cr

langchain/agents/agent.py

@@ -14,15 +14,6 @@ from pydantic import BaseModel, root_validator
 
 from langchain.agents.agent_types import AgentType
 from langchain.agents.tools import InvalidTool
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    AsyncCallbackManagerForToolRun,
-    CallbackManagerForChainRun,
-    CallbackManagerForToolRun,
-    Callbacks,
-)
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.input import get_color_mapping
 from langchain.prompts.few_shot import FewShotPromptTemplate
@@ -34,6 +25,15 @@ from langchain.schema import (
     BasePromptTemplate,
     OutputParserException,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    AsyncCallbackManagerForToolRun,
+    CallbackManagerForChainRun,
+    CallbackManagerForToolRun,
+    Callbacks,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import BaseMessage
 from langchain.tools.base import BaseTool

langchain/agents/agent_toolkits/json/base.py

@@ -6,8 +6,8 @@ from langchain.agents.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
 from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/agents/agent_toolkits/openapi/base.py

@@ -9,8 +9,8 @@ from langchain.agents.agent_toolkits.openapi.prompt import (
 from langchain.agents.agent_toolkits.openapi.toolkit import OpenAPIToolkit
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/agents/agent_toolkits/openapi/planner.py

@@ -28,13 +28,13 @@ from langchain.agents.agent_toolkits.openapi.planner_prompt import (
 from langchain.agents.agent_toolkits.openapi.spec import ReducedOpenAPISpec
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.tools import Tool
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.llms.openai import OpenAI
 from langchain.memory import ReadOnlySharedMemory
 from langchain.prompts import PromptTemplate
 from langchain.requests import RequestsWrapper
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool
 from langchain.tools.requests.tool import BaseRequestsTool

langchain/agents/agent_toolkits/pandas/base.py

@@ -16,9 +16,9 @@ from langchain.agents.agent_toolkits.pandas.prompt import (
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
 from langchain.agents.types import AgentType
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import SystemMessage
 from langchain.tools.python.tool import PythonAstREPLTool

langchain/agents/agent_toolkits/powerbi/base.py

@@ -9,8 +9,8 @@ from langchain.agents.agent_toolkits.powerbi.prompt import (
 from langchain.agents.agent_toolkits.powerbi.toolkit import PowerBIToolkit
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.utilities.powerbi import PowerBIDataset
 

langchain/agents/agent_toolkits/powerbi/chat_base.py

@@ -9,10 +9,10 @@ from langchain.agents.agent_toolkits.powerbi.prompt import (
 )
 from langchain.agents.agent_toolkits.powerbi.toolkit import PowerBIToolkit
 from langchain.agents.conversational_chat.base import ConversationalChatAgent
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chat_models.base import BaseChatModel
 from langchain.memory import ConversationBufferMemory
 from langchain.memory.chat_memory import BaseChatMemory
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.utilities.powerbi import PowerBIDataset
 
 

langchain/agents/agent_toolkits/powerbi/toolkit.py

@@ -4,7 +4,6 @@ from typing import List, Optional, Union
 from pydantic import Field
 
 from langchain.agents.agent_toolkits.base import BaseToolkit
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.chat_models.base import BaseChatModel
 from langchain.prompts import PromptTemplate
@@ -13,6 +12,7 @@ from langchain.prompts.chat import (
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools import BaseTool
 from langchain.tools.powerbi.prompt import (

langchain/agents/agent_toolkits/python/base.py

@@ -7,8 +7,8 @@ from langchain.agents.agent_toolkits.python.prompt import PREFIX
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
 from langchain.agents.types import AgentType
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import SystemMessage
 from langchain.tools.python.tool import PythonREPLTool

langchain/agents/agent_toolkits/spark/base.py

@@ -4,9 +4,9 @@ from typing import Any, Dict, List, Optional
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.agent_toolkits.spark.prompt import PREFIX, SUFFIX
 from langchain.agents.mrkl.base import ZeroShotAgent
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.llms.base import BaseLLM
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.tools.python.tool import PythonAstREPLTool
 
 

langchain/agents/agent_toolkits/spark_sql/base.py

@@ -6,8 +6,8 @@ from langchain.agents.agent_toolkits.spark_sql.prompt import SQL_PREFIX, SQL_SUF
 from langchain.agents.agent_toolkits.spark_sql.toolkit import SparkSQLToolkit
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/agents/agent_toolkits/sql/base.py

@@ -12,13 +12,13 @@ from langchain.agents.agent_types import AgentType
 from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import AIMessage, SystemMessage
 

langchain/agents/agent_toolkits/vectorstore/base.py

@@ -8,8 +8,8 @@ from langchain.agents.agent_toolkits.vectorstore.toolkit import (
     VectorStoreToolkit,
 )
 from langchain.agents.mrkl.base import ZeroShotAgent
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/agents/chat/base.py

@@ -11,7 +11,6 @@ from langchain.agents.chat.prompt import (
     SYSTEM_MESSAGE_SUFFIX,
 )
 from langchain.agents.utils import validate_tools_single_input
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.prompts.chat import (
     ChatPromptTemplate,
@@ -19,6 +18,7 @@ from langchain.prompts.chat import (
     SystemMessagePromptTemplate,
 )
 from langchain.schema import AgentAction, BasePromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool
 

langchain/agents/conversational/base.py

@@ -10,9 +10,9 @@ from langchain.agents.agent_types import AgentType
 from langchain.agents.conversational.output_parser import ConvoOutputParser
 from langchain.agents.conversational.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
 from langchain.agents.utils import validate_tools_single_input
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool
 

langchain/agents/conversational_chat/base.py

@@ -13,7 +13,6 @@ from langchain.agents.conversational_chat.prompt import (
     TEMPLATE_TOOL_RESPONSE,
 )
 from langchain.agents.utils import validate_tools_single_input
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains import LLMChain
 from langchain.prompts.chat import (
     ChatPromptTemplate,
@@ -22,6 +21,7 @@ from langchain.prompts.chat import (
     SystemMessagePromptTemplate,
 )
 from langchain.schema import AgentAction, BaseOutputParser, BasePromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import AIMessage, BaseMessage, HumanMessage
 from langchain.tools.base import BaseTool

langchain/agents/initialize.py

@@ -4,7 +4,7 @@ from typing import Any, Optional, Sequence
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.agent_types import AgentType
 from langchain.agents.loading import AGENT_TO_CLASS, load_agent
-from langchain.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool
 

langchain/agents/load_tools.py

@@ -6,8 +6,8 @@ from mypy_extensions import Arg, KwArg
 
 from langchain.agents.tools import Tool
 from langchain.schema.language_model import BaseLanguageModel
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import Callbacks
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import Callbacks
 from langchain.chains.api import news_docs, open_meteo_docs, podcast_docs, tmdb_docs
 from langchain.chains.api.base import APIChain
 from langchain.chains.llm_math.base import LLMMathChain

langchain/agents/mrkl/base.py

@@ -11,9 +11,9 @@ from langchain.agents.mrkl.output_parser import MRKLOutputParser
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
 from langchain.agents.tools import Tool
 from langchain.agents.utils import validate_tools_single_input
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool
 

langchain/agents/openai_functions_agent/base.py

@@ -7,8 +7,6 @@ from typing import Any, List, Optional, Sequence, Tuple, Union
 from pydantic import root_validator
 
 from langchain.agents import BaseSingleActionAgent
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import Callbacks
 from langchain.chat_models.openai import ChatOpenAI
 from langchain.prompts.chat import (
     BaseMessagePromptTemplate,
@@ -22,6 +20,8 @@ from langchain.schema import (
     BasePromptTemplate,
     OutputParserException,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import Callbacks
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import (
     AIMessage,

langchain/agents/openai_functions_multi_agent/base.py

@@ -7,8 +7,6 @@ from typing import Any, List, Optional, Sequence, Tuple, Union
 from pydantic import root_validator
 
 from langchain.agents import BaseMultiActionAgent
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import Callbacks
 from langchain.chat_models.openai import ChatOpenAI
 from langchain.prompts.chat import (
     BaseMessagePromptTemplate,
@@ -22,6 +20,8 @@ from langchain.schema import (
     BasePromptTemplate,
     OutputParserException,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import Callbacks
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import (
     AIMessage,

