prompt stringlengths 43 25.9k | completion stringlengths 7 362 | api stringlengths 18 90 |
|---|---|---|
get_ipython().run_line_magic('pip', "install --upgrade --quiet langchain-openai 'deeplake[enterprise]' tiktoken")
from langchain_community.vectorstores import DeepLake
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
import getpass
import os
os.environ["OP... | DeepLake(dataset_path="./my_deeplake/", embedding=embeddings, read_only=True) | langchain_community.vectorstores.DeepLake |
import runhouse as rh
from langchain_community.embeddings import (
SelfHostedEmbeddings,
SelfHostedHuggingFaceEmbeddings,
SelfHostedHuggingFaceInstructEmbeddings,
)
gpu = rh.cluster(name="rh-a10x", instance_type="A100:1", use_spot=False)
embeddings = SelfHostedHuggingFaceEmbeddings(hardware=gpu)
tex... | SelfHostedHuggingFaceInstructEmbeddings(hardware=gpu) | langchain_community.embeddings.SelfHostedHuggingFaceInstructEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet tiktoken langchain-openai python-dotenv datasets langchain deeplake beautifulsoup4 html2text ragas')
ORG_ID = "..."
import getpass
import os
from langchain.chains import RetrievalQA
from langchain.vectorstores.deeplake import DeepLake
from langchain_... | Html2TextTransformer() | langchain.document_transformers.Html2TextTransformer |
get_ipython().system(' pip install -U langchain openai chromadb langchain-experimental # (newest versions required for multi-modal)')
get_ipython().system(' pip install "unstructured[all-docs]==0.10.19" pillow pydantic lxml pillow matplotlib tiktoken open_clip_torch torch')
path = "/Users/rlm/Desktop/cpi/"
from ... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
import os
from langchain.chains import ConversationalRetrievalChain
from langchain_community.vectorstores import Vectara
from langchain_openai import OpenAI
from langchain_community.document_loaders import TextLoader
loader = TextLoader("state_of_the_union.txt")
documents = loader.load()
vectara = Vectara.from_... | LLMChain(llm=llm, prompt=CONDENSE_QUESTION_PROMPT) | langchain.chains.llm.LLMChain |
import logging
from langchain.retrievers import RePhraseQueryRetriever
from langchain_community.document_loaders import WebBaseLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from langchain_text_splitters import RecursiveCharacterTextSplitter
loggi... | ChatOpenAI(temperature=0) | langchain_openai.ChatOpenAI |
get_ipython().system(' pip install -U langchain openai chromadb langchain-experimental # (newest versions required for multi-modal)')
get_ipython().system(' pip install "unstructured[all-docs]==0.10.19" pillow pydantic lxml pillow matplotlib tiktoken open_clip_torch torch')
path = "/Users/rlm/Desktop/cpi/"
from ... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
from langchain_core.runnables import RunnableLambda
from langchain_openai import ChatOpenAI
examples = [
{
"input": "Could the members of The Police perform law... | DuckDuckGoSearchAPIWrapper(max_results=4) | langchain_community.utilities.DuckDuckGoSearchAPIWrapper |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet aim')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet google-search-results')
i... | PromptTemplate(input_variables=["title"], template=template) | langchain.prompts.PromptTemplate |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet duckduckgo-search')
from langchain.tools import DuckDuckGoSearchRun
search = DuckDuckGoSearchRun()
search.run("Obama's first name?")
