Add _type for all parsers (#4189)

Used for serialization. Also add test that recurses through
our subclasses to check they have them implemented

Would fix https://github.com/hwchase17/langchain/issues/3217
Blocking: https://github.com/mlflow/mlflow/pull/8297

---------

Signed-off-by: Sunish Sheth <sunishsheth2009@gmail.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>

langchain/agents/chat/output_parser.py

@@ -24,3 +24,7 @@ class ChatOutputParser(AgentOutputParser):
 
         except Exception:
             raise OutputParserException(f"Could not parse LLM output: {text}")
+
+    @property
+    def _type(self) -> str:
+        return "chat"

langchain/agents/conversational/output_parser.py

@@ -24,3 +24,7 @@ class ConvoOutputParser(AgentOutputParser):
         action = match.group(1)
         action_input = match.group(2)
         return AgentAction(action.strip(), action_input.strip(" ").strip('"'), text)
+
+    @property
+    def _type(self) -> str:
+        return "conversational"

langchain/agents/conversational_chat/output_parser.py

@@ -31,3 +31,7 @@ class ConvoOutputParser(AgentOutputParser):
             return AgentFinish({"output": action_input}, text)
         else:
             return AgentAction(action, action_input, text)
+
+    @property
+    def _type(self) -> str:
+        return "conversational_chat"

langchain/agents/mrkl/output_parser.py

@@ -27,3 +27,7 @@ class MRKLOutputParser(AgentOutputParser):
         action = match.group(1).strip()
         action_input = match.group(2)
         return AgentAction(action, action_input.strip(" ").strip('"'), text)
+
+    @property
+    def _type(self) -> str:
+        return "mrkl"

langchain/agents/react/output_parser.py

@@ -24,3 +24,7 @@ class ReActOutputParser(AgentOutputParser):
             return AgentFinish({"output": action_input}, text)
         else:
             return AgentAction(action, action_input, text)
+
+    @property
+    def _type(self) -> str:
+        return "react"

langchain/agents/self_ask_with_search/output_parser.py

@@ -20,3 +20,7 @@ class SelfAskOutputParser(AgentOutputParser):
         if " " == after_colon[0]:
             after_colon = after_colon[1:]
         return AgentAction("Intermediate Answer", after_colon, text)
+
+    @property
+    def _type(self) -> str:
+        return "self_ask"

langchain/agents/structured_chat/output_parser.py

@@ -40,6 +40,10 @@ class StructuredChatOutputParser(AgentOutputParser):
         except Exception as e:
             raise OutputParserException(f"Could not parse LLM output: {text}") from e
 
+    @property
+    def _type(self) -> str:
+        return "structured_chat"
+
 
 class StructuredChatOutputParserWithRetries(AgentOutputParser):
     base_parser: AgentOutputParser = Field(default_factory=StructuredChatOutputParser)
@@ -76,3 +80,7 @@ class StructuredChatOutputParserWithRetries(AgentOutputParser):
             return cls(base_parser=base_parser)
         else:
             return cls()
+
+    @property
+    def _type(self) -> str:
+        return "structured_chat_with_retries"

langchain/chains/api/openapi/requests_chain.py

@@ -31,6 +31,10 @@ class APIRequesterOutputParser(BaseOutputParser):
             return f"MESSAGE: {message_match.group(1).strip()}"
         return "ERROR making request"
 
+    @property
+    def _type(self) -> str:
+        return "api_requester"
+
 
 class APIRequesterChain(LLMChain):
     """Get the request parser."""

langchain/chains/api/openapi/response_chain.py

@@ -31,6 +31,10 @@ class APIResponderOutputParser(BaseOutputParser):
         else:
             raise ValueError(f"No response found in output: {llm_output}.")
 
