Add LLMRunFrame to trigger an LLM response, replacing context_aggregator.user().get_context_frame()

CHANGELOG.md

@@ -9,6 +9,47 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added a new `LLMRunFrame` to trigger an LLM response:
+
+  ```python
+  await task.queue_frames([LLMRunFrame()])
+  ```
+
+  This replaces `OpenAILLMContextFrame`, which you’d previously typically use
+  like this:
+
+  ```python
+  await task.queue_frames([context_aggregator.user().get_context_frame()])
+  ```
+
+  Use this way of kicking off your conversation when you’ve already initialized
+  your context and are simply instructing the bot when to go:
+
+  ```python
+  context = OpenAILLMContext(messages, tools)
+  context_aggregator = llm.create_context_aggregator(context)
+
+  # ...
+
+  @transport.event_handler("on_client_connected")
+  async def on_client_connected(transport, client):
+      # Kick off the conversation.
+      await task.queue_frames([LLMRunFrame()])
+  ```
+
+  Note that if you want to add new messages when kicking off the conversation,
+  you could use `LLMMessagesAppendFrame` with `run_llm=True` instead:
+
+  ```python
+  @transport.event_handler("on_client_connected")
+  async def on_client_connected(transport, client):
+      # Kick off the conversation.
+      await task.queue_frames([LLMMessagesAppendFrame(new_messages, run_llm=True)])
+  ```
+
+  In the rare case you don’t have a context aggregator in your pipeline, then
+  you may continue using a context frame.
+
 - Added support for switching between audio+text to text-only modes within the
   same pipeline. This is done by pushing
   `LLMConfigureOutputFrame(skip_tts=True)` to enter text-only mode, and