langchain[patch], experimental[patch]: replace langchain.schema imports (#15410)

Import from core instead.

Ran:
```bash
git grep -l 'from langchain.schema\.output_parser' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.output_parser/from\ langchain_core.output_parsers/g"
git grep -l 'from langchain.schema\.messages' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.messages/from\ langchain_core.messages/g"
git grep -l 'from langchain.schema\.document' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.document/from\ langchain_core.documents/g"
git grep -l 'from langchain.schema\.runnable' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.runnable/from\ langchain_core.runnables/g"
git grep -l 'from langchain.schema\.vectorstore' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.vectorstore/from\ langchain_core.vectorstores/g"
git grep -l 'from langchain.schema\.language_model' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.language_model/from\ langchain_core.language_models/g"
git grep -l 'from langchain.schema\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.embeddings/from\ langchain_core.embeddings/g"
git grep -l 'from langchain.schema\.storage' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.storage/from\ langchain_core.stores/g"
git checkout master libs/langchain/tests/unit_tests/schema/
make format
cd libs/experimental
make format
cd ../langchain
make format
```

cookbook/Multi_modal_RAG_google.ipynb

@@ -161,8 +161,8 @@
     "from langchain.chat_models import ChatVertexAI\n",
     "from langchain.llms import VertexAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
     "from langchain_core.messages import AIMessage\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_core.runnables import RunnableLambda\n",
     "\n",
     "\n",
@@ -243,7 +243,7 @@
     "import base64\n",
     "import os\n",
     "\n",
-    "from langchain.schema.messages import HumanMessage\n",
+    "from langchain_core.messages import HumanMessage\n",
     "\n",
     "\n",
     "def encode_image(image_path):\n",
@@ -344,9 +344,9 @@
     "\n",
     "from langchain.embeddings import VertexAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
-    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
     "from langchain.vectorstores import Chroma\n",
+    "from langchain_core.documents import Document\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",
@@ -440,7 +440,7 @@
     "import re\n",
     "\n",
     "from IPython.display import HTML, display\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
     "from PIL import Image\n",
     "\n",
     "\n",

docs/docs/integrations/chat/google_generative_ai.ipynb

@@ -151,7 +151,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.messages import HumanMessage, SystemMessage\n",
+    "from langchain_core.messages import HumanMessage, SystemMessage\n",
     "\n",
     "model = ChatGoogleGenerativeAI(model=\"gemini-pro\", convert_system_message_to_human=True)\n",
     "model(\n",

docs/docs/integrations/llms/google_vertex_ai_palm.ipynb

@@ -415,7 +415,7 @@
    ],
    "source": [
     "from langchain.chat_models import ChatVertexAI\n",
-    "from langchain.schema.messages import HumanMessage\n",
+    "from langchain_core.messages import HumanMessage\n",
     "\n",
     "llm = ChatVertexAI(model_name=\"gemini-ultra-vision\")\n",
     "\n",

docs/docs/integrations/providers/cohere.mdx

@@ -49,7 +49,7 @@ print(llm.invoke("Come up with a pet name"))
 ```python
 from langchain.chat_models import ChatCohere
 from langchain.retrievers import CohereRagRetriever
-from langchain.schema.document import Document
+from langchain_core.documents import Document
 
 rag = CohereRagRetriever(llm=ChatCohere())
 print(rag.get_relevant_documents("What is cohere ai?"))
@@ -60,7 +60,7 @@ print(rag.get_relevant_documents("What is cohere ai?"))
 ```python
 from langchain.chat_models import ChatCohere
 from langchain.retrievers import CohereRagRetriever
-from langchain.schema.document import Document
+from langchain_core.documents import Document
 
 rag = CohereRagRetriever(llm=ChatCohere())
 print(rag.get_relevant_documents("What is cohere ai?"))

