docs[patch], templates[patch]: Import from core (#14575)

Update imports to use core for the low-hanging fruit changes. Ran following ```bash git grep -l 'langchain.schema.runnable' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.runnable/langchain_core.runnables/g' git grep -l 'langchain.schema.output_parser' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.output_parser/langchain_core.output_parsers/g' git grep -l 'langchain.schema.messages' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.messages/langchain_core.messages/g' git grep -l 'langchain.schema.chat_histry' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.chat_history/langchain_core.chat_history/g' git grep -l 'langchain.schema.prompt_template' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.prompt_template/langchain_core.prompts/g' git grep -l 'from langchain.pydantic_v1' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.pydantic_v1/from langchain_core.pydantic_v1/g' git grep -l 'from langchain.tools.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.tools\.base/from langchain_core.tools/g' git grep -l 'from langchain.chat_models.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.chat_models.base/from langchain_core.language_models.chat_models/g' git grep -l 'from langchain.llms.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.llms\.base\ /from langchain_core.language_models.llms\ /g' git grep -l 'from langchain.embeddings.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.embeddings\.base/from langchain_core.embeddings/g' git grep -l 'from langchain.vectorstores.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.vectorstores\.base/from langchain_core.vectorstores/g' git grep -l 'from langchain.agents.tools' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.agents\.tools/from langchain_core.tools/g' git grep -l 'from langchain.schema.output' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.output\ /from langchain_core.outputs\ /g' git grep -l 'from langchain.schema.embeddings' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.embeddings/from langchain_core.embeddings/g' git grep -l 'from langchain.schema.document' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.document/from langchain_core.documents/g' git grep -l 'from langchain.schema.agent' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.agent/from langchain_core.agents/g' git grep -l 'from langchain.schema.prompt ' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.prompt\ /from langchain_core.prompt_values /g' git grep -l 'from langchain.schema.language_model' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.language_model/from langchain_core.language_models/g' ```
langchain-ai · Dec 12, 2023 · 9ffca3b · 9ffca3b
1 parent 0a9d933
commit 9ffca3b
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diff --git a/cookbook/LLaMA2_sql_chat.ipynb b/cookbook/LLaMA2_sql_chat.ipynb
@@ -164,8 +164,8 @@
     ")\n",
     "\n",
     "# Chain to query\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "sql_response = (\n",
     "    RunnablePassthrough.assign(schema=get_schema)\n",
@@ -293,7 +293,7 @@
     "memory = ConversationBufferMemory(return_messages=True)\n",
     "\n",
     "# Chain to query with memory\n",
-    "from langchain.schema.runnable import RunnableLambda\n",
+    "from langchain_core.runnables import RunnableLambda\n",
     "\n",
     "sql_chain = (\n",
     "    RunnablePassthrough.assign(\n",

diff --git a/cookbook/Multi_modal_RAG.ipynb b/cookbook/Multi_modal_RAG.ipynb
@@ -200,7 +200,7 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
     "\n",
     "\n",
     "# Generate summaries of text elements\n",
@@ -270,7 +270,7 @@
     "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",
@@ -355,9 +355,9 @@
     "\n",
     "from langchain.embeddings import OpenAIEmbeddings\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",
@@ -442,7 +442,7 @@
     "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",

diff --git a/cookbook/Semi_Structured_RAG.ipynb b/cookbook/Semi_Structured_RAG.ipynb
@@ -237,7 +237,7 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -320,9 +320,9 @@
     "\n",
     "from langchain.embeddings import OpenAIEmbeddings\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",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",
@@ -374,7 +374,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

diff --git a/cookbook/Semi_structured_and_multi_modal_RAG.ipynb b/cookbook/Semi_structured_and_multi_modal_RAG.ipynb
@@ -213,7 +213,7 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -375,9 +375,9 @@
     "\n",
     "from langchain.embeddings import OpenAIEmbeddings\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",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",
@@ -646,7 +646,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

