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docs: import update (#20610)

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Updated imports
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Leonid Ganeline 2024-04-18 13:05:17 -07:00 committed by GitHub
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88 changed files with 115 additions and 115 deletions
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2
docs/docs/expression_language/how_to/inspect.ipynb
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@ -29,9 +29,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings"
]

2
docs/docs/integrations/callbacks/argilla.ipynb
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@ -278,8 +278,8 @@
],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.callbacks.stdout import StdOutCallbackHandler\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"argilla_callback = ArgillaCallbackHandler(\n",

4
docs/docs/integrations/callbacks/context.ipynb
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@ -170,8 +170,8 @@
"import os\n",
"\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain.prompts.chat import (\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
")\n",

2
docs/docs/integrations/callbacks/sagemaker_tracking.ipynb
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@ -91,7 +91,7 @@
"source": [
"from langchain.agents import initialize_agent, load_tools\n",
"from langchain.chains import LLMChain, SimpleSequentialChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"from sagemaker.analytics import ExperimentAnalytics\n",
"from sagemaker.experiments.run import Run\n",

8
docs/docs/integrations/chat/jinachat.ipynb
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@ -19,13 +19,13 @@
},
"outputs": [],
"source": [
"from langchain.prompts.chat import (\n",
"from langchain_community.chat_models import JinaChat\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain_community.chat_models import JinaChat\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
")"
]
},
{

4
docs/docs/integrations/chat/llama2_chat.ipynb
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@ -49,12 +49,12 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts.chat import (\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" MessagesPlaceholder,\n",
")\n",
"from langchain_core.messages import SystemMessage\n",
"\n",
"template_messages = [\n",
" SystemMessage(content=\"You are a helpful assistant.\"),\n",

4
docs/docs/integrations/chat/vllm.ipynb
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@ -31,12 +31,12 @@
},
"outputs": [],
"source": [
"from langchain.prompts.chat import (\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/integrations/chat/yuan2.ipynb
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@ -348,7 +348,7 @@
"outputs": [],
"source": [
"async def ainvoke_with_prompt_template():\n",
" from langchain.prompts.chat import (\n",
" from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" )\n",
"\n",

2
docs/docs/integrations/chat_loaders/facebook.ipynb
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@ -258,7 +258,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.adapters.openai import convert_messages_for_finetuning"
"from langchain_community.adapters.openai import convert_messages_for_finetuning"
]
},
{

2
docs/docs/integrations/chat_loaders/imessage.ipynb
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@ -173,7 +173,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.adapters.openai import convert_messages_for_finetuning"
"from langchain_community.adapters.openai import convert_messages_for_finetuning"
]
},
{

2
docs/docs/integrations/chat_loaders/langsmith_dataset.ipynb
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@ -150,7 +150,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.adapters.openai import convert_messages_for_finetuning\n",
"from langchain_community.adapters.openai import convert_messages_for_finetuning\n",
"\n",
"training_data = convert_messages_for_finetuning(chat_sessions)"
]

2
docs/docs/integrations/chat_loaders/langsmith_llm_runs.ipynb
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@ -285,7 +285,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.adapters.openai import convert_messages_for_finetuning\n",
"from langchain_community.adapters.openai import convert_messages_for_finetuning\n",
"\n",
"training_data = convert_messages_for_finetuning(chat_sessions)"
]

2
docs/docs/integrations/chat_loaders/twitter.ipynb
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@ -21,7 +21,7 @@
"source": [
"import json\n",
"\n",
"from langchain.adapters.openai import convert_message_to_dict\n",
"from langchain_community.adapters.openai import convert_message_to_dict\n",
"from langchain_core.messages import AIMessage"
]
},

2
docs/docs/integrations/document_loaders/airbyte_cdk.ipynb
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@ -166,7 +166,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_gong.ipynb
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@ -149,7 +149,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_hubspot.ipynb
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@ -151,7 +151,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_salesforce.ipynb
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@ -156,7 +156,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_shopify.ipynb
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@ -152,7 +152,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_stripe.ipynb
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@ -149,7 +149,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_typeform.ipynb
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@ -152,7 +152,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/airbyte_zendesk_support.ipynb
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@ -153,7 +153,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def handle_record(record, id):\n",

2
docs/docs/integrations/document_loaders/apify_dataset.ipynb
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@ -100,8 +100,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain.indexes import VectorstoreIndexCreator\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import ApifyDatasetLoader"
]
},

