Document context summarization defaults, limitations, and aggregator params

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

@@ -5,10 +5,39 @@ 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="LLMAutoContextSummarizationConfig | None"
+  default="None"
+>
+  Configuration for automatic summarization thresholds and summary generation.
+  When `None`, default `LLMAutoContextSummarizationConfig` values are used.
+</ParamField>
+
 ## LLMAutoContextSummarizationConfig
 
 ```python
@@ -80,10 +109,10 @@ Controls how summaries are generated. Used as `summary_config` inside `LLMAutoCo
   the pipeline LLM handles summarization.
 </ParamField>
 
-<ParamField path="summarization_timeout" type="Optional[float]" default="120.0">
+<ParamField path="summarization_timeout" type="float" default="120.0">
   Maximum time in seconds to wait for the LLM to generate a summary. If
   exceeded, summarization is aborted and future summarization attempts are
-  unblocked. Set to `None` to disable the timeout.
+  unblocked.
 </ParamField>
 
 ## LLMSummarizeContextFrame
@@ -94,11 +123,7 @@ from pipecat.frames.frames import LLMSummarizeContextFrame
 
 Push this frame into the pipeline to trigger on-demand context summarization without waiting for automatic thresholds.
 
-<ParamField
-  path="config"
-  type="Optional[LLMContextSummaryConfig]"
-  default="None"
->
+<ParamField path="config" type="LLMContextSummaryConfig | None" default="None">
   Per-request override for summary generation settings (prompt, token budget,
   messages to keep). When `None`, the summarizer's default
   `LLMContextSummaryConfig` is used.

pipecat/fundamentals/context-summarization.mdx

@@ -15,7 +15,7 @@ Context summarization automatically triggers when **either** condition is met:
 - **Token limit reached**: Context size exceeds `max_context_tokens` (estimated using ~4 characters per token)
 - **Message count reached**: Number of new messages exceeds `max_unsummarized_messages`
 
-You can disable either threshold by setting it to `None`, as long as at least one remains active.
+You can disable either threshold by setting it to `None`, but at least one must remain active. Summarization always generates a summary and cannot be reduced to pure truncation.
 
 When triggered, the system:
 
@@ -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
 

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,
     ),
 )
 ```