chore: import upstream snapshot with attribution

libs/python-sdk/tests/chat_test.py

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+from open_chatcaht.chatchat_api import ChatChat
+
+# todo 之后改为标准测试
+# chatchat = ChatChat()
+# for data in chatchat.chat.kb_chat(query='你好', kb_name="example_kb", model='glm-4'):
+#     print(data)
+# for data in chatchat.chat.kb_chat(query='你好', kb_name="example_kb", model='glm-4'):
+#     print(data)
+#
+# for data in chatchat.chat.file_chat(query='你好', knowledge_id="16d57480d9654104b405648f54d2485e", model_name='glm-4'):
+#     print(data)
+# print(chatchat.chat.chat_feedback(message_id='a9bb673176cd4e34a827c63fd72945f2'))

libs/python-sdk/tests/data/upload_file1.txt

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+{}

libs/python-sdk/tests/data/upload_file2.txt

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+{}

libs/python-sdk/tests/kb_test.py

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+import logging
+
+from open_chatcaht.chatchat_api import ChatChat
+from open_chatcaht.types.knowledge_base.doc.upload_temp_docs_param import UploadTempDocsParam
+
+# chatchat = ChatChat()
+# print('create_kb', chatchat.knowledge.create_kb(knowledge_base_name="example_kb"))
+# print('update_kb_info', chatchat.knowledge.update_kb_info(knowledge_base_name="example_kb", kb_info='aaaaaaa'))
+# print('list_kb', chatchat.knowledge.list_kb())
+# print('list_kb_docs_file', chatchat.knowledge.list_kb_docs_file(knowledge_base_name="samples"))
+# print('delete_kb', chatchat.knowledge.delete_kb(knowledge_base_name="example_kb"))
+# print('search_kb_docs', chatchat.knowledge.search_kb_docs(knowledge_base_name="example_kb", query="hello"))
+# print('upload_kb_docs', chatchat.knowledge.upload_kb_docs(
+#     files=["data/upload_file1.txt", "data/upload_file2.txt"],
+#     knowledge_base_name="example_kb",
+# ))
+# print('search_kb_docs', chatchat.knowledge.search_kb_docs(knowledge_base_name="example_kb", query="hello"))
+# print('recreate_vector_store', chatchat.knowledge.recreate_vector_store(
+#     knowledge_base_name="samples",
+# ))
+# print('recreate_summary_vector_store', chatchat.knowledge.recreate_summary_vector_store(
+#     knowledge_base_name="example_kb",
+#     embed_model="embedding-2",
+#     model_name="glm-4",
+# ))
+# for data in chatchat.knowledge.summary_file_to_vector_store(
+#         knowledge_base_name="samples",
+#         file_name="data/upload_file1.txt",
+#         embed_model="embedding-2",
+#         max_tokens=10000):
+#     print(data)
+# print('summary_file_to_vector_store', chatchat.knowledge.summary_doc_ids_to_vector_store(
+#     knowledge_base_name="samples",
+#     file_name="data/upload_file1.txt",
+# ))
+# print('delete_kb_docs', chatchat.knowledge.delete_kb_docs(
+#     knowledge_base_name="samples",
+#     file_names=["upload_file1.txt"],
+# ))
+
+# print(chatchat.knowledge.download_kb_doc_file(
+#     knowledge_base_name='example_kb',
+#     file_name='README.md'
+# ))
+# print(chatchat.knowledge.kb_doc_file_content(
+#     knowledge_base_name='example_kb',
+#     file_name='README.md'
+# ))
+# print(chatchat.knowledge.upload_temp_docs(
+#     files=["README.md", ],
+#     knowledge_id="4",
+# ))
+# print(chatchat.knowledge.search_temp_kb_docs(knowledge_id="cf414f74bca24fbdaece1ae8bb4d3970", query="hello"))

libs/python-sdk/tests/server_test.py

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+from open_chatcaht.chatchat_api import ChatChat
+
+# chatchat = ChatChat()
+# print(chatchat.server.get_server_configs())
+# print(chatchat.server.get_prompt_template())

libs/python-sdk/tests/standard_openai_test.py

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+from open_chatcaht.chatchat_api import ChatChat
+from open_chatcaht.types.standard_openai.chat_input import OpenAIChatInput
+#
+# chatchat = ChatChat()

libs/python-sdk/tests/tools_test.py

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+from open_chatcaht.chatchat_api import ChatChat
+
+chatchat = ChatChat()
+print(chatchat.tool.list())
+print(chatchat.tool.call('calculate', {"text": "3+5/2"}))