2
docs/docs/integrations/document_loaders/copypaste.ipynb
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@ -17,7 +17,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document"
"from langchain_community.docstore.document import Document"
]
},
{

4
docs/docs/integrations/document_loaders/figma.ipynb
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@ -24,12 +24,12 @@
"import os\n",
"\n",
"from langchain.indexes import VectorstoreIndexCreator\n",
"from langchain.prompts.chat import (\n",
"from langchain_community.document_loaders.figma import FigmaFileLoader\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain_community.document_loaders.figma import FigmaFileLoader\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/integrations/document_loaders/google_drive.ipynb
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@ -431,7 +431,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"loader = GoogleDriveLoader(\n",
" folder_id=folder_id,\n",

2
docs/docs/integrations/llms/huggingface_endpoint.ipynb
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@ -93,7 +93,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate"
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/integrations/llms/llm_caching.ipynb
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@ -1633,7 +1633,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"docs = [Document(page_content=t) for t in texts[:3]]\n",
"from langchain.chains.summarize import load_summarize_chain"

2
docs/docs/integrations/llms/sagemaker.ipynb
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@ -58,7 +58,7 @@
},
"outputs": [],
"source": [
"from langchain.docstore.document import Document"
"from langchain_community.docstore.document import Document"
]
},
{

4
docs/docs/integrations/llms/titan_takeoff.ipynb
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@ -31,10 +31,10 @@
"\n",
"from langchain.callbacks.manager import CallbackManager\n",
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"from langchain.prompts import PromptTemplate\n",
"\n",
"# Note importing TitanTakeoffPro instead of TitanTakeoff will work as well both use same object under the hood\n",
"from langchain_community.llms import TitanTakeoff"
"from langchain_community.llms import TitanTakeoff\n",
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/integrations/memory/motorhead_memory.ipynb
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@ -36,7 +36,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"template = \"\"\"You are a chatbot having a conversation with a human.\n",

2
docs/docs/integrations/providers/aim_tracking.ipynb
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@ -174,7 +174,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate"
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/integrations/providers/cohere.mdx
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@ -51,7 +51,7 @@ Usage of the Cohere (legacy) [LLM model](/docs/integrations/llms/cohere)
```python
from langchain_community.tools.tavily_search import TavilySearchResults
from langchain_cohere import ChatCohere, create_cohere_react_agent
from langchain.prompts import ChatPromptTemplate
from langchain_core.prompts import ChatPromptTemplate
from langchain.agents import AgentExecutor
llm = ChatCohere()

4
docs/docs/integrations/providers/comet_tracking.ipynb
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@ -154,7 +154,7 @@
"source": [
"from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"comet_callback = CometCallbackHandler(\n",
@ -251,7 +251,7 @@
"source": [
"from langchain.callbacks import CometCallbackHandler, StdOutCallbackHandler\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"from rouge_score import rouge_scorer\n",
"\n",

2
docs/docs/integrations/providers/flyte.mdx
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@ -29,7 +29,7 @@ from langchain.agents import AgentType, initialize_agent, load_tools
from langchain.callbacks import FlyteCallbackHandler
from langchain.chains import LLMChain
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
from langchain_core.messages import HumanMessage
```

2
docs/docs/integrations/providers/javelin_ai_gateway.mdx
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@ -31,7 +31,7 @@ export JAVELIN_API_KEY=...
from langchain.chains import LLMChain
from langchain_community.llms import JavelinAIGateway
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
route_completions = "eng_dept03"

2
docs/docs/integrations/providers/mlflow_ai_gateway.mdx
View File

@ -140,7 +140,7 @@ Please contact a Databricks representative to enroll in the preview.
```python
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
from langchain_community.llms import MlflowAIGateway
gateway = MlflowAIGateway(

2
docs/docs/integrations/providers/mlflow_tracking.ipynb
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@ -123,7 +123,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate"
"from langchain_core.prompts import PromptTemplate"
]
},
{

4
docs/docs/integrations/providers/predictionguard.mdx
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@ -37,7 +37,7 @@ import os
import predictionguard as pg
from langchain_community.llms import PredictionGuard
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
from langchain.chains import LLMChain
# Your Prediction Guard API key. Get one at predictionguard.com
@ -77,7 +77,7 @@ Basic LLM Chaining with the Prediction Guard wrapper:
```python
import os
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain_community.llms import PredictionGuard