docs/docs/integrations/providers/vectara/vectara_summary.ipynb

@@ -76,9 +76,9 @@
    "source": [
     "from langchain.embeddings import FakeEmbeddings\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
-    "from langchain.vectorstores import Vectara"
+    "from langchain.vectorstores import Vectara\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough"
    ]
   },
   {

docs/docs/integrations/retrievers/fleet_context.ipynb

@@ -36,9 +36,9 @@
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers import MultiVectorRetriever\n",
     "from langchain.schema import Document\n",
-    "from langchain.schema.storage import BaseStore\n",
-    "from langchain.schema.vectorstore import VectorStore\n",
     "from langchain.vectorstores import FAISS\n",
+    "from langchain_core.stores import BaseStore\n",
+    "from langchain_core.vectorstores import VectorStore\n",
     "\n",
     "\n",
     "def load_fleet_retriever(\n",

docs/docs/integrations/vectorstores/jaguar.ipynb

@@ -58,10 +58,10 @@
     "from langchain.embeddings.openai import OpenAIEmbeddings\n",
     "from langchain.llms import OpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
     "from langchain_community.vectorstores.jaguar import Jaguar\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "\"\"\" \n",
     "Load a text file into a set of documents \n",

libs/core/langchain_core/runnables/base.py

@@ -3556,7 +3556,7 @@ class RunnableBinding(RunnableBindingBase[Input, Output]):
 
         .. code-block:: python
 
-            from langchain.schema.runnable import RunnableBinding
+            from langchain_core.runnables import RunnableBinding
             runnable_binding = RunnableBinding(
                 bound=model,
                 kwargs={'stop': ['-']} # <-- Note the additional kwargs

libs/experimental/langchain_experimental/agents/agent_toolkits/csv/base.py

@@ -2,7 +2,7 @@ from io import IOBase
 from typing import Any, List, Optional, Union
 
 from langchain.agents.agent import AgentExecutor
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.agents.agent_toolkits.pandas.base import (
     create_pandas_dataframe_agent,

libs/experimental/langchain_experimental/agents/agent_toolkits/pandas/base.py

@@ -8,9 +8,9 @@ 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.language_model import BaseLanguageModel
-from langchain.schema.messages import SystemMessage
 from langchain.tools import BaseTool
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import SystemMessage
 
 from langchain_experimental.agents.agent_toolkits.pandas.prompt import (
     FUNCTIONS_WITH_DF,

libs/experimental/langchain_experimental/agents/agent_toolkits/python/base.py

@@ -8,8 +8,8 @@ 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.language_model import BaseLanguageModel
-from langchain.schema.messages import SystemMessage
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import SystemMessage
 
 from langchain_experimental.agents.agent_toolkits.python.prompt import PREFIX
 from langchain_experimental.tools.python.tool import PythonREPLTool

libs/experimental/langchain_experimental/autonomous_agents/autogpt/agent.py

@@ -9,10 +9,10 @@ from langchain.schema import (
     BaseChatMessageHistory,
     Document,
 )
-from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
-from langchain.schema.vectorstore import VectorStoreRetriever
 from langchain.tools.base import BaseTool
 from langchain.tools.human.tool import HumanInputRun
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
+from langchain_core.vectorstores import VectorStoreRetriever
 
 from langchain_experimental.autonomous_agents.autogpt.output_parser import (
     AutoGPTOutputParser,

libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List
 
 from langchain.memory.chat_memory import BaseChatMemory, get_prompt_input_key
-from langchain.schema.vectorstore import VectorStoreRetriever
+from langchain_core.vectorstores import VectorStoreRetriever
 
 from langchain_experimental.pydantic_v1 import Field
 

libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py

@@ -4,9 +4,9 @@ from typing import Any, Callable, List, cast
 from langchain.prompts.chat import (
     BaseChatPromptTemplate,
 )
-from langchain.schema.messages import BaseMessage, HumanMessage, SystemMessage
-from langchain.schema.vectorstore import VectorStoreRetriever
 from langchain.tools.base import BaseTool
+from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
+from langchain_core.vectorstores import VectorStoreRetriever
 
 from langchain_experimental.autonomous_agents.autogpt.prompt_generator import get_prompt
 from langchain_experimental.pydantic_v1 import BaseModel

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/baby_agi.py

@@ -4,8 +4,8 @@ from typing import Any, Dict, List, Optional
 
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
-from langchain.schema.language_model import BaseLanguageModel
-from langchain.schema.vectorstore import VectorStore
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.vectorstores import VectorStore
 
 from langchain_experimental.autonomous_agents.baby_agi.task_creation import (
     TaskCreationChain,

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/task_creation.py

@@ -1,6 +1,6 @@
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 
 class TaskCreationChain(LLMChain):

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/task_execution.py

@@ -1,6 +1,6 @@
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 
 class TaskExecutionChain(LLMChain):

