp[1], tmp[0])) + # file.write("""{"title":"%s","text":"%s"}\n""" % (tmp[1], tmp[0])) question = tmp[1] - #print(single_round(question)) - #print(tmp[1]) - with open('output1.txt', 'a',encoding='utf-8') as file: - file.write(tmp[0]+"\t"+single_round(question)+'\n') - print("输出完成") \ No newline at end of file + # print(single_round(question)) + # print(tmp[1]) + with open(output_file, 'a', encoding='utf-8') as file: + file.write(tmp[0] + "\t" + single_round(question, prefix="现在改写一下句子：") + '\n') + print("输出完成") diff --git a/robowaiter/llm_client/multi_rounds.py b/robowaiter/llm_client/multi_rounds.py index ba53af9..8b30290 100644 --- a/robowaiter/llm_client/multi_rounds.py +++ b/robowaiter/llm_client/multi_rounds.py @@ -1,10 +1,8 @@ -import json import time 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 @@ -92,7 +90,7 @@ def get_response(sentence, history, allow_function_call = True): if sentence in fix_questions_dict: time.sleep(2) - return parse_fix_question(sentence) + return True, parse_fix_question(sentence) params = dict(model="RoboWaiter") params['messages'] = role_system + list(history) @@ -102,7 +100,7 @@ def get_response(sentence, history, allow_function_call = True): response = requests.post(f"{base_url}/v1/chat/completions", json=params, stream=False, verify=False) decoded_line = response.json() - return decoded_line + return False, decoded_line def deal_response(response, history, func_map=None ): if response["choices"][0]["message"].get("function_call"): @@ -145,7 +143,7 @@ def deal_response(response, history, func_map=None ): def ask_llm(question,history, func_map=None, retry=3): - response = get_response(question, history) + fixed, response = get_response(question, history) function_call,result = deal_response(response, history, func_map) if function_call: @@ -163,7 +161,7 @@ def ask_llm(question,history, func_map=None, retry=3): history.append(message) else: - response = get_response(None, history,allow_function_call=False) + fixed, response = get_response(None, history,allow_function_call=False) _,result = deal_response(response, history, func_map) diff --git a/robowaiter/llm_client/multi_rounds_retri.py b/robowaiter/llm_client/multi_rounds_retri.py new file mode 100644 index 0000000..ec30512 --- /dev/null +++ b/robowaiter/llm_client/multi_rounds_retri.py @@ -0,0 +1,181 @@ +import time + +import openai +from colorama import init, Fore +from loguru import logger +from robowaiter.llm_client.tool_register import get_tools, dispatch_tool +import requests +import json +from collections import deque + +import urllib3 +import copy +init(autoreset=True) +from robowaiter.utils import get_root_path +import os +import re +from robowaiter.llm_client.single_round import single_round +from robowaiter.algos.retrieval.retrieval_lm.retrieval import Retrieval +######################################## +# 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 + +root_path = get_root_path() +# load test questions +# file_path = os.path.join(root_path,"robowaiter/llm_client/data/fix_questions.txt") +# +# fix_questions_dict = {} +# no_reply_functions = ["create_sub_task"] +# + + +functions = get_tools() +retrieval = Retrieval(threshold=1.8) + + +role_system = [{ + "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。如果顾客问你们这里有什么，或者想要点单，你说我们咖啡厅提供咖啡，水，点心，酸奶等食物。如果顾客不需要你了，你就回到吧台招待。如果顾客叫你去做某事，你回复：好的，我马上去做这件事。", + }] + +def new_history(max_length=7): + history = deque(maxlen=max_length) + + return history + +def new_response(): + return {'choices': [{'index': 0, 'message':{} }]} + +def parse_fix_question(question): + response = new_response() + fix_ans = question + if not fix_ans['function']: #简单对话 + message = {'role': 'assistant', 'content': fix_ans["answer"], 'name': None, + 'function_call': None} + else: + func = fix_ans["function"] + args = fix_ans["args"] + # tool_response = dispatch_tool(function_call["name"], json.loads(args)) + # logger.info(f"Tool Call Response: {tool_response}") + message = {'role': 'assistant', + 'content': f"\n <|assistant|> {func}({args})\n ```python\ntool_call(goal={args})\n```", + 'name': None, + 'function_call': {'name': func, 'arguments': args}} + + response["choices"][0]["message"] = message + return response, question["answer"] + +def get_response(sentence, history, allow_function_call = True): + if sentence: + history.append({"role": "user", "content": sentence}) + + retrieval_result = retrieval.get_result(sentence) + if retrieval_result is not None: + time.sleep(1.2) + # 处理多轮 + if retrieval_result["answer"] == "multi_rounds" and len(history) >= 2: + print("触发多轮检索") + last_content = "" + for i in range(-2,-len(history)): + if history[i]["role"] == "user": + last_content = history[i]["content"] + break + retrieval_result = retrieval.get_result(last_content + sentence) + if retrieval_result is not None: + response, answer = parse_fix_question(retrieval_result) + return True,response, answer + + params = dict(model="RoboWaiter") + params['messages'] = role_system + list(history) + if allow_function_call: + params["functions"] = functions + + + response = requests.post(f"{base_url}/v1/chat/completions", json=params, stream=False, verify=False) + decoded_line = response.json() + return False, decoded_line, None + +def deal_response(response, history, func_map=None ): + 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_name = function_call["name"] + function_args = json.loads(function_call["arguments"]) + if func_map: + tool_response = func_map[function_name](**function_args) + else: + try: + tool_response = dispatch_tool(function_call["name"], function_args) + logger.info(f"Tool Call Response: {tool_response}") + except: + logger.info(f"重试工具调用") + # tool_response = dispatch_tool(function_call["name"], function_args) + return function_name,None + + return_message = response["choices"][0]["message"] + + history.append(return_message) + t = { + "role": "function", + "name": function_call["name"], + "content": str(tool_response), # 调用函数返回结果 + } + + history.append(t) + return function_call["name"], tool_response + + else: + return_message = response["choices"][0]["message"] + reply = return_message["content"] + + history.append(return_message) + logger.info(f"Final Reply: \n{reply}") + + return False, reply + + +def ask_llm(question,history, func_map=None, retry=3): + fixed, response, answer = get_response(question, history) + + print(f"response: {response}") + + function_call,result = deal_response(response, history, func_map) + + if function_call: + if fixed: + if function_call == "create_sub_task": + result = single_round(answer, + "你是机器人服务员，请把以下句子换一种表述方式对顾客说，但是意思不变，尽量简短：\n") + # elif function_call in ["get_object_info","find_location"] : + else: + result = single_round(f"你是机器人服务员，顾客想知道{question}, 你的具身场景查询返回的是{result},把返回的英文名词翻译成中文,请把按照以下句子对顾客说，{answer}, 尽量简短。