langchain/agents/structured_chat/base.py

@@ -8,7 +8,6 @@ from langchain.agents.structured_chat.output_parser import (
     StructuredChatOutputParserWithRetries,
 )
 from langchain.agents.structured_chat.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
-from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
 from langchain.prompts.chat import (
     ChatPromptTemplate,
@@ -16,6 +15,7 @@ from langchain.prompts.chat import (
     SystemMessagePromptTemplate,
 )
 from langchain.schema import AgentAction, BasePromptTemplate
+from langchain.schema.callbacks.base import BaseCallbackManager
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools import BaseTool
 

langchain/agents/tools.py

@@ -1,7 +1,7 @@
 """Interface for tools."""
 from typing import Optional
 
-from langchain.callbacks.manager import (
+from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForToolRun,
     CallbackManagerForToolRun,
 )

langchain/callbacks/aim_callback.py

@@ -1,8 +1,8 @@
 from copy import deepcopy
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def import_aim() -> Any:

langchain/callbacks/argilla_callback.py

@@ -2,8 +2,8 @@ import os
 import warnings
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 class ArgillaCallbackHandler(BaseCallbackHandler):

langchain/callbacks/arize_callback.py

@@ -1,9 +1,9 @@
 from datetime import datetime
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import import_pandas
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 class ArizeCallbackHandler(BaseCallbackHandler):

langchain/callbacks/arthur_callback.py

@@ -10,8 +10,8 @@ from typing import TYPE_CHECKING, Any, DefaultDict, Dict, List, Optional, Union
 
 import numpy as np
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 if TYPE_CHECKING:
     import arthurai

langchain/callbacks/base.py

@@ -1,545 +1,7 @@
-"""Base callback handler that can be used to handle callbacks in langchain."""
-from __future__ import annotations
+from langchain.schema.callbacks.base import (
+    AsyncCallbackHandler,
+    BaseCallbackHandler,
+    BaseCallbackManager,
+)
 
-from typing import Any, Dict, List, Optional, Sequence, Union
-from uuid import UUID
-
-from langchain.schema.agent import AgentAction, AgentFinish
-from langchain.schema.document import Document
-from langchain.schema.messages import BaseMessage
-from langchain.schema.output import LLMResult
-
-
-class RetrieverManagerMixin:
-    """Mixin for Retriever callbacks."""
-
-    def on_retriever_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when Retriever errors."""
-
-    def on_retriever_end(
-        self,
-        documents: Sequence[Document],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when Retriever ends running."""
-
-
-class LLMManagerMixin:
-    """Mixin for LLM callbacks."""
-
-    def on_llm_new_token(
-        self,
-        token: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run on new LLM token. Only available when streaming is enabled."""
-
-    def on_llm_end(
-        self,
-        response: LLMResult,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when LLM ends running."""
-
-    def on_llm_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when LLM errors."""
-
-
-class ChainManagerMixin:
-    """Mixin for chain callbacks."""
-
-    def on_chain_end(
-        self,
-        outputs: Dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when chain ends running."""
-
-    def on_chain_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when chain errors."""
-
-    def on_agent_action(
-        self,
-        action: AgentAction,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run on agent action."""
-
-    def on_agent_finish(
-        self,
-        finish: AgentFinish,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run on agent end."""
-
-
-class ToolManagerMixin:
-    """Mixin for tool callbacks."""
-
-    def on_tool_end(
-        self,
-        output: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when tool ends running."""
-
-    def on_tool_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when tool errors."""
-
-
-class CallbackManagerMixin:
-    """Mixin for callback manager."""
-
-    def on_llm_start(
-        self,
-        serialized: Dict[str, Any],
-        prompts: List[str],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when LLM starts running."""
-
-    def on_chat_model_start(
-        self,
-        serialized: Dict[str, Any],
-        messages: List[List[BaseMessage]],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when a chat model starts running."""
-        raise NotImplementedError(
-            f"{self.__class__.__name__} does not implement `on_chat_model_start`"
-        )
-
-    def on_retriever_start(
-        self,
-        serialized: Dict[str, Any],
-        query: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when Retriever starts running."""
-
-    def on_chain_start(
-        self,
-        serialized: Dict[str, Any],
-        inputs: Dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when chain starts running."""
-
-    def on_tool_start(
-        self,
-        serialized: Dict[str, Any],
-        input_str: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when tool starts running."""
-
-
-class RunManagerMixin:
-    """Mixin for run manager."""
-
-    def on_text(
-        self,
-        text: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run on arbitrary text."""
-
-
-class BaseCallbackHandler(
-    LLMManagerMixin,
-    ChainManagerMixin,
-    ToolManagerMixin,
-    RetrieverManagerMixin,
-    CallbackManagerMixin,
-    RunManagerMixin,
-):
-    """Base callback handler that can be used to handle callbacks from langchain."""
-
-    raise_error: bool = False
-
-    run_inline: bool = False
-
-    @property
-    def ignore_llm(self) -> bool:
-        """Whether to ignore LLM callbacks."""
-        return False
-
-    @property
-    def ignore_chain(self) -> bool:
-        """Whether to ignore chain callbacks."""
-        return False
-
-    @property
-    def ignore_agent(self) -> bool:
-        """Whether to ignore agent callbacks."""
-        return False
-
-    @property
-    def ignore_retriever(self) -> bool:
-        """Whether to ignore retriever callbacks."""
-        return False
-
-    @property
-    def ignore_chat_model(self) -> bool:
-        """Whether to ignore chat model callbacks."""
-        return False
-
-
-class AsyncCallbackHandler(BaseCallbackHandler):
-    """Async callback handler that can be used to handle callbacks from langchain."""
-
-    async def on_llm_start(
-        self,
-        serialized: Dict[str, Any],
-        prompts: List[str],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when LLM starts running."""
-
-    async def on_chat_model_start(
-        self,
-        serialized: Dict[str, Any],
-        messages: List[List[BaseMessage]],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> Any:
-        """Run when a chat model starts running."""
-        raise NotImplementedError(
-            f"{self.__class__.__name__} does not implement `on_chat_model_start`"
-        )
-
-    async def on_llm_new_token(
-        self,
-        token: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on new LLM token. Only available when streaming is enabled."""
-
-    async def on_llm_end(
-        self,
-        response: LLMResult,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when LLM ends running."""
-
-    async def on_llm_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when LLM errors."""
-
-    async def on_chain_start(
-        self,
-        serialized: Dict[str, Any],
-        inputs: Dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when chain starts running."""
-
-    async def on_chain_end(
-        self,
-        outputs: Dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when chain ends running."""
-
-    async def on_chain_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when chain errors."""
-
-    async def on_tool_start(
-        self,
-        serialized: Dict[str, Any],
-        input_str: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when tool starts running."""
-
-    async def on_tool_end(
-        self,
-        output: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when tool ends running."""
-
-    async def on_tool_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run when tool errors."""
-
-    async def on_text(
-        self,
-        text: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on arbitrary text."""
-
-    async def on_agent_action(
-        self,
-        action: AgentAction,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on agent action."""
-
-    async def on_agent_finish(
-        self,
-        finish: AgentFinish,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on agent end."""
-
-    async def on_retriever_start(
-        self,
-        serialized: Dict[str, Any],
-        query: str,
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on retriever start."""
-
-    async def on_retriever_end(
-        self,
-        documents: Sequence[Document],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on retriever end."""
-
-    async def on_retriever_error(
-        self,
-        error: Union[Exception, KeyboardInterrupt],
-        *,
-        run_id: UUID,
-        parent_run_id: Optional[UUID] = None,
-        tags: Optional[List[str]] = None,
-        **kwargs: Any,
-    ) -> None:
-        """Run on retriever error."""
-
-
-class BaseCallbackManager(CallbackManagerMixin):
-    """Base callback manager that can be used to handle callbacks from LangChain."""
-
-    def __init__(
-        self,
-        handlers: List[BaseCallbackHandler],
-        inheritable_handlers: Optional[List[BaseCallbackHandler]] = None,
-        parent_run_id: Optional[UUID] = None,
-        *,
-        tags: Optional[List[str]] = None,
-        inheritable_tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        inheritable_metadata: Optional[Dict[str, Any]] = None,
-    ) -> None:
-        """Initialize callback manager."""
-        self.handlers: List[BaseCallbackHandler] = handlers
-        self.inheritable_handlers: List[BaseCallbackHandler] = (
-            inheritable_handlers or []
-        )
-        self.parent_run_id: Optional[UUID] = parent_run_id
-        self.tags = tags or []
-        self.inheritable_tags = inheritable_tags or []
-        self.metadata = metadata or {}
-        self.inheritable_metadata = inheritable_metadata or {}
-
-    @property
-    def is_async(self) -> bool:
-        """Whether the callback manager is async."""
-        return False
-
-    def add_handler(self, handler: BaseCallbackHandler, inherit: bool = True) -> None:
-        """Add a handler to the callback manager."""
-        if handler not in self.handlers:
-            self.handlers.append(handler)
-        if inherit and handler not in self.inheritable_handlers:
-            self.inheritable_handlers.append(handler)
-
-    def remove_handler(self, handler: BaseCallbackHandler) -> None:
-        """Remove a handler from the callback manager."""
-        self.handlers.remove(handler)
-        self.inheritable_handlers.remove(handler)
-
-    def set_handlers(
-        self, handlers: List[BaseCallbackHandler], inherit: bool = True
-    ) -> None:
-        """Set handlers as the only handlers on the callback manager."""
-        self.handlers = []
-        self.inheritable_handlers = []
-        for handler in handlers:
-            self.add_handler(handler, inherit=inherit)
-
-    def set_handler(self, handler: BaseCallbackHandler, inherit: bool = True) -> None:
-        """Set handler as the only handler on the callback manager."""
-        self.set_handlers([handler], inherit=inherit)
-
-    def add_tags(self, tags: List[str], inherit: bool = True) -> None:
-        for tag in tags:
-            if tag in self.tags:
-                self.remove_tags([tag])
-        self.tags.extend(tags)
-        if inherit:
-            self.inheritable_tags.extend(tags)
-
-    def remove_tags(self, tags: List[str]) -> None:
-        for tag in tags:
-            self.tags.remove(tag)
-            self.inheritable_tags.remove(tag)
-
-    def add_metadata(self, metadata: Dict[str, Any], inherit: bool = True) -> None:
-        self.metadata.update(metadata)
-        if inherit:
-            self.inheritable_metadata.update(metadata)
-
-    def remove_metadata(self, keys: List[str]) -> None:
-        for key in keys:
-            self.metadata.pop(key)
-            self.inheritable_metadata.pop(key)
+__all__ = ["BaseCallbackManager", "AsyncCallbackHandler", "BaseCallbackHandler"]

