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docs, templates: update schema imports to core (#17885)

Browse Source 
- chat models, messages
- documents
- agentaction/finish
- baseretriever,document
- stroutputparser
- more messages
- basemessage
- format_document
- baseoutputparser

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
pull/17983/head^2
Erick Friis 3 months ago committed by GitHub
parent 971d29e718
commit ed789be8f4
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
148 changed files with 237 additions and 206 deletions
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2
cookbook/advanced_rag_eval.ipynb
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@ -520,7 +520,7 @@
"source": [
"import re\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"from langchain_core.runnables import RunnableLambda\n",
"\n",
"\n",

2
cookbook/apache_kafka_message_handling.ipynb
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@ -167,7 +167,7 @@
"from langchain.llms import LlamaCpp\n",
"from langchain.memory import ConversationTokenBufferMemory\n",
"from langchain.prompts import PromptTemplate, load_prompt\n",
"from langchain.schema import SystemMessage\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_experimental.chat_models import Llama2Chat\n",
"from quixstreams import Application, State, message_key\n",
"\n",

4
cookbook/custom_agent_with_plugin_retrieval.ipynb
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@ -42,9 +42,9 @@
")\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.agent_toolkits import NLAToolkit\n",
"from langchain_community.tools.plugin import AIPlugin\n",
"from langchain_core.agents import AgentAction, AgentFinish\n",
"from langchain_openai import OpenAI"
]
},
@ -114,8 +114,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings"
]
},

4
cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb
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@ -67,9 +67,9 @@
")\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.agent_toolkits import NLAToolkit\n",
"from langchain_community.tools.plugin import AIPlugin\n",
"from langchain_core.agents import AgentAction, AgentFinish\n",
"from langchain_openai import OpenAI"
]
},
@ -138,8 +138,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings"
]
},

4
cookbook/custom_agent_with_tool_retrieval.ipynb
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@ -40,8 +40,8 @@
")\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.utilities import SerpAPIWrapper\n",
"from langchain_core.agents import AgentAction, AgentFinish\n",
"from langchain_openai import OpenAI"
]
},
@ -103,8 +103,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings"
]
},

2
cookbook/custom_multi_action_agent.ipynb
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@ -72,7 +72,7 @@
"source": [
"from typing import Any, List, Tuple, Union\n",
"\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_core.agents import AgentAction, AgentFinish\n",
"\n",
"\n",
"class FakeAgent(BaseMultiActionAgent):\n",

3
cookbook/forward_looking_retrieval_augmented_generation.ipynb
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@ -73,8 +73,9 @@
" AsyncCallbackManagerForRetrieverRun,\n",
" CallbackManagerForRetrieverRun,\n",
")\n",
"from langchain.schema import BaseRetriever, Document\n",
"from langchain_community.utilities import GoogleSerperAPIWrapper\n",
"from langchain_core.documents import Document\n",
"from langchain_core.retrievers import BaseRetriever\n",
"from langchain_openai import ChatOpenAI, OpenAI"
]
},

2
cookbook/openai_functions_retrieval_qa.ipynb
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@ -358,7 +358,7 @@
"\n",
"from langchain.chains.openai_functions import create_qa_with_structure_chain\n",
"from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from pydantic import BaseModel, Field"
]
},

2
cookbook/sales_agent_with_context.ipynb
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@ -51,10 +51,10 @@
"from langchain.chains.base import Chain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain.prompts.base import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain_community.llms import BaseLLM\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_core.agents import AgentAction, AgentFinish\n",
"from langchain_openai import ChatOpenAI, OpenAI, OpenAIEmbeddings\n",
"from pydantic import BaseModel, Field"
]

2
cookbook/wikibase_agent.ipynb
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@ -401,7 +401,7 @@
")\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish"
"from langchain_core.agents import AgentAction, AgentFinish"
]
},
{

2
docs/docs/expression_language/cookbook/multiple_chains.ipynb
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@ -47,7 +47,7 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.schema import StrOutputParser\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",

