BUGFIX: handle tool message type when converting to string (#13626)

**Description:** Currently, if we pass in a ToolMessage back to the
chain, it crashes with error

`Got unsupported message type: `

This fixes it. 

Tested locally

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>

libs/core/langchain_core/messages/__init__.py

@@ -54,6 +54,8 @@ def get_buffer_string(
             role = "System"
         elif isinstance(m, FunctionMessage):
             role = "Function"
+        elif isinstance(m, ToolMessage):
+            role = "Tool"
         elif isinstance(m, ChatMessage):
             role = m.role
         else:

libs/core/tests/unit_tests/test_messages.py

@@ -1,10 +1,21 @@
+import unittest
+
 import pytest
 
 from langchain_core.messages import (
+    AIMessage,
     AIMessageChunk,
+    ChatMessage,
     ChatMessageChunk,
+    FunctionMessage,
     FunctionMessageChunk,
+    HumanMessage,
     HumanMessageChunk,
+    SystemMessage,
+    ToolMessage,
+    get_buffer_string,
+    messages_from_dict,
+    messages_to_dict,
 )
 
 
@@ -100,3 +111,76 @@ def test_ani_message_chunks() -> None:
         AIMessageChunk(example=True, content="I am") + AIMessageChunk(
             example=False, content=" indeed."
         )
+
+
+class TestGetBufferString(unittest.TestCase):
+    def setUp(self) -> None:
+        self.human_msg = HumanMessage(content="human")
+        self.ai_msg = AIMessage(content="ai")
+        self.sys_msg = SystemMessage(content="system")
+        self.func_msg = FunctionMessage(name="func", content="function")
+        self.tool_msg = ToolMessage(tool_call_id="tool_id", content="tool")
+        self.chat_msg = ChatMessage(role="Chat", content="chat")
+
+    def test_empty_input(self) -> None:
+        self.assertEqual(get_buffer_string([]), "")
+
+    def test_valid_single_message(self) -> None:
+        expected_output = f"Human: {self.human_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.human_msg]),
+            expected_output,
+        )
+
+    def test_custom_human_prefix(self) -> None:
+        prefix = "H"
+        expected_output = f"{prefix}: {self.human_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.human_msg], human_prefix="H"),
+            expected_output,
+        )
+
+    def test_custom_ai_prefix(self) -> None:
+        prefix = "A"
+        expected_output = f"{prefix}: {self.ai_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.ai_msg], ai_prefix="A"),
+            expected_output,
+        )
+
+    def test_multiple_msg(self) -> None:
+        msgs = [
+            self.human_msg,
+            self.ai_msg,
+            self.sys_msg,
+            self.func_msg,
+            self.tool_msg,
+            self.chat_msg,
+        ]
+        expected_output = "\n".join(
+            [
+                "Human: human",
+                "AI: ai",
+                "System: system",
+                "Function: function",
+                "Tool: tool",
+                "Chat: chat",
+            ]
+        )
+        self.assertEqual(
+            get_buffer_string(msgs),
+            expected_output,
+        )
+
+
+def test_multiple_msg() -> None:
+    human_msg = HumanMessage(content="human", additional_kwargs={"key": "value"})
+    ai_msg = AIMessage(content="ai")
+    sys_msg = SystemMessage(content="sys")
+
+    msgs = [
+        human_msg,
+        ai_msg,
+        sys_msg,
+    ]
+    assert messages_from_dict(messages_to_dict(msgs)) == msgs

libs/langchain/tests/unit_tests/test_schema.py

@@ -1,5 +1,4 @@
 """Test formatting functionality."""
-import unittest
 from typing import Union
 
 import pytest
@@ -16,75 +15,12 @@ from langchain_core.messages import (
     HumanMessageChunk,
     SystemMessage,
     SystemMessageChunk,
-    get_buffer_string,
-    messages_from_dict,
-    messages_to_dict,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, Generation
 from langchain_core.prompt_values import ChatPromptValueConcrete, StringPromptValue
 from langchain_core.pydantic_v1 import BaseModel, ValidationError
 
 
-class TestGetBufferString(unittest.TestCase):
-    def setUp(self) -> None:
-        self.human_msg = HumanMessage(content="human")
-        self.ai_msg = AIMessage(content="ai")
-        self.sys_msg = SystemMessage(content="sys")
-
-    def test_empty_input(self) -> None:
-        self.assertEqual(get_buffer_string([]), "")
-
-    def test_valid_single_message(self) -> None:
-        expected_output = f"Human: {self.human_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.human_msg]),
-            expected_output,
-        )
-
-    def test_custom_human_prefix(self) -> None:
-        prefix = "H"
-        expected_output = f"{prefix}: {self.human_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.human_msg], human_prefix="H"),
-            expected_output,
-        )
-
-    def test_custom_ai_prefix(self) -> None:
-        prefix = "A"
-        expected_output = f"{prefix}: {self.ai_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.ai_msg], ai_prefix="A"),
-            expected_output,
-        )
-
-    def test_multiple_msg(self) -> None:
-        msgs = [self.human_msg, self.ai_msg, self.sys_msg]
-        expected_output = "\n".join(
-            [
-                f"Human: {self.human_msg.content}",
-                f"AI: {self.ai_msg.content}",
-                f"System: {self.sys_msg.content}",
-            ]
-        )
-        self.assertEqual(
-            get_buffer_string(msgs),
-            expected_output,
-        )
-
-
-def test_multiple_msg() -> None:
-    human_msg = HumanMessage(content="human", additional_kwargs={"key": "value"})
-    ai_msg = AIMessage(content="ai")
-    sys_msg = SystemMessage(content="sys")
-
-    msgs = [
-        human_msg,
-        ai_msg,
-        sys_msg,
-    ]
-    assert messages_from_dict(messages_to_dict(msgs)) == msgs
-
-
 def test_serialization_of_wellknown_objects() -> None:
     """Test that pydantic is able to serialize and deserialize well known objects."""