from langchain.tools import DuckDuckGoSearchResults
search = DuckDuckGoSearchResults()
search.run("Obama")
... | DuckDuckGoSearchResults(api_wrapper=wrapper, source="news") | langchain.tools.DuckDuckGoSearchResults |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet text-generation transformers google-search-results numexpr langchainhub sentencepiece jinja2')
import os
from langchain_community.llms import HuggingFaceTextGenInference
ENDPOINT_URL = "<YOUR_ENDPOINT_URL_HERE>"
HF_TOKEN = os.getenv("HUGGINGFACEHUB_A... | SystemMessage(content="You're a helpful assistant") | langchain.schema.SystemMessage |
from langchain.agents import AgentExecutor, Tool, ZeroShotAgent
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory, ReadOnlySharedMemory
from langchain.prompts import PromptTemplate
from langchain_community.utilities import GoogleSearchAPIWrapper
from langchain_openai import Ope... | ReadOnlySharedMemory(memory=memory) | langchain.memory.ReadOnlySharedMemory |
from getpass import getpass
from langchain_community.document_loaders.larksuite import LarkSuiteDocLoader
DOMAIN = input("larksuite domain")
ACCESS_TOKEN = getpass("larksuite tenant_access_token or user_access_token")
DOCUMENT_ID = input("larksuite document id")
from pprint import pprint
larksuite_loader = LarkSui... | load_summarize_chain(llm, chain_type="map_reduce") | langchain.chains.summarize.load_summarize_chain |
import asyncio
from typing import Any, Dict, List
from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
from langchain_core.messages import HumanMessage, LLMResult
from langchain_openai import ChatOpenAI
class MyCustomSyncHandler(BaseCallbackHandler):
def on_llm_new_token(self, token: st... | HumanMessage(content="Tell me a joke") | langchain_core.messages.HumanMessage |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet xata langchain-openai tiktoken langchain')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
api_key = getpass.getpass("Xata API key: ")
db_url = input("Xata database URL (copy it from your DB settings):")
... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pymilvus')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Milvus
from langchain_openai import OpenAIE... | Document(page_content="new_foo", metadata={"id": 1}) | langchain.docstore.document.Document |
from langchain.agents import Tool
from langchain.chains import RetrievalQA
from langchain_community.document_loaders import PyPDFLoader
from langchain_community.vectorstores import FAISS
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
from pydantic im... | PyPDFLoader(file["path"]) | langchain_community.document_loaders.PyPDFLoader |
import os
os.environ["LANGCHAIN_WANDB_TRACING"] = "true"
os.environ["WANDB_PROJECT"] = "langchain-tracing"
from langchain.agents import AgentType, initialize_agent, load_tools
from langchain.callbacks import wandb_tracing_enabled
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
tools = | load_tools(["llm-math"], llm=llm) | langchain.agents.load_tools |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-core databricks-vectorsearch langchain-openai tiktoken')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
from langchain_community.document_loaders import TextLoader
from langchain_openai import Op... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
from langchain_core.tools import tool
@tool
def complex_tool(int_arg: int, float_arg: float, dict_arg: dict) -> int:
"""Do something complex... | MessagesPlaceholder("last_output", optional=True) | langchain_core.prompts.MessagesPlaceholder |
get_ipython().system('pip install boto3')
from langchain_experimental.recommenders import AmazonPersonalize
recommender_arn = "<insert_arn>"
client = AmazonPersonalize(
credentials_profile_name="default",
region_name="us-west-2",
recommender_arn=recommender_arn,
)
client.get_recommendations(user_id="1... | LLMChain(llm=bedrock_llm, prompt=RANDOM_PROMPT_2) | langchain.chains.LLMChain |
from langchain_community.document_loaders import UnstructuredURLLoader
urls = [
"https://www.understandingwar.org/backgrounder/russian-offensive-campaign-assessment-february-8-2023",
"https://www.understandingwar.org/backgrounder/russian-offensive-campaign-assessment-february-9-2023",
]
loader = | UnstructuredURLLoader(urls=urls) | langchain_community.document_loaders.UnstructuredURLLoader |
from langchain_community.chat_models.llama_edge import LlamaEdgeChatService
from langchain_core.messages import HumanMessage, SystemMessage
service_url = "https://b008-54-186-154-209.ngrok-free.app"
chat = LlamaEdgeChatService(service_url=service_url)
system_message = SystemMessage(content="You are an AI assistant... | LlamaEdgeChatService(service_url=service_url, streaming=True) | langchain_community.chat_models.llama_edge.LlamaEdgeChatService |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet lark chromadb')
from langchain_community.vectorstores import Chroma
from langchain_core.documents import Document
from langchain_openai import OpenAIEmbeddings
docs = [
Document(
