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docs: langchain-openai (#15513)

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Updates docs and cookbooks to import ChatOpenAI, OpenAI, and OpenAI
Embeddings from `langchain_openai`

There are likely more

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Erick Friis 2024-01-06 15:54:48 -08:00 committed by GitHub
parent be612f408e
commit b1fa726377
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414 changed files with 808 additions and 834 deletions
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4
cookbook/LLaMA2_sql_chat.ipynb
View File

@ -149,7 +149,7 @@
],
"source": [
"# Prompt\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"# Update the template based on the type of SQL Database like MySQL, Microsoft SQL Server and so on\n",
"template = \"\"\"Based on the table schema below, write a SQL query that would answer the user's question:\n",
@ -278,7 +278,7 @@
"source": [
"# Prompt\n",
"from langchain.memory import ConversationBufferMemory\n",
"from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"\n",
"template = \"\"\"Given an input question, convert it to a SQL query. No pre-amble. Based on the table schema below, write a SQL query that would answer the user's question:\n",
"{schema}\n",

6
cookbook/Multi_modal_RAG.ipynb
View File

@ -198,9 +198,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",
"# Generate summaries of text elements\n",
@ -355,9 +355,9 @@
"\n",
"from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
"from langchain.storage import InMemoryStore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"\n",
"def create_multi_vector_retriever(\n",

8
cookbook/Semi_Structured_RAG.ipynb
View File

@ -235,9 +235,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -320,9 +320,9 @@
"\n",
"from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
"from langchain.storage import InMemoryStore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"# The vectorstore to use to index the child chunks\n",
"vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",

8
cookbook/Semi_structured_and_multi_modal_RAG.ipynb
View File

@ -211,9 +211,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -375,9 +375,9 @@
"\n",
"from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
"from langchain.storage import InMemoryStore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"# The vectorstore to use to index the child chunks\n",
"vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",

4
cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb
View File

@ -209,9 +209,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOllama\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate"
]
},
{

6
cookbook/advanced_rag_eval.ipynb
View File

@ -132,8 +132,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"baseline = Chroma.from_texts(\n",
" texts=all_splits_pypdf_texts,\n",
@ -160,9 +160,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Prompt\n",
"prompt_text = \"\"\"You are an assistant tasked with summarizing tables and text for retrieval. \\\n",

5
cookbook/agent_vectorstore.ipynb
View File

@ -29,9 +29,8 @@
"source": [
"from langchain.chains import RetrievalQA\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_openai import OpenAI, OpenAIEmbeddings\n",
"\n",
"llm = OpenAI(temperature=0)"
]
@ -161,7 +160,7 @@
"source": [
"# Import things that are needed generically\n",
"from langchain.agents import AgentType, Tool, initialize_agent\n",
"from langchain_community.llms import OpenAI"
"from langchain_openai import OpenAI"
]
},
{

2
cookbook/analyze_document.ipynb
View File

@ -29,7 +29,7 @@
"outputs": [],
"source": [
"from langchain.chains import AnalyzeDocumentChain\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)"
]

8
cookbook/autogpt/autogpt.ipynb
View File

@ -62,8 +62,8 @@
"outputs": [],
"source": [
"from langchain.docstore import InMemoryDocstore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS"
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
{
@ -100,8 +100,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_experimental.autonomous_agents import AutoGPT"
"from langchain_experimental.autonomous_agents import AutoGPT\n",
"from langchain_openai import ChatOpenAI"
]
},
{

4
cookbook/autogpt/marathon_times.ipynb
View File

@ -41,8 +41,8 @@
"import pandas as pd\n",
"from langchain.docstore.document import Document\n",
"from langchain_community.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_experimental.autonomous_agents import AutoGPT\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Needed synce jupyter runs an async eventloop\n",
"nest_asyncio.apply()"
@ -311,8 +311,8 @@
"# Memory\n",
"import faiss\n",
"from langchain.docstore import InMemoryDocstore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings_model = OpenAIEmbeddings()\n",
"embedding_size = 1536\n",

5
cookbook/baby_agi.ipynb
View File

@ -31,9 +31,8 @@
"source": [
"from typing import Optional\n",
"\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.autonomous_agents import BabyAGI"
"from langchain_experimental.autonomous_agents import BabyAGI\n",
"from langchain_openai import OpenAI, OpenAIEmbeddings"
]
},
{

7
cookbook/baby_agi_with_agent.ipynb
View File

@ -29,9 +29,8 @@
"\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.autonomous_agents import BabyAGI"
"from langchain_experimental.autonomous_agents import BabyAGI\n",
"from langchain_openai import OpenAI, OpenAIEmbeddings"
]
},
{
@ -108,8 +107,8 @@
"source": [
"from langchain.agents import AgentExecutor, Tool, ZeroShotAgent\n",
"from langchain.chains import LLMChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities import SerpAPIWrapper\n",
"from langchain_openai import OpenAI\n",
"\n",
"todo_prompt = PromptTemplate.from_template(\n",
" \"You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}\"\n",