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/task_prioritization.py

@@ -1,6 +1,6 @@
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 
 class TaskPrioritizationChain(LLMChain):

libs/experimental/langchain_experimental/fallacy_removal/base.py

@@ -7,7 +7,7 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.schema import BasePromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.fallacy_removal.fallacies import FALLACIES
 from langchain_experimental.fallacy_removal.models import LogicalFallacy

libs/experimental/langchain_experimental/generative_agents/generative_agent.py

@@ -4,7 +4,7 @@ from typing import Any, Dict, List, Optional, Tuple
 
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.generative_agents.memory import GenerativeAgentMemory
 from langchain_experimental.pydantic_v1 import BaseModel, Field

libs/experimental/langchain_experimental/generative_agents/memory.py

@@ -7,8 +7,8 @@ from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
 from langchain.retrievers import TimeWeightedVectorStoreRetriever
 from langchain.schema import BaseMemory, Document
-from langchain.schema.language_model import BaseLanguageModel
 from langchain.utils import mock_now
+from langchain_core.language_models import BaseLanguageModel
 
 logger = logging.getLogger(__name__)
 

libs/experimental/langchain_experimental/llm_bash/base.py

@@ -9,7 +9,7 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.schema import BasePromptTemplate, OutputParserException
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.llm_bash.bash import BashProcess
 from langchain_experimental.llm_bash.prompt import PROMPT

libs/experimental/langchain_experimental/llms/anthropic_functions.py

@@ -12,7 +12,7 @@ from langchain.schema import (
     ChatGeneration,
     ChatResult,
 )
-from langchain.schema.messages import (
+from langchain_core.messages import (
     AIMessage,
     BaseMessage,
     SystemMessage,

libs/experimental/langchain_experimental/llms/llamaapi.py

@@ -15,7 +15,7 @@ from langchain.schema import (
     ChatGeneration,
     ChatResult,
 )
-from langchain.schema.messages import (
+from langchain_core.messages import (
     AIMessage,
     BaseMessage,
     ChatMessage,

libs/experimental/langchain_experimental/open_clip/open_clip.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List
 
 from langchain.pydantic_v1 import BaseModel, root_validator
-from langchain.schema.embeddings import Embeddings
+from langchain_core.embeddings import Embeddings
 
 
 class OpenCLIPEmbeddings(BaseModel, Embeddings):

libs/experimental/langchain_experimental/pal_chain/base.py

@@ -13,8 +13,8 @@ from typing import Any, Dict, List, Optional
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
-from langchain.schema.language_model import BaseLanguageModel
 from langchain.utilities import PythonREPL
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.pal_chain.colored_object_prompt import COLORED_OBJECT_PROMPT
 from langchain_experimental.pal_chain.math_prompt import MATH_PROMPT

libs/experimental/langchain_experimental/plan_and_execute/executors/agent_executor.py

@@ -2,8 +2,8 @@ from typing import List
 
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.structured_chat.base import StructuredChatAgent
-from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools import BaseTool
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.plan_and_execute.executors.base import ChainExecutor
 

libs/experimental/langchain_experimental/plan_and_execute/planners/chat_planner.py

@@ -2,8 +2,8 @@ import re
 
 from langchain.chains import LLMChain
 from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
-from langchain.schema.messages import SystemMessage
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.messages import SystemMessage
 
 from langchain_experimental.plan_and_execute.planners.base import LLMPlanner
 from langchain_experimental.plan_and_execute.schema import (

libs/experimental/langchain_experimental/sql/base.py

@@ -10,9 +10,9 @@ 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.language_model import BaseLanguageModel
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 from langchain.utilities.sql_database import SQLDatabase
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.pydantic_v1 import Extra, Field, root_validator
 

libs/experimental/langchain_experimental/sql/vector_sql.py

@@ -8,10 +8,10 @@ from langchain.chains.llm import LLMChain
 from langchain.chains.sql_database.prompt import PROMPT, SQL_PROMPTS
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser, BasePromptTemplate
-from langchain.schema.embeddings import Embeddings
-from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 from langchain.utilities.sql_database import SQLDatabase
+from langchain_core.embeddings import Embeddings
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.sql.base import INTERMEDIATE_STEPS_KEY, SQLDatabaseChain
 

libs/experimental/langchain_experimental/synthetic_data/__init__.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Optional
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 from langchain_experimental.synthetic_data.prompts import SENTENCE_PROMPT
 

libs/experimental/langchain_experimental/tabular_synthetic_data/base.py

@@ -5,7 +5,7 @@ from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.prompts.few_shot import FewShotPromptTemplate
 from langchain.pydantic_v1 import BaseModel, root_validator
-from langchain.schema.language_model import BaseLanguageModel
+from langchain_core.language_models import BaseLanguageModel
 
 
 class SyntheticDataGenerator(BaseModel):

libs/langchain/langchain/chains/ernie_functions/base.py

@@ -13,6 +13,9 @@ from typing import (
     cast,
 )
 