2
docs/docs/expression_language/cookbook/retrieval.ipynb
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@ -169,8 +169,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import format_document\n",
"from langchain_core.messages import AIMessage, HumanMessage, get_buffer_string\n",
"from langchain_core.prompts import format_document\n",
"from langchain_core.runnables import RunnableParallel"
]
},

2
docs/docs/expression_language/how_to/binding.ipynb
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@ -29,7 +29,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import StrOutputParser\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"

2
docs/docs/expression_language/streaming.ipynb
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@ -68,7 +68,7 @@
"source": [
"# Showing the example using anthropic, but you can use\n",
"# your favorite chat model!\n",
"from langchain.chat_models import ChatAnthropic\n",
"from langchain_community.chat_models import ChatAnthropic\n",
"\n",
"model = ChatAnthropic()\n",
"\n",

2
docs/docs/guides/evaluation/trajectory/custom.ipynb
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@ -35,7 +35,7 @@
"\n",
"from langchain.chains import LLMChain\n",
"from langchain.evaluation import AgentTrajectoryEvaluator\n",
"from langchain.schema import AgentAction\n",
"from langchain_core.agents import AgentAction\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",

4
docs/docs/guides/privacy/presidio_data_anonymization/qa_privacy_protection.ipynb
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@ -90,7 +90,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"\n",
"documents = [Document(page_content=document_content)]"
]
@ -879,7 +879,7 @@
"outputs": [],
"source": [
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain.schema import format_document\n",
"from langchain_core.prompts import format_document\n",
"\n",
"DEFAULT_DOCUMENT_PROMPT = PromptTemplate.from_template(template=\"{page_content}\")\n",
"\n",

2
docs/docs/integrations/callbacks/labelstudio.ipynb
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@ -242,7 +242,7 @@
"outputs": [],
"source": [
"from langchain.callbacks import LabelStudioCallbackHandler\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"chat_llm = ChatOpenAI(\n",