+    @property
+    def _type(self) -> str:
+        return "api_responder"
+
 
 class APIResponderChain(LLMChain):
     """Get the response parser."""

langchain/chains/llm_bash/prompt.py

@@ -52,6 +52,10 @@ class BashOutputParser(BaseOutputParser):
 
         return code_blocks
 
+    @property
+    def _type(self) -> str:
+        return "bash"
+
 
 PROMPT = PromptTemplate(
     input_variables=["question"],

langchain/output_parsers/fix.py

@@ -45,4 +45,4 @@ class OutputFixingParser(BaseOutputParser[T]):
 
     @property
     def _type(self) -> str:
-        return self.parser._type
+        return "output_fixing"

langchain/output_parsers/retry.py

@@ -78,7 +78,7 @@ class RetryOutputParser(BaseOutputParser[T]):
 
     @property
     def _type(self) -> str:
-        return self.parser._type
+        return "retry"
 
 
 class RetryWithErrorOutputParser(BaseOutputParser[T]):
@@ -122,3 +122,7 @@ class RetryWithErrorOutputParser(BaseOutputParser[T]):
 
     def get_format_instructions(self) -> str:
         return self.parser.get_format_instructions()
+
+    @property
+    def _type(self) -> str:
+        return "retry_with_error"

langchain/schema.py

@@ -227,25 +227,25 @@ class BaseChatMessageHistory(ABC):
             class FileChatMessageHistory(BaseChatMessageHistory):
                 storage_path:  str
                 session_id: str
-               
+
                @property
                def messages(self):
                    with open(os.path.join(storage_path, session_id), 'r:utf-8') as f:
                        messages = json.loads(f.read())
-                    return messages_from_dict(messages)     
-                
+                    return messages_from_dict(messages)
+
                def add_user_message(self, message: str):
                    message_ = HumanMessage(content=message)
                    messages = self.messages.append(_message_to_dict(_message))
                    with open(os.path.join(storage_path, session_id), 'w') as f:
                        json.dump(f, messages)
-               
+
                def add_ai_message(self, message: str):
                    message_ = AIMessage(content=message)
                    messages = self.messages.append(_message_to_dict(_message))
                    with open(os.path.join(storage_path, session_id), 'w') as f:
                        json.dump(f, messages)
-                       
+
                def clear(self):
                    with open(os.path.join(storage_path, session_id), 'w') as f:
                        f.write("[]")
@@ -348,7 +348,10 @@ class BaseOutputParser(BaseModel, ABC, Generic[T]):
     @property
     def _type(self) -> str:
         """Return the type key."""
-        raise NotImplementedError
+        raise NotImplementedError(
+            f"_type property is not implemented in class {self.__class__.__name__}."
+            " This is required for serialization."
+        )
 
     def dict(self, **kwargs: Any) -> Dict:
         """Return dictionary representation of output parser."""

tests/unit_tests/output_parsers/test_base_output_parser.py

@@ -0,0 +1,47 @@
+"""Test the BaseOutputParser class and its sub-classes."""
+from abc import ABC
+from typing import List, Optional, Set, Type
+
+import pytest
+
+from langchain.schema import BaseOutputParser
+
+
+def non_abstract_subclasses(
+    cls: Type[ABC], to_skip: Optional[Set] = None
+) -> List[Type]:
+    """Recursively find all non-abstract subclasses of a class."""
+    _to_skip = to_skip or set()
+    subclasses = []
+    for subclass in cls.__subclasses__():
+        if not getattr(subclass, "__abstractmethods__", None):
+            if subclass.__name__ not in _to_skip:
+                subclasses.append(subclass)
+        subclasses.extend(non_abstract_subclasses(subclass, to_skip=_to_skip))
+    return subclasses
+
+
+_PARSERS_TO_SKIP = {"FakeOutputParser", "BaseOutputParser"}
+_NON_ABSTRACT_PARSERS = non_abstract_subclasses(
+    BaseOutputParser, to_skip=_PARSERS_TO_SKIP
+)
+
+
+@pytest.mark.parametrize("cls", _NON_ABSTRACT_PARSERS)
+def test_subclass_implements_type(cls: Type[BaseOutputParser]) -> None:
+    try:
+        cls._type
+    except NotImplementedError:
+        pytest.fail(f"_type property is not implemented in class {cls.__name__}")
+
+
+def test_all_subclasses_implement_unique_type() -> None:
+    types = []
+    for cls in _NON_ABSTRACT_PARSERS:
+        try:
+            types.append(cls._type)
+        except NotImplementedError:
+            # This is handled in the previous test
+            pass
+    dups = set([t for t in types if types.count(t) > 1])
+    assert not dups, f"Duplicate types: {dups}"