2
cookbook/camel_role_playing.ipynb
View File

@ -46,7 +46,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/causal_program_aided_language_model.ipynb
View File

@ -47,9 +47,9 @@
"outputs": [],
"source": [
"from IPython.display import SVG\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.cpal.base import CPALChain\n",
"from langchain_experimental.pal_chain import PALChain\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0, max_tokens=512)\n",
"cpal_chain = CPALChain.from_univariate_prompt(llm=llm, verbose=True)\n",

4
cookbook/code-analysis-deeplake.ipynb
View File

@ -657,7 +657,7 @@
}
],
"source": [
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()\n",
"embeddings"
@ -834,7 +834,7 @@
"outputs": [],
"source": [
"from langchain.chains import ConversationalRetrievalChain\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI(\n",
" model_name=\"gpt-3.5-turbo-0613\"\n",

8
cookbook/custom_agent_with_plugin_retrieval.ipynb
View File

@ -44,8 +44,8 @@
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.agent_toolkits import NLAToolkit\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.tools.plugin import AIPlugin"
"from langchain_community.tools.plugin import AIPlugin\n",
"from langchain_openai import OpenAI"
]
},
{
@ -115,8 +115,8 @@
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS"
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
{

8
cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb
View File

@ -69,8 +69,8 @@
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.agent_toolkits import NLAToolkit\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.tools.plugin import AIPlugin"
"from langchain_community.tools.plugin import AIPlugin\n",
"from langchain_openai import OpenAI"
]
},
{
@ -139,8 +139,8 @@
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS"
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
{

8
cookbook/custom_agent_with_tool_retrieval.ipynb
View File

@ -41,8 +41,8 @@
"from langchain.chains import LLMChain\n",
"from langchain.prompts import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities import SerpAPIWrapper"
"from langchain_community.utilities import SerpAPIWrapper\n",
"from langchain_openai import OpenAI"
]
},
{
@ -104,8 +104,8 @@
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS"
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
{

2
cookbook/databricks_sql_db.ipynb
View File

@ -93,7 +93,7 @@
"outputs": [],
"source": [
"# Creating a OpenAI Chat LLM wrapper\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(temperature=0, model_name=\"gpt-4\")"
]

3
cookbook/deeplake_semantic_search_over_chat.ipynb
View File

@ -56,9 +56,8 @@
" CharacterTextSplitter,\n",
" RecursiveCharacterTextSplitter,\n",
")\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.vectorstores import DeepLake\n",
"from langchain_openai import OpenAI, OpenAIEmbeddings\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
"activeloop_token = getpass.getpass(\"Activeloop Token:\")\n",

6
cookbook/docugami_xml_kg_rag.ipynb
View File

@ -475,8 +475,8 @@
" HumanMessagePromptTemplate,\n",
" SystemMessagePromptTemplate,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -547,9 +547,9 @@
"\n",
"from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
"from langchain.storage import InMemoryStore\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores.chroma import Chroma\n",
"from langchain_core.documents import Document\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"\n",
"def build_retriever(text_elements, tables, table_summaries):\n",

2
cookbook/elasticsearch_db_qa.ipynb
View File

@ -39,7 +39,7 @@
"source": [
"from elasticsearch import Elasticsearch\n",
"from langchain.chains.elasticsearch_database import ElasticsearchDatabaseChain\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

6
cookbook/extraction_openai_tools.ipynb
View File

@ -22,8 +22,8 @@
"from typing import List, Optional\n",
"\n",
"from langchain.chains.openai_tools import create_extraction_chain_pydantic\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.pydantic_v1 import BaseModel"
"from langchain_core.pydantic_v1 import BaseModel\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -153,7 +153,7 @@
"from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
"from langchain_core.runnables import Runnable\n",
"from langchain_core.pydantic_v1 import BaseModel\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.messages import SystemMessage\n",
"from langchain_core.language_models import BaseLanguageModel\n",
"\n",

5
cookbook/forward_looking_retrieval_augmented_generation.ipynb
View File

@ -74,9 +74,8 @@
" CallbackManagerForRetrieverRun,\n",
")\n",
"from langchain.schema import BaseRetriever, Document\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities import GoogleSerperAPIWrapper"
"from langchain_community.utilities import GoogleSerperAPIWrapper\n",
"from langchain_openai import ChatOpenAI, OpenAI"
]
},
{

3
cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb
View File

@ -49,9 +49,8 @@
"\n",
"from langchain.docstore import InMemoryDocstore\n",
"from langchain.retrievers import TimeWeightedVectorStoreRetriever\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
"from termcolor import colored"
]
},

2
cookbook/hugginggpt.ipynb
View File

@ -75,8 +75,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.autonomous_agents import HuggingGPT\n",
"from langchain_openai import OpenAI\n",
"\n",
"# %env OPENAI_API_BASE=http://localhost:8000/v1"
]