langchain/callbacks/clearml_callback.py

@@ -3,7 +3,6 @@ from copy import deepcopy
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Sequence, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import (
     BaseMetadataCallbackHandler,
     flatten_dict,
@@ -14,6 +13,7 @@ from langchain.callbacks.utils import (
     load_json,
 )
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def import_clearml() -> Any:

langchain/callbacks/comet_ml_callback.py

@@ -4,7 +4,6 @@ from pathlib import Path
 from typing import Any, Callable, Dict, List, Optional, Sequence, Union
 
 import langchain
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import (
     BaseMetadataCallbackHandler,
     flatten_dict,
@@ -13,6 +12,7 @@ from langchain.callbacks.utils import (
     import_textstat,
 )
 from langchain.schema import AgentAction, AgentFinish, Generation, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 LANGCHAIN_MODEL_NAME = "langchain-model"
 

langchain/callbacks/context_callback.py

@@ -3,11 +3,11 @@ import os
 from typing import Any, Dict, List
 from uuid import UUID
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import (
     BaseMessage,
     LLMResult,
 )
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def import_context() -> Any:

langchain/callbacks/file.py

@@ -1,9 +1,9 @@
 """Callback Handler that writes to a file."""
 from typing import Any, Dict, Optional, TextIO, cast
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.input import print_text
 from langchain.schema import AgentAction, AgentFinish
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 class FileCallbackHandler(BaseCallbackHandler):

langchain/callbacks/flyte_callback.py

@@ -5,7 +5,6 @@ import logging
 from copy import deepcopy
 from typing import TYPE_CHECKING, Any, Dict, List, Tuple, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import (
     BaseMetadataCallbackHandler,
     flatten_dict,
@@ -14,6 +13,7 @@ from langchain.callbacks.utils import (
     import_textstat,
 )
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 if TYPE_CHECKING:
     import flytekit

langchain/callbacks/human.py

@@ -1,7 +1,7 @@
 from typing import Any, Callable, Dict, Optional
 from uuid import UUID
 
-from langchain.callbacks.base import BaseCallbackHandler
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def _default_approve(_input: str) -> bool:

langchain/callbacks/infino_callback.py

@@ -1,8 +1,8 @@
 import time
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def import_infino() -> Any:

langchain/callbacks/mlflow_callback.py

@@ -6,7 +6,6 @@ from copy import deepcopy
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import (
     BaseMetadataCallbackHandler,
     flatten_dict,
@@ -16,6 +15,7 @@ from langchain.callbacks.utils import (
     import_textstat,
 )
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 from langchain.utils import get_from_dict_or_env
 
 

langchain/callbacks/openai_info.py

@@ -1,8 +1,8 @@
 """Callback Handler that prints to std out."""
 from typing import Any, Dict, List
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 MODEL_COST_PER_1K_TOKENS = {
     # GPT-4 input

langchain/callbacks/promptlayer_callback.py

@@ -5,11 +5,11 @@ import datetime
 from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple
 from uuid import UUID
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import (
     ChatGeneration,
     LLMResult,
 )
+from langchain.schema.callbacks.base import BaseCallbackHandler
 from langchain.schema.messages import (
     AIMessage,
     BaseMessage,

langchain/callbacks/stdout.py

@@ -1,9 +1,9 @@
 """Callback Handler that prints to std out."""
 from typing import Any, Dict, List, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.input import print_text
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 class StdOutCallbackHandler(BaseCallbackHandler):

langchain/callbacks/streaming_aiter.py

@@ -3,8 +3,8 @@ from __future__ import annotations
 import asyncio
 from typing import Any, AsyncIterator, Dict, List, Literal, Union, cast
 
-from langchain.callbacks.base import AsyncCallbackHandler
 from langchain.schema import LLMResult
+from langchain.schema.callbacks.base import AsyncCallbackHandler
 
 # TODO If used by two LLM runs in parallel this won't work as expected
 

langchain/callbacks/streaming_stdout.py

@@ -2,8 +2,8 @@
 import sys
 from typing import Any, Dict, List, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 class StreamingStdOutCallbackHandler(BaseCallbackHandler):

langchain/callbacks/streamlit/__init__.py

@@ -2,13 +2,13 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, Optional
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.streamlit.streamlit_callback_handler import (
     LLMThoughtLabeler as LLMThoughtLabeler,
 )
 from langchain.callbacks.streamlit.streamlit_callback_handler import (
     StreamlitCallbackHandler as _InternalStreamlitCallbackHandler,
 )
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 if TYPE_CHECKING:
     from streamlit.delta_generator import DeltaGenerator

langchain/callbacks/streamlit/streamlit_callback_handler.py

@@ -5,9 +5,9 @@ from __future__ import annotations
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Optional, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.streamlit.mutable_expander import MutableExpander
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 if TYPE_CHECKING:
     from streamlit.delta_generator import DeltaGenerator

langchain/callbacks/tracers/base.py

@@ -7,9 +7,9 @@ from datetime import datetime
 from typing import Any, Dict, List, Optional, Sequence, Union, cast
 from uuid import UUID
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.tracers.schemas import Run, RunTypeEnum
 from langchain.load.dump import dumpd
+from langchain.schema.callbacks.base import BaseCallbackHandler
 from langchain.schema.document import Document
 from langchain.schema.output import ChatGeneration, LLMResult
 

langchain/callbacks/wandb_callback.py

@@ -4,7 +4,6 @@ from copy import deepcopy
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Sequence, Union
 
-from langchain.callbacks.base import BaseCallbackHandler
 from langchain.callbacks.utils import (
     BaseMetadataCallbackHandler,
     flatten_dict,
@@ -14,6 +13,7 @@ from langchain.callbacks.utils import (
     import_textstat,
 )
 from langchain.schema import AgentAction, AgentFinish, LLMResult
+from langchain.schema.callbacks.base import BaseCallbackHandler
 
 
 def import_wandb() -> Any:

langchain/callbacks/whylabs_callback.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import logging
 from typing import TYPE_CHECKING, Any, Optional
 