2
docs/docs/integrations/callbacks/llmonitor.md
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@ -53,7 +53,7 @@ Example:
```python
from langchain_openai import ChatOpenAI
from langchain.schema import SystemMessage, HumanMessage
from langchain_core.messages import SystemMessage, HumanMessage
from langchain.agents import OpenAIFunctionsAgent, AgentExecutor, tool
from langchain.callbacks import LLMonitorCallbackHandler

2
docs/docs/integrations/callbacks/trubrics.ipynb
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@ -267,7 +267,7 @@
"outputs": [],
"source": [
"from langchain.callbacks import TrubricsCallbackHandler\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/integrations/chat/anthropic_functions.ipynb
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@ -83,7 +83,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage"
"from langchain_core.messages import HumanMessage"
]
},
{

2
docs/docs/integrations/chat/anyscale.ipynb
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@ -109,7 +109,7 @@
"source": [
"import asyncio\n",
"\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(content=\"You are a helpful AI that shares everything you know.\"),\n",

2
docs/docs/integrations/chat/azure_chat_openai.ipynb
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@ -31,7 +31,7 @@
"source": [
"import os\n",
"\n",
"from langchain.schema import HumanMessage\n",
"from langchain_core.messages import HumanMessage\n",
"from langchain_openai import AzureChatOpenAI"
]
},

6
docs/docs/integrations/chat/azureml_chat_endpoint.ipynb
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@ -74,11 +74,11 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models.azureml_endpoint import (\n",
" AzureMLEndpointApiType,\n",
" LlamaChatContentFormatter,\n",
")"
")\n",
"from langchain_core.messages import HumanMessage"
]
},
{
@ -105,8 +105,8 @@
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models.azureml_endpoint import LlamaContentFormatter\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chat = AzureMLChatOnlineEndpoint(\n",
" endpoint_url=\"https://<your-endpoint>.<your_region>.inference.ml.azure.com/score\",\n",

4
docs/docs/integrations/chat/baichuan.ipynb
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@ -29,8 +29,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatBaichuan"
"from langchain_community.chat_models import ChatBaichuan\n",
"from langchain_core.messages import HumanMessage"
]
},
{

4
docs/docs/integrations/chat/bedrock.ipynb
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@ -47,8 +47,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import BedrockChat"
"from langchain_community.chat_models import BedrockChat\n",
"from langchain_core.messages import HumanMessage"
]
},
{

6
docs/docs/integrations/chat/deepinfra.ipynb
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@ -68,8 +68,8 @@
},
"outputs": [],
"source": [
"from langchain.chat_models import ChatDeepInfra\n",
"from langchain.schema import HumanMessage"
"from langchain_community.chat_models import ChatDeepInfra\n",
"from langchain_core.messages import HumanMessage"
]
},
{
@ -216,7 +216,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.11.4"
}
},
"nbformat": 4,

2
docs/docs/integrations/chat/ernie.ipynb
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@ -76,8 +76,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ErnieBotChat\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chat = ErnieBotChat(\n",
" ernie_client_id=\"YOUR_CLIENT_ID\", ernie_client_secret=\"YOUR_CLIENT_SECRET\"\n",

6
docs/docs/integrations/chat/everlyai.ipynb
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@ -73,8 +73,8 @@
}
],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatEverlyAI\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(content=\"You are a helpful AI that shares everything you know.\"),\n",
@ -127,8 +127,8 @@
],
"source": [
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatEverlyAI\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(content=\"You are a humorous AI that delights people.\"),\n",
@ -185,8 +185,8 @@
],
"source": [
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatEverlyAI\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(content=\"You are a humorous AI that delights people.\"),\n",

4
docs/docs/integrations/chat/fireworks.ipynb
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@ -37,8 +37,8 @@
"source": [
"import os\n",
"\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models.fireworks import ChatFireworks"
"from langchain_community.chat_models.fireworks import ChatFireworks\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
]
},
{

2
docs/docs/integrations/chat/gigachat.ipynb
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@ -75,7 +75,7 @@
}
],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(\n",

4
docs/docs/integrations/chat/gpt_router.ipynb
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@ -70,9 +70,9 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import GPTRouter\n",
"from langchain_community.chat_models.gpt_router import GPTRouterModel"
"from langchain_community.chat_models.gpt_router import GPTRouterModel\n",
"from langchain_core.messages import HumanMessage"
]
},
{

4
docs/docs/integrations/chat/jinachat.ipynb
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@ -24,8 +24,8 @@
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import JinaChat"
"from langchain_community.chat_models import JinaChat\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
]
},
{

4
docs/docs/integrations/chat/konko.ipynb
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@ -40,8 +40,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatKonko"
"from langchain_community.chat_models import ChatKonko\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
]
},
{

4
docs/docs/integrations/chat/litellm.ipynb
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@ -32,8 +32,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatLiteLLM"
"from langchain_community.chat_models import ChatLiteLLM\n",
"from langchain_core.messages import HumanMessage"
]
},
{

2
docs/docs/integrations/chat/litellm_router.ipynb
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@ -38,8 +38,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatLiteLLMRouter\n",
"from langchain_core.messages import HumanMessage\n",
"from litellm import Router"
]
},

2
docs/docs/integrations/chat/llama2_chat.ipynb
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@ -54,7 +54,7 @@
" HumanMessagePromptTemplate,\n",
" MessagesPlaceholder,\n",
")\n",
"from langchain.schema import SystemMessage\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/minimax.ipynb
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@ -39,8 +39,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import MiniMaxChat"
"from langchain_community.chat_models import MiniMaxChat\n",
"from langchain_core.messages import HumanMessage"
]
},
{

6
docs/docs/integrations/chat/ollama.ipynb
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@ -278,7 +278,7 @@
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"messages = [\n",
" HumanMessage(\n",
@ -313,8 +313,8 @@
"source": [
"import json\n",
"\n",
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatOllama\n",
"from langchain_core.messages import HumanMessage\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
@ -463,8 +463,8 @@
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatOllama\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"llm = ChatOllama(model=\"bakllava\", temperature=0)\n",
"\n",

2
docs/docs/integrations/chat/ollama_functions.ipynb
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@ -102,7 +102,7 @@
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"model.invoke(\"what is the weather in Boston?\")"
]

2
docs/docs/integrations/chat/openai.ipynb
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@ -34,7 +34,7 @@
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

4
docs/docs/integrations/chat/promptlayer_chatopenai.ipynb
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@ -62,8 +62,8 @@
"source": [
"import os\n",
"\n",
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import PromptLayerChatOpenAI"