2
cookbook/human_approval.ipynb
View File

@ -159,7 +159,7 @@
"outputs": [],
"source": [
"from langchain.agents import AgentType, initialize_agent, load_tools\n",
"from langchain_community.llms import OpenAI"
"from langchain_openai import OpenAI"
]
},
{

3
cookbook/hypothetical_document_embeddings.ipynb
View File

@ -22,8 +22,7 @@
"source": [
"from langchain.chains import HypotheticalDocumentEmbedder, LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.llms import OpenAI"
"from langchain_openai import OpenAI, OpenAIEmbeddings"
]
},
{

2
cookbook/learned_prompt_optimization.ipynb
View File

@ -49,7 +49,7 @@
"source": [
"# pick and configure the LLM of your choice\n",
"\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")"
]

2
cookbook/llm_bash.ipynb
View File

@ -43,8 +43,8 @@
}
],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.llm_bash.base import LLMBashChain\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"\n",

2
cookbook/llm_checker.ipynb
View File

@ -42,7 +42,7 @@
],
"source": [
"from langchain.chains import LLMCheckerChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0.7)\n",
"\n",

2
cookbook/llm_math.ipynb
View File

@ -46,7 +46,7 @@
],
"source": [
"from langchain.chains import LLMMathChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"llm_math = LLMMathChain.from_llm(llm, verbose=True)\n",

6
cookbook/llm_summarization_checker.ipynb
View File

@ -331,7 +331,7 @@
],
"source": [
"from langchain.chains import LLMSummarizationCheckerChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=2)\n",
@ -822,7 +822,7 @@
],
"source": [
"from langchain.chains import LLMSummarizationCheckerChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=3)\n",
@ -1096,7 +1096,7 @@
],
"source": [
"from langchain.chains import LLMSummarizationCheckerChain\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"checker_chain = LLMSummarizationCheckerChain.from_llm(llm, max_checks=3, verbose=True)\n",

2
cookbook/llm_symbolic_math.ipynb
View File

@ -14,8 +14,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.llm_symbolic_math.base import LLMSymbolicMathChain\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"llm_symbolic_math = LLMSymbolicMathChain.from_llm(llm)"

2
cookbook/meta_prompt.ipynb
View File

@ -59,7 +59,7 @@
"from langchain.chains import LLMChain\n",
"from langchain.memory import ConversationBufferWindowMemory\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import OpenAI"
"from langchain_openai import OpenAI"
]
},
{

4
cookbook/multi_modal_QA.ipynb
View File

@ -91,8 +91,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/multi_modal_RAG_chroma.ipynb
View File

@ -315,10 +315,10 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain_community.chat_models import ChatOpenAI\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",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",
"def prompt_func(data_dict):\n",

2
cookbook/multi_modal_output_agent.ipynb
View File

@ -44,7 +44,7 @@
"source": [
"from langchain.agents import AgentType, initialize_agent\n",
"from langchain.tools import SteamshipImageGenerationTool\n",
"from langchain_community.llms import OpenAI"
"from langchain_openai import OpenAI"
]
},
{

2
cookbook/multi_player_dnd.ipynb
View File

@ -32,7 +32,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/multiagent_authoritarian.ipynb
View File

@ -41,7 +41,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/multiagent_bidding.ipynb
View File

@ -33,7 +33,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

6
cookbook/myscale_vector_sql.ipynb
View File

@ -32,9 +32,9 @@
"\n",
"from langchain.chains import LLMChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities import SQLDatabase\n",
"from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
"from langchain_openai import OpenAI\n",
"from sqlalchemy import MetaData, create_engine\n",
"\n",
"MYSCALE_HOST = \"msc-4a9e710a.us-east-1.aws.staging.myscale.cloud\"\n",
@ -75,10 +75,10 @@
"outputs": [],
"source": [
"from langchain.callbacks import StdOutCallbackHandler\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities.sql_database import SQLDatabase\n",
"from langchain_experimental.sql.prompt import MYSCALE_PROMPT\n",
"from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
"from langchain_openai import OpenAI\n",
"\n",
"chain = VectorSQLDatabaseChain(\n",
" llm_chain=LLMChain(\n",
@ -117,7 +117,6 @@
"outputs": [],
"source": [
"from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_experimental.retrievers.vector_sql_database import (\n",
" VectorSQLDatabaseChainRetriever,\n",
")\n",
@ -126,6 +125,7 @@
" VectorSQLDatabaseChain,\n",
" VectorSQLRetrieveAllOutputParser,\n",
")\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"output_parser_retrieve_all = VectorSQLRetrieveAllOutputParser.from_embeddings(\n",
" output_parser.model\n",

6
cookbook/openai_functions_retrieval_qa.ipynb
View File

@ -22,8 +22,8 @@
"from langchain.chains import RetrievalQA\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Chroma"
"from langchain_community.vectorstores import Chroma\n",
"from langchain_openai import OpenAIEmbeddings"
]
},
{
@ -53,7 +53,7 @@
"from langchain.chains import create_qa_with_sources_chain\n",
"from langchain.chains.combine_documents.stuff import StuffDocumentsChain\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