-from langchain.callbacks.base import BaseCallbackHandler
+from langchain.schema.callbacks.base import BaseCallbackHandler
 from langchain.utils import get_from_env
 
 if TYPE_CHECKING:

langchain/chains/api/base.py

@@ -5,15 +5,15 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains.api.prompt import API_RESPONSE_PROMPT, API_URL_PROMPT
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.requests import TextRequestsWrapper
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/api/openapi/chain.py

@@ -7,12 +7,12 @@ from typing import Any, Dict, List, NamedTuple, Optional, cast
 from pydantic import BaseModel, Field
 from requests import Response
 
-from langchain.callbacks.manager import CallbackManagerForChainRun, Callbacks
 from langchain.chains.api.openapi.requests_chain import APIRequesterChain
 from langchain.chains.api.openapi.response_chain import APIResponderChain
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.requests import Requests
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun, Callbacks
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.openapi.utils.api_models import APIOperation
 

langchain/chains/base.py

@@ -1,598 +1,6 @@
-"""Base interface that all chains should implement."""
-import inspect
-import json
-import logging
-import warnings
-from abc import ABC, abstractmethod
-from pathlib import Path
-from typing import Any, Dict, List, Optional, Union
+"""Purely for backwards compatibility.
 
-import yaml
-from pydantic import Field, root_validator, validator
+Chain used to be defined here before moving to schema."""
+from langchain.schema.chain import Chain
 