"from langchain_community.chat_models import PromptLayerChatOpenAI\n",
"from langchain_core.messages import HumanMessage"
]
},
{

4
docs/docs/integrations/chat/sparkllm.ipynb
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@ -30,8 +30,8 @@
"outputs": [],
"source": [
"\"\"\"For basic init and call\"\"\"\n",
"from langchain.chat_models import ChatSparkLLM\n",
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatSparkLLM\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chat = ChatSparkLLM(\n",
" spark_app_id=\"<app_id>\", spark_api_key=\"<api_key>\", spark_api_secret=\"<api_secret>\"\n",

4
docs/docs/integrations/chat/tencent_hunyuan.ipynb
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@ -36,8 +36,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatHunyuan"
"from langchain_community.chat_models import ChatHunyuan\n",
"from langchain_core.messages import HumanMessage"
]
},
{

4
docs/docs/integrations/chat/tongyi.ipynb
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@ -100,8 +100,8 @@
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models.tongyi import ChatTongyi\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"chatLLM = ChatTongyi(\n",
" streaming=True,\n",
@ -128,7 +128,7 @@
}
],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(\n",

2
docs/docs/integrations/chat/vllm.ipynb
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@ -36,7 +36,7 @@
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

4
docs/docs/integrations/chat/volcengine_maas.ipynb
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@ -48,8 +48,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import VolcEngineMaasChat"
"from langchain_community.chat_models import VolcEngineMaasChat\n",
"from langchain_core.messages import HumanMessage"
]
},
{

4
docs/docs/integrations/chat/yandex.ipynb
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@ -58,8 +58,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatYandexGPT"
"from langchain_community.chat_models import ChatYandexGPT\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
]
},
{

2
docs/docs/integrations/chat_loaders/discord.ipynb
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@ -79,8 +79,8 @@
"import re\n",
"from typing import Iterator, List\n",
"\n",
"from langchain.schema import BaseMessage, HumanMessage\n",
"from langchain_community.chat_loaders import base as chat_loaders\n",
"from langchain_core.messages import BaseMessage, HumanMessage\n",
"\n",
"logger = logging.getLogger()\n",
"\n",

2
docs/docs/integrations/chat_loaders/twitter.ipynb
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@ -22,7 +22,7 @@
"import json\n",
"\n",
"from langchain.adapters.openai import convert_message_to_dict\n",
"from langchain.schema import AIMessage"
"from langchain_core.messages import AIMessage"
]
},
{

2
docs/docs/integrations/chat_loaders/wechat.ipynb
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@ -78,8 +78,8 @@
"import re\n",
"from typing import Iterator, List\n",
"\n",
"from langchain.schema import BaseMessage, HumanMessage\n",
"from langchain_community.chat_loaders import base as chat_loaders\n",
"from langchain_core.messages import BaseMessage, HumanMessage\n",
"\n",
"logger = logging.getLogger()\n",
"\n",

2
docs/docs/integrations/document_loaders/tensorflow_datasets.ipynb
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@ -198,8 +198,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.document_loaders import TensorflowDatasetLoader\n",
"from langchain_core.documents import Document\n",
"\n",
"loader = TensorflowDatasetLoader(\n",
" dataset_name=\"mlqa/en\",\n",

4
docs/docs/integrations/document_transformers/doctran_extract_properties.ipynb
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@ -32,8 +32,8 @@
"source": [
"import json\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_community.document_transformers import DoctranPropertyExtractor"
"from langchain_community.document_transformers import DoctranPropertyExtractor\n",
"from langchain_core.documents import Document"
]
},
{

4
docs/docs/integrations/document_transformers/doctran_interrogate_document.ipynb
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@ -30,8 +30,8 @@
"source": [
"import json\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_community.document_transformers import DoctranQATransformer"
"from langchain_community.document_transformers import DoctranQATransformer\n",
"from langchain_core.documents import Document"
]
},
{

4
docs/docs/integrations/document_transformers/doctran_translate_document.ipynb
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@ -28,8 +28,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.document_transformers import DoctranTextTranslator"
"from langchain_community.document_transformers import DoctranTextTranslator\n",
"from langchain_core.documents import Document"
]
},
{

4
docs/docs/integrations/document_transformers/google_translate.ipynb
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@ -31,8 +31,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.document_transformers import GoogleTranslateTransformer"
"from langchain_community.document_transformers import GoogleTranslateTransformer\n",
"from langchain_core.documents import Document"
]
},
{

2
docs/docs/integrations/document_transformers/openai_metadata_tagger.ipynb
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@ -21,10 +21,10 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.document_transformers.openai_functions import (\n",
" create_metadata_tagger,\n",
")\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import ChatOpenAI"
]
},

4
docs/docs/integrations/llms/azure_ml.ipynb
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@ -70,11 +70,11 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.llms.azureml_endpoint import (\n",
" AzureMLEndpointApiType,\n",
" LlamaContentFormatter,\n",
")\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"llm = AzureMLOnlineEndpoint(\n",
" endpoint_url=\"https://<your-endpoint>.<your_region>.inference.ml.azure.com/score\",\n",
@ -117,11 +117,11 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.llms.azureml_endpoint import (\n",
" AzureMLEndpointApiType,\n",
" LlamaContentFormatter,\n",
")\n",
"from langchain_core.messages import HumanMessage\n",
"\n",
"llm = AzureMLOnlineEndpoint(\n",
" endpoint_url=\"https://<your-endpoint>.<your_region>.inference.ml.azure.com/v1/completions\",\n",

2
docs/docs/integrations/llms/javelin.ipynb
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@ -180,8 +180,8 @@
}
],
"source": [
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_community.chat_models import ChatJavelinAIGateway\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"\n",
"messages = [\n",
" SystemMessage(\n",

2
docs/docs/integrations/memory/zep_memory.ipynb
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@ -52,8 +52,8 @@
"from langchain.agents import AgentType, Tool, initialize_agent\n",
"from langchain.memory import ZepMemory\n",
"from langchain.retrievers import ZepRetriever\n",
"from langchain.schema import AIMessage, HumanMessage\n",
"from langchain_community.utilities import WikipediaAPIWrapper\n",
"from langchain_core.messages import AIMessage, HumanMessage\n",
"from langchain_openai import OpenAI\n",
"\n",
"# Set this to your Zep server URL\n",

2
docs/docs/integrations/providers/arthur_tracking.ipynb
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@ -28,7 +28,7 @@
"source": [
"from langchain.callbacks import ArthurCallbackHandler\n",
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
"from langchain.schema import HumanMessage\n",
"from langchain_core.messages import HumanMessage\n",
"from langchain_openai import ChatOpenAI"
]
},

2
docs/docs/integrations/providers/cohere.mdx
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@ -27,7 +27,7 @@ Get a [Cohere api key](https://dashboard.cohere.ai/) and set it as an environmen
```python
from langchain_community.chat_models import ChatCohere
from langchain.schema import HumanMessage
from langchain_core.messages import HumanMessage
chat = ChatCohere()
messages = [HumanMessage(content="knock knock")]
print(chat(messages))

