爬glm代码

README.md

@@ -15,6 +15,8 @@ pip install -e .
 ### 安装UI
 1. 安装 [graphviz-9.0.0](https://gitlab.com/api/v4/projects/4207231/packages/generic/graphviz-releases/9.0.0/windows_10_cmake_Release_graphviz-install-9.0.0-win64.exe) (详见[官网](https://www.graphviz.org/download/#windows))
 2. 将软件安装目录的bin文件添加到系统环境中。如电脑是Windows系统，Graphviz安装在D:\Program Files (x86)\Graphviz2.38，该目录下有bin文件，将该路径添加到电脑系统环境变量path中，即D:\Program Files (x86)\Graphviz2.38\bin。
+3. 安装向量数据库
+conda install -c conda-forge faiss
 
 ### 快速入门
 1. 安装UE及Harix插件，打开默认项目并运行

robowaiter/llm_client/passage_retrieval3.py

@@ -21,7 +21,8 @@ from robowaiter.algos.retrieval.retrieval_lm.src.data import load_passages
 
 from robowaiter.algos.retrieval.retrieval_lm.src.evaluation import calculate_matches
 import warnings
-
+from robowaiter.utils.basic import get_root_path
+root_path = get_root_path()
 warnings.filterwarnings('ignore')
 os.environ["TOKENIZERS_PARALLELISM"] = "true"
 
@@ -244,8 +245,8 @@ def retri(query):
     )
     # parser.add_argument("--passages", type=str, default='C:/Users/huangyu/Desktop/RoboWaiter-main/RoboWaiter-main/train_robot.jsonl', help="Path to passages (.tsv file)")
     # parser.add_argument("--passages_embeddings", type=str, default='C:/Users/huangyu/Desktop/RoboWaiter-main/RoboWaiter-main/robot_embeddings/*', help="Glob path to encoded passages")
-    parser.add_argument("--passages", type=str, default='D:/AAAAA_EI_LLM/UnrealProject/RobotProject/Plugins/RoboWaiter/robowaiter/llm_client/train_robot.jsonl', help="Path to passages (.tsv file)")
-    parser.add_argument("--passages_embeddings", type=str, default='D:/AAAAA_EI_LLM/UnrealProject/RobotProject/Plugins/RoboWaiter/robowaiter/algos/retrieval/robot_embeddings/*', help="Glob path to encoded passages")
+    parser.add_argument("--passages", type=str, default=f'{root_path}/robowaiter/llm_client/train_robot.jsonl', help="Path to passages (.tsv file)")
+    parser.add_argument("--passages_embeddings", type=str, default=f'{root_path}/robowaiter/algos/retrieval/robot_embeddings/*', help="Glob path to encoded passages")
 
     parser.add_argument(
         "--output_dir", type=str, default='robot_result', help="Results are written to outputdir with data suffix"
@@ -262,7 +263,7 @@ def retri(query):
     #     "--model_name_or_path", type=str, default='C:\\Users\\huangyu\\Desktop\\RoboWaiter-main\\RoboWaiter-main\\contriever-msmarco',help="path to directory containing model weights and config file"
     # )
     parser.add_argument(
-        "--model_name_or_path", type=str, default='D:\\AAAAA_EI_LLM\\UnrealProject\\RobotProject\\Plugins\\RoboWaiter\\robowaiter\\algos\\retrieval\\contriever-msmarco',help="path to directory containing model weights and config file"
+        "--model_name_or_path", type=str, default=f'{root_path}/robowaiter/algos/retrieval/contriever-msmarco',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")

robowaiter/llm_client/robot_result/test_robot.jsonl

@@ -1 +1 @@
-{"id": 1, "question": "你能把空调打开一下吗？", "ctxs": [{"id": "505", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8559918"}, {"id": "313", "title": "你能把空调打开一下吗？", "text": "Is(AC,1)", "score": "1.8559918"}, {"id": "312", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8559918"}, {"id": "120", "title": "你能把空调打开一下吗？", "text": "Is(AC,1)", "score": "1.8559918"}, {"id": "119", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8559918"}]}
+{"id": 1, "question": "你能把空调打开一下吗？", "ctxs": [{"id": "505", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8567487"}, {"id": "313", "title": "你能把空调打开一下吗？", "text": "Is(AC,1)", "score": "1.8567487"}, {"id": "312", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8567487"}, {"id": "120", "title": "你能把空调打开一下吗？", "text": "Is(AC,1)", "score": "1.8567487"}, {"id": "119", "title": "你能把空调关闭一下吗？", "text": "Is(AC,0)", "score": "1.8567487"}]}

robowaiter/llm_client/single_round_crawer.py

@@ -0,0 +1,43 @@
+
+import requests
+import urllib3
+########################################
+#   该文件实现了与大模型的简单通信
+########################################
+
+# 忽略https的安全性警告
+urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
+
+
+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
+          }
+        ]
+      }
+
+    response = requests.post(url, headers=headers, json=data, verify=False)
+
+    if response.status_code == 200:
+        result = response.json()
+        return result['choices'][0]['message']['content'].strip()
+    else:
+        return "大模型请求失败:", response.status_code
+
+
+if __name__ == '__main__':
+    question = '''
+    给我一杯拿铁
+    '''
+
+    print(single_round(question))