2
docs/docs/integrations/providers/ray_serve.ipynb
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@ -108,7 +108,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI"
]
},

2
docs/docs/integrations/providers/rebuff.ipynb
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@ -104,7 +104,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"# Set up the LangChain SDK with the environment variable\n",

2
docs/docs/integrations/providers/shaleprotocol.md
View File

@ -20,7 +20,7 @@ As of June 2023, the API supports Vicuna-13B by default. We are going to support
For example
```python
from langchain_openai import OpenAI
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
from langchain.chains import LLMChain
import os

2
docs/docs/integrations/providers/wandb_tracking.ipynb
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@ -382,7 +382,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate"
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/integrations/retrievers/chatgpt-plugin.ipynb
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@ -45,7 +45,7 @@
"import json\n",
"from typing import List\n",
"\n",
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"\n",
"def write_json(path: str, documents: List[Document]) -> None:\n",

2
docs/docs/integrations/retrievers/google_drive.ipynb
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@ -171,7 +171,7 @@
},
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"retriever = GoogleDriveRetriever(\n",
" template=PromptTemplate(\n",

2
docs/docs/integrations/retrievers/re_phrase.ipynb
View File

@ -141,7 +141,7 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"QUERY_PROMPT = PromptTemplate(\n",
" input_variables=[\"question\"],\n",

4
docs/docs/integrations/text_embedding/clarifai.ipynb
View File

@ -74,8 +74,8 @@
"source": [
"# Import the required modules\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.embeddings import ClarifaiEmbeddings"
"from langchain_community.embeddings import ClarifaiEmbeddings\n",
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/integrations/tools/dalle_image_generator.ipynb
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@ -52,8 +52,8 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.utilities.dalle_image_generator import DallEAPIWrapper\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0.9)\n",

2
docs/docs/integrations/tools/reddit_search.ipynb
View File

@ -172,9 +172,9 @@
"from langchain.agents import AgentExecutor, StructuredChatAgent, Tool\n",
"from langchain.chains import LLMChain\n",
"from langchain.memory import ConversationBufferMemory, ReadOnlySharedMemory\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.tools.reddit_search.tool import RedditSearchRun\n",
"from langchain_community.utilities.reddit_search import RedditSearchAPIWrapper\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Provide keys for Reddit\n",

2
docs/docs/integrations/tools/zapier.ipynb
View File

@ -161,9 +161,9 @@
"outputs": [],
"source": [
"from langchain.chains import LLMChain, SimpleSequentialChain, TransformChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.tools.zapier.tool import ZapierNLARunAction\n",
"from langchain_community.utilities.zapier import ZapierNLAWrapper\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI"
]
},

4
docs/docs/integrations/vectorstores/annoy.ipynb
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@ -497,8 +497,8 @@
"import uuid\n",
"\n",
"from annoy import AnnoyIndex\n",
"from langchain.docstore.document import Document\n",
"from langchain.docstore.in_memory import InMemoryDocstore\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.docstore.in_memory import InMemoryDocstore\n",
"\n",
"metadatas = [{\"x\": \"food\"}, {\"x\": \"food\"}, {\"x\": \"stuff\"}, {\"x\": \"animal\"}]\n",
"\n",

2
docs/docs/integrations/vectorstores/kinetica.ipynb
View File

@ -113,7 +113,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.vectorstores import (\n",
" DistanceStrategy,\n",

2
docs/docs/integrations/vectorstores/milvus.ipynb
View File

@ -340,7 +340,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"\n",
"# Insert data sample\n",
"docs = [\n",

2
docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
View File

@ -365,7 +365,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"prompt_template = \"\"\"Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n",
"\n",

2
docs/docs/integrations/vectorstores/neo4jvector.ipynb
View File

@ -72,7 +72,7 @@
},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.vectorstores import Neo4jVector\n",
"from langchain_openai import OpenAIEmbeddings\n",

2
docs/docs/integrations/vectorstores/pgembedding.ipynb
View File

@ -81,7 +81,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.vectorstores import PGEmbedding\n",
"from langchain_openai import OpenAIEmbeddings\n",

2
docs/docs/integrations/vectorstores/pgvecto_rs.ipynb
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@ -26,7 +26,7 @@
"source": [
"from typing import List\n",
"\n",
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.embeddings.fake import FakeEmbeddings\n",
"from langchain_community.vectorstores.pgvecto_rs import PGVecto_rs\n",

2
docs/docs/integrations/vectorstores/sap_hanavector.ipynb
View File

@ -109,7 +109,7 @@
},
"outputs": [],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.vectorstores.hanavector import HanaDB\n",
"from langchain_openai import OpenAIEmbeddings\n",

2
docs/docs/integrations/vectorstores/timescalevector.ipynb
View File

@ -122,7 +122,7 @@
"source": [
"from datetime import datetime, timedelta\n",
"\n",
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.document_loaders.json_loader import JSONLoader\n",
"from langchain_community.vectorstores.timescalevector import TimescaleVector\n",

4
docs/docs/integrations/vectorstores/yellowbrick.ipynb
View File

@ -98,7 +98,7 @@
"import psycopg2\n",
"from IPython.display import Markdown, display\n",
"from langchain.chains import LLMChain, RetrievalQAWithSourcesChain\n",
"from langchain.docstore.document import Document\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.vectorstores import Yellowbrick\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
"from langchain_text_splitters import RecursiveCharacterTextSplitter\n",
@ -115,7 +115,7 @@
"# API Key for OpenAI. Signup at https://platform.openai.com\n",
"os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY\n",
"\n",
"from langchain.prompts.chat import (\n",
"from langchain_core.prompts.chat import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",

2
docs/docs/modules/agents/how_to/custom_agent.ipynb
View File

@ -302,7 +302,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import MessagesPlaceholder\n",
"from langchain_core.prompts import MessagesPlaceholder\n",
"\n",
"MEMORY_KEY = \"chat_history\"\n",
"prompt = ChatPromptTemplate.from_messages(\n",

2
docs/docs/modules/agents/how_to/streaming.ipynb
View File

@ -40,9 +40,9 @@
"source": [
"from langchain import hub\n",
"from langchain.agents import AgentExecutor, create_openai_tools_agent\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.tools import tool\n",
"from langchain_core.callbacks import Callbacks\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/modules/data_connection/document_loaders/pdf.mdx
View File

@ -298,7 +298,7 @@ snippets.append((cur_text,cur_fs))
```python
from langchain.docstore.document import Document
from langchain_community.docstore.document import Document
cur_idx = -1
semantic_snippets = []
# Assumption: headings have higher font size than their respective content