diff --git a/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb b/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb
@@ -211,7 +211,7 @@
    "source": [
     "from langchain.chat_models import ChatOllama\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -378,9 +378,9 @@
     "\n",
     "from langchain.embeddings import GPT4AllEmbeddings\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",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(\n",
@@ -532,7 +532,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

diff --git a/cookbook/advanced_rag_eval.ipynb b/cookbook/advanced_rag_eval.ipynb
@@ -162,7 +162,7 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
     "\n",
     "# Prompt\n",
     "prompt_text = \"\"\"You are an assistant tasked with summarizing tables and text for retrieval. \\\n",
@@ -202,7 +202,7 @@
     "import os\n",
     "from io import BytesIO\n",
     "\n",
-    "from langchain.schema.messages import HumanMessage\n",
+    "from langchain_core.messages import HumanMessage\n",
     "from PIL import Image\n",
     "\n",
     "\n",
@@ -273,8 +273,8 @@
     "from base64 import b64decode\n",
     "\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
-    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
+    "from langchain_core.documents import Document\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",
@@ -475,7 +475,7 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "# Prompt\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",
@@ -521,7 +521,7 @@
     "import re\n",
     "\n",
     "from langchain.schema import Document\n",
-    "from langchain.schema.runnable import RunnableLambda\n",
+    "from langchain_core.runnables import RunnableLambda\n",
     "\n",
     "\n",
     "def looks_like_base64(sb):\n",

diff --git a/cookbook/docugami_xml_kg_rag.ipynb b/cookbook/docugami_xml_kg_rag.ipynb
@@ -476,7 +476,7 @@
     "    HumanMessagePromptTemplate,\n",
     "    SystemMessagePromptTemplate,\n",
     ")\n",
-    "from langchain.schema.output_parser import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {
@@ -547,9 +547,9 @@
     "\n",
     "from langchain.embeddings import OpenAIEmbeddings\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.chroma import Chroma\n",
+    "from langchain_core.documents import Document\n",
     "\n",
     "\n",
     "def build_retriever(text_elements, tables, table_summaries):\n",
@@ -605,7 +605,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "system_prompt = SystemMessagePromptTemplate.from_template(\n",
     "    \"You are a helpful assistant that answers questions based on provided context. Your provided context can include text or tables, \"\n",

diff --git a/cookbook/extraction_openai_tools.ipynb b/cookbook/extraction_openai_tools.ipynb
@@ -23,7 +23,7 @@
     "\n",
     "from langchain.chains.openai_tools import create_extraction_chain_pydantic\n",
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.pydantic_v1 import BaseModel"
+    "from langchain_core.pydantic_v1 import BaseModel"
    ]
   },
   {
@@ -151,11 +151,11 @@
     "\n",
     "from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
-    "from langchain.schema.runnable import Runnable\n",
-    "from langchain.pydantic_v1 import BaseModel\n",
+    "from langchain_core.runnables import Runnable\n",
+    "from langchain_core.pydantic_v1 import BaseModel\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.messages import SystemMessage\n",
-    "from langchain.schema.language_model import BaseLanguageModel\n",
+    "from langchain_core.messages import SystemMessage\n",
+    "from langchain_core.language_models import BaseLanguageModel\n",
     "\n",
     "_EXTRACTION_TEMPLATE = \"\"\"Extract and save the relevant entities mentioned \\\n",
     "in the following passage together with their properties.\n",

diff --git a/cookbook/multi_modal_QA.ipynb b/cookbook/multi_modal_QA.ipynb
@@ -92,7 +92,7 @@
    "outputs": [],
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.schema.messages import HumanMessage, SystemMessage"
+    "from langchain_core.messages import HumanMessage, SystemMessage"
    ]
   },
   {

diff --git a/cookbook/multi_modal_RAG_chroma.ipynb b/cookbook/multi_modal_RAG_chroma.ipynb
@@ -316,9 +316,9 @@
     "from operator import itemgetter\n",
     "\n",
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.schema.messages import HumanMessage, SystemMessage\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
+    "from langchain_core.messages import HumanMessage, SystemMessage\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
     "\n",
     "\n",
     "def prompt_func(data_dict):\n",