2
docs/docs/integrations/providers/flyte.mdx
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@ -30,7 +30,7 @@ from langchain.callbacks import FlyteCallbackHandler
from langchain.chains import LLMChain
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain.schema import HumanMessage
from langchain_core.messages import HumanMessage
```
Set up the necessary environment variables to utilize the OpenAI API and Serp API:

2
docs/docs/integrations/providers/javelin_ai_gateway.mdx
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@ -66,7 +66,7 @@ print(embeddings.embed_documents(["hello"]))
## Chat Example
```python
from langchain_community.chat_models import ChatJavelinAIGateway
from langchain.schema import HumanMessage, SystemMessage
from langchain_core.messages import HumanMessage, SystemMessage
messages = [
SystemMessage(

2
docs/docs/integrations/providers/konko.mdx
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@ -55,7 +55,7 @@ See a usage [example](/docs/integrations/chat/konko).
- **ChatCompletion with Mistral-7B:**
```python
from langchain.schema import HumanMessage
from langchain_core.messages import HumanMessage
from langchain_community.chat_models import ChatKonko
chat_instance = ChatKonko(max_tokens=10, model = 'mistralai/mistral-7b-instruct-v0.1')
msg = HumanMessage(content="Hi")

4
docs/docs/integrations/providers/log10.mdx
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@ -18,7 +18,7 @@ Integration with log10 is a simple one-line `log10_callback` integration as show
```python
from langchain_openai import ChatOpenAI
from langchain.schema import HumanMessage
from langchain_core.messages import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config
@ -43,7 +43,7 @@ llm = ChatOpenAI(model_name="gpt-3.5-turbo", callbacks=[log10_callback])
from langchain_openai import OpenAI
from langchain_community.chat_models import ChatAnthropic
from langchain_openai import ChatOpenAI
from langchain.schema import HumanMessage
from langchain_core.messages import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config