2
docs/docs/modules/data_connection/retrievers/long_context_reorder.ipynb
View File

@ -52,12 +52,12 @@
],
"source": [
"from langchain.chains import LLMChain, StuffDocumentsChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_chroma import Chroma\n",
"from langchain_community.document_transformers import (\n",
" LongContextReorder,\n",
")\n",
"from langchain_community.embeddings import HuggingFaceEmbeddings\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI\n",
"\n",
"# Get embeddings.\n",

4
docs/docs/modules/memory/adding_memory.ipynb
View File

@ -176,12 +176,12 @@
},
"outputs": [],
"source": [
"from langchain.prompts import (\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_core.prompts import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" MessagesPlaceholder,\n",
")\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

4
docs/docs/modules/memory/conversational_customization.ipynb
View File

@ -135,7 +135,7 @@
"outputs": [],
"source": [
"# Now we can override it and set it to \"AI Assistant\"\n",
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"template = \"\"\"The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\n",
"\n",
@ -250,7 +250,7 @@
"outputs": [],
"source": [
"# Now we can override it and set it to \"Friend\"\n",
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"template = \"\"\"The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\n",
"\n",

2
docs/docs/modules/memory/custom_memory.ipynb
View File

@ -131,7 +131,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"template = \"\"\"The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know. You are provided with information about entities the Human mentions, if relevant.\n",
"\n",

2
docs/docs/modules/memory/index.mdx
View File

@ -201,7 +201,7 @@ conversation({"question": "hi"})
```python
from langchain_openai import ChatOpenAI
from langchain.prompts import (
from langchain_core.prompts import (
ChatPromptTemplate,
MessagesPlaceholder,
SystemMessagePromptTemplate,

2
docs/docs/modules/memory/types/kg.ipynb
View File

@ -181,7 +181,7 @@
"source": [
"llm = OpenAI(temperature=0)\n",
"from langchain.chains import ConversationChain\n",
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"template = \"\"\"The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. \n",
"If the AI does not know the answer to a question, it truthfully says it does not know. The AI ONLY uses information contained in the \"Relevant Information\" section and does not hallucinate.\n",

2
docs/docs/modules/memory/types/vectorstore_retriever_memory.mdx
View File

@ -23,7 +23,7 @@ Depending on the store you choose, this step may look different. Consult the rel
```python
import faiss
from langchain.docstore import InMemoryDocstore
from langchain_community.docstore import InMemoryDocstore
from langchain_community.vectorstores import FAISS