8
cookbook/openai_v1_cookbook.ipynb
View File

@ -28,8 +28,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.messages import HumanMessage, SystemMessage"
"from langchain_core.messages import HumanMessage, SystemMessage\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -414,7 +414,7 @@
"BREAKING CHANGES:\n",
"- To use Azure embeddings with OpenAI V1, you'll need to use the new `AzureOpenAIEmbeddings` instead of the existing `OpenAIEmbeddings`. `OpenAIEmbeddings` continue to work when using Azure with `openai<1`.\n",
"```python\n",
"from langchain_community.embeddings import AzureOpenAIEmbeddings\n",
"from langchain_openai import AzureOpenAIEmbeddings\n",
"```\n",
"\n",
"\n",
@ -456,8 +456,8 @@
"from typing import Literal\n",
"\n",
"from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.pydantic_v1 import BaseModel, Field\n",
"\n",
"\n",

2
cookbook/petting_zoo.ipynb
View File

@ -52,7 +52,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

5
cookbook/plan_and_execute_agent.ipynb
View File

@ -30,15 +30,14 @@
"outputs": [],
"source": [
"from langchain.chains import LLMMathChain\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.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",
" load_chat_planner,\n",
")"
")\n",
"from langchain_openai import ChatOpenAI, OpenAI"
]
},
{

2
cookbook/press_releases.ipynb
View File

@ -82,7 +82,7 @@
"source": [
"from langchain.chains import ConversationalRetrievalChain\n",
"from langchain.retrievers import KayAiRetriever\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI(model_name=\"gpt-3.5-turbo\")\n",
"retriever = KayAiRetriever.create(\n",

4
cookbook/program_aided_language_model.ipynb
View File

@ -17,8 +17,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_experimental.pal_chain import PALChain"
"from langchain_experimental.pal_chain import PALChain\n",
"from langchain_openai import OpenAI"
]
},
{

2
cookbook/qa_citations.ipynb
View File

@ -27,7 +27,7 @@
],
"source": [
"from langchain.chains import create_citation_fuzzy_match_chain\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

6
cookbook/rag_fusion.ipynb
View File

@ -30,8 +30,8 @@
"outputs": [],
"source": [
"import pinecone\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import Pinecone\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"pinecone.init(api_key=\"...\", environment=\"...\")"
]
@ -86,8 +86,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_openai import ChatOpenAI"
]
},
{

8
cookbook/retrieval_in_sql.ipynb
View File

@ -43,7 +43,7 @@
"outputs": [],
"source": [
"from langchain.sql_database import SQLDatabase\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"CONNECTION_STRING = \"postgresql+psycopg2://postgres:test@localhost:5432/vectordb\" # Replace with your own\n",
"db = SQLDatabase.from_uri(CONNECTION_STRING)"
@ -88,7 +88,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings_model = OpenAIEmbeddings()"
]
@ -219,7 +219,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"template = \"\"\"You are a Postgres expert. Given an input question, first create a syntactically correct Postgres query to run, then look at the results of the query and return the answer to the input question.\n",
"Unless the user specifies in the question a specific number of examples to obtain, query for at most 5 results using the LIMIT clause as per Postgres. You can order the results to return the most informative data in the database.\n",
@ -267,9 +267,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"db = SQLDatabase.from_uri(\n",
" CONNECTION_STRING\n",

6
cookbook/rewrite.ipynb
View File

@ -31,11 +31,11 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnablePassthrough"
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI"
]
},
{

5
cookbook/sales_agent_with_context.ipynb
View File

@ -53,10 +53,9 @@
"from langchain.prompts.base import StringPromptTemplate\n",
"from langchain.schema import AgentAction, AgentFinish\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.llms import BaseLLM, OpenAI\n",
"from langchain_community.llms import BaseLLM\n",
"from langchain_community.vectorstores import Chroma\n",
"from langchain_openai import ChatOpenAI, OpenAI, OpenAIEmbeddings\n",
"from pydantic import BaseModel, Field"
]
},

4
cookbook/selecting_llms_based_on_context_length.ipynb
View File

@ -18,9 +18,9 @@
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompt_values import PromptValue"
"from langchain_core.prompt_values import PromptValue\n",
"from langchain_openai import ChatOpenAI"
]
},
{

4
cookbook/self_query_hotel_search.ipynb
View File

@ -255,7 +255,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI(model=\"gpt-4\")\n",
"res = model.predict(\n",
@ -1083,8 +1083,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import ElasticsearchStore\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings()"
]

4
cookbook/sharedmemory_for_tools.ipynb
View File

@ -26,8 +26,8 @@
"from langchain.chains import LLMChain\n",
"from langchain.memory import ConversationBufferMemory, ReadOnlySharedMemory\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.utilities import GoogleSearchAPIWrapper"
"from langchain_community.utilities import GoogleSearchAPIWrapper\n",
"from langchain_openai import OpenAI"
]
},
{