page_content="A bunch of scientists bring back dinosaurs and m... | ChromaTranslator() | langchain.retrievers.self_query.chroma.ChromaTranslator |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet wikipedia')
from langchain.tools import WikipediaQueryRun
from langchain_community.utilities import WikipediaAPIWrapper
wikipedia = WikipediaQueryRun(api_wrapper= | WikipediaAPIWrapper() | langchain_community.utilities.WikipediaAPIWrapper |
from langchain.chains import LLMSummarizationCheckerChain
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
checker_chain = | LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=2) | langchain.chains.LLMSummarizationCheckerChain.from_llm |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet opaqueprompts langchain')
import os
os.environ["OPAQUEPROMPTS_API_KEY"] = "<OPAQUEPROMPTS_API_KEY>"
os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>"
from langchain.callbacks.stdout import StdOutCallbackHandler
from langchain.chains import LLMChain... | ConversationBufferWindowMemory(k=2) | langchain.memory.ConversationBufferWindowMemory |
import os
import pprint
os.environ["SERPER_API_KEY"] = ""
from langchain_community.utilities import GoogleSerperAPIWrapper
search = GoogleSerperAPIWrapper()
search.run("Obama's first name?")
os.environ["OPENAI_API_KEY"] = ""
from langchain.agents import AgentType, Tool, initialize_agent
from langchain_commu... | GoogleSerperAPIWrapper(type="images") | langchain_community.utilities.GoogleSerperAPIWrapper |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-community')
import os
os.environ["YDC_API_KEY"] = ""
os.environ["OPENAI_API_KEY"] = ""
from langchain_community.tools.you import YouSearchTool
from langchain_community.utilities.you import YouSearchAPIWrapper
api_wrapper = YouSearchAP... | YouSearchTool(api_wrapper=api_wrapper) | langchain_community.tools.you.YouSearchTool |
get_ipython().run_line_magic('pip', 'install -qU langchain langchain-openai langchain-anthropic langchain-community wikipedia')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
os.environ["ANTHROPIC_API_KEY"] = getpass.getpass()
from langchain_community.retrievers import WikipediaRetrieve... | RunnablePassthrough() | langchain_core.runnables.RunnablePassthrough |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-community langchainhub gpt4all chromadb')
from langchain_community.document_loaders import WebBaseLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
loader = WebBaseLoader("https://lilianweng.github.io/posts/... | GPT4AllEmbeddings() | langchain_community.embeddings.GPT4AllEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from operator import itemgetter
from langchain.memory import ConversationBufferMemory
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.runnables import RunnableLambda, RunnablePa... | MessagesPlaceholder(variable_name="history") | langchain_core.prompts.MessagesPlaceholder |
import os
from langchain_openai import OpenAI
from lemonai import execute_workflow
""" Load all relevant API Keys and Access Tokens into your environment variables """
os.environ["OPENAI_API_KEY"] = "*INSERT OPENAI API KEY HERE*"
os.environ["AIRTABLE_ACCESS_TOKEN"] = "*INSERT AIRTABLE TOKEN HERE*"
hackernews_user... | OpenAI(temperature=0) | langchain_openai.OpenAI |
from langchain.chains import LLMMathChain
from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
from langchain_core.tools import Tool
from langchain_experimental.plan_and_execute import (
PlanAndExecute,
load_agent_executor,
load_chat_planner,
)
from langchain_openai import ChatOpenAI, OpenAI... | OpenAI(temperature=0) | langchain_openai.OpenAI |
from typing import Optional
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_experimental.autonomous_agents import BabyAGI
from langchain_openai import OpenAI, OpenAIEmbeddings
get_ipython().run_line_magic('pip', 'install faiss-cpu > /dev/null')
get_ipython().run_lin... | LLMChain(llm=llm, prompt=prompt) | langchain.chains.LLMChain |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain_openai')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("Input your OpenAI API key:")
tidb_connection_string_template = "mysql+pymysql://<USER>:<PASSWORD>@<HOST>:4000/<DB>?ssl_ca=/etc/ssl/cert.pem&ssl_veri... | MessagesPlaceholder(variable_name="history") | langchain_core.prompts.MessagesPlaceholder |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet boto3 nltk')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain_experimental')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain pydantic')
import os
import boto3
comprehend_client = boto3.client("comp... | ModerationToxicityConfig(threshold=0.5) | langchain_experimental.comprehend_moderation.ModerationToxicityConfig |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet sagemaker')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet google-search-results')
import os
os.environ["OPENAI_API_KEY"] = "<ADD-KEY-HERE>"
os.environ[... | SageMakerCallbackHandler(run) | langchain.callbacks.SageMakerCallbackHandler |
from langchain_experimental.llm_bash.base import LLMBashChain
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
text = "Please write a bash script that prints 'Hello World' to the console."
