example implementation for SummarizationMiddleware

libs/langchain_v1/langchain/agents/middleware/summarization.py

@@ -3,6 +3,7 @@
 import uuid
 from collections.abc import Callable, Iterable
 from typing import Any, cast
+import warnings
 
 from langchain_core.messages import (
     AIMessage,
@@ -93,12 +94,31 @@ class SummarizationMiddleware(AgentMiddleware):
             model = init_chat_model(model)
 
         self.model = model
-        self.max_tokens_before_summary = max_tokens_before_summary
         self.messages_to_keep = messages_to_keep
         self.token_counter = token_counter
         self.summary_prompt = summary_prompt
         self.summary_prefix = summary_prefix
 
+        if max_tokens_before_summary is None:
+            # Need to resolve https://github.com/langchain-ai/langchain/issues/33701
+            # to clarify desired behavior in None case
+            self.max_tokens_before_summary = None
+            try:
+                model_capabilities = model.capabilities
+                if model_capabilities["max_input_tokens"]:
+                    self.max_tokens_before_summary = (
+                        # 75% of max input tokens as threshold
+                        # Could also parametrize this
+                        int(model_capabilities["max_input_tokens"] * 0.75)
+                    )
+            except ImportError:
+                warning_msg = (
+                    "Defaulting to None max_tokens_before_summary. pip install "
+                    "langchain-llm-capabilities to enable setting based on model "
+                    "context window size."
+                )
+                warnings.warn(warning_msg, ImportWarning)
+
     def before_model(self, state: AgentState, runtime: Runtime) -> dict[str, Any] | None:  # noqa: ARG002
         """Process messages before model invocation, potentially triggering summarization."""
         messages = state["messages"]