4
cookbook/smart_llm.ipynb
View File

@ -52,8 +52,8 @@
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_experimental.smart_llm import SmartLLMChain"
"from langchain_experimental.smart_llm import SmartLLMChain\n",
"from langchain_openai import ChatOpenAI"
]
},
{

4
cookbook/sql_db_qa.mdx
View File

@ -9,7 +9,7 @@ To set it up, follow the instructions on https://database.guide/2-sample-databas
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_community.utilities import SQLDatabase
from langchain_experimental.sql import SQLDatabaseChain
```
@ -200,7 +200,7 @@ result["intermediate_steps"]
How to add memory to a SQLDatabaseChain:
```python
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain_community.utilities import SQLDatabase
from langchain_experimental.sql import SQLDatabaseChain
```

6
cookbook/stepback-qa.ipynb
View File

@ -23,10 +23,10 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnableLambda"
"from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate\n",
"from langchain_core.runnables import RunnableLambda\n",
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/tree_of_thought.ipynb
View File

@ -24,7 +24,7 @@
}
],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=1, max_tokens=512, model=\"gpt-3.5-turbo-instruct\")"
]

4
cookbook/twitter-the-algorithm-analysis-deeplake.ipynb
View File

@ -37,8 +37,8 @@
"import getpass\n",
"import os\n",
"\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import DeepLake\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
"activeloop_token = getpass.getpass(\"Activeloop Token:\")\n",
@ -3809,7 +3809,7 @@
"outputs": [],
"source": [
"from langchain.chains import ConversationalRetrievalChain\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI(model_name=\"gpt-3.5-turbo-0613\") # switch to 'gpt-4'\n",
"qa = ConversationalRetrievalChain.from_llm(model, retriever=retriever)"

2
cookbook/two_agent_debate_tools.ipynb
View File

@ -30,7 +30,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/two_player_dnd.ipynb
View File

@ -28,7 +28,7 @@
" HumanMessage,\n",
" SystemMessage,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI"
"from langchain_openai import ChatOpenAI"
]
},
{

2
cookbook/wikibase_agent.ipynb
View File

@ -599,7 +599,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"llm = ChatOpenAI(model_name=\"gpt-4\", temperature=0)"
]

4
docs/docs/expression_language/cookbook/code_writing.ipynb
View File

@ -20,9 +20,9 @@
"from langchain.prompts import (\n",
" ChatPromptTemplate,\n",
")\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_experimental.utilities import PythonREPL"
"from langchain_experimental.utilities import PythonREPL\n",
"from langchain_openai import ChatOpenAI"
]
},
{

3
docs/docs/expression_language/cookbook/embedding_router.ipynb
View File

@ -21,10 +21,9 @@
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain.utils.math import cosine_similarity\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings\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",

4
docs/docs/expression_language/cookbook/memory.ipynb
View File

@ -20,9 +20,9 @@
"from operator import itemgetter\n",
"\n",
"from langchain.memory import ConversationBufferMemory\n",
"from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI()\n",
"prompt = ChatPromptTemplate.from_messages(\n",

4
docs/docs/expression_language/cookbook/moderation.ipynb
View File

@ -18,8 +18,8 @@
"outputs": [],
"source": [
"from langchain.chains import OpenAIModerationChain\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.llms import OpenAI"
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import OpenAI"
]
},
{

4
docs/docs/expression_language/cookbook/multiple_chains.ipynb
View File

@ -39,9 +39,9 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.schema import StrOutputParser\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"prompt1 = ChatPromptTemplate.from_template(\"what is the city {person} is from?\")\n",
"prompt2 = ChatPromptTemplate.from_template(\n",

4
docs/docs/expression_language/cookbook/prompt_llm_parser.ipynb
View File

@ -42,8 +42,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"prompt = ChatPromptTemplate.from_template(\"tell me a joke about {foo}\")\n",
"model = ChatOpenAI()\n",

6
docs/docs/expression_language/cookbook/prompt_size.ipynb
View File

@ -26,12 +26,12 @@
"from langchain.agents import AgentExecutor, load_tools\n",
"from langchain.agents.format_scratchpad import format_to_openai_function_messages\n",
"from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser\n",
"from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain.prompts.chat import ChatPromptValue\n",
"from langchain.tools import WikipediaQueryRun\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.tools.convert_to_openai import format_tool_to_openai_function\n",
"from langchain_community.utilities import WikipediaAPIWrapper"
"from langchain_community.utilities import WikipediaAPIWrapper\n",
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_openai import ChatOpenAI"
]
},
{

7
docs/docs/expression_language/cookbook/retrieval.ipynb
View File

@ -38,12 +38,11 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough"
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings"
]
},
{

4
docs/docs/expression_language/cookbook/sql_db.ipynb
View File

@ -26,7 +26,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"template = \"\"\"Based on the table schema below, write a SQL query that would answer the user's question:\n",
"{schema}\n",
@ -93,9 +93,9 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI()\n",
"\n",

6
docs/docs/expression_language/cookbook/tools.ipynb
View File

@ -27,10 +27,10 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.tools import DuckDuckGoSearchRun\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser"
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI"
]
},
{

46
docs/docs/expression_language/get_started.ipynb
View File

@ -32,28 +32,28 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 1,