bash_chain = LLMBashChain.from_llm(llm, verbose=True)
bash_chain.run(text)
from langchain.prompts.prompt impo... | BashProcess(persistent=True) | langchain_experimental.llm_bash.bash.BashProcess |
meals = [
"Beef Enchiladas with Feta cheese. Mexican-Greek fusion",
"Chicken Flatbreads with red sauce. Italian-Mexican fusion",
"Veggie sweet potato quesadillas with vegan cheese",
"One-Pan Tortelonni bake with peppers and onions",
]
from langchain_openai import OpenAI
llm = OpenAI(model="gpt-3.5-t... | rl_chain.ToSelectFrom(meals) | langchain_experimental.rl_chain.ToSelectFrom |
get_ipython().system(' pip install langchain unstructured[all-docs] pydantic lxml langchainhub')
get_ipython().system(' brew install tesseract')
get_ipython().system(' brew install poppler')
path = "/Users/rlm/Desktop/Papers/LLaMA2/"
from typing import Any
from pydantic import BaseModel
from unstructured.parti... | InMemoryStore() | langchain.storage.InMemoryStore |
get_ipython().run_line_magic('pip', 'install -qU langchain langchain-openai langchain-anthropic langchain-community wikipedia')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
os.environ["ANTHROPIC_API_KEY"] = getpass.getpass()
from langchain_community.retrievers import WikipediaRetrieve... | WikipediaRetriever(top_k_results=6, doc_content_chars_max=2000) | langchain_community.retrievers.WikipediaRetriever |
from langchain_community.llms import Baseten
mistral = | Baseten(model="MODEL_ID", deployment="production") | langchain_community.llms.Baseten |
from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import ChatOpenAI
template = """Answer the users question ... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet comet_ml langchain langchain-openai google-search-results spacy textstat pandas')
get_ipython().system('{sys.executable} -m spacy download en_core_web_sm')
import comet_ml
comet_ml.init(project_name="comet-example-langchain")
import os
os.envir... | PromptTemplate(input_variables=["article"], template=template) | langchain.prompts.PromptTemplate |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai argilla')
import os
os.environ["ARGILLA_API_URL"] = "..."
os.environ["ARGILLA_API_KEY"] = "..."
os.environ["OPENAI_API_KEY"] = "..."