2
docs/docs/integrations/providers/mlflow.mdx
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@ -100,7 +100,7 @@ print(embeddings.embed_documents(["hello"]))
```python
from langchain_community.chat_models import ChatMlflow
from langchain.schema import HumanMessage, SystemMessage
from langchain_core.messages import HumanMessage, SystemMessage
chat = ChatMlflow(
target_uri="http://127.0.0.1:5000",

2
docs/docs/integrations/providers/mlflow_ai_gateway.mdx
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@ -113,7 +113,7 @@ print(embeddings.embed_documents(["hello"]))
```python
from langchain_community.chat_models import ChatMLflowAIGateway
from langchain.schema import HumanMessage, SystemMessage
from langchain_core.messages import HumanMessage, SystemMessage
chat = ChatMLflowAIGateway(
gateway_uri="http://127.0.0.1:5000",

2
docs/docs/integrations/retrievers/activeloop.ipynb
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@ -276,7 +276,7 @@
"from langchain.chains.openai_functions import (\n",
" create_structured_output_chain,\n",
")\n",
"from langchain.schema import HumanMessage, SystemMessage\n",
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_core.prompts import ChatPromptTemplate, HumanMessagePromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"from pydantic import BaseModel, Field"

2
docs/docs/integrations/retrievers/bm25.ipynb
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@ -81,7 +81,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"\n",
"retriever = BM25Retriever.from_documents(\n",
" [\n",

4
docs/docs/integrations/retrievers/fleet_context.ipynb
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@ -34,8 +34,8 @@
"\n",
"import pandas as pd\n",
"from langchain.retrievers import MultiVectorRetriever\n",
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.documents import Document\n",
"from langchain_core.stores import BaseStore\n",
"from langchain_core.vectorstores import VectorStore\n",
"from langchain_openai import OpenAIEmbeddings\n",
@ -194,7 +194,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import StrOutputParser\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\n",

2
docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb
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@ -83,8 +83,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import DeepLake\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/astradb.ipynb
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@ -84,8 +84,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain.vectorstores import AstraDB\n",
"from langchain_core.documents import Document\n",
"\n",
"docs = [\n",
" Document(\n",

2
docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb
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@ -87,8 +87,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/dashvector.ipynb
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@ -92,9 +92,9 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.embeddings import DashScopeEmbeddings\n",
"from langchain_community.vectorstores import DashVector\n",
"from langchain_core.documents import Document\n",
"\n",
"embeddings = DashScopeEmbeddings()\n",
"\n",