-import langchain
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import (
-    AsyncCallbackManager,
-    AsyncCallbackManagerForChainRun,
-    CallbackManager,
-    CallbackManagerForChainRun,
-    Callbacks,
-)
-from langchain.load.dump import dumpd
-from langchain.load.serializable import Serializable
-from langchain.schema import RUN_KEY, BaseMemory, RunInfo
-
-logger = logging.getLogger(__name__)
-
-
-def _get_verbosity() -> bool:
-    return langchain.verbose
-
-
-class Chain(Serializable, ABC):
-    """Abstract base class for creating structured sequences of calls to components.
-
-    Chains should be used to encode a sequence of calls to components like
-    models, document retrievers, other chains, etc., and provide a simple interface
-    to this sequence.
-
-    The Chain interface makes it easy to create apps that are:
-        - Stateful: add Memory to any Chain to give it state,
-        - Observable: pass Callbacks to a Chain to execute additional functionality,
-            like logging, outside the main sequence of component calls,
-        - Composable: the Chain API is flexible enough that it is easy to combine
-            Chains with other components, including other Chains.
-
-    The main methods exposed by chains are:
-        - `__call__`: Chains are callable. The `__call__` method is the primary way to
-            execute a Chain. This takes inputs as a dictionary and returns a
-            dictionary output.
-        - `run`: A convenience method that takes inputs as args/kwargs and returns the
-            output as a string. This method can only be used for a subset of chains and
-            cannot return as rich of an output as `__call__`.
-    """
-
-    memory: Optional[BaseMemory] = None
-    """Optional memory object. Defaults to None.
-    Memory is a class that gets called at the start 
-    and at the end of every chain. At the start, memory loads variables and passes
-    them along in the chain. At the end, it saves any returned variables.
-    There are many different types of memory - please see memory docs 
-    for the full catalog."""
-    callbacks: Callbacks = Field(default=None, exclude=True)
-    """Optional list of callback handlers (or callback manager). Defaults to None.
-    Callback handlers are called throughout the lifecycle of a call to a chain,
-    starting with on_chain_start, ending with on_chain_end or on_chain_error.
-    Each custom chain can optionally call additional callback methods, see Callback docs
-    for full details."""
-    callback_manager: Optional[BaseCallbackManager] = Field(default=None, exclude=True)
-    """Deprecated, use `callbacks` instead."""
-    verbose: bool = Field(default_factory=_get_verbosity)
-    """Whether or not run in verbose mode. In verbose mode, some intermediate logs
-    will be printed to the console. Defaults to `langchain.verbose` value."""
-    tags: Optional[List[str]] = None
-    """Optional list of tags associated with the chain. Defaults to None
-    These tags will be associated with each call to this chain,
-    and passed as arguments to the handlers defined in `callbacks`.
-    You can use these to eg identify a specific instance of a chain with its use case.
-    """
-    metadata: Optional[Dict[str, Any]] = None
-    """Optional metadata associated with the chain. Defaults to None
-    This metadata will be associated with each call to this chain,
-    and passed as arguments to the handlers defined in `callbacks`.
-    You can use these to eg identify a specific instance of a chain with its use case.
-    """
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
-
-    @property
-    def _chain_type(self) -> str:
-        raise NotImplementedError("Saving not supported for this chain type.")
-
-    @root_validator()
-    def raise_callback_manager_deprecation(cls, values: Dict) -> Dict:
-        """Raise deprecation warning if callback_manager is used."""
-        if values.get("callback_manager") is not None:
-            warnings.warn(
-                "callback_manager is deprecated. Please use callbacks instead.",
-                DeprecationWarning,
-            )
-            values["callbacks"] = values.pop("callback_manager", None)
-        return values
-
-    @validator("verbose", pre=True, always=True)
-    def set_verbose(cls, verbose: Optional[bool]) -> bool:
-        """Set the chain verbosity.
-
-        Defaults to the global setting if not specified by the user.
-        """
-        if verbose is None:
-            return _get_verbosity()
-        else:
-            return verbose
-
-    @property
-    @abstractmethod
-    def input_keys(self) -> List[str]:
-        """Return the keys expected to be in the chain input."""
-
-    @property
-    @abstractmethod
-    def output_keys(self) -> List[str]:
-        """Return the keys expected to be in the chain output."""
-
-    def _validate_inputs(self, inputs: Dict[str, Any]) -> None:
-        """Check that all inputs are present."""
-        missing_keys = set(self.input_keys).difference(inputs)
-        if missing_keys:
-            raise ValueError(f"Missing some input keys: {missing_keys}")
-
-    def _validate_outputs(self, outputs: Dict[str, Any]) -> None:
-        missing_keys = set(self.output_keys).difference(outputs)
-        if missing_keys:
-            raise ValueError(f"Missing some output keys: {missing_keys}")
-
-    @abstractmethod
-    def _call(
-        self,
-        inputs: Dict[str, Any],
-        run_manager: Optional[CallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        """Execute the chain.
-
-        This is a private method that is not user-facing. It is only called within
-            `Chain.__call__`, which is the user-facing wrapper method that handles
-            callbacks configuration and some input/output processing.
-
-        Args:
-            inputs: A dict of named inputs to the chain. Assumed to contain all inputs
-                specified in `Chain.input_keys`, including any inputs added by memory.
-            run_manager: The callbacks manager that contains the callback handlers for
-                this run of the chain.
-
-        Returns:
-            A dict of named outputs. Should contain all outputs specified in
-                `Chain.output_keys`.
-        """
-
-    async def _acall(
-        self,
-        inputs: Dict[str, Any],
-        run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
-    ) -> Dict[str, Any]:
-        """Asynchronously execute the chain.
-
-        This is a private method that is not user-facing. It is only called within
-            `Chain.acall`, which is the user-facing wrapper method that handles
-            callbacks configuration and some input/output processing.
-
-        Args:
-            inputs: A dict of named inputs to the chain. Assumed to contain all inputs
-                specified in `Chain.input_keys`, including any inputs added by memory.
-            run_manager: The callbacks manager that contains the callback handlers for
-                this run of the chain.
-
-        Returns:
-            A dict of named outputs. Should contain all outputs specified in
-                `Chain.output_keys`.
-        """
-        raise NotImplementedError("Async call not supported for this chain type.")
-
-    def __call__(
-        self,
-        inputs: Union[Dict[str, Any], Any],
-        return_only_outputs: bool = False,
-        callbacks: Callbacks = None,
-        *,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        include_run_info: bool = False,
-    ) -> Dict[str, Any]:
-        """Execute the chain.
-
-        Args:
-            inputs: Dictionary of inputs, or single input if chain expects
-                only one param. Should contain all inputs specified in
-                `Chain.input_keys` except for inputs that will be set by the chain's
-                memory.
-            return_only_outputs: Whether to return only outputs in the
-                response. If True, only new keys generated by this chain will be
-                returned. If False, both input keys and new keys generated by this
-                chain will be returned. Defaults to False.
-            callbacks: Callbacks to use for this chain run. These will be called in
-                addition to callbacks passed to the chain during construction, but only
-                these runtime callbacks will propagate to calls to other objects.
-            tags: List of string tags to pass to all callbacks. These will be passed in
-                addition to tags passed to the chain during construction, but only
-                these runtime tags will propagate to calls to other objects.
-            metadata: Optional metadata associated with the chain. Defaults to None
-            include_run_info: Whether to include run info in the response. Defaults
-                to False.
-
-        Returns:
-            A dict of named outputs. Should contain all outputs specified in
-                `Chain.output_keys`.
-        """
-        inputs = self.prep_inputs(inputs)
-        callback_manager = CallbackManager.configure(
-            callbacks,
-            self.callbacks,
-            self.verbose,
-            tags,
-            self.tags,
-            metadata,
-            self.metadata,
-        )
-        new_arg_supported = inspect.signature(self._call).parameters.get("run_manager")
-        run_manager = callback_manager.on_chain_start(
-            dumpd(self),
-            inputs,
-        )
-        try:
-            outputs = (
-                self._call(inputs, run_manager=run_manager)
-                if new_arg_supported
-                else self._call(inputs)
-            )
-        except (KeyboardInterrupt, Exception) as e:
-            run_manager.on_chain_error(e)
-            raise e
-        run_manager.on_chain_end(outputs)
-        final_outputs: Dict[str, Any] = self.prep_outputs(
-            inputs, outputs, return_only_outputs
-        )
-        if include_run_info:
-            final_outputs[RUN_KEY] = RunInfo(run_id=run_manager.run_id)
-        return final_outputs
-
-    async def acall(
-        self,
-        inputs: Union[Dict[str, Any], Any],
-        return_only_outputs: bool = False,
-        callbacks: Callbacks = None,
-        *,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        include_run_info: bool = False,
-    ) -> Dict[str, Any]:
-        """Asynchronously execute the chain.
-
-        Args:
-            inputs: Dictionary of inputs, or single input if chain expects
-                only one param. Should contain all inputs specified in
-                `Chain.input_keys` except for inputs that will be set by the chain's
-                memory.
-            return_only_outputs: Whether to return only outputs in the
-                response. If True, only new keys generated by this chain will be
-                returned. If False, both input keys and new keys generated by this
-                chain will be returned. Defaults to False.
-            callbacks: Callbacks to use for this chain run. These will be called in
-                addition to callbacks passed to the chain during construction, but only
-                these runtime callbacks will propagate to calls to other objects.
-            tags: List of string tags to pass to all callbacks. These will be passed in
-                addition to tags passed to the chain during construction, but only
-                these runtime tags will propagate to calls to other objects.
-            metadata: Optional metadata associated with the chain. Defaults to None
-            include_run_info: Whether to include run info in the response. Defaults
-                to False.
-
-        Returns:
-            A dict of named outputs. Should contain all outputs specified in
-                `Chain.output_keys`.
-        """
-        inputs = self.prep_inputs(inputs)
-        callback_manager = AsyncCallbackManager.configure(
-            callbacks,
-            self.callbacks,
-            self.verbose,
-            tags,
-            self.tags,
-            metadata,
-            self.metadata,
-        )
-        new_arg_supported = inspect.signature(self._acall).parameters.get("run_manager")
-        run_manager = await callback_manager.on_chain_start(
-            dumpd(self),
-            inputs,
-        )
-        try:
-            outputs = (
-                await self._acall(inputs, run_manager=run_manager)
-                if new_arg_supported
-                else await self._acall(inputs)
-            )
-        except (KeyboardInterrupt, Exception) as e:
-            await run_manager.on_chain_error(e)
-            raise e
-        await run_manager.on_chain_end(outputs)
-        final_outputs: Dict[str, Any] = self.prep_outputs(
-            inputs, outputs, return_only_outputs
-        )
-        if include_run_info:
-            final_outputs[RUN_KEY] = RunInfo(run_id=run_manager.run_id)
-        return final_outputs
-
-    def prep_outputs(
-        self,
-        inputs: Dict[str, str],
-        outputs: Dict[str, str],
-        return_only_outputs: bool = False,
-    ) -> Dict[str, str]:
-        """Validate and prepare chain outputs, and save info about this run to memory.
-
-        Args:
-            inputs: Dictionary of chain inputs, including any inputs added by chain
-                memory.
-            outputs: Dictionary of initial chain outputs.
-            return_only_outputs: Whether to only return the chain outputs. If False,
-                inputs are also added to the final outputs.
-
-        Returns:
-            A dict of the final chain outputs.
-        """
-        self._validate_outputs(outputs)
-        if self.memory is not None:
-            self.memory.save_context(inputs, outputs)
-        if return_only_outputs:
-            return outputs
-        else:
-            return {**inputs, **outputs}
-
-    def prep_inputs(self, inputs: Union[Dict[str, Any], Any]) -> Dict[str, str]:
-        """Validate and prepare chain inputs, including adding inputs from memory.
-
-        Args:
-            inputs: Dictionary of raw inputs, or single input if chain expects
-                only one param. Should contain all inputs specified in
-                `Chain.input_keys` except for inputs that will be set by the chain's
-                memory.
-
-        Returns:
-            A dictionary of all inputs, including those added by the chain's memory.
-        """
-        if not isinstance(inputs, dict):
-            _input_keys = set(self.input_keys)
-            if self.memory is not None:
-                # If there are multiple input keys, but some get set by memory so that
-                # only one is not set, we can still figure out which key it is.
-                _input_keys = _input_keys.difference(self.memory.memory_variables)
-            if len(_input_keys) != 1:
-                raise ValueError(
-                    f"A single string input was passed in, but this chain expects "
-                    f"multiple inputs ({_input_keys}). When a chain expects "
-                    f"multiple inputs, please call it by passing in a dictionary, "
-                    "eg `chain({'foo': 1, 'bar': 2})`"
-                )
-            inputs = {list(_input_keys)[0]: inputs}
-        if self.memory is not None:
-            external_context = self.memory.load_memory_variables(inputs)
-            inputs = dict(inputs, **external_context)
-        self._validate_inputs(inputs)
-        return inputs
-
-    @property
-    def _run_output_key(self) -> str:
-        if len(self.output_keys) != 1:
-            raise ValueError(
-                f"`run` not supported when there is not exactly "
-                f"one output key. Got {self.output_keys}."
-            )
-        return self.output_keys[0]
-
-    def run(
-        self,
-        *args: Any,
-        callbacks: Callbacks = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> str:
-        """Convenience method for executing chain when there's a single string output.
-
-        The main difference between this method and `Chain.__call__` is that this method
-            can only be used for chains that return a single string output. If a Chain
-            has more outputs, a non-string output, or you want to return the inputs/run
-            info along with the outputs, use `Chain.__call__`.
-
-        The other difference is that this method expects inputs to be passed directly in
-        as positional arguments or keyword arguments, whereas `Chain.__call__` expects
-        a single input dictionary with all the inputs.
-
-        Args:
-            *args: If the chain expects a single input, it can be passed in as the
-                sole positional argument.
-            callbacks: Callbacks to use for this chain run. These will be called in
-                addition to callbacks passed to the chain during construction, but only
-                these runtime callbacks will propagate to calls to other objects.
-            tags: List of string tags to pass to all callbacks. These will be passed in
-                addition to tags passed to the chain during construction, but only
-                these runtime tags will propagate to calls to other objects.
-            **kwargs: If the chain expects multiple inputs, they can be passed in
-                directly as keyword arguments.
-
-        Returns:
-            The chain output as a string.
-
-        Example:
-            .. code-block:: python
-
-                # Suppose we have a single-input chain that takes a 'question' string:
-                chain.run("What's the temperature in Boise, Idaho?")
-                # -> "The temperature in Boise is..."
-
-                # Suppose we have a multi-input chain that takes a 'question' string
-                # and 'context' string:
-                question = "What's the temperature in Boise, Idaho?"
-                context = "Weather report for Boise, Idaho on 07/03/23..."
-                chain.run(question=question, context=context)
-                # -> "The temperature in Boise is..."
-        """
-        # Run at start to make sure this is possible/defined
-        _output_key = self._run_output_key
-
-        if args and not kwargs:
-            if len(args) != 1:
-                raise ValueError("`run` supports only one positional argument.")
-            return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[
-                _output_key
-            ]
-
-        if kwargs and not args:
-            return self(kwargs, callbacks=callbacks, tags=tags, metadata=metadata)[
-                _output_key
-            ]
-
-        if not kwargs and not args:
-            raise ValueError(
-                "`run` supported with either positional arguments or keyword arguments,"
-                " but none were provided."
-            )
-        else:
-            raise ValueError(
-                f"`run` supported with either positional arguments or keyword arguments"
-                f" but not both. Got args: {args} and kwargs: {kwargs}."
-            )
-
-    async def arun(
-        self,
-        *args: Any,
-        callbacks: Callbacks = None,
-        tags: Optional[List[str]] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> str:
-        """Convenience method for executing chain when there's a single string output.
-
-        The main difference between this method and `Chain.__call__` is that this method
-            can only be used for chains that return a single string output. If a Chain
-            has more outputs, a non-string output, or you want to return the inputs/run
-            info along with the outputs, use `Chain.__call__`.
-
-        The other difference is that this method expects inputs to be passed directly in
-        as positional arguments or keyword arguments, whereas `Chain.__call__` expects
-        a single input dictionary with all the inputs.
-
-        Args:
-            *args: If the chain expects a single input, it can be passed in as the
-                sole positional argument.
-            callbacks: Callbacks to use for this chain run. These will be called in
-                addition to callbacks passed to the chain during construction, but only
-                these runtime callbacks will propagate to calls to other objects.
-            tags: List of string tags to pass to all callbacks. These will be passed in
-                addition to tags passed to the chain during construction, but only
-                these runtime tags will propagate to calls to other objects.
-            **kwargs: If the chain expects multiple inputs, they can be passed in
-                directly as keyword arguments.
-
-        Returns:
-            The chain output as a string.
-
-        Example:
-            .. code-block:: python
-
-                # Suppose we have a single-input chain that takes a 'question' string:
-                await chain.arun("What's the temperature in Boise, Idaho?")
-                # -> "The temperature in Boise is..."
-
-                # Suppose we have a multi-input chain that takes a 'question' string
-                # and 'context' string:
-                question = "What's the temperature in Boise, Idaho?"
-                context = "Weather report for Boise, Idaho on 07/03/23..."
-                await chain.arun(question=question, context=context)
-                # -> "The temperature in Boise is..."
-        """
-        if len(self.output_keys) != 1:
-            raise ValueError(
-                f"`run` not supported when there is not exactly "
-                f"one output key. Got {self.output_keys}."
-            )
-        elif args and not kwargs:
-            if len(args) != 1:
-                raise ValueError("`run` supports only one positional argument.")
-            return (
-                await self.acall(
-                    args[0], callbacks=callbacks, tags=tags, metadata=metadata
-                )
-            )[self.output_keys[0]]
-
-        if kwargs and not args:
-            return (
-                await self.acall(
-                    kwargs, callbacks=callbacks, tags=tags, metadata=metadata
-                )
-            )[self.output_keys[0]]
-
-        raise ValueError(
-            f"`run` supported with either positional arguments or keyword arguments"
-            f" but not both. Got args: {args} and kwargs: {kwargs}."
-        )
-
-    def dict(self, **kwargs: Any) -> Dict:
-        """Return dictionary representation of chain.
-
-        Expects `Chain._chain_type` property to be implemented and for memory to be
-            null.
-
-        Args:
-            **kwargs: Keyword arguments passed to default `pydantic.BaseModel.dict`
-                method.
-
-        Returns:
-            A dictionary representation of the chain.
-
-        Example:
-            ..code-block:: python
-
-                chain.dict(exclude_unset=True)
-                # -> {"_type": "foo", "verbose": False, ...}
-        """
-        if self.memory is not None:
-            raise ValueError("Saving of memory is not yet supported.")
-        _dict = super().dict(**kwargs)
-        _dict["_type"] = self._chain_type
-        return _dict
-
-    def save(self, file_path: Union[Path, str]) -> None:
-        """Save the chain.
-
-        Expects `Chain._chain_type` property to be implemented and for memory to be
-            null.
-
-        Args:
-            file_path: Path to file to save the chain to.
-
-        Example:
-            .. code-block:: python
-
-                chain.save(file_path="path/chain.yaml")
-        """
-        # Convert file to Path object.
-        if isinstance(file_path, str):
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
-
-        directory_path = save_path.parent
-        directory_path.mkdir(parents=True, exist_ok=True)
-
-        # Fetch dictionary to save
-        chain_dict = self.dict()
-
-        if save_path.suffix == ".json":
-            with open(file_path, "w") as f:
-                json.dump(chain_dict, f, indent=4)
-        elif save_path.suffix == ".yaml":
-            with open(file_path, "w") as f:
-                yaml.dump(chain_dict, f, default_flow_style=False)
-        else:
-            raise ValueError(f"{save_path} must be json or yaml")
-
-    def apply(
-        self, input_list: List[Dict[str, Any]], callbacks: Callbacks = None
-    ) -> List[Dict[str, str]]:
-        """Call the chain on all inputs in the list."""
-        return [self(inputs, callbacks=callbacks) for inputs in input_list]
+__all__ = ["Chain"]