import argilla as rg
from packaging.version import parse as parse_version
if parse_ve... | StdOutCallbackHandler() | langchain.callbacks.StdOutCallbackHandler |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet boto3 langchain-openai tiktoken python-dotenv')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet "amazon-textract-caller>=0.2.0"')
from langchain_community.document_loaders import AmazonTextractPDFLoader
loader = AmazonTextractPDFLoade... | AmazonTextractPDFLoader(
"https://amazon-textract-public-content.s3.us-east-2.amazonaws.com/langchain/alejandro_rosalez_sample_1.jpg"
) | langchain_community.document_loaders.AmazonTextractPDFLoader |
import getpass
import os
os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY") or getpass.getpass(
"OpenAI API Key:"
)
from langchain.sql_database import SQLDatabase
from langchain_openai import ChatOpenAI
CONNECTION_STRING = "postgresql+psycopg2://postgres:test@localhost:5432/vectordb" # Replace wit... | RunnablePassthrough.assign(schema=get_schema) | langchain_core.runnables.RunnablePassthrough.assign |
from langchain.retrievers import ParentDocumentRetriever
from langchain.storage import InMemoryStore
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import RecursiveCharacterText... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pymongo')
import os
CONNECTION_STRING = "YOUR_CONNECTION_STRING"
INDEX_NAME = "izzy-test-index"
NAMESPACE = "izzy_test_db.izzy_test_collection"
DB_NAME, COLLECTION_NAME = NAMESPACE.split(".")
os.environ["OPENAI_API_TYPE"] = "azure"
os.environ["OPENAI... | TextLoader(SOURCE_FILE_NAME) | langchain_community.document_loaders.TextLoader |
from typing import Optional
from langchain_experimental.autonomous_agents import BabyAGI
from langchain_openai import OpenAI, OpenAIEmbeddings
from langchain.docstore import InMemoryDocstore
from langchain_community.vectorstores import FAISS
embeddings_model = | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-robocorp')
from langchain.agents import AgentExecutor, OpenAIFunctionsAgent
from langchain_core.messages import SystemMessage
from langchain_openai import ChatOpenAI
from langchain_robocorp import ActionServerToolkit
llm = ChatOpenAI(model="g... | SystemMessage(content="You are a helpful assistant") | langchain_core.messages.SystemMessage |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet airbyte-source-stripe')
from langchain_community.document_loaders.airbyte import AirbyteStripeLoader
config = {
}
loader = AirbyteStripeLoader(
config=config, stream_name="invoices"
) # check the documentation linked above for a list of all stre... | Document(page_content=record.data["title"], metadata=record.data) | langchain.docstore.document.Document |
from langchain_community.tools.edenai import (
EdenAiExplicitImageTool,
EdenAiObjectDetectionTool,
EdenAiParsingIDTool,
EdenAiParsingInvoiceTool,
EdenAiSpeechToTextTool,
EdenAiTextModerationTool,
EdenAiTextToSpeechTool,
)
from langchain.agents import AgentType, initialize_agent
from langch... | EdenAiTextToSpeechTool(providers=["amazon"], language="en", voice="MALE") | langchain_community.tools.edenai.EdenAiTextToSpeechTool |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet dingodb')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet git+https://git@github.com/dingodb/pydingo.git')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
from langchain_community.document_lo... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install -qU chromadb langchain langchain-community langchain-openai')
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import RecursiveCharact... | RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.RecursiveCharacterTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet opencv-python scikit-image')
import os
from langchain_openai import OpenAI
os.environ["OPENAI_API_KEY"] = "<your-key-here>"
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.utilities.dalle_i... | DallEAPIWrapper() | langchain_community.utilities.dalle_image_generator.DallEAPIWrapper |
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
from langchain.prompts import PromptTemplate
from langchain_openai import OpenAI
template = """You are a chatbot having a conversation with a human.
{chat_history}
Human: {human_input}
Chatbot:"""
prompt = PromptTemplate(
... | OpenAI() | langchain_openai.OpenAI |
meals = [
"Beef Enchiladas with Feta cheese. Mexican-Greek fusion",
"Chicken Flatbreads with red sauce. Italian-Mexican fusion",
"Veggie sweet potato quesadillas with vegan cheese",
"One-Pan Tortelonni bake with peppers and onions",
]
from langchain_openai import OpenAI
llm = OpenAI(model="gpt-3.5-t... | rl_chain.ToSelectFrom(meals) | langchain_experimental.rl_chain.ToSelectFrom |
from typing import Callable, List
from langchain.memory import ConversationBufferMemory
from langchain.schema import (
AIMessage,
HumanMessage,
SystemMessage,
)
from langchain_openai import ChatOpenAI
from langchain.agents import AgentType, initialize_agent, load_tools
class DialogueAgent:
def __... | SystemMessage(content="You can make a topic more specific.") | langchain.schema.SystemMessage |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet titan-iris')
from langchain_community.llms import TitanTakeoff
llm = TitanTakeoff(
base_url="http://localhost:8000", generate_max_length=128, temperature=1.0
)
prompt = "What is the largest planet in the solar system?"