\n") + + message = {'role': 'assistant', 'content': result, 'name': None, + 'function_call': None} + history.append(message) + else: + _,response,_ = get_response(None, history,allow_function_call=False) + _,result = deal_response(response, history, func_map) + + + print(f'{len(history)}条历史记录:') + for x in history: + print(x) + return function_call, result + +if __name__ == "__main__": + question = input("\n顾客：") + history = new_history() + n = 1 + max_retry = 2 + + while question != 'end': + function_call, return_message = ask_llm(question,history) + + question = input("\n顾客：") diff --git a/robowaiter/llm_client/passage_retrieval3.py b/robowaiter/llm_client/passage_retrieval3.py index 693b072..5b5291b 100644 --- a/robowaiter/llm_client/passage_retrieval3.py +++ b/robowaiter/llm_client/passage_retrieval3.py @@ -233,6 +233,7 @@ def get_answer(): answer = example["ctxs"][0]["text"] score = example["ctxs"][0]["score"] return score, answer + def retri(query): get_json(query) parser = argparse.ArgumentParser() diff --git a/robowaiter/llm_client/retrieval/__init__.py b/robowaiter/llm_client/retrieval/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/robowaiter/llm_client/retrieval/create_embeding.bat b/robowaiter/llm_client/retrieval/create_embeding.bat new file mode 100644 index 0000000..e69de29 diff --git a/robowaiter/llm_client/data/fix_questions.txt b/robowaiter/llm_client/retrieval/fix_questions.txt similarity index 100% rename from robowaiter/llm_client/data/fix_questions.txt rename to robowaiter/llm_client/retrieval/fix_questions.txt diff --git a/robowaiter/llm_client/single_round.py b/robowaiter/llm_client/single_round.py index d0c88c6..364ecce 100644 --- a/robowaiter/llm_client/single_round.py +++ b/robowaiter/llm_client/single_round.py @@ -1,6 +1,8 @@ +import time import requests import urllib3 + ######################################## # 该文件实现了与大模型的简单通信 ######################################## @@ -9,22 +11,29 @@ import urllib3 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) -def single_round(question,prefix=""): +def single_round(question, prefix=""): url = "https://45.125.46.134:25344/v1/chat/completions" headers = {"Content-Type": "application/json"} data = { "model": "RoboWaiter", "messages": [ - { - "role": "system", - "content": "你是一个机器人服务员：RoboWaiter. 你的职责是为顾客提供对话及具身服务。" - }, - { - "role": "user", - "content": prefix + question - } + { + "role": "system", + "content": "你是一个机器人服务员：RoboWaiter. 你的职责是为顾客提供对话及具身服务。" + # "content": + # """ + # 你是一个熟悉行为树的工程师，你的职责是根据用户需求，为一个人型的机器人设计完成用户需求的行为树序列。 + # 行为树是一种有向根树，他的内部节点称为控制节点，控制节点包括选择、顺序，顺序节点只有所有子节点返回成功之后他才成功。 + # 选择节点只要有一个子节点返回成功最后就成功。叶节点称为执行节点，执行节点包括动作节点和条件节点。动作节点执行具体的动作，条件节点检查环境中的条件是否满足。 + # """ + # "content": "你是一个优秀的目标状态规划师，能够根据用户输入，规划出所需要的目标状态。例如：打开窗帘的目标状态可以是Is(Curtain, On)" + }, + { + "role": "user", + "content": prefix + question + } ] - } + } response = requests.post(url, headers=headers, json=data, verify=False) @@ -37,7 +46,10 @@ def single_round(question,prefix=""): if __name__ == '__main__': question = ''' - 给我一杯拿铁 + 嘿！能做一杯咖啡吗？咖啡就行！ ''' + import timeit - print(single_round(question)) \ No newline at end of file + cur_time = time.time() + print(single_round(question, prefix='现在给出符合这句话要求的目标状态: ')) + print(f"单次生成耗时：{time.time() - cur_time} s \n") diff --git a/robowaiter/llm_client/tool_register.py b/robowaiter/llm_client/tool_register.py index f15a927..a16ee1d 100644 --- a/robowaiter/llm_client/tool_register.py +++ b/robowaiter/llm_client/tool_register.py @@ -160,14 +160,40 @@ def stop_serve( @register_tool def get_object_info( - obj: Annotated[str, '需要获取信息的物体名称', True] + obj: Annotated[str, '需要获取位置的物体名称', True] ) -> str: """ - 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，则输出大门。 - 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 + 获取场景中`object`的位置信息。在询问物品位置时调用该函数，以辅助场景交互，不执行动作 + 例如： + `object`在哪里？ + 哪有`object` + 哪里有`object`？ + `object`在哪里 + 哪里有`object` + `object`放在哪里 + 我在哪儿能找到`object` + 你们这儿有`object`吗？ + 你们这里有`object` + 你看见`object`了吗？ + `object`在你们这里吗 + `object`，你看见过吗？ + 遇到上述问题时，调用该函数，并根据返回的结果回复物体位置信息，例如 + 回答： + `object`在输出的物品附近 + 如果`object` 是一个地点，例如洗手间，则输出大门。 + 如果`object`是咖啡，输出桌子，则咖啡在桌子上。 + 如果`object`是酸奶，输出冰红茶，则酸奶在冰红茶附近。 + 如果`object` 是空桌子，则输出一号桌 """ + + # 桌上有 + # `object` + # 吗？ + # 咖啡厅里哪里有 + # `object` + # `object` + # 放在哪里？ + near_object = None # if obj == "Table": # near_object = "Bar" @@ -192,22 +218,44 @@ def get_object_info( # 获取的location为英文 # 用户想找某个地点 # """ -# near_location = None -# query_token = nlp(location) -# max_similarity = 0 -# similar_word = None -# for w in find_obj_utils.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) -# if similar_word: -# mp = list(find_obj_utils.loc_map_en[similar_word]) -# near_location = random.choice(mp) -# return near_location + # near_location = None + # query_token = nlp(location) + # max_similarity = 0 + # similar_word = None + # for w in find_obj_utils.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) + # if similar_word: + # mp = list(find_obj_utils.loc_map_en[similar_word]) + # near_location = random.choice(mp) + # return near_location + + +@register_tool +def get_number_of_objects( + obj: Annotated[str, '需要获取数量的物体名称', True] +) -> str: + """ + 当询问场景中的物体数量时，需要调用这个工具。 + 例如询问： + `obj`有多少？ + 有多少`obj` + 你们还有`obj` + '桌子有几张' + `obj`还有多的吗？ + `obj`有几个 + `obj`有多少个 + 这个工具用于获取场景中指定物体 `obj` 的数量，返回一个整数，不涉及到具体的执行任务。 + 如果`obj`是咖啡，如果场景中有5杯咖啡，就返回 5 + 如果`obj`是桌子，如果场景中有7张桌子，就返回 7 + 如果`obj`是行人，如果场景中有10个顾客，就返回 10 + """ + if __name__ == "__main__": print(dispatch_tool("get_weather", {"city_name": "beijing"})) diff --git a/robowaiter/scene/outputs/current_bt.dot b/robowaiter/scene/outputs/current_bt.dot new file mode 100644 index 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fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "ae1795ad-99ad-4a19-ae19-3dfac64b96d5"; +"3f5584f5-98e4-4d97-ada4-518fd930efe1" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Coffee)", shape=ellipse, style=filled]; +"ae1795ad-99ad-4a19-ae19-3dfac64b96d5" -> "3f5584f5-98e4-4d97-ada4-518fd930efe1"; +"feb9d0bd-81ef-4de4-a011-554cfab12dfc" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(WaterTable)", shape=box, style=filled]; +"ae1795ad-99ad-4a19-ae19-3dfac64b96d5" -> "feb9d0bd-81ef-4de4-a011-554cfab12dfc"; +"0304536e-fa59-485d-a452-47a668dfe2ea" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "0304536e-fa59-485d-a452-47a668dfe2ea"; +"4a75fcc7-7c99-4d64-8150-add03da82ef7" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Coffee)", shape=ellipse, style=filled]; +"0304536e-fa59-485d-a452-47a668dfe2ea" -> "4a75fcc7-7c99-4d64-8150-add03da82ef7"; +"911690ee-a827-4fde-9846-5f291ef0ff6e" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"0304536e-fa59-485d-a452-47a668dfe2ea" -> "911690ee-a827-4fde-9846-5f291ef0ff6e"; +"c35cb7a2-15d2-4440-bbf8-7667b5711653" [fillcolor=yellow, fontcolor=black, fontsize=20, label="On(Water,WaterTable)", shape=ellipse, style=filled]; +"0304536e-fa59-485d-a452-47a668dfe2ea" -> "c35cb7a2-15d2-4440-bbf8-7667b5711653"; +"7baadc46-e643-4db4-bbd7-d8f109ea6c06" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="PickUp(Coffee)", shape=box, style=filled]; +"0304536e-fa59-485d-a452-47a668dfe2ea" -> "7baadc46-e643-4db4-bbd7-d8f109ea6c06"; +"b7923c0f-0992-4266-868d-558efbd07716" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "b7923c0f-0992-4266-868d-558efbd07716"; +"d5c99c51-2edc-4d41-b2db-0068f92aa77c" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Coffee)", shape=ellipse, style=filled]; +"b7923c0f-0992-4266-868d-558efbd07716" -> "d5c99c51-2edc-4d41-b2db-0068f92aa77c"; +"89129311-b249-4eab-83a7-c5cf21a35c00" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"b7923c0f-0992-4266-868d-558efbd07716" -> "89129311-b249-4eab-83a7-c5cf21a35c00"; +"711d4b2e-0087-4520-9528-ad5b252aadd5" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="PickUp(Coffee)", shape=box, style=filled]; +"b7923c0f-0992-4266-868d-558efbd07716" -> "711d4b2e-0087-4520-9528-ad5b252aadd5"; +"6de54193-aa93-4d1a-b3f3-d04adb06a7ac" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "6de54193-aa93-4d1a-b3f3-d04adb06a7ac"; +"55153a6f-cb38-4bd1-8602-d6960b6bdbfa" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Coffee)", shape=ellipse, style=filled]; +"6de54193-aa93-4d1a-b3f3-d04adb06a7ac" -> "55153a6f-cb38-4bd1-8602-d6960b6bdbfa"; +"88c8b174-727b-4249-8768-17630e6e37e0" [fillcolor=yellow, fontcolor=black, fontsize=20, label="On(Water,WaterTable)", shape=ellipse, style=filled]; +"6de54193-aa93-4d1a-b3f3-d04adb06a7ac" -> "88c8b174-727b-4249-8768-17630e6e37e0"; +"c7f0187c-a4c8-4b76-8da1-4ac790e56ee5" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="FreeHands()", shape=box, style=filled]; +"6de54193-aa93-4d1a-b3f3-d04adb06a7ac" -> "c7f0187c-a4c8-4b76-8da1-4ac790e56ee5"; +"acc92740-05eb-4963-b01b-63b41cf20140" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "acc92740-05eb-4963-b01b-63b41cf20140"; +"5508c6dc-6c58-4d91-a2f7-81b19be0f22d" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"acc92740-05eb-4963-b01b-63b41cf20140" -> "5508c6dc-6c58-4d91-a2f7-81b19be0f22d"; +"ed0d3415-95b4-4ce5-9341-b7352f78eff1" [fillcolor=yellow, fontcolor=black, fontsize=20, label="On(Water,WaterTable)", shape=ellipse, style=filled]; +"acc92740-05eb-4963-b01b-63b41cf20140" -> "ed0d3415-95b4-4ce5-9341-b7352f78eff1"; +"248b5d9a-5160-4154-a747-35c180c26788" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Exist(Coffee)", shape=ellipse, style=filled]; +"acc92740-05eb-4963-b01b-63b41cf20140" -> "248b5d9a-5160-4154-a747-35c180c26788"; +"96ea24c5-198d-46ff-88e6-375a310463c2" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Coffee)", shape=box, style=filled]; +"acc92740-05eb-4963-b01b-63b41cf20140" -> "96ea24c5-198d-46ff-88e6-375a310463c2"; +"370f4fa8-1789-47cf-86d4-43c1fcaec40d" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "370f4fa8-1789-47cf-86d4-43c1fcaec40d"; +"3b4e2601-a215-4c53-9725-024a7272ca01" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Coffee)", shape=ellipse, style=filled]; +"370f4fa8-1789-47cf-86d4-43c1fcaec40d" -> "3b4e2601-a215-4c53-9725-024a7272ca01"; +"5207249d-7ed3-4374-8c35-551323aa6e6f" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="FreeHands()", shape=box, style=filled]; +"370f4fa8-1789-47cf-86d4-43c1fcaec40d" -> "5207249d-7ed3-4374-8c35-551323aa6e6f"; +"adb07734-f041-4c2e-9e4c-360fc7932ec9" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "adb07734-f041-4c2e-9e4c-360fc7932ec9"; +"c050928b-ea79-40c0-b9ba-fdf1cb60a773" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"adb07734-f041-4c2e-9e4c-360fc7932ec9" -> "c050928b-ea79-40c0-b9ba-fdf1cb60a773"; +"07b147ab-23b5-48ae-9449-c810c93e28b4" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Exist(Coffee)", shape=ellipse, style=filled]; +"adb07734-f041-4c2e-9e4c-360fc7932ec9" -> "07b147ab-23b5-48ae-9449-c810c93e28b4"; +"59f2afe9-173b-41f8-921e-29cfd4ecc1c4" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Coffee)", shape=box, style=filled]; +"adb07734-f041-4c2e-9e4c-360fc7932ec9" -> "59f2afe9-173b-41f8-921e-29cfd4ecc1c4"; +"fcbee6e1-0e5e-41c3-9db5-5bf808bac68b" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "fcbee6e1-0e5e-41c3-9db5-5bf808bac68b"; +"f0843e6c-a65a-4d9f-971d-06766e94df66" [fillcolor=yellow, fontcolor=black, fontsize=20, label="On(Water,WaterTable)", shape=ellipse, style=filled]; +"fcbee6e1-0e5e-41c3-9db5-5bf808bac68b" -> "f0843e6c-a65a-4d9f-971d-06766e94df66"; +"6dab056a-a232-4212-af57-5c1c1465db99" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Exist(Coffee)", shape=ellipse, style=filled]; +"fcbee6e1-0e5e-41c3-9db5-5bf808bac68b" -> "6dab056a-a232-4212-af57-5c1c1465db99"; +"0c2f54f1-85e8-486d-9c81-3d18f5f12ae8" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Coffee)", shape=box, style=filled]; +"fcbee6e1-0e5e-41c3-9db5-5bf808bac68b" -> "0c2f54f1-85e8-486d-9c81-3d18f5f12ae8"; +"1c873ce0-8037-40a0-9394-037257e6ef1f" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "1c873ce0-8037-40a0-9394-037257e6ef1f"; +"4c2f06f6-fa4b-41a2-a50d-cbd4f2370b5b" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"1c873ce0-8037-40a0-9394-037257e6ef1f" -> "4c2f06f6-fa4b-41a2-a50d-cbd4f2370b5b"; +"e311ac9a-4505-442e-9ec9-47c2a0fd2ac8" [fillcolor=yellow, fontcolor=black, fontsize=20, label="On(Water,WaterTable)", shape=ellipse, style=filled]; +"1c873ce0-8037-40a0-9394-037257e6ef1f" -> "e311ac9a-4505-442e-9ec9-47c2a0fd2ac8"; +"b3880316-85f0-4124-a18a-fa84896d3485" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="Make(Coffee)", shape=box, style=filled]; +"1c873ce0-8037-40a0-9394-037257e6ef1f" -> "b3880316-85f0-4124-a18a-fa84896d3485"; +"96e46656-34ac-47aa-83b1-902ec66e53b5" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "96e46656-34ac-47aa-83b1-902ec66e53b5"; +"41ad97fa-7ea9-48e4-8cd3-187dc53fe992" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,WaterTable)", shape=ellipse, style=filled]; +"96e46656-34ac-47aa-83b1-902ec66e53b5" -> "41ad97fa-7ea9-48e4-8cd3-187dc53fe992"; +"7e7163b1-eadd-4f81-99c5-5cd238252a79" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Water)", shape=ellipse, style=filled]; +"96e46656-34ac-47aa-83b1-902ec66e53b5" -> "7e7163b1-eadd-4f81-99c5-5cd238252a79"; +"18b63af1-2803-4a7d-95c2-c701dff29a51" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Exist(Coffee)", shape=ellipse, style=filled]; +"96e46656-34ac-47aa-83b1-902ec66e53b5" -> "18b63af1-2803-4a7d-95c2-c701dff29a51"; +"1f492236-0a16-4e47-bca0-d6cda8fc1e79" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="PutDown(Water,WaterTable)", shape=box, style=filled]; +"96e46656-34ac-47aa-83b1-902ec66e53b5" -> "1f492236-0a16-4e47-bca0-d6cda8fc1e79"; +"26396b01-8762-46f0-be46-224b590173ce" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "26396b01-8762-46f0-be46-224b590173ce"; +"bee79c41-c84d-427a-a0b4-fe732ab6e448" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Exist(Coffee)", shape=ellipse, style=filled]; +"26396b01-8762-46f0-be46-224b590173ce" -> "bee79c41-c84d-427a-a0b4-fe732ab6e448"; +"7845d148-bef6-4b74-959b-5e13fbe75330" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Coffee)", shape=box, style=filled]; +"26396b01-8762-46f0-be46-224b590173ce" -> "7845d148-bef6-4b74-959b-5e13fbe75330"; +"eee68ac0-f125-4074-a523-dcd9b1d25e42" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"89809d74-1aa6-4401-b296-b10cb96a0017" -> "eee68ac0-f125-4074-a523-dcd9b1d25e42"; +"bc97fe9a-8eeb-4d4f-8865-