Python: Removes the _async suffix where is not needed

python/DEV_SETUP.md

@@ -121,6 +121,14 @@ You can also run all the tests together under the [tests](tests/) folder.
 
 ## Tools and scripts
 
+## Implementation Decisions 
+
+### Asynchronous programming
+
+It's important to note that most of this library is written with asynchronous in mind. The 
+developer should always assume everything is asynchronous. One can use the function signature 
+with either `async def` or `def` to understand if something is asynchronous or not.
+
 ## Pydantic and Serialization
 
 [Pydantic Documentation](https://docs.pydantic.dev/1.10/)

python/samples/kernel-syntax-examples/action_planner.py

@@ -30,7 +30,7 @@ async def main():
     ask = "What is the sum of 110 and 990?"
 
     # ask the action planner to identify a suitable function from the list of functions available.
-    plan = await planner.create_plan_async(goal=ask)
+    plan = await planner.create_plan(goal=ask)
 
     # ask the action planner to execute the identified function.
     result = await plan.invoke_async()

python/samples/kernel-syntax-examples/azure_chat_gpt_api.py

@@ -77,13 +77,13 @@ async def chat() -> bool:
 
     stream = True
     if stream:
-        answer = kernel.run_stream_async(chat_function, input_vars=context_vars)
+        answer = kernel.run_stream(chat_function, input_vars=context_vars)
         print("Mosscap:> ", end="")
         async for message in answer:
             print(message, end="")
         print("\n")
         return True
-    answer = await kernel.run_async(chat_function, input_vars=context_vars)
+    answer = await kernel.run(chat_function, input_vars=context_vars)
     print(f"Mosscap:> {answer}")
     return True
 

python/samples/kernel-syntax-examples/azure_chat_gpt_with_data_api.py

@@ -81,7 +81,7 @@ async def chat() -> bool:
     # answer = await kernel.run_async(chat_function, input_vars=context_vars)
     # print(f"Assistant:> {answer}")
 
-    answer = kernel.run_stream_async(chat_function, input_vars=context_vars, input_context=context)
+    answer = kernel.run_stream(chat_function, input_vars=context_vars, input_context=context)
     print("Assistant:> ", end="")
     async for message in answer:
         print(message, end="")

python/samples/kernel-syntax-examples/azure_chat_gpt_with_data_api_cross_lingual.py

@@ -79,7 +79,7 @@ async def chat() -> bool:
     # answer = await kernel.run_async(chat_function, input_vars=context_vars)
     # print(f"Assistant:> {answer}")
 
-    answer = kernel.run_stream_async(chat_function, input_vars=context_vars)
+    answer = kernel.run_stream(chat_function, input_vars=context_vars)
     print("Assistant:> ", end="")
     async for message in answer:
         print(message, end="")

python/samples/kernel-syntax-examples/azure_chat_gpt_with_data_api_vector_search.py

@@ -87,7 +87,7 @@ async def chat() -> bool:
     # answer = await kernel.run_async(chat_function, input_vars=context_vars)
     # print(f"Assistant:> {answer}")
 
-    answer = kernel.run_stream_async(chat_function, input_vars=context_vars, input_context=context)
+    answer = kernel.run_stream(chat_function, input_vars=context_vars, input_context=context)
     print("Assistant:> ", end="")
     async for message in answer:
         print(message, end="")

python/samples/kernel-syntax-examples/azure_cognitive_search_memory.py

@@ -18,17 +18,15 @@
 
 async def populate_memory(kernel: sk.Kernel) -> None:
     # Add some documents to the ACS semantic memory
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info1", text="My name is Andrea")
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info2", text="I currently work as a tour guide")
-    await kernel.memory.save_information_async(
-        COLLECTION_NAME, id="info3", text="I've been living in Seattle since 2005"
-    )
-    await kernel.memory.save_information_async(
+    await kernel.memory.save_information(COLLECTION_NAME, id="info1", text="My name is Andrea")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info2", text="I currently work as a tour guide")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info3", text="I've been living in Seattle since 2005")
+    await kernel.memory.save_information(
         COLLECTION_NAME,
         id="info4",
         text="I visited France and Italy five times since 2015",
     )
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info5", text="My family is from New York")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info5", text="My family is from New York")
 