"id": "466b65b3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\"Why did the ice cream go to therapy?\\n\\nBecause it had too many toppings and couldn't find its cone-fidence!\""
"\"Why don't ice creams ever get invited to parties?\\n\\nBecause they always drip when things heat up!\""
]
},
"execution_count": 7,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"prompt = ChatPromptTemplate.from_template(\"tell me a short joke about {topic}\")\n",
"model = ChatOpenAI()\n",
"model = ChatOpenAI(model=\"gpt-4\")\n",
"output_parser = StrOutputParser()\n",
"\n",
"chain = prompt | model | output_parser\n",
@ -89,7 +89,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 2,
"id": "b8656990",
"metadata": {},
"outputs": [
@ -99,7 +99,7 @@
"ChatPromptValue(messages=[HumanMessage(content='tell me a short joke about ice cream')])"
]
},
"execution_count": 8,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
@ -111,7 +111,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 3,
"id": "e6034488",
"metadata": {},
"outputs": [
@ -121,7 +121,7 @@
"[HumanMessage(content='tell me a short joke about ice cream')]"
]
},
"execution_count": 9,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@ -132,7 +132,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 4,
"id": "60565463",
"metadata": {},
"outputs": [
@ -142,7 +142,7 @@
"'Human: tell me a short joke about ice cream'"
]
},
"execution_count": 10,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@ -163,17 +163,17 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 5,
"id": "33cf5f72",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AIMessage(content=\"Why did the ice cream go to therapy? \\n\\nBecause it had too many toppings and couldn't find its cone-fidence!\")"
"AIMessage(content=\"Why don't ice creams ever get invited to parties?\\n\\nBecause they always bring a melt down!\")"
]
},
"execution_count": 11,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@ -193,23 +193,23 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 6,
"id": "8feb05da",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\n\\nRobot: Why did the ice cream go to therapy? Because it had a rocky road.'"
"'\\n\\nRobot: Why did the ice cream truck break down? Because it had a meltdown!'"
]
},
"execution_count": 12,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_openai.llms import OpenAI\n",
"\n",
"llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")\n",
"llm.invoke(prompt_value)"
@ -324,12 +324,12 @@
"# Requires:\n",
"# pip install langchain docarray tiktoken\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import DocArrayInMemorySearch\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnableParallel, RunnablePassthrough\n",
"from langchain_openai.chat_models import ChatOpenAI\n",
"from langchain_openai.embeddings import OpenAIEmbeddings\n",
"\n",
"vectorstore = DocArrayInMemorySearch.from_texts(\n",
" [\"harrison worked at kensho\", \"bears like to eat honey\"],\n",
@ -486,7 +486,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.10.1"
}
},
"nbformat": 4,

6
docs/docs/expression_language/how_to/binding.ipynb
View File

@ -19,10 +19,10 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.schema import StrOutputParser\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.runnables import RunnablePassthrough"
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI"
]
},
{

7
docs/docs/expression_language/how_to/configure.ipynb
View File

@ -42,8 +42,8 @@
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.runnables import ConfigurableField\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI(temperature=0).configurable_fields(\n",
" temperature=ConfigurableField(\n",
@ -264,8 +264,9 @@
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.chat_models import ChatAnthropic, ChatOpenAI\n",
"from langchain_core.runnables import ConfigurableField"
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_core.runnables import ConfigurableField\n",
"from langchain_openai import ChatOpenAI"
]
},
{

4
docs/docs/expression_language/how_to/decorator.ipynb
View File

@ -23,10 +23,10 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import chain"
"from langchain_core.runnables import chain\n",
"from langchain_openai import ChatOpenAI"
]
},
{

9
docs/docs/expression_language/how_to/fallbacks.ipynb
View File

@ -31,7 +31,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatAnthropic, ChatOpenAI"
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -141,7 +142,7 @@
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
@ -241,7 +242,7 @@
"source": [
"# Now lets create a chain with the normal OpenAI model\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"prompt_template = \"\"\"Instructions: You should always include a compliment in your response.\n",
"\n",
@ -291,7 +292,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
"version": "3.11.4"
}
},
"nbformat": 4,

4
docs/docs/expression_language/how_to/functions.ipynb
View File

@ -33,9 +33,9 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnableLambda\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",
"def length_function(text):\n",

2
docs/docs/expression_language/how_to/generators.ipynb
View File

@ -33,8 +33,8 @@
"from typing import Iterator, List\n",
"\n",
"from langchain.prompts.chat import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"prompt = ChatPromptTemplate.from_template(\n",
" \"Write a comma-separated list of 5 animals similar to: {animal}\"\n",

5
docs/docs/expression_language/how_to/inspect.ipynb
View File

@ -33,10 +33,9 @@
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.vectorstores import FAISS\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough"
"from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
"from langchain_openai import ChatOpenAI, OpenAIEmbeddings"
]
},
{

14
docs/docs/expression_language/how_to/map.ipynb
View File

@ -44,12 +44,11 @@
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\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\n",
"\n",
"vectorstore = FAISS.from_texts(\n",
" [\"harrison worked at kensho\"], embedding=OpenAIEmbeddings()\n",
