Update regex in output parser (#15082)

The regex used to match "Action" and "Action Input" in the output parser
has been updated. Previously, the regex did not correctly handle
multi-line inputs for "Action Input". The updated code uses the
're.DOTALL' flag to ensure multi-line inputs are correctly captured.

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---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

libs/langchain/langchain/agents/conversational/output_parser.py

@@ -22,8 +22,8 @@ class ConvoOutputParser(AgentOutputParser):
             return AgentFinish(
                 {"output": text.split(f"{self.ai_prefix}:")[-1].strip()}, text
             )
-        regex = r"Action: (.*?)[\n]*Action Input: (.*)"
-        match = re.search(regex, text)
+        regex = r"Action: (.*?)[\n]*Action Input: ([\s\S]*)"
+        match = re.search(regex, text, re.DOTALL)
         if not match:
             raise OutputParserException(f"Could not parse LLM output: `{text}`")
         action = match.group(1)

libs/langchain/tests/unit_tests/agents/output_parsers/test_convo_output_parser.py

@@ -0,0 +1,42 @@
+from langchain_core.agents import AgentAction
+
+from langchain.agents.conversational.output_parser import ConvoOutputParser
+
+
+def test_normal_output_parsing() -> None:
+    _test_convo_output(
+        """
+Action: my_action
+Action Input: my action input
+""",
+        "my_action",
+        "my action input",
+    )
+
+
+def test_multiline_output_parsing() -> None:
+    _test_convo_output(
+        """
+Thought: Do I need to use a tool? Yes
+Action: evaluate_code
+Action Input: Evaluate Code with the following Python content:
+```python
+print("Hello fifty shades of gray mans!"[::-1])
+```
+""",
+        "evaluate_code",
+        """
+Evaluate Code with the following Python content:
+```python
+print("Hello fifty shades of gray mans!"[::-1])
+```""".lstrip(),
+    )
+
+
+def _test_convo_output(
+    input: str, expected_tool: str, expected_tool_input: str
+) -> None:
+    result = ConvoOutputParser().parse(input.strip())
+    assert isinstance(result, AgentAction)
+    assert result.tool == expected_tool
+    assert result.tool_input == expected_tool_input