langchain/chains/combine_documents/base.py

@@ -5,12 +5,12 @@ from typing import Any, Dict, List, Optional, Tuple
 
 from pydantic import Field
 
-from langchain.callbacks.manager import (
+from langchain.docstore.document import Document
+from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
 )
-from langchain.chains.base import Chain
-from langchain.docstore.document import Document
+from langchain.schema.chain import Chain
 from langchain.text_splitter import RecursiveCharacterTextSplitter, TextSplitter
 
 

langchain/chains/combine_documents/map_reduce.py

@@ -6,11 +6,11 @@ from typing import Any, Dict, List, Optional, Tuple
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.reduce import ReduceDocumentsChain
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
+from langchain.schema.callbacks.manager import Callbacks
 
 
 class MapReduceDocumentsChain(BaseCombineDocumentsChain):

langchain/chains/combine_documents/map_rerank.py

@@ -6,11 +6,11 @@ from typing import Any, Dict, List, Optional, Sequence, Tuple, Union, cast
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
 from langchain.output_parsers.regex import RegexParser
+from langchain.schema.callbacks.manager import Callbacks
 
 
 class MapRerankDocumentsChain(BaseCombineDocumentsChain):

langchain/chains/combine_documents/reduce.py

@@ -6,9 +6,9 @@ from typing import Any, Callable, List, Optional, Protocol, Tuple
 
 from pydantic import Extra
 
-from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.docstore.document import Document
+from langchain.schema.callbacks.manager import Callbacks
 
 
 class CombineDocsProtocol(Protocol):

langchain/chains/combine_documents/refine.py

@@ -6,7 +6,6 @@ from typing import Any, Dict, List, Tuple
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import (
     BaseCombineDocumentsChain,
 )
@@ -14,6 +13,7 @@ from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate, format_document
+from langchain.schema.callbacks.manager import Callbacks
 
 
 def _get_default_document_prompt() -> PromptTemplate:

langchain/chains/combine_documents/stuff.py

@@ -4,7 +4,6 @@ from typing import Any, Dict, List, Optional, Tuple
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import Callbacks
 from langchain.chains.combine_documents.base import (
     BaseCombineDocumentsChain,
 )
@@ -12,6 +11,7 @@ from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate, format_document
+from langchain.schema.callbacks.manager import Callbacks
 
 
 def _get_default_document_prompt() -> PromptTemplate:

langchain/chains/constitutional_ai/base.py

@@ -1,13 +1,13 @@
 """Chain for applying constitutional principles to the outputs of another chain."""
 from typing import Any, Dict, List, Optional
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.constitutional_ai.models import ConstitutionalPrinciple
 from langchain.chains.constitutional_ai.principles import PRINCIPLES
 from langchain.chains.constitutional_ai.prompts import CRITIQUE_PROMPT, REVISION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/conversational_retrieval/base.py