025bf8ab1d0e" [fillcolor=yellow, fontcolor=black, fontsize=20, label="Holding(Nothing)", shape=ellipse, style=filled]; +"eee68ac0-f125-4074-a523-dcd9b1d25e42" -> "bc97fe9a-8eeb-4d4f-8865-025bf8ab1d0e"; +"e631843b-92d8-4612-8dcf-7dd66b86a531" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="Make(Coffee)", shape=box, style=filled]; +"eee68ac0-f125-4074-a523-dcd9b1d25e42" -> "e631843b-92d8-4612-8dcf-7dd66b86a531"; +"1c7e5f57-89fe-40d3-a5fe-45d7fa2e7f90" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="DelSubTree()", shape=box, style=filled]; +"057834e6-77b3-416b-bebe-0e1690ea7b77" -> "1c7e5f57-89fe-40d3-a5fe-45d7fa2e7f90"; +"deb5f50b-93ac-4601-a5f1-af68f0f9d50a" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"a582faee-7147-4195-81ba-85add86624b4" -> "deb5f50b-93ac-4601-a5f1-af68f0f9d50a"; +"8d9e0427-c7c4-4c8a-b6a1-d3cf0a7ae4c6" [fillcolor=yellow, fontcolor=black, fontsize=20, label="FocusingCustomer()", shape=ellipse, style=filled]; +"deb5f50b-93ac-4601-a5f1-af68f0f9d50a" -> "8d9e0427-c7c4-4c8a-b6a1-d3cf0a7ae4c6"; +"a8ab831b-5e89-41c6-9a6a-15441aa1d32b" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="ServeCustomer()", shape=box, style=filled]; +"deb5f50b-93ac-4601-a5f1-af68f0f9d50a" -> "a8ab831b-5e89-41c6-9a6a-15441aa1d32b"; +"cc071d28-4cb6-4bbd-a866-38f48b77efda" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"a582faee-7147-4195-81ba-85add86624b4" -> "cc071d28-4cb6-4bbd-a866-38f48b77efda"; +"e227e659-1432-4fba-8b6a-a9364e51076c" [fillcolor=yellow, fontcolor=black, fontsize=20, label="NewCustomer()", shape=ellipse, style=filled]; +"cc071d28-4cb6-4bbd-a866-38f48b77efda" -> "e227e659-1432-4fba-8b6a-a9364e51076c"; +"d3a930dc-8300-4510-a83c-5f070170bb5b" [fillcolor=cyan, fontcolor=black, fontsize=20, height=0.01, label=Selector, shape=diamond, style=filled, width=0.01]; +"cc071d28-4cb6-4bbd-a866-38f48b77efda" -> "d3a930dc-8300-4510-a83c-5f070170bb5b"; +"85295be4-2eed-4dac-98f6-040450241204" [fillcolor=yellow, fontcolor=black, fontsize=20, label="At(Robot,Bar)", shape=ellipse, style=filled]; +"d3a930dc-8300-4510-a83c-5f070170bb5b" -> "85295be4-2eed-4dac-98f6-040450241204"; +"5a775c24-2a6b-445c-87e9-9eeab2b6882c" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="MoveTo(Bar)", shape=box, style=filled]; +"d3a930dc-8300-4510-a83c-5f070170bb5b" -> "5a775c24-2a6b-445c-87e9-9eeab2b6882c"; +"3b8f863e-eef0-43e9-8ccc-4086c59af2a1" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="GreetCustomer()", shape=box, style=filled]; +"cc071d28-4cb6-4bbd-a866-38f48b77efda" -> "3b8f863e-eef0-43e9-8ccc-4086c59af2a1"; +"16c9b1ee-9159-4816-92a4-37c149d0233a" [fillcolor=orange, fontcolor=black, fontsize=20, height=0.01, label=Sequence, shape=octagon, style=filled, width=0.01]; +"a582faee-7147-4195-81ba-85add86624b4" -> "16c9b1ee-9159-4816-92a4-37c149d0233a"; +"967d7a51-f3e2-4b8f-9331-dc75660d7136" [fillcolor=yellow, fontcolor=black, fontsize=20, label="AnomalyDetected()", shape=ellipse, style=filled]; +"16c9b1ee-9159-4816-92a4-37c149d0233a" -> "967d7a51-f3e2-4b8f-9331-dc75660d7136"; +"9b9909d3-e999-4706-b4de-1c60dfe53a14" [fillcolor=lawngreen, fontcolor=black, fontsize=20, label="ResolveAnomaly()", shape=box, style=filled]; +"16c9b1ee-9159-4816-92a4-37c149d0233a" -> "9b9909d3-e999-4706-b4de-1c60dfe53a14"; +} diff --git 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+1c873ce0-8037-40a0-9394-037257e6ef1f->4c2f06f6-fa4b-41a2-a50d-cbd4f2370b5b + + + + + +e311ac9a-4505-442e-9ec9-47c2a0fd2ac8 + +On(Water,WaterTable) + + + +1c873ce0-8037-40a0-9394-037257e6ef1f->e311ac9a-4505-442e-9ec9-47c2a0fd2ac8 + + + + + +b3880316-85f0-4124-a18a-fa84896d3485 + +Make(Coffee) + + + +1c873ce0-8037-40a0-9394-037257e6ef1f->b3880316-85f0-4124-a18a-fa84896d3485 + + + + + +41ad97fa-7ea9-48e4-8cd3-187dc53fe992 + +At(Robot,WaterTable) + + + +96e46656-34ac-47aa-83b1-902ec66e53b5->41ad97fa-7ea9-48e4-8cd3-187dc53fe992 + + + + + +7e7163b1-eadd-4f81-99c5-5cd238252a79 + +Holding(Water) + + + +96e46656-34ac-47aa-83b1-902ec66e53b5->7e7163b1-eadd-4f81-99c5-5cd238252a79 + + + + + +18b63af1-2803-4a7d-95c2-c701dff29a51 + +Exist(Coffee) + + + +96e46656-34ac-47aa-83b1-902ec66e53b5->18b63af1-2803-4a7d-95c2-c701dff29a51 + + + + + +1f492236-0a16-4e47-bca0-d6cda8fc1e79 + +PutDown(Water,WaterTable) + + + +96e46656-34ac-47aa-83b1-902ec66e53b5->1f492236-0a16-4e47-bca0-d6cda8fc1e79 + + + + + +bee79c41-c84d-427a-a0b4-fe732ab6e448 + +Exist(Coffee) + + + +26396b01-8762-46f0-be46-224b590173ce->bee79c41-c84d-427a-a0b4-fe732ab6e448 + + + + + +7845d148-bef6-4b74-959b-5e13fbe75330 + +MoveTo(Coffee) + + + +26396b01-8762-46f0-be46-224b590173ce->7845d148-bef6-4b74-959b-5e13fbe75330 + + + + + +bc97fe9a-8eeb-4d4f-8865-025bf8ab1d0e + +Holding(Nothing) + + + +eee68ac0-f125-4074-a523-dcd9b1d25e42->bc97fe9a-8eeb-4d4f-8865-025bf8ab1d0e + + + + + +e631843b-92d8-4612-8dcf-7dd66b86a531 + +Make(Coffee) + + + +eee68ac0-f125-4074-a523-dcd9b1d25e42->e631843b-92d8-4612-8dcf-7dd66b86a531 + + + + + +8d9e0427-c7c4-4c8a-b6a1-d3cf0a7ae4c6 + +FocusingCustomer() + + + +deb5f50b-93ac-4601-a5f1-af68f0f9d50a->8d9e0427-c7c4-4c8a-b6a1-d3cf0a7ae4c6 + + + + + +a8ab831b-5e89-41c6-9a6a-15441aa1d32b + +ServeCustomer() + + + +deb5f50b-93ac-4601-a5f1-af68f0f9d50a->a8ab831b-5e89-41c6-9a6a-15441aa1d32b + + + + + +e227e659-1432-4fba-8b6a-a9364e51076c + +NewCustomer() + + + +cc071d28-4cb6-4bbd-a866-38f48b77efda->e227e659-1432-4fba-8b6a-a9364e51076c + + + + + +d3a930dc-8300-4510-a83c-5f070170bb5b + +Selector + + + +cc071d28-4cb6-4bbd-a866-38f48b77efda->d3a930dc-8300-4510-a83c-5f070170bb5b + + + + + +3b8f863e-eef0-43e9-8ccc-4086c59af2a1 + +GreetCustomer() + + + +cc071d28-4cb6-4bbd-a866-38f48b77efda->3b8f863e-eef0-43e9-8ccc-4086c59af2a1 + + + + + +85295be4-2eed-4dac-98f6-040450241204 + +At(Robot,Bar) + + + +d3a930dc-8300-4510-a83c-5f070170bb5b->85295be4-2eed-4dac-98f6-040450241204 + + + + + +5a775c24-2a6b-445c-87e9-9eeab2b6882c + +MoveTo(Bar) + + + +d3a930dc-8300-4510-a83c-5f070170bb5b->5a775c24-2a6b-445c-87e9-9eeab2b6882c + + + + + +967d7a51-f3e2-4b8f-9331-dc75660d7136 + +AnomalyDetected() + + + +16c9b1ee-9159-4816-92a4-37c149d0233a->967d7a51-f3e2-4b8f-9331-dc75660d7136 + + + + + +9b9909d3-e999-4706-b4de-1c60dfe53a14 + +ResolveAnomaly() + + + +16c9b1ee-9159-4816-92a4-37c149d0233a->9b9909d3-e999-4706-b4de-1c60dfe53a14 + + + + + diff --git a/robowaiter/scene/scene.py b/robowaiter/scene/scene.py index bcf6e01..02c3c80 100644 --- a/robowaiter/scene/scene.py +++ b/robowaiter/scene/scene.py @@ -16,7 +16,7 @@ from robowaiter.proto import GrabSim_pb2_grpc import copy import os -from robowaiter.scene.ui import scene_ui +# from robowaiter.scene.ui import scene_ui from robowaiter.utils import get_root_path from sklearn.cluster import DBSCAN from matplotlib import pyplot as plt @@ -39,7 +39,143 @@ channel = grpc.insecure_channel( animation_step = [4, 5, 7, 3, 3] loc_offset = [-700, -1400] - +objname_en2zh_dic_goal = { +'Customer':'顾客', +'Banana': '香蕉', +'Toothpaste': '牙膏', +'Bread': '面包', +'Softdrink': '盒装饮料', +'Yogurt': '酸奶', +'ADMilk': '安佳牛奶', +'VacuumCup': '真空杯', +'Bernachon': '贝尔纳松', +'BottledDrink': '瓶装饮料', +'PencilVase': '铅笔花瓶', +'Teacup': '茶杯', +'Dictionary': '字典', +'Cake': '蛋糕', +'Stapler': '订书机', +'LunchBox': '午餐盒', +'Bracelet': '手镯', +'CoconutWater': '椰水', +'Walnut': '核桃', +'HamSausage': '火腿肠', +'GlueStick': '胶棒', +'AdhesiveTape': '胶带', +'Calculator': '计算器', +'Chess': '棋', +'Orange': '橙子', +'Glass': '玻璃杯', +'Washbowl': '洗碗盆', +'Durian': '榴莲', +'Gum': '口香糖', +'Towel': '毛巾', +'OrangeJuice': '橙汁', +'Cardcase': '卡包', +'RubikCube': '魔方', +'StickyNotes': '便签', +'NFCJuice': 'NFC果汁', +'SpringWater': '矿泉水', +'Apple': '苹果', +'Coffee': '咖啡', +'Gauze': '纱布', +'Mangosteen': '山竹', +'SesameSeedCake': '芝麻糕', +'Glove': '手套', +'Mouse': '鼠标', +'Kettle': '水壶', +'Atomize': '喷雾器', +'Chips': '薯片', +'SpongeGourd': '丝瓜', +'Garlic': '大蒜', +'Potato': '土豆', +'Tray': '托盘', +'Hemomanometer': '血压计', +'TennisBall': '网球', +'ToyDog': '玩具狗', +'ToyBear': '玩具熊', +'TeaTray': '茶盘', +'Sock': '袜子', +'Scarf': '围巾', +'ToiletPaper': '卫生纸', +'Milk': '牛奶', +'Novel': '小说', +'Watermelon': '西瓜', +'Tomato': '番茄', +'CleansingFoam': '洁面泡沫', +'CoconutMilk': '椰奶', +'SugarlessGum': '无糖口香糖', +'MedicalAdhesiveTape': '医用胶带', +'PaperCup': '纸杯', +'Caddy': '茶匙', +'Date': '日期', +'MilkDrink': '牛奶饮品', +'CocountWater': '椰水', +'AdhensiveTape': '胶带', +'Towl': '毛巾', +'Soap': '肥皂', +'CocountMilk': '椰奶', +'MedicalAdhensiveTape': '医用胶带', +'SourMilkDrink': '酸奶饮品', +'Tissue': '纸巾', +'YogurtDrink': '酸奶饮品', +'Newspaper': '报纸', +'Box': '盒子', +'PaperCupStarbucks': '星巴克纸杯', +'CoffeeMachine': '咖啡机', +'GingerLHand': '机器人左手', +'GingerRHand': '机器人右手', +'Straw': '吸管', +'Door': '门', +'Machine': '机器', +'PackagedCoffee': '包装咖啡', +'CubeSugar': '方糖', +'Spoon': '勺子', +'Drinks': '饮料', +'Drink': '饮料', +'Take-AwayCup': '外带杯', +'Saucer': '茶杯', +'TrashBin': '垃圾桶', +'Knife': '刀', +'Ginger': '姜', +'Floor': '地板', +'Roof': '屋顶', +'Wall': '墙', +'Broom':'扫帚', +'CoffeeCup': '咖啡杯', +'Mug': '马克杯', +'ZhuZi': '著子', +'LaJiTong': '垃圾桶', +'ZaoTai': '灶台', +'Sofa': '沙发', +'ChaTou': '插头', +'Plate': '盘子', +'CoffeeBag': '咖啡袋', +'TuoBu': '拖布', +'KaiGuan': '开关', +'ChaZuo': '插座', +'Sugar': '糖', +'BaTai': '吧台', +'BaoJing': '报警', +'DrinkMachine': '饮料机', +'KongTiao': '空调', +'Desk': '桌子', +'Clip': '夹子', +'TuoPan': '托盘', +'BoJi': '簸箕', +'ZhiBeiHe': '纸杯盒', +'WaterCup': '水杯', +'Chair': '椅子', +'Hand': '手', +'XiGuan': '吸管', +'Container': '容器', +'IceMachine': '制冰机', +'KaoXiang': '烤箱', +'SaoBa': '扫把', +'XiangGui': '香柜', +} +objname_zh2en_dic_goal = dict(zip(objname_en2zh_dic_goal.values(), objname_en2zh_dic_goal.keys())) +# print(objname_zh2eh_dic) def show_image(camera_data): print('------------------show_image----------------------') @@ -66,6 +202,9 @@ class Scene: # camera_interval = 1.5 output_path = os.path.join(os.path.dirname(__file__), "outputs") + objname_en2zh_dic = objname_en2zh_dic_goal + objname_zh2en_dic = objname_zh2en_dic_goal + default_state = { "map": { "2d": None, @@ -124,7 +263,7 @@ class Scene: # 是否展示UI self.show_ui = False # 图像分割 - self.take_picture = False + self.take_picture = True self.map_ratio = 5 self.map_map = np.zeros((math.ceil(950 / self.map_ratio), math.ceil(1850 / self.map_ratio))) self.db = DBSCAN(eps=self.map_ratio, min_samples=int(self.map_ratio / 2)) @@ -880,6 +1019,8 @@ class Scene: scene = self.stub.AddObjects(GrabSim_pb2.ObjectList(objects=obj_list, scene=self.sceneID)) time.sleep(1.0) + + # 实现抓握操作 def grasp_obj(self, obj_id, hand_id=1): print('------------------adjust_joints----------------------') @@ -1142,6 +1283,10 @@ class Scene: def getDistance(self, pos1, pos2): return math.sqrt((pos1[0] - pos2[0]) ** 2 + (pos1[1] - pos2[1]) ** 2) + def getDistanc3D(self, pos1, pos2): + return math.sqrt((pos1[0] - pos2[0]) ** 2 + (pos1[1] - pos2[1]) ** 2+ (pos1[2] - pos2[2]) ** 2) + + def getNearestFrontier(self, cur_pos, frontiers): dis_min = sys.maxsize frontier_best = None @@ -1456,7 +1601,16 @@ class Scene: # plt.text(0, 0.1, f'已存语义信息：{self.infoCount}', fontsize=10) # 元组传参 pyqt5中的函数名， 四个参数 - self.ui_func(("get_info", walker_detect_count, obj_detect_count, update_info_count, self.infoCount)) + # self.ui_func(("get_info", walker_detect_count, obj_detect_count, update_info_count, self.infoCount)) + semantic_info_str="" + semantic_info_str+= f'检测行人数量：{walker_detect_count}'+"\n" + semantic_info_str += f'检测物体数量：{obj_detect_count}' + "\n" + semantic_info_str += f'更新语义信息：{update_info_count}' + "\n" + semantic_info_str += f'已存语义信息：{self.infoCount}' + "\n" + + # print("======semantic_info_str===========") + + self.ui_func(("get_semantic_info", semantic_info_str)) # draw figures diff --git a/robowaiter/scene/ui/pyqt5.py b/robowaiter/scene/ui/pyqt5.py index 05d5041..754db44 100644 --- a/robowaiter/scene/ui/pyqt5.py +++ b/robowaiter/scene/ui/pyqt5.py @@ -1,9 +1,11 @@ import importlib import os +from PyQt5.QtSvg import QGraphicsSvgItem, QSvgWidget from PyQt5.QtWidgets import QApplication, QMainWindow, QListWidgetItem, QGraphicsView, QGraphicsScene, \ - QGraphicsPixmapItem + QGraphicsPixmapItem, QGraphicsProxyWidget from PyQt5.QtCore import QTimer, QPoint, QRectF +from PyQt5 import QtCore import sys from robowaiter.scene.ui.window import Ui_MainWindow @@ -11,7 +13,7 @@ from robowaiter.utils.basic import get_root_path from PyQt5.QtCore import QThread import queue import numpy as np -from PyQt5.QtGui import QImage, QPixmap, QDrag +from PyQt5.QtGui import QImage, QPixmap, QDrag, QPainter from PyQt5.QtCore import Qt from PyQt5.QtCore import QThread, pyqtSignal from robowaiter.scene.ui.scene_ui import SceneUI @@ -56,6 +58,29 @@ def run_scene(scene_cls,robot_cls,scene_queue,ui_queue): # print("Robot system error:", str(e)) example_list = ("AEM","VLN","VLM",'GQA',"OT","AT","reset") +more_example_list = ("VLM_AC","CafeDaily") +dic_more2zh={ + "VLM_AC":"开空调并调节空调温度", + "CafeDaily":"咖啡厅的一天" +} +more_example_list_zh = [value for value in dic_more2zh.values()] + +class GraphicsView(QGraphicsView): + def __init__(self, parent=None): + super(GraphicsView, self).__init__(parent) + self.setRenderHint(QPainter.Antialiasing) + self.setOptimizationFlag(QGraphicsView.DontAdjustForAntialiasing, True) + self.setViewportUpdateMode(QGraphicsView.FullViewportUpdate) + self.setDragMode(QGraphicsView.ScrollHandDrag) + self.setHorizontalScrollBarPolicy(QtCore.Qt.ScrollBarAlwaysOff) + self.setVerticalScrollBarPolicy(QtCore.Qt.ScrollBarAlwaysOff) + + def wheelEvent(self, event): + factor = 1.15 + if event.angleDelta().y() > 0: + self.scale(factor, factor) + else: + self.scale(1.0 / factor, 1.0 / factor) class UI(QMainWindow, Ui_MainWindow): scene = None @@ -78,6 +103,10 @@ class UI(QMainWindow, Ui_MainWindow): # 绑定说话按钮 self.btn_say.clicked.connect(self.btn_say_on_click) + self.verticalLayout_2.removeWidget(self.img_view_bt) + self.img_view_bt = GraphicsView(self.centralwidget) + self.img_view_bt.setObjectName("img_view_bt") + self.verticalLayout_2.addWidget(self.img_view_bt) self.img_view_bt.setDragMode(QGraphicsView.ScrollHandDrag) @@ -90,12 +119,12 @@ class UI(QMainWindow, Ui_MainWindow): # self.drag_start_position = QPoint() # 记录鼠标按下时的位置 self.cb_task.setCurrentIndex(-1) - self.cb_task.setPlaceholderText("请选择城市") + self.cb_task.setPlaceholderText("请选择更多任务") # 多个添加条目 - self.cb_task.addItems(['Java', 'C#', 'PHP']) + self.cb_task.addItems(more_example_list_zh) # 当下拉索引发生改变时发射信号触发绑定的事件 - self.cb_task.currentIndexChanged.connect(self.selectionchange) + self.cb_task.currentIndexChanged.connect(self.cb_selectionchange) # 绑定任务演示按钮 for example in example_list: @@ -116,24 +145,15 @@ class UI(QMainWindow, Ui_MainWindow): sys.exit(app.exec_()) - def selectionchange(self, i): + def cb_selectionchange(self, i): print(i) - # self.create_example_click(dic[i]) - # 标签用来显示选中的文本 - # currentText()：返回选中选项的文本 - # self.btn1.setText(self.cb.currentText()) - # print('Items in the list are:') - # # 输出选项集合中每个选项的索引与对应的内容 - # # count()：返回选项集合中的数目 - # for count in range(self.cb.count()): - # print('Item' + str(count) + '=' + self.cb.itemText(count)) - # print('current index', i, 'selection changed', self.cb.currentText()) + self.create_example_click(more_example_list[i])() - def get_info(self, walker_detect_count, obj_detect_count, update_info_count, infoCount): - print(obj_detect_count) - self.textEdit_5.clear() - self.textEdit_5.append(str(obj_detect_count)) - # self.textEdit_5.setText(walker_detect_count + "_" + obj_detect_count + "_" + update_info_count + "_" + infoCount) + def get_semantic_info(self, semantic_info_str): + # self.textEdit_5.clear() + # self.textEdit_5.append(semantic_info_str) + self.textBrowser_5.clear() + self.textBrowser_5.append(semantic_info_str) def new_history(self,customer_name,chat): role = chat["role"] @@ -246,6 +266,17 @@ class UI(QMainWindow, Ui_MainWindow): self.img_view_bt.setScene(scene) pixmap_item = QGraphicsPixmapItem(pixmap) scene.addItem(pixmap_item) + + + # widget = QSvgWidget(file_name) + # # widget.resize(10000, 1600) + # svg_width = widget.width() + # widget.resize(svg_width*2, 1600) + # proxy = QGraphicsProxyWidget() + # proxy.setWidget(widget) + # scene.addItem(+proxy) + + elif control_name == "img_label_obj": return # self.label.setPixmap(pixmap) diff --git a/robowaiter/scene/ui/scene_ui.py b/robowaiter/scene/ui/scene_ui.py index f97b158..b070a3a 100644 --- a/robowaiter/scene/ui/scene_ui.py +++ b/robowaiter/scene/ui/scene_ui.py @@ -10,13 +10,15 @@ import pickle import time import os +from robowaiter.scene.scene import Scene + plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签 plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号 from robowaiter.utils import get_root_path root_path = get_root_path() -from robowaiter.scene.scene import Scene + from robowaiter.utils.bt.draw import render_dot_tree @@ -160,20 +162,30 @@ class SceneUI(Scene): self.new_event_list = [ (5, self.customer_say, (0, "请问哪里有空位啊？")), - (13, self.customer_say, (0, "我想坐高凳子。")), + (13, self.customer_say, (0, "我想坐高脚凳子。")), (3, self.customer_say, (0, "你带我去吧。")), - (45, self.control_walker, (0, False, 100, -250, 480, -90)), + (60, self.control_walker, (0, False, 100, -250, 480, -90)), #45 (-1, self.customer_say, (0, "谢谢你！这儿还不错！")), ] def run_VLM(self): + # 场景一 拿放物品 self.gen_obj() + self.state["condition_set"]={'At(Robot,Bar)', 'Is(AC,Off)', + 'Holding(Nothing)', 'Exist(Yogurt)', 'Exist(BottledDrink)', + 'Exist(Softdrink)', + 'Exist(Chips)', 'Exist(NFCJuice)', 'Exist(Bernachon)', 'Exist(ADMilk)', 'Exist(SpringWater)' + 'Exist(VacuumCup)', 'On(VacuumCup,Table2)', + 'Is(HallLight,Off)', 'Is(TubeLight,On)', 'Is(Curtain,On)', + 'Is(Table1,Dirty)', 'Is(Floor,Dirty)', 'Is(Chairs,Dirty)'} + self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) - self. control_walkers(walker_loc=[[-55, 750], [70, -200], [250, 1200], [0, 880]],is_autowalk = True) + # self.control_walkers(walker_loc=[[-55, 750], [70, -200], [250, 1200], [0, 880]],is_autowalk = True) + self.control_walkers(walker_loc=[[-55, 750]], is_autowalk=True) self.signal_event_list = [ (3, self.add_walker, (20,0,700)), (1, self.control_walker, (6, False,100, 60, 520,0)), - (1, self.customer_say, (6, "给我来份薯片和果汁，我坐在对面的桌子那儿。")), + (1, self.customer_say, (6, "给我来份薯片和果汁，我坐在对面的水杯桌那儿。")), #给我来份薯片和果汁，我坐在对面的桌子那儿。 (5, self.control_walker, (6, False, 100, -250, 480, 0)), ] pass @@ -220,6 +232,26 @@ class SceneUI(Scene): ] pass + + def run_VLM_AC(self): + # 开关空调 + # 场景二 开和调节空调温度 + self.gen_obj() + self.add_walkers([[4,1, 880], [31,250, 1200],[6,-55, 750],[10,70, -200],[27,-290, 400, 180],[26, 60,-320,90]]) + self.control_walkers(walker_loc=[[-55, 750]],is_autowalk = True) + self.signal_event_list = [ + (3, self.add_walker, (0,0,700)), + (1, self.control_walker, (6, False,100, 60, 520,0)), #[walkerID,autowalk,speed,X,Y,Yaw] + (2, self.customer_say, (6, "好热呀，想开空调，想要温度调低点！")), + (6, self.control_walker, (6, False, 200, 60, 80, 0)), + (-1, self.customer_say, (6, "谢谢！这下凉快了！")), #(-100,600) + ] + pass + + def run_CafeDaily(self): + pass + + def run_reset(self): pass @@ -232,8 +264,9 @@ class SceneUI(Scene): self.draw_current_bt() def draw_current_bt(self): - render_dot_tree(self.robot.bt.root,target_directory=self.output_path,name="current_bt") + render_dot_tree(self.robot.bt.root,target_directory=self.output_path,name="current_bt",png_only=True) self.ui_queue.put(('draw_from_file',"img_view_bt", f"{self.output_path}/current_bt.png")) + # self.ui_queue.put(('draw_from_file', "img_view_bt", f"{self.output_path}/current_bt.svg")) def ui_func(self,args): # _,_,output_path = args diff --git a/robowaiter/scene/ui/window.py b/robowaiter/scene/ui/window.py index 6bc8b79..9d5c4d9 100644 --- a/robowaiter/scene/ui/window.py +++ b/robowaiter/scene/ui/window.py @@ -2,7 +2,7 @@ # Form implementation generated from reading ui file 'window.ui' # -# Created by: PyQt5 UI code generator 5.15.7 +# Created by: PyQt5 UI code generator 5.15.10 # # WARNING: Any manual changes made to this file will be lost when pyuic5 is # run again. Do not edit this file unless you know what you are doing. @@ -101,45 +101,6 @@ class Ui_MainWindow(object): self.gridLayout_3.addLayout(self.verticalLayout_2, 1, 0, 1, 1) self.gridLayout_2 = QtWidgets.QGridLayout() self.gridLayout_2.setObjectName("gridLayout_2") - self.horizontalLayout_5 = QtWidgets.QHBoxLayout() - self.horizontalLayout_5.setObjectName("horizontalLayout_5") - self.img_label_map = QtWidgets.QLabel(self.centralwidget) - self.img_label_map.setEnabled(True) - sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) - sizePolicy.setHorizontalStretch(0) - sizePolicy.setVerticalStretch(0) - sizePolicy.setHeightForWidth(self.img_label_map.sizePolicy().hasHeightForWidth()) - self.img_label_map.setSizePolicy(sizePolicy) - self.img_label_map.setMinimumSize(QtCore.QSize(345, 200)) - self.img_label_map.setStyleSheet("border: 2px solid black;") - self.img_label_map.setText("") - self.img_label_map.setObjectName("img_label_map") - self.horizontalLayout_5.addWidget(self.img_label_map) - self.img_label_seg = QtWidgets.QLabel(self.centralwidget) - self.img_label_seg.setEnabled(True) - sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) - sizePolicy.setHorizontalStretch(0) - sizePolicy.setVerticalStretch(0) - sizePolicy.setHeightForWidth(self.img_label_seg.sizePolicy().hasHeightForWidth()) - self.img_label_seg.setSizePolicy(sizePolicy) - self.img_label_seg.setMinimumSize(QtCore.QSize(250, 