4
docs/docs/modules/model_io/index.mdx
View File

@ -209,7 +209,7 @@ They bundle up all the logic for going from user input into a fully formatted pr
This can start off very simple - for example, a prompt to produce the above string would just be:
```python
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
prompt = PromptTemplate.from_template("What is a good name for a company that makes {product}?")
prompt.format(product="colorful socks")
@ -231,7 +231,7 @@ Each `ChatMessageTemplate` contains instructions for how to format that `ChatMes
Let's take a look at this below:
```python
from langchain.prompts.chat import ChatPromptTemplate
from langchain_core.prompts.chat import ChatPromptTemplate
template = "You are a helpful assistant that translates {input_language} to {output_language}."
human_template = "{text}"

2
docs/docs/modules/model_io/output_parsers/quick_start.ipynb
View File

@ -51,7 +51,7 @@
],
"source": [
"from langchain.output_parsers import PydanticOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel, Field, validator\n",
"from langchain_openai import OpenAI\n",
"\n",

2
docs/docs/modules/model_io/output_parsers/types/csv.ipynb
View File

@ -18,7 +18,7 @@
"outputs": [],
"source": [
"from langchain.output_parsers import CommaSeparatedListOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"output_parser = CommaSeparatedListOutputParser()\n",

2
docs/docs/modules/model_io/output_parsers/types/datetime.ipynb
View File

@ -18,7 +18,7 @@
"outputs": [],
"source": [
"from langchain.output_parsers import DatetimeOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import OpenAI"
]
},

2
docs/docs/modules/model_io/output_parsers/types/json.ipynb
View File

@ -22,8 +22,8 @@
"source": [
"from typing import List\n",
"\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.output_parsers import JsonOutputParser\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel, Field\n",
"from langchain_openai import ChatOpenAI"
]

2
docs/docs/modules/model_io/output_parsers/types/pandas_dataframe.ipynb
View File

@ -24,7 +24,7 @@
"\n",
"import pandas as pd\n",
"from langchain.output_parsers import PandasDataFrameOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/modules/model_io/output_parsers/types/pydantic.ipynb
View File

@ -23,7 +23,7 @@
"from typing import List\n",
"\n",
"from langchain.output_parsers import PydanticOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel, Field, validator\n",
"from langchain_openai import ChatOpenAI"
]

2
docs/docs/modules/model_io/output_parsers/types/retry.ipynb
View File

@ -21,7 +21,7 @@
" OutputFixingParser,\n",
" PydanticOutputParser,\n",
")\n",
"from langchain.prompts import (\n",
"from langchain_core.prompts import (\n",
" PromptTemplate,\n",
")\n",
"from langchain_core.pydantic_v1 import BaseModel, Field\n",

2
docs/docs/modules/model_io/output_parsers/types/structured.ipynb
View File

@ -18,7 +18,7 @@
"outputs": [],
"source": [
"from langchain.output_parsers import ResponseSchema, StructuredOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},

4
docs/docs/modules/model_io/output_parsers/types/xml.ipynb
View File

@ -21,8 +21,8 @@
"outputs": [],
"source": [
"from langchain.output_parsers import XMLOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatAnthropic"
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_core.prompts import PromptTemplate"
]
},
{

2
docs/docs/modules/model_io/output_parsers/types/yaml.ipynb
View File

@ -23,7 +23,7 @@
"from typing import List\n",
"\n",
"from langchain.output_parsers import YamlOutputParser\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel, Field\n",
"from langchain_openai import ChatOpenAI"
]

6
docs/docs/modules/model_io/prompts/composition.ipynb
View File

@ -37,7 +37,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate"
"from langchain_core.prompts import PromptTemplate"
]
},
{
@ -339,8 +339,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts.pipeline import PipelinePromptTemplate\n",
"from langchain.prompts.prompt import PromptTemplate"
"from langchain_core.prompts.pipeline import PipelinePromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate"
]
},
{