@@ -9,18 +9,18 @@ from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-    Callbacks,
-)
-from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.conversational_retrieval.prompts import CONDENSE_QUESTION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.chains.question_answering import load_qa_chain
 from langchain.schema import BasePromptTemplate, BaseRetriever, Document
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+    Callbacks,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import BaseMessage
 from langchain.vectorstores.base import VectorStore

langchain/chains/flare/base.py

@@ -7,10 +7,6 @@ from typing import Any, Dict, List, Optional, Sequence, Tuple
 import numpy as np
 from pydantic import Field
 
-from langchain.callbacks.manager import (
-    CallbackManagerForChainRun,
-)
-from langchain.chains.base import Chain
 from langchain.chains.flare.prompts import (
     PROMPT,
     QUESTION_GENERATOR_PROMPT,
@@ -19,6 +15,8 @@ from langchain.chains.flare.prompts import (
 from langchain.chains.llm import LLMChain
 from langchain.llms import OpenAI
 from langchain.schema import BasePromptTemplate, BaseRetriever, Generation
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/graph_qa/base.py

@@ -5,12 +5,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import ENTITY_EXTRACTION_PROMPT, GRAPH_QA_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.networkx_graph import NetworkxEntityGraph, get_entities
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/graph_qa/cypher.py

@@ -6,12 +6,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_GENERATION_PROMPT, CYPHER_QA_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.neo4j_graph import Neo4jGraph
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 INTERMEDIATE_STEPS_KEY = "intermediate_steps"

langchain/chains/graph_qa/hugegraph.py

@@ -5,8 +5,6 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,
     GREMLIN_GENERATION_PROMPT,
@@ -14,6 +12,8 @@ from langchain.chains.graph_qa.prompts import (
 from langchain.chains.llm import LLMChain
 from langchain.graphs.hugegraph import HugeGraph
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/graph_qa/kuzu.py

@@ -5,12 +5,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_QA_PROMPT, KUZU_GENERATION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.kuzu_graph import KuzuGraph
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/graph_qa/nebulagraph.py

@@ -5,12 +5,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_QA_PROMPT, NGQL_GENERATION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.nebula_graph import NebulaGraph
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/graph_qa/sparql.py

@@ -7,8 +7,6 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import (
     SPARQL_GENERATION_SELECT_PROMPT,
     SPARQL_GENERATION_UPDATE_PROMPT,
@@ -18,6 +16,8 @@ from langchain.chains.graph_qa.prompts import (
 from langchain.chains.llm import LLMChain
 from langchain.graphs.rdf_graph import RdfGraph
 from langchain.prompts.base import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/hyde/base.py

@@ -9,11 +9,11 @@ from typing import Any, Dict, List, Optional
 import numpy as np
 from pydantic import Extra
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.hyde.prompts import PROMPT_MAP
 from langchain.chains.llm import LLMChain
 from langchain.embeddings.base import Embeddings
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/llm.py

@@ -6,14 +6,6 @@ from typing import Any, Dict, List, Optional, Sequence, Tuple, Union
 
 from pydantic import Extra, Field
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManager,
-    AsyncCallbackManagerForChainRun,
-    CallbackManager,
-    CallbackManagerForChainRun,
-    Callbacks,
-)
-from langchain.chains.base import Chain
 from langchain.input import get_colored_text
 from langchain.load.dump import dumpd
 from langchain.prompts.prompt import PromptTemplate
@@ -24,6 +16,14 @@ from langchain.schema import (
     NoOpOutputParser,
     PromptValue,
 )
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManager,
+    AsyncCallbackManagerForChainRun,
+    CallbackManager,
+    CallbackManagerForChainRun,
+    Callbacks,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/llm_bash/base.py

@@ -7,11 +7,11 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_bash.prompt import PROMPT
 from langchain.schema import BasePromptTemplate, OutputParserException
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.utilities.bash import BashProcess
 

langchain/chains/llm_checker/base.py

@@ -6,8 +6,6 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_checker.prompt import (
     CHECK_ASSERTIONS_PROMPT,
@@ -17,6 +15,8 @@ from langchain.chains.llm_checker.prompt import (
 )
 from langchain.chains.sequential import SequentialChain
 from langchain.prompts import PromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/llm_math/base.py

@@ -9,14 +9,14 @@ from typing import Any, Dict, List, Optional
 import numexpr
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_math.prompt import PROMPT
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/llm_requests.py

@@ -5,10 +5,10 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains import LLMChain
-from langchain.chains.base import Chain
 from langchain.requests import TextRequestsWrapper
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 
 DEFAULT_HEADERS = {
     "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36"  # noqa: E501

langchain/chains/llm_summarization_checker/base.py

@@ -8,11 +8,11 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.sequential import SequentialChain
 from langchain.prompts.prompt import PromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 PROMPTS_DIR = Path(__file__).parent / "prompts"

langchain/chains/llm_symbolic_math/base.py

@@ -7,14 +7,14 @@ from typing import Any, Dict, List, Optional
 from pydantic import Extra
 
 from langchain.base_language import BaseLanguageModel
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_symbolic_math.prompt import PROMPT
 from langchain.prompts.base import BasePromptTemplate
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
 
 
 class LLMSymbolicMathChain(Chain):

langchain/chains/loading.py

@@ -7,7 +7,6 @@ import yaml
 
 from langchain.chains import ReduceDocumentsChain
 from langchain.chains.api.base import APIChain
-from langchain.chains.base import Chain
 from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
 from langchain.chains.combine_documents.map_rerank import MapRerankDocumentsChain
 from langchain.chains.combine_documents.refine import RefineDocumentsChain
@@ -30,6 +29,7 @@ from langchain.prompts.loading import (
     load_prompt,
     load_prompt_from_config,
 )
+from langchain.schema.chain import Chain
 from langchain.utilities.loading import try_load_from_hub
 
 URL_BASE = "https://raw.githubusercontent.com/hwchase17/langchain-hub/master/chains/"

langchain/chains/mapreduce.py

@@ -9,15 +9,15 @@ from typing import Any, Dict, List, Mapping, Optional
 
 from pydantic import Extra
 
-from langchain.callbacks.manager import CallbackManagerForChainRun, Callbacks
 from langchain.chains import ReduceDocumentsChain
-from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun, Callbacks
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.text_splitter import TextSplitter
 

langchain/chains/moderation.py

@@ -3,8 +3,8 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.utils import get_from_dict_or_env
 
 

langchain/chains/natbot/base.py

@@ -6,11 +6,11 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.natbot.prompt import PROMPT
 from langchain.llms.openai import OpenAI
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/openai_functions/extraction.py

@@ -2,7 +2,6 @@ from typing import Any, List
 
 from pydantic import BaseModel
 
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.openai_functions.utils import (
     _convert_schema,
@@ -14,6 +13,7 @@ from langchain.output_parsers.openai_functions import (
     PydanticAttrOutputFunctionsParser,
 )
 from langchain.prompts import ChatPromptTemplate
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/openai_functions/openapi.py

@@ -8,14 +8,14 @@ from openapi_schema_pydantic import Parameter
 from requests import Response
 
 from langchain import LLMChain
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.sequential import SequentialChain
 from langchain.chat_models import ChatOpenAI
 from langchain.input import get_colored_text
 from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools import APIOperation
 from langchain.utilities.openapi import OpenAPISpec

langchain/chains/openai_functions/tagging.py

@@ -1,6 +1,5 @@
 from typing import Any, Optional
 
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.openai_functions.utils import _convert_schema, get_llm_kwargs
 from langchain.output_parsers.openai_functions import (
@@ -8,6 +7,7 @@ from langchain.output_parsers.openai_functions import (
     PydanticOutputFunctionsParser,
 )
 from langchain.prompts import ChatPromptTemplate
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/pal/base.py

@@ -9,12 +9,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.pal.colored_object_prompt import COLORED_OBJECT_PROMPT
 from langchain.chains.pal.math_prompt import MATH_PROMPT
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.utilities import PythonREPL
 

langchain/chains/qa_generation/base.py

@@ -5,11 +5,11 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Field
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.qa_generation.prompt import PROMPT_SELECTOR
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.text_splitter import RecursiveCharacterTextSplitter, TextSplitter
 

langchain/chains/qa_with_sources/base.py

@@ -9,12 +9,7 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains import ReduceDocumentsChain
-from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
@@ -27,6 +22,11 @@ from langchain.chains.qa_with_sources.map_reduce_prompt import (
 )
 from langchain.docstore.document import Document
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/qa_with_sources/retrieval.py