llm(prompt)
from langc... | PromptTemplate.from_template(template) | langchain.prompts.PromptTemplate.from_template |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet "cassio>=0.1.4"')
import os
from getpass import getpass
from datasets import (
load_dataset,
)
from langchain_community.document_loaders import PyPDFLoader
from langchain_core.documents import Document
from langchain_core.output_parsers import StrOu... | ChatOpenAI() | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from langchain.evaluation import load_evaluator
from langchain_openai import ChatOpenAI
evaluator = load_evaluator("labeled_score_string", llm= | ChatOpenAI(model="gpt-4") | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet rank_bm25')
from langchain.retrievers import BM25Retriever
retriever = BM25Retriever.from_texts(["foo", "bar", "world", "hello", "foo bar"])
from langchain_core.documents import Document
retriever = BM25Retriever.from_documents(
[
Docu... | Document(page_content="foo bar") | langchain_core.documents.Document |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-nvidia-ai-endpoints')
import getpass
import os
if not os.environ.get("NVIDIA_API_KEY", "").startswith("nvapi-"):
nvapi_key = getpass.getpass("Enter your NVIDIA API key: ")
assert nvapi_key.startswith("nvapi-"), f"{nvapi_key[:5]}... is ... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
get_ipython().system(' docker run -d -p 8123:8123 -p9000:9000 --name langchain-clickhouse-server --ulimit nofile=262144:262144 clickhouse/clickhouse-server:23.4.2.11')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet clickhouse-connect')
import getpass
import os
if not os.environ["OPENAI_API_KEY"]... | TextLoader("../../modules/state_of_the_union.txt") | langchain_community.document_loaders.TextLoader |
get_ipython().system('pip3 install cerebrium')
import os
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import CerebriumAI
os.environ["CEREBRIUMAI_API_KEY"] = "YOUR_KEY_HERE"
llm = CerebriumAI(endpoint_url="YOUR ENDPOINT URL HERE")
template ... | PromptTemplate.from_template(template) | langchain.prompts.PromptTemplate.from_template |
get_ipython().system("python3 -m pip install --upgrade langchain 'deeplake[enterprise]' openai tiktoken")
import getpass
import os
from langchain.chains import RetrievalQA
from langchain_community.vectorstores import DeepLake
from langchain_openai import OpenAI, OpenAIEmbeddings
from langchain_text_splitters impor... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
from langchain.indexes import SQLRecordManager, index
from langchain_core.documents import Document
from langchain_elasticsearch import ElasticsearchStore
from langchain_openai import OpenAIEmbeddings
collection_name = "test_index"
embedding = OpenAIEmbeddings()
vectorstore = ElasticsearchStore(
es_url="http:/... | index([], record_manager, vectorstore, cleanup="full", source_id_key="source") | langchain.indexes.index |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet google-api-python-client google-auth-httplib2 google-auth-oauthlib')
folder_id = "root"
get_ipython().run_line_magic('pip', 'install --upgrade --quiet unstructured')
from langchain_community.tools.google_drive.tool import GoogleDriveSearchTool
fro... | OpenAI(temperature=0) | langchain_openai.OpenAI |
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
from langchain_core.runnables import RunnableLambda
from langchain_openai import ChatOpenAI
examples = [
{
"input": "Could the members of The Police perform law... | ChatOpenAI(temperature=0) | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet praw')
client_id = ""
client_secret = ""
user_agent = ""
from langchain_community.tools.reddit_search.tool import RedditSearchRun
from langchain_community.utilities.reddit_search import RedditSearchAPIWrapper
search = RedditSearchRun(
api_wrapper... | LLMChain(llm=llm, prompt=prompt) | langchain.chains.LLMChain |
