Fix minor typos in AgentChat and Core python documentation

python/docs/src/user-guide/agentchat-user-guide/selector-group-chat.ipynb

@@ -224,7 +224,7 @@
                 "\n",
                 "Let's use two termination conditions:\n",
                 "{py:class}`~autogen_agentchat.conditions.TextMentionTermination` to end the conversation when the Planning Agent sends \"TERMINATE\",\n",
-                "and {py:class}`~autogen_agentchat.conditions.MaxMessageTermination` to limit the conversation to 25 messages to avoid infinite loop."
+                "and {py:class}`~autogen_agentchat.conditions.MaxMessageTermination` to limit the conversation to 25 messages to avoid entering an infinite loop."
             ]
         },
         {
@@ -550,7 +550,7 @@
                 "Each participant agent only makes one step (executing tools, generating a response, etc.)\n",
                 "on each turn. \n",
                 "If you want an {py:class}`~autogen_agentchat.agents.AssistantAgent` to repeat\n",
-                "until it stop returning a {py:class}`~autogen_agentchat.messages.ToolCallSummaryMessage`\n",
+                "until it stops by returning a {py:class}`~autogen_agentchat.messages.ToolCallSummaryMessage`\n",
                 "when it has finished running all the tools it needs to run, you can do so by\n",
                 "checking the last message and returning the agent if it is a\n",
                 "{py:class}`~autogen_agentchat.messages.ToolCallSummaryMessage`.\n",
@@ -689,7 +689,7 @@
                 "    if web_search_agent.name in previous_set_of_agents and data_analyst_agent.name in previous_set_of_agents:\n",
                 "        return [planning_agent.name]\n",
                 "\n",
-                "    # if no-conditions are met then return all the agents\n",
+                "    # if no conditions are met then return all the agents\n",
                 "    return [planning_agent.name, web_search_agent.name, data_analyst_agent.name]\n",
                 "\n",
                 "\n",

python/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb

@@ -698,7 +698,7 @@
     "\n",
     "The following preset agents are available:\n",
     "\n",
-    "- {py:class}`~autogen_agentchat.agents.UserProxyAgent`: An agent that takes user input returns it as responses.\n",
+    "- {py:class}`~autogen_agentchat.agents.UserProxyAgent`: An agent that takes user input and returns it as responses.\n",
     "- {py:class}`~autogen_agentchat.agents.CodeExecutorAgent`: An agent that can execute code.\n",
     "- {py:class}`~autogen_ext.agents.openai.OpenAIAssistantAgent`: An agent that is backed by an OpenAI Assistant, with ability to use custom tools.\n",
     "- {py:class}`~autogen_ext.agents.web_surfer.MultimodalWebSurfer`: A multi-modal agent that can search the web and visit web pages for information.\n",

python/docs/src/user-guide/core-user-guide/components/command-line-code-executors.ipynb

@@ -31,7 +31,7 @@
     "\n",
     "### Inspecting the container\n",
     "\n",
-    "If you wish to keep the container around after AutoGen is finished using it for whatever reason (e.g. to inspect the container), \n",
+    "If you wish to keep the container around after AutoGen is finished using it for whatever reason (e.g., to inspect the container), \n",
     "then you can set the `auto_remove` parameter to `False` when creating the executor. \n",
     "`stop_container` can also be set to `False` to prevent the container from being stopped at the end of the execution.\n",
     "\n",

python/docs/src/user-guide/core-user-guide/components/model-clients.ipynb

@@ -180,8 +180,7 @@
     "## Structured Output\n",
     "\n",
     "Structured output can be enabled by setting the `response_format` field in\n",
-    "{py:class}`~autogen_ext.models.openai.OpenAIChatCompletionClient` and {py:class}`~autogen_ext.models.openai.AzureOpenAIChatCompletionClient` to\n",
-    "as a [Pydantic BaseModel](https://docs.pydantic.dev/latest/concepts/models/) class.\n",
+    "{py:class}`~autogen_ext.models.openai.OpenAIChatCompletionClient` and {py:class}`~autogen_ext.models.openai.AzureOpenAIChatCompletionClient` to a [Pydantic BaseModel](https://docs.pydantic.dev/latest/concepts/models/) class.\n",
     "\n",
     "```{note}\n",
     "Structured output is only available for models that support it. It also\n",

python/docs/src/user-guide/core-user-guide/core-concepts/agent-identity-and-lifecycle.md

@@ -3,16 +3,16 @@
 
 The agent runtime manages agents' identities
 and lifecycles.
-Application does not create agents directly, rather,
+An application does not create agents directly, rather,
 it registers an agent type with a factory function for
 agent instances.
 In this section, we explain how agents are identified
 and created by the runtime.
 
