Document context summarization defaults, limitations, and aggregator params

api-reference/server/utilities/context-summarization.mdx

@@ -5,10 +5,42 @@ description: "Reference for LLMAutoContextSummarizationConfig, LLMContextSummary
 
 ## Overview
 
-Context summarization automatically compresses older conversation history when token or message limits are reached. It is configured via `LLMAutoContextSummarizationConfig` (auto-trigger thresholds) and `LLMContextSummaryConfig` (summary generation params), and managed by `LLMContextSummarizer`.
+Context summarization automatically compresses older conversation history when token or message limits are reached. It is enabled on `LLMAssistantAggregatorParams`, configured via `LLMAutoContextSummarizationConfig` (auto-trigger thresholds) and `LLMContextSummaryConfig` (summary generation params), and managed by `LLMContextSummarizer`.
 
 For a walkthrough of how to enable and customize context summarization, see the [Context Summarization guide](/pipecat/fundamentals/context-summarization).
 
+## LLMAssistantAggregatorParams
+
+```python
+from pipecat.processors.aggregators.llm_response_universal import LLMAssistantAggregatorParams
+```
+
+The summarization-related fields on `LLMAssistantAggregatorParams`.
+
+<ParamField path="enable_auto_context_summarization" type="bool" default="False">
+  Enables automatic context summarization. When `False` (the default), the
+  summarizer is still created internally so that on-demand summarization via
+  `LLMSummarizeContextFrame` works, but automatic trigger checks are skipped.
+  Set to `True` to enable automatic summarization when either
+  `max_context_tokens` or `max_unsummarized_messages` is reached.
+</ParamField>
+
+<ParamField
+  path="auto_context_summarization_config"
+  type="Optional[LLMAutoContextSummarizationConfig]"
+  default="None"
+>
+  Configuration for automatic summarization thresholds and summary generation.
+  When `None`, default `LLMAutoContextSummarizationConfig` values are used.
+</ParamField>
+
+<Note>
+  The older field names `enable_context_summarization` and
+  `context_summarization_config` are deprecated but still accepted. Passing
+  them emits a `DeprecationWarning` and the values are mapped to the new
+  fields. See the deprecation section at the bottom of this page.
+</Note>
+
 ## LLMAutoContextSummarizationConfig
 
 ```python

pipecat/fundamentals/context-summarization.mdx

@@ -49,7 +49,7 @@ user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
 )
 ```
 
-With the default configuration, summarization triggers at 8000 estimated tokens or after 20 new messages, whichever comes first.
+Automatic summarization is **disabled by default** (`enable_auto_context_summarization=False`). When enabled with the default configuration, summarization triggers at 8000 estimated tokens or after 20 new messages, whichever comes first.
 
 ## Customizing Behavior
 
@@ -88,6 +88,28 @@ Context summarization intelligently preserves:
 - **Function call sequences**: Incomplete function call/result pairs are not split during summarization
 - **Developer messages are NOT preserved**: Developer messages (`"role": "developer"`) are included in the summarization range like any other message and may be compressed or dropped. If instructions need to survive summarization, use [`system_instruction`](/pipecat/learn/context-management#using-system_instruction-recommended-for-personality) instead.
 
+## Limitations
+
+<Warning>
+  Context summarization always generates a summary. Pipecat does not provide
+  a truncation-only mode that drops old messages without summarizing them. If
+  you want to bound context size, the available knob is to tune
+  `max_context_tokens`, `max_unsummarized_messages`, `target_context_tokens`,
+  and `min_messages_after_summary`. Setting both `max_context_tokens` and
+  `max_unsummarized_messages` to `None` is not allowed, so summarization
+  cannot be reduced to pure truncation.
+</Warning>
+
+<Warning>
+  Only the message at `messages[0]` is preserved as the initial system
+  message. Preserving additional system messages (for example, the first two)
+  is not configurable. Mid-conversation system messages are treated as
+  regular messages and are included in the summarization range. If you need
+  persistent instructions that survive summarization, use
+  [`system_instruction`](/pipecat/learn/context-management#using-system_instruction-recommended-for-personality)
+  in LLM Settings instead of additional system-role messages.
+</Warning>
+
 ## Custom Summarization Prompts
 
 You can override the default summarization prompt to control how the LLM generates summaries:

pipecat/learn/context-management.mdx

@@ -259,13 +259,13 @@ context = context_aggregator.user().context
 
 In long-running conversations, context grows with every exchange, increasing token usage and potentially hitting context window limits. Pipecat includes built-in context summarization that automatically compresses older conversation history while preserving recent messages.
 
-Enable it by setting `enable_context_summarization=True` when creating your context aggregators:
+Enable it by setting `enable_auto_context_summarization=True` when creating your context aggregators (default: `False`):
 
 ```python
 user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
     context,
     assistant_params=LLMAssistantAggregatorParams(
-        enable_context_summarization=True,
+        enable_auto_context_summarization=True,
     ),
 )
 ```