200)) - self.img_label_seg.setStyleSheet("border: 2px solid black;") - self.img_label_seg.setText("") - self.img_label_seg.setObjectName("img_label_seg") - self.horizontalLayout_5.addWidget(self.img_label_seg) - self.img_label_obj = QtWidgets.QLabel(self.centralwidget) - self.img_label_obj.setEnabled(True) - sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) - sizePolicy.setHorizontalStretch(0) - sizePolicy.setVerticalStretch(0) - sizePolicy.setHeightForWidth(self.img_label_obj.sizePolicy().hasHeightForWidth()) - self.img_label_obj.setSizePolicy(sizePolicy) - self.img_label_obj.setMinimumSize(QtCore.QSize(250, 200)) - self.img_label_obj.setStyleSheet("border: 2px solid black;") - self.img_label_obj.setText("") - self.img_label_obj.setObjectName("img_label_obj") - self.horizontalLayout_5.addWidget(self.img_label_obj) - self.gridLayout_2.addLayout(self.horizontalLayout_5, 1, 0, 1, 1) self.horizontalLayout_4 = QtWidgets.QHBoxLayout() self.horizontalLayout_4.setContentsMargins(0, -1, -1, -1) self.horizontalLayout_4.setSpacing(0) @@ -184,14 +145,92 @@ class Ui_MainWindow(object): self.label_8.setObjectName("label_8") self.horizontalLayout_4.addWidget(self.label_8) self.gridLayout_2.addLayout(self.horizontalLayout_4, 0, 0, 1, 1) + self.horizontalLayout_5 = QtWidgets.QHBoxLayout() + self.horizontalLayout_5.setObjectName("horizontalLayout_5") + self.img_label_map = QtWidgets.QLabel(self.centralwidget) + self.img_label_map.setEnabled(True) + sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) + sizePolicy.setHorizontalStretch(0) + sizePolicy.setVerticalStretch(0) + sizePolicy.setHeightForWidth(self.img_label_map.sizePolicy().hasHeightForWidth()) + self.img_label_map.setSizePolicy(sizePolicy) + self.img_label_map.setMinimumSize(QtCore.QSize(345, 200)) + self.img_label_map.setStyleSheet("border: 2px solid black;") + self.img_label_map.setText("") + self.img_label_map.setObjectName("img_label_map") + self.horizontalLayout_5.addWidget(self.img_label_map) + self.img_label_seg = QtWidgets.QLabel(self.centralwidget) + self.img_label_seg.setEnabled(True) + sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) + sizePolicy.setHorizontalStretch(0) + sizePolicy.setVerticalStretch(0) + sizePolicy.setHeightForWidth(self.img_label_seg.sizePolicy().hasHeightForWidth()) + self.img_label_seg.setSizePolicy(sizePolicy) + self.img_label_seg.setMinimumSize(QtCore.QSize(250, 200)) + self.img_label_seg.setStyleSheet("border: 2px solid black;") + self.img_label_seg.setText("") + self.img_label_seg.setObjectName("img_label_seg") + self.horizontalLayout_5.addWidget(self.img_label_seg) + self.img_label_obj = QtWidgets.QLabel(self.centralwidget) + self.img_label_obj.setEnabled(True) + sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) + sizePolicy.setHorizontalStretch(0) + sizePolicy.setVerticalStretch(0) + sizePolicy.setHeightForWidth(self.img_label_obj.sizePolicy().hasHeightForWidth()) + self.img_label_obj.setSizePolicy(sizePolicy) + self.img_label_obj.setMinimumSize(QtCore.QSize(250, 200)) + self.img_label_obj.setStyleSheet("border: 2px solid black;") + self.img_label_obj.setText("") + self.img_label_obj.setObjectName("img_label_obj") + self.horizontalLayout_5.addWidget(self.img_label_obj) + self.gridLayout_2.addLayout(self.horizontalLayout_5, 1, 0, 1, 1) self.gridLayout_3.addLayout(self.gridLayout_2, 0, 0, 1, 1) self.gridLayout.addLayout(self.gridLayout_3, 6, 0, 1, 3) self.verticalLayout_3 = QtWidgets.QVBoxLayout() self.verticalLayout_3.setObjectName("verticalLayout_3") - self.textEdit_5 = QtWidgets.QTextEdit(self.centralwidget) - self.textEdit_5.setObjectName("textEdit_5") - self.verticalLayout_3.addWidget(self.textEdit_5) + self.textBrowser_5 = QtWidgets.QTextBrowser(self.centralwidget) + font = QtGui.QFont() + font.setFamily("黑体") + font.setPointSize(13) + font.setBold(False) + font.setWeight(50) + self.textBrowser_5.setFont(font) + self.textBrowser_5.setLayoutDirection(QtCore.Qt.LeftToRight) + self.textBrowser_5.setStyleSheet("text-align:center;") + self.textBrowser_5.setMarkdown("") + self.textBrowser_5.setObjectName("textBrowser_5") + self.verticalLayout_3.addWidget(self.textBrowser_5) self.gridLayout.addLayout(self.verticalLayout_3, 5, 0, 1, 1) + self.label_9 = QtWidgets.QLabel(self.centralwidget) + font = QtGui.QFont() + font.setFamily("等线") + font.setPointSize(10) + font.setBold(True) + font.setWeight(75) + self.label_9.setFont(font) + self.label_9.setObjectName("label_9") + self.gridLayout.addWidget(self.label_9, 0, 0, 1, 1) + self.btn_say = QtWidgets.QPushButton(self.centralwidget) + font = QtGui.QFont() + font.setFamily("黑体") + font.setPointSize(14) + self.btn_say.setFont(font) + self.btn_say.setObjectName("btn_say") + self.gridLayout.addWidget(self.btn_say, 0, 2, 1, 1) + self.edit_say = QtWidgets.QLineEdit(self.centralwidget) + font = QtGui.QFont() + font.setFamily("Times New Roman") + font.setPointSize(14) + self.edit_say.setFont(font) + self.edit_say.setObjectName("edit_say") + self.gridLayout.addWidget(self.edit_say, 0, 1, 1, 1) + self.label = QtWidgets.QLabel(self.centralwidget) + font = QtGui.QFont() + font.setFamily("黑体") + font.setPointSize(14) + self.label.setFont(font) + self.label.setObjectName("label") + self.gridLayout.addWidget(self.label, 4, 0, 1, 1) self.verticalLayout = QtWidgets.QVBoxLayout() self.verticalLayout.setObjectName("verticalLayout") self.btn_reset = QtWidgets.QPushButton(self.centralwidget) @@ -250,42 +289,16 @@ class Ui_MainWindow(object): sizePolicy.setHeightForWidth(self.cb_task.sizePolicy().hasHeightForWidth()) self.cb_task.setSizePolicy(sizePolicy) self.cb_task.setMinimumSize(QtCore.QSize(0, 25)) + font = QtGui.QFont() + font.setFamily("黑体") + font.setPointSize(14) + self.cb_task.setFont(font) self.cb_task.setEditable(True) self.cb_task.setCurrentText("") self.cb_task.setInsertPolicy(QtWidgets.QComboBox.InsertAtBottom) self.cb_task.setObjectName("cb_task") self.verticalLayout.addWidget(self.cb_task) self.gridLayout.addLayout(self.verticalLayout, 1, 0, 1, 1) - self.label_9 = QtWidgets.QLabel(self.centralwidget) - font = QtGui.QFont() - font.setFamily("等线") - font.setPointSize(10) - font.setBold(True) - font.setWeight(75) - self.label_9.setFont(font) - self.label_9.setObjectName("label_9") - self.gridLayout.addWidget(self.label_9, 0, 0, 1, 1) - self.btn_say = QtWidgets.QPushButton(self.centralwidget) - font = QtGui.QFont() - font.setFamily("黑体") - font.setPointSize(14) - self.btn_say.setFont(font) - self.btn_say.setObjectName("btn_say") - self.gridLayout.addWidget(self.btn_say, 0, 2, 1, 1) - self.label = QtWidgets.QLabel(self.centralwidget) - font = QtGui.QFont() - font.setFamily("黑体") - font.setPointSize(14) - self.label.setFont(font) - self.label.setObjectName("label") - self.gridLayout.addWidget(self.label, 4, 0, 1, 1) - self.edit_say = QtWidgets.QLineEdit(self.centralwidget) - font = QtGui.QFont() - font.setFamily("Times New Roman") - font.setPointSize(14) - self.edit_say.setFont(font) - self.edit_say.setObjectName("edit_say") - self.gridLayout.addWidget(self.edit_say, 0, 1, 1, 1) MainWindow.setCentralWidget(self.centralwidget) self.statusbar = QtWidgets.QStatusBar(MainWindow) self.statusbar.setObjectName("statusbar") @@ -311,6 +324,15 @@ class Ui_MainWindow(object): self.label_6.setText(_translate("MainWindow", "可达性地图")) self.label_7.setText(_translate("MainWindow", "实例分割")) self.label_8.setText(_translate("MainWindow", "目标检测")) + self.textBrowser_5.setHtml(_translate("MainWindow", "\n" +"\n" +"