@ -128,12 +127,11 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\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\n",
"\n",
"vectorstore = FAISS.from_texts(\n",
" [\"harrison worked at kensho\"], embedding=OpenAIEmbeddings()\n",
@ -192,9 +190,9 @@
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnableParallel\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI()\n",
"joke_chain = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\") | model\n",

2
docs/docs/expression_language/how_to/message_history.ipynb
View File

@ -131,10 +131,10 @@
"source": [
"from typing import Optional\n",
"\n",
"from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_community.chat_message_histories import RedisChatMessageHistory\n",
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_core.chat_history import BaseChatMessageHistory\n",
"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
"from langchain_core.runnables.history import RunnableWithMessageHistory"
]
},

5
docs/docs/expression_language/how_to/passthrough.ipynb
View File

@ -97,12 +97,11 @@
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.embeddings import OpenAIEmbeddings\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\n",
"\n",
"vectorstore = FAISS.from_texts(\n",
" [\"harrison worked at kensho\"], embedding=OpenAIEmbeddings()\n",

6
docs/docs/expression_language/interface.ipynb
View File

@ -57,8 +57,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"model = ChatOpenAI()\n",
"prompt = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\")\n",
@ -659,10 +659,10 @@
}
],
"source": [
"from langchain_community.embeddings import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.runnables import RunnablePassthrough\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"template = \"\"\"Answer the question based only on the following context:\n",
"{context}\n",

11
docs/docs/expression_language/why.ipynb
View File

@ -42,8 +42,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"\n",
"\n",
@ -389,7 +389,7 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")\n",
"llm_chain = (\n",
@ -1002,8 +1002,9 @@
"source": [
"import os\n",
"\n",
"from langchain_community.chat_models import ChatAnthropic, ChatOpenAI\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_openai import ChatOpenAI\n",
"from langchain_openai import OpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import RunnablePassthrough\n",

24
docs/docs/get_started/quickstart.mdx
View File

@ -70,10 +70,10 @@ For this getting started guide, we will provide two options: using OpenAI (a pop
<Tabs>
<TabItem value="openai" label="OpenAI" default>
First we'll need to install their Python package:
First we'll need to the LangChain <> OpenAI integration package.
```shell
pip install openai
pip install langchain_openai
```
Accessing the API requires an API key, which you can get by creating an account and heading [here](https://platform.openai.com/account/api-keys). Once we have a key we'll want to set it as an environment variable by running:
@ -85,7 +85,7 @@ export OPENAI_API_KEY="..."
We can then initialize the model:
```python
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
llm = ChatOpenAI()
```
@ -93,7 +93,7 @@ llm = ChatOpenAI()
If you'd prefer not to set an environment variable you can pass the key in directly via the `openai_api_key` named parameter when initiating the OpenAI LLM class:
```python
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(openai_api_key="...")
```
@ -128,7 +128,7 @@ We can also guide it's response with a prompt template.
Prompt templates are used to convert raw user input to a better input to the LLM.
```python
from langchain.prompts import ChatPromptTemplate
from langchain_core.prompts import ChatPromptTemplate
prompt = ChatPromptTemplate.from_messages([
("system", "You are world class technical documentation writer."),
("user", "{input}")
@ -199,10 +199,10 @@ For embedding models, we once again provide examples for accessing via OpenAI or
<Tabs>
<TabItem value="openai" label="OpenAI" default>
Make sure you have the openai package installed an the appropriate environment variables set (these are the same as needed for the LLM).
Make sure you have the `langchain_openai` package installed an the appropriate environment variables set (these are the same as needed for the LLM).
```python
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_openai import OpenAIEmbeddings
embeddings = OpenAIEmbeddings()
```
@ -416,7 +416,7 @@ pip install langchainhub
Now we can use it to get a predefined prompt
```python
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain import hub
from langchain.agents import create_openai_functions_agent
from langchain.agents import AgentExecutor
@ -479,15 +479,15 @@ To create a server for our application we'll make a `serve.py` file. This will c
from typing import List
from fastapi import FastAPI
from langchain.prompts import ChatPromptTemplate
from langchain_community.chat_models import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from langchain_community.document_loaders import WebBaseLoader
from langchain_community.embeddings import OpenAIEmbeddings
from langchain_openai import OpenAIEmbeddings
from langchain_community.vectorstores import DocArrayInMemorySearch
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.tools.retriever import create_retriever_tool
from langchain_community.tools.tavily_search import TavilySearchResults
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
from langchain import hub
from langchain.agents import create_openai_functions_agent
from langchain.agents import AgentExecutor

2
docs/docs/guides/debugging.md
View File

@ -25,7 +25,7 @@ Let's suppose we have a simple agent, and want to visualize the actions it takes
```python
from langchain.agents import AgentType, initialize_agent, load_tools
from langchain_community.chat_models import ChatOpenAI
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(model_name="gpt-4", temperature=0)
tools = load_tools(["ddg-search", "llm-math"], llm=llm)