2
docs/docs/integrations/retrievers/self_query/elasticsearch_self_query.ipynb
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@ -60,8 +60,8 @@
"import getpass\n",
"import os\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import ElasticsearchStore\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",

2
docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb
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@ -67,8 +67,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Milvus\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb
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@ -57,8 +57,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import MongoDBAtlasVectorSearch\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"from pymongo import MongoClient\n",
"\n",

2
docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb
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@ -78,8 +78,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import MyScale\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb
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@ -59,8 +59,8 @@
"import getpass\n",
"import os\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import OpenSearchVectorSearch\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",

2
docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb
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@ -67,8 +67,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import PGVector\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"collection = \"Name of your collection\"\n",

3
docs/docs/integrations/retrievers/self_query/pinecone.ipynb
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@ -77,7 +77,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Pinecone\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"from langchain_pinecone import PineconeVectorStore\n",
"\n",

2
docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb
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@ -70,8 +70,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Qdrant\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb
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@ -67,8 +67,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Redis\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb
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@ -217,8 +217,8 @@
"source": [
"import os\n",
"\n",
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import SupabaseVectorStore\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"from supabase.client import Client, create_client\n",
"\n",

2
docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb
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@ -143,8 +143,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores.timescalevector import TimescaleVector\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb
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@ -89,11 +89,11 @@
"from langchain.chains import ConversationalRetrievalChain\n",
"from langchain.chains.query_constructor.base import AttributeInfo\n",
"from langchain.retrievers.self_query.base import SelfQueryRetriever\n",
"from langchain.schema import Document\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.embeddings import FakeEmbeddings\n",
"from langchain_community.vectorstores import Vectara\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAI"
]
},

2
docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb
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@ -45,8 +45,8 @@
},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.vectorstores import Weaviate\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"

2
docs/docs/integrations/retrievers/tf_idf.ipynb
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@ -73,7 +73,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"\n",
"retriever = TFIDFRetriever.from_documents(\n",
" [\n",

2
docs/docs/integrations/retrievers/weaviate-hybrid.ipynb
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@ -74,7 +74,7 @@
],
"source": [
"from langchain.retrievers.weaviate_hybrid_search import WeaviateHybridSearchRetriever\n",
"from langchain.schema import Document"
"from langchain_core.documents import Document"
]
},
{

2
docs/docs/integrations/retrievers/zep_memorystore.ipynb
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@ -63,7 +63,7 @@
"from uuid import uuid4\n",
"\n",
"from langchain.memory import ZepMemory\n",
"from langchain.schema import AIMessage, HumanMessage\n",
"from langchain_core.messages import AIMessage, HumanMessage\n",
"\n",
"# Set this to your Zep server URL\n",
"ZEP_API_URL = \"http://localhost:8000\""

22
docs/docs/integrations/toolkits/cogniswitch.ipynb
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@ -8,13 +8,19 @@
"## Cogniswitch Tools\n",
"\n",
"**Use CogniSwitch to build production ready applications that can consume, organize and retrieve knowledge flawlessly. Using the framework of your choice, in this case Langchain CogniSwitch helps alleviate the stress of decision making when it comes to, choosing the right storage and retrieval formats. It also eradicates reliability issues and hallucinations when it comes to responses that are generated. Get started by interacting with your knowledge in just two simple steps.**\n",
"\n",
"visit [https://www.cogniswitch.ai/developer to register](https://www.cogniswitch.ai/developer?utm_source=langchain&utm_medium=langchainbuild&utm_id=dev).\n\n",
"**Registration:** \n\n",
"- Signup with your email and verify your registration \n\n",
"- You will get a mail with a platform token and oauth token for using the services.\n\n\n",
"\n",
"**step 1: Instantiate the toolkit and get the tools:**\n\n",
"visit [https://www.cogniswitch.ai/developer to register](https://www.cogniswitch.ai/developer?utm_source=langchain&utm_medium=langchainbuild&utm_id=dev).\n",
"\n",
"**Registration:** \n",
"\n",
"- Signup with your email and verify your registration \n",
"\n",
"- You will get a mail with a platform token and oauth token for using the services.\n",
"\n",
"\n",
"\n",
"**step 1: Instantiate the toolkit and get the tools:**\n",
"\n",
"- Instantiate the cogniswitch toolkit with the cogniswitch token, openAI API key and OAuth token and get the tools. \n",
"\n",
"**step 2: Instantiate the agent with the tools and llm:**\n",
@ -61,8 +67,8 @@
"import os\n",
"\n",
"from langchain.agents.agent_toolkits import create_conversational_retrieval_agent\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain_community.agent_toolkits import CogniswitchToolkit"
"from langchain_community.agent_toolkits import CogniswitchToolkit\n",
"from langchain_openai import ChatOpenAI"
]
},
{