 
 async def search_acs_memory_questions(kernel: sk.Kernel) -> None:
@@ -42,7 +40,7 @@ async def search_acs_memory_questions(kernel: sk.Kernel) -> None:
 
     for question in questions:
         print(f"Question: {question}")
-        result = await kernel.memory.search_async(COLLECTION_NAME, question)
+        result = await kernel.memory.search(COLLECTION_NAME, question)
         print(f"Answer: {result[0].text}\n")
 
 
@@ -88,7 +86,7 @@ async def main() -> None:
     print("Asking questions... (manually)")
     await search_acs_memory_questions(kernel)
 
-    await connector.close_async()
+    await connector.close()
 
 
 if __name__ == "__main__":

python/samples/kernel-syntax-examples/bing_search_plugin.py

@@ -26,8 +26,8 @@ async def main():
     web_plugin = kernel.import_plugin(WebSearchEnginePlugin(connector), "WebSearch")
 
     prompt = "Who is Leonardo DiCaprio's current girlfriend?"
-    search_async = web_plugin["searchAsync"]
-    result = await search_async.invoke_async(prompt)
+    search = web_plugin["searchAsync"]
+    result = await search.invoke_async(prompt)
     print(result)
 
     """

python/samples/kernel-syntax-examples/chat.py

@@ -43,7 +43,7 @@ async def chat(context_vars: sk.ContextVariables) -> bool:
         print("\n\nExiting chat...")
         return False
 
-    answer = await kernel.run_async(chat_function, input_vars=context_vars)
+    answer = await kernel.run(chat_function, input_vars=context_vars)
     context_vars["chat_history"] += f"\nUser:> {user_input}\nChatBot:> {answer}\n"
 
     print(f"ChatBot:> {answer}")

python/samples/kernel-syntax-examples/chat_gpt_api.py

@@ -48,7 +48,7 @@ async def chat() -> bool:
         print("\n\nExiting chat...")
         return False
 
-    answer = await kernel.run_async(chat_function, input_vars=context_vars)
+    answer = await kernel.run(chat_function, input_vars=context_vars)
     print(f"Mosscap:> {answer}")
     return True
 

python/samples/kernel-syntax-examples/google_palm_chat.py

@@ -17,11 +17,11 @@ async def chat_request_example(api_key):
     chat_messages = list()
     user_mssg = "I'm planning a vacation. Which are some must-visit places in Europe?"
     chat_messages.append(("user", user_mssg))
-    answer = await palm_chat_completion.complete_chat_async(chat_messages, settings)
+    answer = await palm_chat_completion.complete_chat(chat_messages, settings)
     chat_messages.append(("assistant", str(answer)))
     user_mssg = "Where should I go in France?"
     chat_messages.append(("user", user_mssg))
-    answer = await palm_chat_completion.complete_chat_async(chat_messages, settings)
+    answer = await palm_chat_completion.complete_chat(chat_messages, settings)
     chat_messages.append(("assistant", str(answer)))
 
     context_vars = sk.ContextVariables()

python/samples/kernel-syntax-examples/google_palm_chat_with_memory.py

@@ -18,11 +18,11 @@
 
 async def populate_memory(kernel: sk.Kernel) -> None:
     # Add some documents to the semantic memory
-    await kernel.memory.save_information_async("aboutMe", id="info1", text="My name is Andrea")
-    await kernel.memory.save_information_async("aboutMe", id="info2", text="I currently work as a tour guide")
-    await kernel.memory.save_information_async("aboutMe", id="info3", text="My favorite hobby is hiking")
-    await kernel.memory.save_information_async("aboutMe", id="info4", text="I visitied Iceland last year.")
-    await kernel.memory.save_information_async("aboutMe", id="info5", text="My family is from New York")
+    await kernel.memory.save_information("aboutMe", id="info1", text="My name is Andrea")
+    await kernel.memory.save_information("aboutMe", id="info2", text="I currently work as a tour guide")
+    await kernel.memory.save_information("aboutMe", id="info3", text="My favorite hobby is hiking")
+    await kernel.memory.save_information("aboutMe", id="info4", text="I visitied Iceland last year.")
+    await kernel.memory.save_information("aboutMe", id="info5", text="My family is from New York")
 