+from langchain_core.output_parsers import BaseGenerationOutputParser, BaseOutputParser
+from langchain_core.runnables import Runnable
+
 from langchain.base_language import BaseLanguageModel
 from langchain.chains import LLMChain
 from langchain.output_parsers.ernie_functions import (
@@ -23,8 +26,6 @@ from langchain.output_parsers.ernie_functions import (
 from langchain.prompts import BasePromptTemplate
 from langchain.pydantic_v1 import BaseModel
 from langchain.schema import BaseLLMOutputParser
-from langchain.schema.output_parser import BaseGenerationOutputParser, BaseOutputParser
-from langchain.schema.runnable import Runnable
 from langchain.utils.ernie_functions import convert_pydantic_to_ernie_function
 
 PYTHON_TO_JSON_TYPES = {

libs/langchain/langchain/output_parsers/ernie_functions.py

@@ -3,6 +3,10 @@ import json
 from typing import Any, Dict, List, Optional, Type, Union
 
 import jsonpatch
+from langchain_core.output_parsers import (
+    BaseCumulativeTransformOutputParser,
+    BaseGenerationOutputParser,
+)
 
 from langchain.output_parsers.json import parse_partial_json
 from langchain.pydantic_v1 import BaseModel, root_validator
@@ -11,10 +15,6 @@ from langchain.schema import (
     Generation,
     OutputParserException,
 )
-from langchain.schema.output_parser import (
-    BaseCumulativeTransformOutputParser,
-    BaseGenerationOutputParser,
-)
 
 
 class OutputFunctionsParser(BaseGenerationOutputParser[Any]):

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

@@ -5,11 +5,11 @@ from typing import Any, Dict, List, Optional
 from langchain_core.agents import AgentAction, AgentStep
 from langchain_core.language_models.llms import LLM
 from langchain_core.messages import AIMessage, HumanMessage
+from langchain_core.runnables.utils import add
 from langchain_core.tools import Tool
 
 from langchain.agents import AgentExecutor, AgentType, initialize_agent
 from langchain.callbacks.manager import CallbackManagerForLLMRun
-from langchain.schema.runnable.utils import add
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
 
 

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

@@ -5,11 +5,11 @@ from typing import Any, Dict, List, Optional
 from langchain_core.agents import AgentAction, AgentStep
 from langchain_core.language_models.llms import LLM
 from langchain_core.messages import AIMessage, HumanMessage
+from langchain_core.runnables.utils import add
 from langchain_core.tools import Tool
 
 from langchain.agents import AgentExecutor, AgentType, initialize_agent
 from langchain.callbacks.manager import CallbackManagerForLLMRun
-from langchain.schema.runnable.utils import add
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
 
 

templates/bedrock-jcvd/bedrock_jcvd/chain.py

@@ -2,7 +2,7 @@ import os
 
 from langchain.chat_models import BedrockChat
 from langchain.prompts import ChatPromptTemplate
-from langchain.schema.runnable import ConfigurableField
+from langchain_core.runnables import ConfigurableField
 
 # For a description of each inference parameter, see
 # https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-claude.html

templates/cohere-librarian/cohere_librarian/router.py

@@ -1,6 +1,6 @@
 from langchain.prompts import ChatPromptTemplate
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableBranch
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnableBranch
 
 from .blurb_matcher import book_rec_chain
 from .chat import chat

templates/python-lint/python_lint/agent_executor.py

@@ -9,7 +9,7 @@ from langchain.chat_models import ChatOpenAI
 from langchain.llms.base import BaseLLM
 from langchain.prompts import ChatPromptTemplate
 from langchain.pydantic_v1 import BaseModel, Field, ValidationError, validator
-from langchain.schema.runnable import ConfigurableField, Runnable
+from langchain_core.runnables import ConfigurableField, Runnable
 
 
 def strip_python_markdown_tags(text: str) -> str:

templates/rag-chroma-multi-modal-multi-vector/ingest.py

@@ -9,10 +9,10 @@ import pypdfium2 as pdfium
 from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.retrievers.multi_vector import MultiVectorRetriever
-from langchain.schema.document import Document
-from langchain.schema.messages import HumanMessage
 from langchain.storage import LocalFileStore, UpstashRedisByteStore
 from langchain.vectorstores import Chroma
+from langchain_core.documents import Document
+from langchain_core.messages import HumanMessage
 from PIL import Image
 