diff --git a/cookbook/openai_v1_cookbook.ipynb b/cookbook/openai_v1_cookbook.ipynb
@@ -29,7 +29,7 @@
    "outputs": [],
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.schema.messages import HumanMessage, SystemMessage"
+    "from langchain_core.messages import HumanMessage, SystemMessage"
    ]
   },
   {
@@ -252,7 +252,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.schema.agent import AgentFinish\n",
+    "from langchain_core.agents import AgentFinish\n",
     "\n",
     "\n",
     "def execute_agent(agent, tools, input):\n",
@@ -457,8 +457,8 @@
     "\n",
     "from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.pydantic_v1 import BaseModel, Field\n",
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
+    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
     "\n",
     "\n",
     "class GetCurrentWeather(BaseModel):\n",

diff --git a/cookbook/plan_and_execute_agent.ipynb b/cookbook/plan_and_execute_agent.ipynb
@@ -29,11 +29,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.agents.tools import Tool\n",
     "from langchain.chains import LLMMathChain\n",
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.llms import OpenAI\n",
     "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
+    "from langchain_core.tools import Tool\n",
     "from langchain_experimental.plan_and_execute import (\n",
     "    PlanAndExecute,\n",
     "    load_agent_executor,\n",

diff --git a/cookbook/rag_fusion.ipynb b/cookbook/rag_fusion.ipynb
@@ -87,7 +87,7 @@
    "outputs": [],
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.schema.output_parser import StrOutputParser"
+    "from langchain_core.output_parsers import StrOutputParser"
    ]
   },
   {

diff --git a/cookbook/retrieval_in_sql.ipynb b/cookbook/retrieval_in_sql.ipynb
@@ -268,8 +268,8 @@
    "outputs": [],
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
     "\n",
     "db = SQLDatabase.from_uri(\n",
     "    CONNECTION_STRING\n",
@@ -324,7 +324,7 @@
    "source": [
     "import re\n",
     "\n",
-    "from langchain.schema.runnable import RunnableLambda\n",
+    "from langchain_core.runnables import RunnableLambda\n",
     "\n",
     "\n",
     "def replace_brackets(match):\n",

diff --git a/cookbook/rewrite.ipynb b/cookbook/rewrite.ipynb
@@ -33,9 +33,9 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnablePassthrough\n",
-    "from langchain.utilities import DuckDuckGoSearchAPIWrapper"
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnablePassthrough"
    ]
   },
   {

diff --git a/cookbook/selecting_llms_based_on_context_length.ipynb b/cookbook/selecting_llms_based_on_context_length.ipynb
@@ -19,8 +19,8 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.prompt import PromptValue"
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.prompt_values import PromptValue"
    ]
   },
   {

diff --git a/cookbook/stepback-qa.ipynb b/cookbook/stepback-qa.ipynb
@@ -25,8 +25,8 @@
    "source": [
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnableLambda"
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnableLambda"
    ]
   },
   {

diff --git a/docs/docs/expression_language/cookbook/code_writing.ipynb b/docs/docs/expression_language/cookbook/code_writing.ipynb
@@ -21,7 +21,7 @@
     "from langchain.prompts import (\n",
     "    ChatPromptTemplate,\n",
     ")\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
     "from langchain_experimental.utilities import PythonREPL"
    ]
   },

diff --git a/docs/docs/expression_language/cookbook/embedding_router.ipynb b/docs/docs/expression_language/cookbook/embedding_router.ipynb
@@ -22,9 +22,9 @@
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain.schema.output_parser import StrOutputParser\n",
-    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
     "from langchain.utils.math import cosine_similarity\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
     "\n",
     "physics_template = \"\"\"You are a very smart physics professor. \\\n",
     "You are great at answering questions about physics in a concise and easy to understand manner. \\\n",