 
 async def search_memory_examples(kernel: sk.Kernel) -> None:
@@ -36,7 +36,7 @@ async def search_memory_examples(kernel: sk.Kernel) -> None:
 
     for question in questions:
         print(f"Question: {question}")
-        result = await kernel.memory.search_async("aboutMe", question)
+        result = await kernel.memory.search("aboutMe", question)
         print(f"Answer: {result}\n")
 
 
@@ -105,7 +105,7 @@ async def chat(kernel: sk.Kernel, chat_func: sk.KernelFunctionBase, context: sk.
         print("\n\nExiting chat...")
         return False
 
-    answer = await kernel.run_async(chat_func, input_vars=context.variables)
+    answer = await kernel.run(chat_func, input_vars=context.variables)
     context["chat_history"] += f"\nUser:> {user_input}\nChatBot:> {answer}\n"
 
     print(f"ChatBot:> {answer}")

python/samples/kernel-syntax-examples/google_palm_chat_with_plugin.py

@@ -56,7 +56,7 @@ async def chat() -> bool:
         print("\n\nExiting chat...")
         return False
 
-    answer = await kernel.run_async(chat_function, input_vars=context_vars)
+    answer = await kernel.run(chat_function, input_vars=context_vars)
     print(f"Blackbeard:> {answer}")
     return True
 

python/samples/kernel-syntax-examples/google_palm_text_completion.py

@@ -9,13 +9,13 @@
 )
 
 
-async def text_completion_example_complete_async(kernel, api_key, user_mssg, settings):
+async def text_completion_example_complete(kernel, api_key, user_mssg, settings):
     """
     Complete a text prompt using the Google PaLM model and print the results.
     """
     palm_text_completion = sk_gp.GooglePalmTextCompletion("models/text-bison-001", api_key)
     kernel.add_text_completion_service("models/text-bison-001", palm_text_completion)
-    answer = await palm_text_completion.complete_async(user_mssg, settings)
+    answer = await palm_text_completion.complete(user_mssg, settings)
     return answer
 
 
@@ -31,13 +31,13 @@ async def main() -> None:
         "boxes have 98 coins in total. How many coins are there in each box? "
         "Think about it step by step, and show your work."
     )
-    response = await text_completion_example_complete_async(kernel, apikey, user_mssg1, settings)
+    response = await text_completion_example_complete(kernel, apikey, user_mssg1, settings)
     print(f"User:> {user_mssg1}\n\nChatBot:> {response}\n")
     # Use temperature to influence the variance of the responses
     settings.number_of_responses = 3
     settings.temperature = 1
     user_mssg2 = "I need a concise answer. A common method for traversing a binary tree is"
-    response = await text_completion_example_complete_async(kernel, apikey, user_mssg2, settings)
+    response = await text_completion_example_complete(kernel, apikey, user_mssg2, settings)
     print(f"User:> {user_mssg2}\n\nChatBot:> {response}")
     return
 

python/samples/kernel-syntax-examples/google_search_plugin.py

@@ -38,10 +38,10 @@ async def main():
 
     # The search query
     prompt = "Who is Leonardo DiCaprio's current girlfriend?"
-    search_async = web_plugin["searchAsync"]
+    search = web_plugin["searchAsync"]
 
     # By default, only one search result is provided
-    result = await search_async.invoke_async(prompt)
+    result = await search.invoke_async(prompt)
     print(result)
 