 

templates/rag-chroma-multi-modal-multi-vector/rag_chroma_multi_modal_multi_vector/chain.py

@@ -7,12 +7,12 @@ from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.pydantic_v1 import BaseModel
 from langchain.retrievers.multi_vector import MultiVectorRetriever
-from langchain.schema.document import Document
-from langchain.schema.messages import HumanMessage
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableLambda, RunnablePassthrough
 from langchain.storage import LocalFileStore, UpstashRedisByteStore
 from langchain.vectorstores import Chroma
+from langchain_core.documents import Document
+from langchain_core.messages import HumanMessage
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnableLambda, RunnablePassthrough
 from PIL import Image
 
 

templates/rag-multi-modal-mv-local/ingest.py

@@ -8,10 +8,10 @@ from pathlib import Path
 from langchain.chat_models import ChatOllama
 from langchain.embeddings import OllamaEmbeddings
 from langchain.retrievers.multi_vector import MultiVectorRetriever
-from langchain.schema.document import Document
-from langchain.schema.messages import HumanMessage
 from langchain.storage import LocalFileStore
 from langchain.vectorstores import Chroma
+from langchain_core.documents import Document
+from langchain_core.messages import HumanMessage
 from PIL import Image
 
 

templates/rag-multi-modal-mv-local/rag_multi_modal_mv_local/chain.py

@@ -6,12 +6,12 @@ from langchain.chat_models import ChatOllama
 from langchain.embeddings import OllamaEmbeddings
 from langchain.pydantic_v1 import BaseModel
 from langchain.retrievers.multi_vector import MultiVectorRetriever
-from langchain.schema.document import Document
-from langchain.schema.messages import HumanMessage
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnableLambda, RunnablePassthrough
 from langchain.storage import LocalFileStore
 from langchain.vectorstores import Chroma
+from langchain_core.documents import Document
+from langchain_core.messages import HumanMessage
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnableLambda, RunnablePassthrough
 from PIL import Image
 
 

templates/sql-research-assistant/sql_research_assistant/chain.py

@@ -1,5 +1,5 @@
 from langchain.pydantic_v1 import BaseModel
-from langchain.schema.runnable import RunnablePassthrough
+from langchain_core.runnables import RunnablePassthrough
 
 from sql_research_assistant.search.web import chain as search_chain
 from sql_research_assistant.writer import chain as writer_chain

templates/sql-research-assistant/sql_research_assistant/search/sql.py

@@ -4,9 +4,9 @@ from langchain.chat_models import ChatOllama, ChatOpenAI
 from langchain.memory import ConversationBufferMemory
 from langchain.prompts import ChatPromptTemplate
 from langchain.pydantic_v1 import BaseModel
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import RunnablePassthrough
 from langchain.utilities import SQLDatabase
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnablePassthrough
 
 # Add the LLM downloaded from Ollama
 ollama_llm = "llama2"

templates/sql-research-assistant/sql_research_assistant/search/web.py

@@ -5,15 +5,15 @@ import requests
 from bs4 import BeautifulSoup
 from langchain.chat_models import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate
-from langchain.schema.messages import SystemMessage
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import (
+from langchain.utilities import DuckDuckGoSearchAPIWrapper
+from langchain_core.messages import SystemMessage
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import (
     Runnable,
     RunnableLambda,
     RunnableParallel,
     RunnablePassthrough,
 )
-from langchain.utilities import DuckDuckGoSearchAPIWrapper
 
 from sql_research_assistant.search.sql import sql_answer_chain
 

templates/sql-research-assistant/sql_research_assistant/writer.py

@@ -1,7 +1,7 @@
 from langchain.chat_models import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate
-from langchain.schema.output_parser import StrOutputParser
-from langchain.schema.runnable import ConfigurableField
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import ConfigurableField
 
 WRITER_SYSTEM_PROMPT = "You are an AI critical thinker research assistant. Your sole purpose is to write well written, critically acclaimed, objective and structured reports on given text."  # noqa: E501