get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')
get_ipython().system('poetry run pip install replicate')
from getpass import getpass
REPLICATE_API_TOKEN = getpass()
import os
os.environ["REPLICATE_API_TOKEN"] = REPLICATE_API_TOKEN
from langchain.chains ... | LLMChain(llm=text2image, prompt=third_prompt) | langchain.chains.LLMChain |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet clickhouse-connect')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
os.environ["OPENAI_API_BASE"] = getpass.getpass("OpenAI Base:")
os.environ["MYSCALE_HOST"] = getpass.getpass("MyScale Host:")
os.environ["MY... | MyScale.from_documents(docs, embeddings) | langchain_community.vectorstores.MyScale.from_documents |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
import os
import uuid
uid = uuid.uuid4().hex[:6]
project_name = f"Run Fine-tuning Walkthrough {uid}"
os.environ["LANGCHAIN_TRACING_V2"] = "true"
os.environ["LANGCHAIN_API_KEY"] = "YOUR API KEY"
os.environ["LANGCHAIN_PROJECT"... | PydanticOutputFunctionsParser(pydantic_schema=Calculator) | langchain.output_parsers.openai_functions.PydanticOutputFunctionsParser |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain label-studio label-studio-sdk langchain-openai')
import os
os.environ["LABEL_STUDIO_URL"] = "<YOUR-LABEL-STUDIO-URL>" # e.g. http://localhost:8080
os.environ["LABEL_STUDIO_API_KEY"] = "<YOUR-LABEL-STUDIO-API-KEY>"
os.environ["OPENAI_API_KEY"... | LabelStudioCallbackHandler(project_name="My Project") | langchain.callbacks.LabelStudioCallbackHandler |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet runhouse')
import runhouse as rh
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import SelfHostedHuggingFaceLLM, SelfHostedPipeline
gpu = rh.cluster(name="rh-a10x", instance_type="A100:1... | PromptTemplate.from_template(template) | langchain.prompts.PromptTemplate.from_template |
from langchain_community.utils.openai_functions import (
convert_pydantic_to_openai_function,
)
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel, Field, validator
from langchain_openai import ChatOpenAI
class Joke(BaseModel):
"""Joke to tell user."""
... | JsonOutputFunctionsParser() | langchain.output_parsers.openai_functions.JsonOutputFunctionsParser |
get_ipython().system('pip install --upgrade langchain langchain-google-vertexai')
project: str = "PUT_YOUR_PROJECT_ID_HERE" # @param {type:"string"}
endpoint_id: str = "PUT_YOUR_ENDPOINT_ID_HERE" # @param {type:"string"}
location: str = "PUT_YOUR_ENDPOINT_LOCAtION_HERE" # @param {type:"string"}
from langchain_... | HumanMessage(content="Hi! Who are you?") | langchain_core.messages.HumanMessage |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langsmith langchainhub --quiet')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai tiktoken pandas duckduckgo-search --quiet')
import os
from uuid import uuid4
unique_id = uuid4().hex[0:8]
os.environ["LANGCHAIN_T... | OpenAIToolsAgentOutputParser() | langchain.agents.output_parsers.openai_tools.OpenAIToolsAgentOutputParser |
get_ipython().run_line_magic('pip', 'install -qU langchain langchain-openai langchain-anthropic langchain-community wikipedia')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
os.environ["ANTHROPIC_API_KEY"] = getpass.getpass()
from langchain_community.retrievers import WikipediaRetrieve... | RunnablePassthrough() | langchain_core.runnables.RunnablePassthrough |
from langchain.chains import LLMSummarizationCheckerChain
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=2)
text = """
Your 9-year old might like these recent discoveries made by The James Webb Space Telescope (JWST):
... | LLMSummarizationCheckerChain.from_llm(llm, max_checks=3, verbose=True) | langchain.chains.LLMSummarizationCheckerChain.from_llm |
get_ipython().system(' pip install -U langchain openai chromadb langchain-experimental # (newest versions required for multi-modal)')