     """

python/samples/kernel-syntax-examples/memory.py

@@ -9,13 +9,11 @@
 
 async def populate_memory(kernel: sk.Kernel) -> None:
     # Add some documents to the semantic memory
-    await kernel.memory.save_information_async("aboutMe", id="info1", text="My name is Andrea")
-    await kernel.memory.save_information_async("aboutMe", id="info2", text="I currently work as a tour guide")
-    await kernel.memory.save_information_async("aboutMe", id="info3", text="I've been living in Seattle since 2005")
-    await kernel.memory.save_information_async(
-        "aboutMe", id="info4", text="I visited France and Italy five times since 2015"
-    )
-    await kernel.memory.save_information_async("aboutMe", id="info5", text="My family is from New York")
+    await kernel.memory.save_information("aboutMe", id="info1", text="My name is Andrea")
+    await kernel.memory.save_information("aboutMe", id="info2", text="I currently work as a tour guide")
+    await kernel.memory.save_information("aboutMe", id="info3", text="I've been living in Seattle since 2005")
+    await kernel.memory.save_information("aboutMe", id="info4", text="I visited France and Italy five times since 2015")
+    await kernel.memory.save_information("aboutMe", id="info5", text="My family is from New York")
 
 
 async def search_memory_examples(kernel: sk.Kernel) -> None:
@@ -29,7 +27,7 @@ async def search_memory_examples(kernel: sk.Kernel) -> None:
 
     for question in questions:
         print(f"Question: {question}")
-        result = await kernel.memory.search_async("aboutMe", question)
+        result = await kernel.memory.search("aboutMe", question)
         print(f"Answer: {result[0].text}\n")
 
 
@@ -85,7 +83,7 @@ async def chat(kernel: sk.Kernel, chat_func: sk.KernelFunctionBase, context: sk.
         print("\n\nExiting chat...")
         return False
 
-    answer = await kernel.run_async(chat_func, input_vars=context.variables)
+    answer = await kernel.run(chat_func, input_vars=context.variables)
     context["chat_history"] += f"\nUser:> {user_input}\nChatBot:> {answer}\n"
 
     print(f"ChatBot:> {answer}")

python/samples/kernel-syntax-examples/openai_logit_bias.py

@@ -82,13 +82,13 @@ async def chat_request_example(kernel, api_key, org_id):
     messages = [{"role": "user", "content": user_mssg}]
 
     chat_messages.append(("user", user_mssg))
-    answer = await openai_chat_completion.complete_chat_async(messages=messages, settings=settings)
+    answer = await openai_chat_completion.complete_chat(messages=messages, settings=settings)
     chat_messages.append(("assistant", str(answer[0])))
 
     user_mssg = "What are his best all-time stats?"
     messages = [{"role": "user", "content": user_mssg}]
     chat_messages.append(("user", user_mssg))
-    answer = await openai_chat_completion.complete_chat_async(messages=messages, settings=settings)
+    answer = await openai_chat_completion.complete_chat(messages=messages, settings=settings)
     chat_messages.append(("assistant", str(answer[0])))
 
     context_vars = sk.ContextVariables()
@@ -154,7 +154,7 @@ async def text_complete_request_example(kernel, api_key, org_id):
     settings = _config_ban_tokens(settings, keys)
 
     user_mssg = "The best pie flavor to have in autumn is"
-    answer = await openai_text_completion.complete_async(user_mssg, settings)
+    answer = await openai_text_completion.complete(user_mssg, settings)
 
     context_vars = sk.ContextVariables()
     context_vars["chat_history"] = f"User:> {user_mssg}\nChatBot:> {answer}\n"

python/samples/kernel-syntax-examples/plugins_from_dir.py

@@ -30,5 +30,5 @@
 plugins_directory = os.path.join(__file__, "../../../../samples/plugins")
 plugin = kernel.import_semantic_plugin_from_directory(plugins_directory, "FunPlugin")
 