 ## Agent ID
 
-Agent ID uniquely identifies an agent instance within
-an agent runtime -- including distributed runtime.
+An Agent ID uniquely identifies an agent instance within
+an agent runtime -- including in a distributed runtime.
 It is the "address" of the agent instance for receiving messages.
 It has two components: agent type and agent key.
 

python/docs/src/user-guide/core-user-guide/core-concepts/topic-and-subscription.md

@@ -35,7 +35,7 @@ when publishing messages about new issues.
 Topic source is the unique identifier for a topic within a topic type.
 It is typically defined by application data.
 For example, the GitHub agent may use `"github.com/{repo_name}/issues/{issue_number}"`
-as the topic source to uniquely identifies the topic.
+as the topic source to uniquely identify the topic.
 Topic source allows the publisher to limit the scope of messages and create
 silos.
 
@@ -71,7 +71,7 @@ exact topic sources and agent keys.
 The mechanism is simple: any topic matching the type-based subscription's
 topic type will be mapped to an agent ID with the subscription's agent type
 and the agent key assigned to the value of the topic source.
-For Python API, use {py:class}`~autogen_core.components.TypeSubscription`.
+For the Python API, use {py:class}`~autogen_core.components.TypeSubscription`.
 
 ```{note}
 Type-Based Subscription = Topic Type --> Agent Type

python/docs/src/user-guide/core-user-guide/design-patterns/mixture-of-agents.ipynb

@@ -18,7 +18,7 @@
     "following the [original implementation](https://github.com/togethercomputer/moa) of multi-layer mixture of agents.\n",
     "\n",
     "Here is a high-level procedure overview of the pattern:\n",
-    "1. The orchestrator agent takes input a user task and first dispatches it to the worker agents in the first layer.\n",
+    "1. The orchestrator agent takes as input a user task and first dispatches it to the worker agents in the first layer.\n",
     "2. The worker agents in the first layer process the task and return the results to the orchestrator agent.\n",
     "3. The orchestrator agent then synthesizes the results from the first layer and dispatches an updated task with the previous results to the worker agents in the second layer.\n",
     "4. The process continues until the final layer is reached.\n",

python/docs/src/user-guide/core-user-guide/framework/agent-and-agent-runtime.ipynb

@@ -28,7 +28,7 @@
                 "It has a unique identifier of the type {py:class}`~autogen_core.AgentId`,\n",
                 "a metadata dictionary of the type {py:class}`~autogen_core.AgentMetadata`.\n",
                 "\n",
-                "In most cases, you can subclass your agents from higher level class {py:class}`~autogen_core.RoutedAgent` which enables you to route messages to corresponding message handler specified with {py:meth}`~autogen_core.message_handler` decorator and proper type hint for the `message` variable.\n",
+                "In most cases, you can subclass your agents from a higher level class {py:class}`~autogen_core.RoutedAgent`, which enables you to route messages to corresponding message handler specified with the {py:meth}`~autogen_core.message_handler` decorator and proper type hints for the `message` variable.\n",
                 "An agent runtime is the execution environment for agents in AutoGen.\n",
                 "\n",
                 "Similar to the runtime environment of a programming language,\n",
@@ -282,7 +282,7 @@
                 "For batch scenarios such as running benchmarks for evaluating agents,\n",
                 "you may want to wait for the background task to stop automatically when\n",
                 "there are no unprocessed messages and no agent is handling messages --\n",
-                "the batch may considered complete.\n",
+                "the batch may be considered complete.\n",
                 "You can achieve this by using the {py:meth}`~autogen_core.SingleThreadedAgentRuntime.stop_when_idle` method:"
             ]
         },

python/docs/src/user-guide/core-user-guide/quickstart.ipynb

@@ -82,7 +82,7 @@
                 "a local embedded agent runtime implementation.\n",
                 "\n",
                 "```{note}\n",
-                "If you are using VSCode or other Editor remember to import asyncio and wrap the code with async def main() -> None: and run the code with asyncio.run(main()) function.\n",
+                "If you are using VSCode or another editor, remember to import asyncio and wrap the code with async def main() -> None: and run the code with asyncio.run(main()) function.\n",
                 "```"
             ]
         },