6
docs/docs/modules/model_io/prompts/few_shot_examples.ipynb
View File

@ -38,8 +38,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts.few_shot import FewShotPromptTemplate\n",
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_core.prompts.few_shot import FewShotPromptTemplate\n",
"from langchain_core.prompts.prompt import PromptTemplate\n",
"\n",
"examples = [\n",
" {\n",
@ -253,8 +253,8 @@
}
],
"source": [
"from langchain.prompts.example_selector import SemanticSimilarityExampleSelector\n",
"from langchain_chroma import Chroma\n",
"from langchain_core.prompts.example_selector import SemanticSimilarityExampleSelector\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"example_selector = SemanticSimilarityExampleSelector.from_examples(\n",

6
docs/docs/modules/model_io/prompts/few_shot_examples_chat.ipynb
View File

@ -52,7 +52,7 @@
},
"outputs": [],
"source": [
"from langchain.prompts import (\n",
"from langchain_core.prompts import (\n",
" ChatPromptTemplate,\n",
" FewShotChatMessagePromptTemplate,\n",
")"
@ -201,8 +201,8 @@
},
"outputs": [],
"source": [
"from langchain.prompts import SemanticSimilarityExampleSelector\n",
"from langchain_chroma import Chroma\n",
"from langchain_core.prompts import SemanticSimilarityExampleSelector\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
@ -298,7 +298,7 @@
},
"outputs": [],
"source": [
"from langchain.prompts import (\n",
"from langchain_core.prompts import (\n",
" ChatPromptTemplate,\n",
" FewShotChatMessagePromptTemplate,\n",
")\n",

2
docs/docs/modules/model_io/prompts/partial.ipynb
View File

@ -45,7 +45,7 @@
}
],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"prompt = PromptTemplate.from_template(\"{foo}{bar}\")\n",
"partial_prompt = prompt.partial(foo=\"foo\")\n",

10
docs/docs/modules/model_io/prompts/quick_start.ipynb
View File

@ -56,7 +56,7 @@
}
],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"prompt_template = PromptTemplate.from_template(\n",
" \"Tell me a {adjective} joke about {content}.\"\n",
@ -90,7 +90,7 @@
}
],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_core.prompts import PromptTemplate\n",
"\n",
"prompt_template = PromptTemplate.from_template(\"Tell me a joke\")\n",
"prompt_template.format()"
@ -201,8 +201,8 @@
}
],
"source": [
"from langchain.prompts import HumanMessagePromptTemplate\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_core.prompts import HumanMessagePromptTemplate\n",
"\n",
"chat_template = ChatPromptTemplate.from_messages(\n",
" [\n",
@ -263,7 +263,7 @@
}
],
"source": [
"from langchain.prompts import ChatMessagePromptTemplate\n",
"from langchain_core.prompts import ChatMessagePromptTemplate\n",
"\n",
"prompt = \"May the {subject} be with you\"\n",
"\n",
@ -290,7 +290,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import (\n",
"from langchain_core.prompts import (\n",
" ChatPromptTemplate,\n",
" HumanMessagePromptTemplate,\n",
" MessagesPlaceholder,\n",

2
docs/docs/modules/model_io/quick_start.mdx
View File

@ -161,7 +161,7 @@ They bundle up all the logic for going from user input into a fully formatted pr
This can start off very simple - for example, a prompt to produce the above string would just be:
```python
from langchain.prompts import PromptTemplate
from langchain_core.prompts import PromptTemplate
prompt = PromptTemplate.from_template("What is a good name for a company that makes {product}?")
prompt.format(product="colorful socks")

2
docs/docs/use_cases/data_generation.ipynb
View File

@ -64,7 +64,7 @@
"# import dotenv\n",
"# dotenv.load_dotenv()\n",
"\n",
"from langchain.prompts import FewShotPromptTemplate, PromptTemplate\n",
"from langchain_core.prompts import FewShotPromptTemplate, PromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel\n",
"from langchain_experimental.tabular_synthetic_data.openai import (\n",
" OPENAI_TEMPLATE,\n",

2
docs/docs/use_cases/web_scraping.ipynb
View File

@ -628,8 +628,8 @@
}
],
"source": [
"from langchain.docstore.document import Document\n",
"from langchain.indexes import VectorstoreIndexCreator\n",
"from langchain_community.docstore.document import Document\n",
"from langchain_community.utilities import ApifyWrapper\n",
"\n",
"apify = ApifyWrapper()\n",