libs/python-sdk/tests/装饰器声明请求_test.py

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+from functools import wraps
+from typing import Type, get_type_hints
+
+import httpx
+import requests
+from pydantic import BaseModel
+
+from open_chatcaht.api_client import ApiClient
+from open_chatcaht.types.knowledge_base.delete_knowledge_base_param import DeleteKnowledgeBaseParam
+from open_chatcaht.types.response.base import ListResponse
+
+base_url = "https://api.example.com"
+headers = {"Authorization": "Bearer token"}
+
+
+def http_request(method):
+    def decorator(url, base_url='', headers=None, body_model: Type[BaseModel] = None, **options):
+        headers = headers or {}
+
+        def wrapper(func):
+            @wraps(func)
+            def inner(*args, **kwargs):
+                try:
+
+                    print("args", args)
+                    print("kwargs", kwargs)
+                    # Prepare the request URL
+                    full_url = base_url + url
+
+                    # Prepare the request data
+                    data = kwargs
+                    return_type = get_type_hints(func).get('return')
+                    print(f"Return type: {return_type}")
+                    print(body_model)
+                    print(f"body_model: {body_model}")
+                    # Send the HTTP request
+                    response = method(full_url, headers=headers, json=data)
+                    response.raise_for_status()
+
+                    # Return the response JSON
+                    return response.json()
+                except requests.exceptions.HTTPError as http_err:
+                    print(f"HTTP error occurred: {http_err}")
+                except Exception as err:
+                    print(f"An error occurred: {err}")
+
+            return inner
+
+        return wrapper
+
+    return decorator
+
+
+# Usage example
+post = http_request(httpx.post)
+
+
+class MyAPIClient(ApiClient):
+
+    @post(url='/api/kb/recreate_summary_vector_store', base_url=base_url, headers=headers,
+          body_model=DeleteKnowledgeBaseParam)
+    def recreate_summary_vector_store(
+            self,
+            a: int,
+            b: int
+    ) -> ListResponse:
+        pass
+
+
+@post(url='/api/kb/recreate_summary_vector_store', base_url=base_url, headers=headers,
+      body_model=DeleteKnowledgeBaseParam)
+def recreate_summary_vector_store(
+        a: int,
+        b: int
+) -> ListResponse:
+    pass
+
+
+# Example usage
+if __name__ == "__main__":
+    # Call the decorated function
+    # response = recreate_summary_vector_store(a=1, b=1)
+    # print(response)
+    api_client = MyAPIClient()
+    response = api_client.recreate_summary_vector_store(a=1, b=2)
+    print("response", response)

libs/python-sdk/tests/装饰器声明请求_test1.py

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+import inspect
+from functools import wraps
+import requests
+
+
+class HTTPClient:
+    def __init__(self, base_url='', headers=None):
+        self.base_url = base_url
+        self.headers = headers or {}
+
+    def http_request(self, method):
+        def decorator(url, **options):
+            headers = options.get('headers', self.headers)
+
+            def wrapper(func):
+                @wraps(func)
+                def inner(*args, **kwargs):
+                    try:
+                        # Prepare the request URL
+                        full_url = self.base_url + url
+                        instance = args[0]  # Assuming func is a method of the class
+                        print(f"Instance: {instance}")
+                        # Prepare the request data from function arguments
+                        data = kwargs
+                        print(kwargs)
+                        # Send the HTTP request
+                        response = method(full_url, headers=headers, json=data)
+                        response.raise_for_status()
+
+                        # Return the response JSON
+                        return response.json()
+                    except requests.exceptions.HTTPError as http_err:
+                        print(f"HTTP error occurred: {http_err}")
+                    except Exception as err:
+                        print(f"An error occurred: {err}")
+
+                return inner
+
+            return wrapper
+
+        return decorator
+
+    def post(self, url, **options):
+        print(self)
+
+        # Define a function that applies the decorator
+        def decorator(func):
+            return self.http_request(requests.post)(url, **options)(func)
+
+        return decorator
+
+
+app: HTTPClient = HTTPClient()
+
+
+# Example usage of the class and its decorators
+class MyAPIClient(HTTPClient):
+    def __init__(self):
+        super().__init__(base_url="https://api.example.com", headers={"Authorization": "Bearer token"})
+
+    @app.post(url='/api/kb/recreate_summary_vector_store')
+    def recreate_summary_vector_store(self, a: int, b: int):
+        ...
+
+
+# Example call to the decorated method
+if __name__ == "__main__":
+    client = MyAPIClient()
+    response = client.recreate_summary_vector_store(a=1, b=1)
+    print(response)