2
docs/docs/guides/evaluation/examples/comparisons.ipynb
View File

@ -99,8 +99,8 @@
"outputs": [],
"source": [
"from langchain.agents import AgentType, Tool, initialize_agent\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_community.utilities import SerpAPIWrapper\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# Initialize the language model\n",
"# You can add your own OpenAI API key by adding openai_api_key=\"<your_api_key>\"\n",

2
docs/docs/guides/evaluation/string/scoring_eval_chain.ipynb
View File

@ -25,7 +25,7 @@
"outputs": [],
"source": [
"from langchain.evaluation import load_evaluator\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"evaluator = load_evaluator(\"labeled_score_string\", llm=ChatOpenAI(model=\"gpt-4\"))"
]

2
docs/docs/guides/evaluation/trajectory/custom.ipynb
View File

@ -26,7 +26,7 @@
"from langchain.chains import LLMChain\n",
"from langchain.evaluation import AgentTrajectoryEvaluator\n",
"from langchain.schema import AgentAction\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"\n",
"class StepNecessityEvaluator(AgentTrajectoryEvaluator):\n",

2
docs/docs/guides/evaluation/trajectory/trajectory_eval.ipynb
View File

@ -76,7 +76,7 @@
"\n",
"from langchain.agents import AgentType, initialize_agent\n",
"from langchain.tools import tool\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"from pydantic import HttpUrl\n",
"\n",
"\n",

7
docs/docs/guides/fallbacks.ipynb
View File

@ -33,7 +33,8 @@
"metadata": {},
"outputs": [],
"source": [
"from langchain_community.chat_models import ChatAnthropic, ChatOpenAI"
"from langchain_community.chat_models import ChatAnthropic\n",
"from langchain_openai import ChatOpenAI"
]
},
{
@ -143,7 +144,7 @@
}
],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
@ -206,7 +207,7 @@
"source": [
"# Now lets create a chain with the normal OpenAI model\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"prompt_template = \"\"\"Instructions: You should always include a compliment in your response.\n",
"\n",

3
docs/docs/guides/model_laboratory.ipynb
View File

@ -21,7 +21,8 @@
"source": [
"from langchain.model_laboratory import ModelLaboratory\n",
"from langchain.prompts import PromptTemplate\n",
"from langchain_community.llms import Cohere, HuggingFaceHub, OpenAI"
"from langchain_community.llms import Cohere, HuggingFaceHub\n",
"from langchain_openai import OpenAI"
]
},
{

2
docs/docs/guides/privacy/presidio_data_anonymization/index.ipynb
View File

@ -130,7 +130,7 @@
],
"source": [
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"anonymizer = PresidioAnonymizer()\n",
"\n",

6
docs/docs/guides/privacy/presidio_data_anonymization/qa_privacy_protection.ipynb
View File

@ -638,8 +638,8 @@
"outputs": [],
"source": [
"from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
"from langchain_community.embeddings.openai import OpenAIEmbeddings\n",
"from langchain_community.vectorstores import FAISS\n",
"from langchain_openai import OpenAIEmbeddings\n",
"\n",
"# 2. Load the data: In our case data's already loaded\n",
"# 3. Anonymize the data before indexing\n",
@ -664,14 +664,14 @@
"source": [
"from operator import itemgetter\n",
"\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain_community.chat_models.openai import ChatOpenAI\n",
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_core.runnables import (\n",
" RunnableLambda,\n",
" RunnableParallel,\n",
" RunnablePassthrough,\n",
")\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# 6. Create anonymizer chain\n",
"template = \"\"\"Answer the question based only on the following context:\n",

2
docs/docs/guides/privacy/presidio_data_anonymization/reversible.ipynb
View File

@ -208,7 +208,7 @@
],
"source": [
"from langchain.prompts.prompt import PromptTemplate\n",
"from langchain_community.chat_models import ChatOpenAI\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"anonymizer = PresidioReversibleAnonymizer()\n",
"\n",

2
docs/docs/guides/safety/constitutional_chain.mdx
View File

@ -12,7 +12,7 @@ content that may violate guidelines, be offensive, or deviate from the desired c
```python
# Imports
from langchain_community.llms import OpenAI
from langchain_openai import OpenAI
from langchain.prompts import PromptTemplate
from langchain.chains.llm import LLMChain
from langchain.chains.constitutional_ai.base import ConstitutionalChain

2
docs/docs/guides/safety/hugging_face_prompt_injection.ipynb
View File

@ -207,7 +207,7 @@
],
"source": [
"from langchain.agents import AgentType, initialize_agent\n",
"from langchain_community.llms import OpenAI\n",
"from langchain_openai import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"agent = initialize_agent(\n",

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