2
docs/docs/integrations/toolkits/connery.ipynb
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@ -74,8 +74,8 @@
"import os\n",
"\n",
"from langchain.agents import AgentType, initialize_agent\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain_community.agent_toolkits.connery import ConneryToolkit\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.tools.connery import ConneryService\n",
"\n",
"# Specify your Connery Runner credentials.\n",

2
docs/docs/integrations/toolkits/robocorp.ipynb
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@ -131,8 +131,8 @@
],
"source": [
"from langchain.agents import AgentExecutor, OpenAIFunctionsAgent\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_openai import ChatOpenAI\n",
"from langchain_robocorp import ActionServerToolkit\n",
"\n",
"# Initialize LLM chat model\n",

2
docs/docs/integrations/tools/connery.ipynb
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@ -49,8 +49,8 @@
"import os\n",
"\n",
"from langchain.agents import AgentType, initialize_agent\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain_community.tools.connery import ConneryService\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Specify your Connery Runner credentials.\n",
"os.environ[\"CONNERY_RUNNER_URL\"] = \"\"\n",

4
docs/docs/integrations/tools/exa_search.ipynb
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@ -204,7 +204,7 @@
"outputs": [],
"source": [
"from langchain.agents import AgentExecutor, OpenAIFunctionsAgent\n",
"from langchain.schema import SystemMessage\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(temperature=0)\n",
@ -393,7 +393,7 @@
"outputs": [],
"source": [
"from langchain.agents import AgentExecutor, OpenAIFunctionsAgent\n",
"from langchain.schema import SystemMessage\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(temperature=0, model=\"gpt-4\")\n",

2
docs/docs/integrations/vectorstores/astradb.ipynb
Unescape Escape View File

@ -91,9 +91,9 @@
"from datasets import (\n",
" load_dataset,\n",
")\n",
"from langchain.schema import Document\n",
"from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
"from langchain_community.document_loaders import PyPDFLoader\n",
"from langchain_core.documents import Document\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",

2
docs/docs/integrations/vectorstores/cassandra.ipynb
Unescape Escape View File

@ -74,9 +74,9 @@
"from datasets import (\n",
" load_dataset,\n",
")\n",
"from langchain.schema import Document\n",
"from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
"from langchain_community.document_loaders import PyPDFLoader\n",
"from langchain_core.documents import Document\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",

2
docs/docs/integrations/vectorstores/faiss.ipynb
Unescape Escape View File

@ -437,7 +437,7 @@
}
],
"source": [
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"\n",
"list_of_documents = [\n",
" Document(page_content=\"foo\", metadata=dict(page=1)),\n",

2
docs/docs/integrations/vectorstores/faiss_async.ipynb
Unescape Escape View File

@ -288,7 +288,7 @@
}
],
"source": [
"from langchain.schema import Document\n",
"from langchain_core.documents import Document\n",
"\n",
"list_of_documents = [\n",
" Document(page_content=\"foo\", metadata=dict(page=1)),\n",

2
docs/docs/modules/callbacks/async_callbacks.ipynb
Unescape Escape View File

@ -62,7 +62,7 @@
"from typing import Any, Dict, List\n",
"\n",
"from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler\n",
"from langchain.schema import HumanMessage, LLMResult\n",
"from langchain_core.messages import HumanMessage, LLMResult\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",

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