-result = asyncio.run(kernel.run_async(plugin["Joke"], input_str="time travel to dinosaur age"))
+result = asyncio.run(kernel.run(plugin["Joke"], input_str="time travel to dinosaur age"))
 print(result)

python/samples/kernel-syntax-examples/self-critique_rag.py

@@ -20,17 +20,15 @@
 
 async def populate_memory(kernel: sk.Kernel) -> None:
     # Add some documents to the ACS semantic memory
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info1", text="My name is Andrea")
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info2", text="I currently work as a tour guide")
-    await kernel.memory.save_information_async(
-        COLLECTION_NAME, id="info3", text="I've been living in Seattle since 2005"
-    )
-    await kernel.memory.save_information_async(
+    await kernel.memory.save_information(COLLECTION_NAME, id="info1", text="My name is Andrea")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info2", text="I currently work as a tour guide")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info3", text="I've been living in Seattle since 2005")
+    await kernel.memory.save_information(
         COLLECTION_NAME,
         id="info4",
         text="I visited France and Italy five times since 2015",
     )
-    await kernel.memory.save_information_async(COLLECTION_NAME, id="info5", text="My family is from New York")
+    await kernel.memory.save_information(COLLECTION_NAME, id="info5", text="My family is from New York")
 
 
 async def main() -> None:
@@ -99,7 +97,7 @@ async def main() -> None:
     chat_func = kernel.create_semantic_function(sk_prompt_rag, max_tokens=1000, temperature=0.5)
     self_critique_func = kernel.create_semantic_function(sk_prompt_rag_sc, max_tokens=4, temperature=0.0)
 
-    answer = await kernel.run_async(
+    answer = await kernel.run(
         chat_func,
         input_vars=ContextVariables(
             variables={
@@ -110,24 +108,24 @@ async def main() -> None:
         ),
     )
     print(f"Answer: {str(answer).strip()}")
-    check = await kernel.run_async(self_critique_func, input_context=answer)
+    check = await kernel.run(self_critique_func, input_context=answer)
     print(f"The answer was {str(check).strip()}")
 
     print("-" * 50)
     print("   Let's pretend the answer was wrong...")
     answer.variables.variables["input"] = "Yes, you live in New York City."
     print(f"Answer: {str(answer).strip()}")
-    check = await kernel.run_async(self_critique_func, input_context=answer)
+    check = await kernel.run(self_critique_func, input_context=answer)
     print(f"The answer was {str(check).strip()}")
 
     print("-" * 50)
     print("   Let's pretend the answer is not related...")
     answer.variables.variables["input"] = "Yes, the earth is not flat."
     print(f"Answer: {str(answer).strip()}")
-    check = await kernel.run_async(self_critique_func, input_context=answer)
+    check = await kernel.run(self_critique_func, input_context=answer)
     print(f"The answer was {str(check).strip()}")
 
-    await connector.close_async()
+    await connector.close()
 
 
 if __name__ == "__main__":

python/samples/kernel-syntax-examples/sequential_planner.py

@@ -28,7 +28,7 @@ async def main():
     ask = "What day of the week is today, all uppercase?"
 
     # ask the sequential planner to identify a suitable function from the list of functions available.
-    plan = await planner.create_plan_async(goal=ask)
+    plan = await planner.create_plan(goal=ask)
 
     # ask the sequential planner to execute the identified function.
     result = await plan.invoke_async()

python/semantic_kernel/connectors/ai/chat_completion_client_base.py

@@ -10,7 +10,7 @@
 
 class ChatCompletionClientBase(ABC):
     @abstractmethod
-    async def complete_chat_async(
+    async def complete_chat(
         self,
         messages: List["ChatMessage"],
         settings: "AIRequestSettings",
@@ -31,7 +31,7 @@ async def complete_chat_async(
         pass
 
     @abstractmethod
-    async def complete_chat_stream_async(
+    async def complete_chat_stream(
         self,
         messages: List["ChatMessage"],
         settings: "AIRequestSettings",