Fix OpenAIFunctionsAgent function call message content retrieving (la…

…ngchain-ai#10488)

`langchain.agents.openai_functions[_multi]_agent._parse_ai_message()`
incorrectly extracts AI message content, thus LLM response ("thoughts")
is lost and can't be logged or processed by callbacks.

This PR fixes function call message content retrieving.

libs/langchain/langchain/agents/openai_functions_agent/base.py

@@ -127,7 +127,7 @@ def _parse_ai_message(message: BaseMessage) -> Union[AgentAction, AgentFinish]:
         else:
             tool_input = _tool_input
 
-        content_msg = "responded: {content}\n" if message.content else "\n"
+        content_msg = f"responded: {message.content}\n" if message.content else "\n"
 
         return _FunctionsAgentAction(
             tool=function_name,

libs/langchain/langchain/agents/openai_functions_multi_agent/base.py

@@ -129,7 +129,7 @@ def _parse_ai_message(message: BaseMessage) -> Union[List[AgentAction], AgentFin
             else:
                 tool_input = _tool_input
 
-            content_msg = "responded: {content}\n" if message.content else "\n"
+            content_msg = f"responded: {message.content}\n" if message.content else "\n"
             log = f"\nInvoking: `{function_name}` with `{tool_input}`\n{content_msg}\n"
             _tool = _FunctionsAgentAction(
                 tool=function_name,

libs/langchain/tests/unit_tests/agents/test_openai_functions.py

@@ -0,0 +1,76 @@
+import pytest
+
+from langchain.agents.openai_functions_agent.base import (
+    _FunctionsAgentAction,
+    _parse_ai_message,
+)
+from langchain.schema import AgentFinish, OutputParserException
+from langchain.schema.messages import AIMessage, SystemMessage
+
+
+# Test: _parse_ai_message() function.
+class TestParseAIMessage:
+    # Test: Pass Non-AIMessage.
+    def test_not_an_ai(self) -> None:
+        err = f"Expected an AI message got {str(SystemMessage)}"
+        with pytest.raises(TypeError, match=err):
+            _parse_ai_message(SystemMessage(content="x"))
+
+    # Test: Model response (not a function call).
+    def test_model_response(self) -> None:
+        msg = AIMessage(content="Model response.")
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, AgentFinish)
+        assert result.return_values == {"output": "Model response."}
+        assert result.log == "Model response."
+
+    # Test: Model response with a function call.
+    def test_func_call(self) -> None:
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={
+                "function_call": {"name": "foo", "arguments": '{"param": 42}'}
+            },
+        )
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, _FunctionsAgentAction)
+        assert result.tool == "foo"
+        assert result.tool_input == {"param": 42}
+        assert result.log == (
+            "\nInvoking: `foo` with `{'param': 42}`\nresponded: LLM thoughts.\n\n"
+        )
+        assert result.message_log == [msg]
+
+    # Test: Model response with a function call (old style tools).
+    def test_func_call_oldstyle(self) -> None:
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={
+                "function_call": {"name": "foo", "arguments": '{"__arg1": "42"}'}
+            },
+        )
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, _FunctionsAgentAction)
+        assert result.tool == "foo"
+        assert result.tool_input == "42"
+        assert result.log == (
+            "\nInvoking: `foo` with `42`\nresponded: LLM thoughts.\n\n"
+        )
+        assert result.message_log == [msg]
+
+    # Test: Invalid function call args.
+    def test_func_call_invalid(self) -> None:
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={"function_call": {"name": "foo", "arguments": "{42]"}},
+        )
+
+        err = (
+            "Could not parse tool input: {'name': 'foo', 'arguments': '{42]'} "
+            "because the `arguments` is not valid JSON."
+        )
+        with pytest.raises(OutputParserException, match=err):
+            _parse_ai_message(msg)

libs/langchain/tests/unit_tests/agents/test_openai_functions_multi.py

@@ -0,0 +1,90 @@
+import json
+
+import pytest
+
+from langchain.agents.openai_functions_multi_agent.base import (
+    _FunctionsAgentAction,
+    _parse_ai_message,
+)
+from langchain.schema import AgentFinish, OutputParserException
+from langchain.schema.messages import AIMessage, SystemMessage
+
+
+# Test: _parse_ai_message() function.
+class TestParseAIMessage:
+    # Test: Pass Non-AIMessage.
+    def test_not_an_ai(self) -> None:
+        err = f"Expected an AI message got {str(SystemMessage)}"
+        with pytest.raises(TypeError, match=err):
+            _parse_ai_message(SystemMessage(content="x"))
+
+    # Test: Model response (not a function call).
+    def test_model_response(self) -> None:
+        msg = AIMessage(content="Model response.")
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, AgentFinish)
+        assert result.return_values == {"output": "Model response."}
+        assert result.log == "Model response."
+
+    # Test: Model response with a function call.
+    def test_func_call(self) -> None:
+        act = json.dumps([{"action_name": "foo", "action": {"param": 42}}])
+
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={
+                "function_call": {"name": "foo", "arguments": f'{{"actions": {act}}}'}
+            },
+        )
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, list)
+        assert len(result) == 1
+
+        action = result[0]
+        assert isinstance(action, _FunctionsAgentAction)
+        assert action.tool == "foo"
+        assert action.tool_input == {"param": 42}
+        assert action.log == (
+            "\nInvoking: `foo` with `{'param': 42}`\nresponded: LLM thoughts.\n\n"
+        )
+        assert action.message_log == [msg]
+
+    # Test: Model response with a function call (old style tools).
+    def test_func_call_oldstyle(self) -> None:
+        act = json.dumps([{"action_name": "foo", "action": {"__arg1": "42"}}])
+
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={
+                "function_call": {"name": "foo", "arguments": f'{{"actions": {act}}}'}
+            },
+        )
+        result = _parse_ai_message(msg)
+
+        assert isinstance(result, list)
+        assert len(result) == 1
+
+        action = result[0]
+        assert isinstance(action, _FunctionsAgentAction)
+        assert action.tool == "foo"
+        assert action.tool_input == "42"
+        assert action.log == (
+            "\nInvoking: `foo` with `42`\nresponded: LLM thoughts.\n\n"
+        )
+        assert action.message_log == [msg]
+
+    # Test: Invalid function call args.
+    def test_func_call_invalid(self) -> None:
+        msg = AIMessage(
+            content="LLM thoughts.",
+            additional_kwargs={"function_call": {"name": "foo", "arguments": "{42]"}},
+        )
+
+        err = (
+            "Could not parse tool input: {'name': 'foo', 'arguments': '{42]'} "
+            "because the `arguments` is not valid JSON."
+        )
+        with pytest.raises(OutputParserException, match=err):
+            _parse_ai_message(msg)