@@ -4,14 +4,14 @@ from typing import Any, Dict, List
 
 from pydantic import Field
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.qa_with_sources.base import BaseQAWithSourcesChain
 from langchain.docstore.document import Document
 from langchain.schema import BaseRetriever
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
 
 
 class RetrievalQAWithSourcesChain(BaseQAWithSourcesChain):

langchain/chains/qa_with_sources/vector_db.py

@@ -5,13 +5,13 @@ from typing import Any, Dict, List
 
 from pydantic import Field, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.qa_with_sources.base import BaseQAWithSourcesChain
 from langchain.docstore.document import Document
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
 from langchain.vectorstores.base import VectorStore
 
 

langchain/chains/question_answering/__init__.py

@@ -1,8 +1,6 @@
 """Load question answering chains."""
 from typing import Any, Mapping, Optional, Protocol
 
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import Callbacks
 from langchain.chains import ReduceDocumentsChain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
@@ -18,6 +16,8 @@ from langchain.chains.question_answering import (
 from langchain.chains.question_answering.map_rerank_prompt import (
     PROMPT as MAP_RERANK_PROMPT,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import Callbacks
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.prompt_template import BasePromptTemplate
 

langchain/chains/retrieval_qa/base.py

@@ -8,11 +8,6 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
-from langchain.chains.base import Chain
 from langchain.chains.combine_documents.base import BaseCombineDocumentsChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.llm import LLMChain
@@ -20,6 +15,11 @@ from langchain.chains.question_answering import load_qa_chain
 from langchain.chains.question_answering.stuff_prompt import PROMPT_SELECTOR
 from langchain.prompts import PromptTemplate
 from langchain.schema import BaseRetriever, Document
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.vectorstores.base import VectorStore
 

langchain/chains/router/base.py

@@ -6,12 +6,12 @@ from typing import Any, Dict, List, Mapping, NamedTuple, Optional
 
 from pydantic import Extra
 
-from langchain.callbacks.manager import (
+from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
     Callbacks,
 )
-from langchain.chains.base import Chain
+from langchain.schema.chain import Chain
 
 
 class Route(NamedTuple):

langchain/chains/router/embedding_router.py

@@ -4,10 +4,10 @@ from typing import Any, Dict, List, Optional, Sequence, Tuple, Type
 
 from pydantic import Extra
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.router.base import RouterChain
 from langchain.docstore.document import Document
 from langchain.embeddings.base import Embeddings
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
 from langchain.vectorstores.base import VectorStore
 
 

langchain/chains/router/llm_router.py

@@ -5,14 +5,14 @@ from typing import Any, Dict, List, Optional, Type, cast
 
 from pydantic import root_validator
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForChainRun,
-    CallbackManagerForChainRun,
-)
 from langchain.chains import LLMChain
 from langchain.chains.router.base import RouterChain
 from langchain.output_parsers.json import parse_and_check_json_markdown
 from langchain.schema import BaseOutputParser, BasePromptTemplate, OutputParserException
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForChainRun,
+    CallbackManagerForChainRun,
+)
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/router/multi_retrieval_qa.py

@@ -4,7 +4,6 @@ from __future__ import annotations
 from typing import Any, Dict, List, Mapping, Optional
 
 from langchain.chains import ConversationChain
-from langchain.chains.base import Chain
 from langchain.chains.conversation.prompt import DEFAULT_TEMPLATE
 from langchain.chains.retrieval_qa.base import BaseRetrievalQA, RetrievalQA
 from langchain.chains.router.base import MultiRouteChain
@@ -15,6 +14,7 @@ from langchain.chains.router.multi_retrieval_prompt import (
 from langchain.chat_models import ChatOpenAI
 from langchain.prompts import PromptTemplate
 from langchain.schema import BaseRetriever
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 
 

langchain/chains/sequential.py

@@ -3,12 +3,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.callbacks.manager import (
+from langchain.input import get_color_mapping
+from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForChainRun,
     CallbackManagerForChainRun,
 )
-from langchain.chains.base import Chain
-from langchain.input import get_color_mapping
+from langchain.schema.chain import Chain
 
 
 class SequentialChain(Chain):

langchain/chains/sql_database/base.py

@@ -6,12 +6,12 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, Field, root_validator
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.sql_database.prompt import DECIDER_PROMPT, PROMPT, SQL_PROMPTS
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.sql_database import SQLDatabase
 from langchain.tools.sql_database.prompt import QUERY_CHECKER

langchain/chains/transform.py

@@ -1,8 +1,8 @@
 """Chain that runs an arbitrary python function."""
 from typing import Callable, Dict, List, Optional
 
-from langchain.callbacks.manager import CallbackManagerForChainRun
-from langchain.chains.base import Chain
+from langchain.schema.callbacks.manager import CallbackManagerForChainRun
+from langchain.schema.chain import Chain
 
 
 class TransformChain(Chain):

langchain/chat_models/anthropic.py

@@ -1,15 +1,15 @@
 from typing import Any, Dict, List, Optional
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForLLMRun,
-    CallbackManagerForLLMRun,
-)
 from langchain.chat_models.base import BaseChatModel
 from langchain.llms.anthropic import _AnthropicCommon
 from langchain.schema import (
     ChatGeneration,
     ChatResult,
 )
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
 from langchain.schema.messages import (
     AIMessage,
     BaseMessage,

langchain/chat_models/base.py

@@ -8,14 +8,6 @@ from typing import Any, Dict, List, Mapping, Optional, Sequence
 from pydantic import Field, root_validator
 
 import langchain
-from langchain.callbacks.base import BaseCallbackManager
-from langchain.callbacks.manager import (
-    AsyncCallbackManager,
-    AsyncCallbackManagerForLLMRun,
-    CallbackManager,
-    CallbackManagerForLLMRun,
-    Callbacks,
-)
 from langchain.load.dump import dumpd, dumps
 from langchain.schema import (
     ChatGeneration,
@@ -24,6 +16,14 @@ from langchain.schema import (
     PromptValue,
     RunInfo,
 )
+from langchain.schema.callbacks.base import BaseCallbackManager
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManager,
+    AsyncCallbackManagerForLLMRun,
+    CallbackManager,
+    CallbackManagerForLLMRun,
+    Callbacks,
+)
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import AIMessage, BaseMessage, HumanMessage
 

langchain/chat_models/fake.py

@@ -1,8 +1,8 @@
 """Fake ChatModel for testing purposes."""
 from typing import Any, List, Mapping, Optional
 
-from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.chat_models.base import SimpleChatModel
+from langchain.schema.callbacks.manager import CallbackManagerForLLMRun
 from langchain.schema.messages import BaseMessage
 
 

langchain/chat_models/google_palm.py

@@ -13,15 +13,15 @@ from tenacity import (
     wait_exponential,
 )
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForLLMRun,
-    CallbackManagerForLLMRun,
-)
 from langchain.chat_models.base import BaseChatModel
 from langchain.schema import (
     ChatGeneration,
     ChatResult,
 )
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
 from langchain.schema.messages import (
     AIMessage,
     BaseMessage,

langchain/chat_models/human.py

@@ -7,12 +7,12 @@ from typing import Any, Callable, List, Mapping, Optional
 import yaml
 from pydantic import Field
 
-from langchain.callbacks.manager import (
+from langchain.chat_models.base import BaseChatModel
+from langchain.llms.utils import enforce_stop_tokens
+from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain.chat_models.base import BaseChatModel
-from langchain.llms.utils import enforce_stop_tokens
 from langchain.schema.messages import (
     BaseMessage,
     HumanMessage,

langchain/chat_models/jinachat.py

@@ -22,10 +22,6 @@ from tenacity import (
     wait_exponential,
 )
 
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForLLMRun,
-    CallbackManagerForLLMRun,
-)
 from langchain.chat_models.base import BaseChatModel
 from langchain.schema import (
     AIMessage,
@@ -36,6 +32,10 @@ from langchain.schema import (
     HumanMessage,
     SystemMessage,
 )
+from langchain.schema.callbacks.manager import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
 from langchain.utils import get_from_dict_or_env
 
 logger = logging.getLogger(__name__)