")) + self.label_9.setText(_translate("MainWindow", "任务演示：（播放动画时需等待动画播放完毕才会重置场景）")) + self.btn_say.setText(_translate("MainWindow", "说话")) + self.edit_say.setText(_translate("MainWindow", "Is(AC,On)")) + self.label.setText(_translate("MainWindow", "语义信息")) self.btn_reset.setText(_translate("MainWindow", "重置场景")) self.btn_AEM.setText(_translate("MainWindow", "环境主动探索")) self.btn_VLN.setText(_translate("MainWindow", "视觉语言导航")) @@ -319,10 +341,6 @@ class Ui_MainWindow(object): self.btn_OT.setText(_translate("MainWindow", "开放具身任务")) self.btn_AT.setText(_translate("MainWindow", "自主具身任务")) self.cb_task.setPlaceholderText(_translate("MainWindow", "其他任务")) - self.label_9.setText(_translate("MainWindow", "任务演示：（播放动画时需等待动画播放完毕才会重置场景）")) - self.btn_say.setText(_translate("MainWindow", "说话")) - self.label.setText(_translate("MainWindow", "语义信息")) - self.edit_say.setText(_translate("MainWindow", "Is(AC,On)")) if __name__ == "__main__": diff --git a/robowaiter/scene/ui/window.ui b/robowaiter/scene/ui/window.ui index afae9af..5da0597 100644 --- a/robowaiter/scene/ui/window.ui +++ b/robowaiter/scene/ui/window.ui @@ -153,85 +153,6 @@ - - - - - - true - - - - 0 - 0 - - - - - 345 - 200 - - - - border: 2px solid black; - - - - - - - - - - true - - - - 0 - 0 - - - - - 250 - 200 - - - - border: 2px solid black; - - - - - - - - - - true - - - - 0 - 0 - - - - - 250 - 200 - - - - border: 2px solid black; - - - - - - - - @@ -317,6 +238,85 @@ + + + + + + true + + + + 0 + 0 + + + + + 345 + 200 + + + + border: 2px solid black; + + + + + + + + + + true + + + + 0 + 0 + + + + + 250 + 200 + + + + border: 2px solid black; + + + + + + + + + + true + + + + 0 + 0 + + + + + 250 + 200 + + + + border: 2px solid black; + + + + + + + + @@ -324,10 +324,89 @@ - + + + + 黑体 + 13 + 50 + false + + + + Qt::LeftToRight + + + text-align:center; + + + + + + <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//EN" "http://www.w3.org/TR/REC-html40/strict.dtd"> +<html><head><meta name="qrichtext" content="1" /><style type="text/css"> +p, li { white-space: pre-wrap; } +</style></head><body style=" font-family:'黑体'; font-size:13pt; font-weight:400; font-style:normal;"> +<p style="-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:11pt;"><br /></p></body></html> + + + + + + + 等线 + 10 + 75 + true + + + + 任务演示：（播放动画时需等待动画播放完毕才会重置场景） + + + + + + + + 黑体 + 14 + + + + 说话 + + + + + + + + Times New Roman + 14 + + + + Is(AC,On) + + + + + + + + 黑体 + 14 + + + + 语义信息 + + + @@ -435,6 +514,12 @@ 25 + + + 黑体 + 14 + + false @@ -454,60 +539,6 @@ - - - - - 等线 - 10 - 75 - true - - - - 任务演示：（播放动画时需等待动画播放完毕才会重置场景） - - - - - - - - 黑体 - 14 - - - - 说话 - - - - - - - - 黑体 - 14 - - - - 语义信息 - - - - - - - - Times New Roman - 14 - - - - Is(AC,On) - - - diff --git a/robowaiter/utils/draw_bt/Default.ptml b/robowaiter/utils/draw_bt/Default.ptml index 55a6f88..d5ec102 100644 --- a/robowaiter/utils/draw_bt/Default.ptml +++ b/robowaiter/utils/draw_bt/Default.ptml @@ -1,10 +1,26 @@ +selector{ +cond On(Yogurt,Bar) sequence{ -cond Holding(Nothing) -sequence{ -cond Is(Curtain,Off) -act Turn(Curtain,On) +cond Holding(Yogurt) + cond At(Robot,Bar) +act PutDown(Yogurt,Bar) } sequence{ -cond Is(AC,Off) -act Turn(AC,On) -}} \ No newline at end of file +cond Holding(Yogurt) +act MoveTo(Bar) +} +sequence{ +cond Holding(Nothing) + cond At(Robot,Yogurt) +act PickUp(Yogurt) +} +sequence{ +cond At(Robot,Yogurt) +act FreeHands() +} +sequence{ +cond Holding(Nothing) + cond Exist(Yogurt) +act MoveTo(Yogurt) +} +} diff --git a/robowaiter/utils/draw_bt/Default_bracket.ptml b/robowaiter/utils/draw_bt/Default_bracket.ptml index 844db49..7eed65e 100644 --- a/robowaiter/utils/draw_bt/Default_bracket.ptml +++ b/robowaiter/utils/draw_bt/Default_bracket.ptml @@ -1,29 +1,38 @@ -selector +Selector { - sequence + cond On(Yogurt,Bar) + Sequence { - cond Chatting() - act DealChat() - } sequence + cond Holding(Yogurt) + cond At(Robot,Bar) + act PutDown(Yogurt,Bar) + } Sequence { - cond HasSubTask() - sequence + cond Holding(Yogurt) + act MoveTo(Bar) + } Sequence { - act SubTaskPlaceHolder() - } } sequence + cond Holding(Nothing) + cond At(Robot,Yogurt) + cond At(Robot,Bar) + act PickUp(Yogurt) + } Sequence { - cond FocusingCustomer() - act ServeCustomer() - } sequence + cond Holding(Nothing) + cond At(Robot,Yogurt) + act PickUp(Yogurt) + } Sequence { - cond NewCustomer() - selector + cond At(Robot,Yogurt) + cond At(Robot,Bar) + act FreeHands() + } Sequence { - cond At(Robot,Bar) - act MoveTo(Bar) - } act GreetCustomer() - } sequence + cond At(Robot,Yogurt) + act FreeHands() + } Sequence { - cond AnomalyDetected() - act ResolveAnomaly() + cond Holding(Nothing) + cond Exist(Yogurt) + act MoveTo(Yogurt) }} \ No newline at end of file diff --git a/robowaiter/utils/draw_bt/test.png b/robowaiter/utils/draw_bt/test.png index 15a3183..dce3fe0 100644 Binary files a/robowaiter/utils/draw_bt/test.png and b/robowaiter/utils/draw_bt/test.png differ diff --git a/tasks_no_ui/OT/Open_tasks_test.py b/tasks_no_ui/OT/Open_tasks_test.py index 996c28a..a49796c 100644 --- a/tasks_no_ui/OT/Open_tasks_test.py +++ b/tasks_no_ui/OT/Open_tasks_test.py @@ -18,7 +18,32 @@ class SceneOT(Scene): super().__init__(robot) # 在这里加入场景中发生的事件 self.signal_event_list = [ - (3, self.customer_say, ("System", "冰红茶")), + # (3, self.customer_say, ("System", "有多少盒装饮料")), + # (3, self.customer_say, ("System", "桌子有几张")), + # (3, self.customer_say, ("System", "你们这儿有军棋吗")), + # (3, self.customer_say, ("System", "军棋有几个")), + # (3, self.customer_say, ("System", "有几把椅子呀")), + # (3, self.customer_say, ("System", "有多少顾客")), + # (3, self.customer_say, ("System", "你们这儿有多少军棋")), + + # (3, self.customer_say, ("System", "哪里有盒装饮料？")), + # (3, self.customer_say, ("System", "洗手间在哪里？")),卫生间 + # (3, self.customer_say, ("System", "卫生间在哪里？")), + + # (3, self.customer_say, ("System", "你们这里有棋吗，在哪里")), + + # (3, self.customer_say, ("System", "有几副棋")), + # (3, self.customer_say, ("System", "我的手镯，你有看到吗")), + # (3, self.customer_say, ("System", "你们这有小说吗？")), + # (3, self.customer_say, ("System", "我昨天保温杯落在你们咖啡厅了，你看到了吗？")), + # (3, self.customer_say, ("System", "你们这有魔方吗？")), + # (3, self.customer_say, ("System", "垃圾桶在哪呀？")), + + # (3, self.customer_say, ("System", "这有小说吗？在哪里")), + + + # (3, self.customer_say, ("System", "把盒装冰红茶放到水桌")), + # (3, self.customer_say, ("System", "冰红茶")), # (3, self.customer_say, ("System", "酸奶。")), # (3, self.customer_say, ("System","来一号桌")), # (-1, self.customer_say, ("System","回去吧")), @@ -30,7 +55,7 @@ class SceneOT(Scene): # ] def _reset(self): - # self.add_walkers([[0, 880], [250, 1200]]) + self.add_walkers([[0, 880], [250, 1200]]) self.gen_obj() pass