get_ipython().system(' pip install "unstructured[all-docs]==0.10.19" pillow pydantic lxml pillow matplotlib tiktoken open_clip_torch torch')
path = "/Users/rlm/Desktop/photos/"
fr... | ChatOpenAI(temperature=0, model="gpt-4-vision-preview", max_tokens=1024) | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet airbyte-source-zendesk-support')
from langchain_community.document_loaders.airbyte import AirbyteZendeskSupportLoader
config = {
}
loader = AirbyteZendeskSupportLoader(
config=config, stream_name="tickets"
) # check the documentation linked abov... | Document(page_content=record.data["title"], metadata=record.data) | langchain.docstore.document.Document |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pgvector')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet psycopg2-binary')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet tiktoken')
im... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
from langchain_community.graphs import NeptuneGraph
host = "<neptune-host>"
port = 8182
use_https = True
graph = NeptuneGraph(host=host, port=port, use_https=use_https)
from langchain.chains import NeptuneOpenCypherQAChain
from langchain_openai import ChatOpenAI
llm = | ChatOpenAI(temperature=0, model="gpt-4") | langchain_openai.ChatOpenAI |
from langchain.retrievers import KNNRetriever
from langchain_openai import OpenAIEmbeddings
retriever = KNNRetriever.from_texts(
["foo", "bar", "world", "hello", "foo bar"], | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
import asyncio
import os
import nest_asyncio
import pandas as pd
from langchain.docstore.document import Document
from langchain_community.agent_toolkits.pandas.base import create_pandas_dataframe_agent
from langchain_experimental.autonomous_agents import AutoGPT
from langchain_openai import ChatOpenAI
nest_asyncio.a... | InMemoryDocstore({}) | langchain.docstore.InMemoryDocstore |
from langchain_openai import OpenAIEmbeddings
from langchain_pinecone import PineconeVectorStore
all_documents = {
"doc1": "Climate change and economic impact.",
"doc2": "Public health concerns due to climate change.",
"doc3": "Climate change: A social perspective.",
"doc4": "Technological solutions t... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain fleet-context langchain-openai pandas faiss-cpu # faiss-gpu for CUDA supported GPU')
from operator import itemgetter
from typing import Any, Optional, Type
import pandas as pd
from langchain.retrievers import MultiVectorRetriever
from langchai... | Document(page_content=text, metadata=metadata) | langchain_core.documents.Document |
from getpass import getpass
MOSAICML_API_TOKEN = getpass()
import os
os.environ["MOSAICML_API_TOKEN"] = MOSAICML_API_TOKEN
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import MosaicML
template = """Question: {question}"""
prompt = PromptTempla... | LLMChain(prompt=prompt, llm=llm) | langchain.chains.LLMChain |
import os
import yaml
get_ipython().system('wget https://raw.githubusercontent.com/openai/openai-openapi/master/openapi.yaml -O openai_openapi.yaml')
get_ipython().system('wget https://www.klarna.com/us/shopping/public/openai/v0/api-docs -O klarna_openapi.yaml')
get_ipython().system('wget https://raw.githubuserconte... | reduce_openapi_spec(raw_klarna_api_spec) | langchain_community.agent_toolkits.openapi.spec.reduce_openapi_spec |
from langchain.chains import GraphCypherQAChain
from langchain_community.graphs import Neo4jGraph
from langchain_openai import ChatOpenAI
graph = Neo4jGraph(
url="bolt://localhost:7687", username="neo4j", password="pleaseletmein"
)
graph.query(
"""
MERGE (m:Movie {name:"Top Gun"})
WITH m
UNWIND ["Tom Cruis... | ChatOpenAI(temperature=0, model="gpt-3.5-turbo-16k") | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet supabase')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
os.environ["SUPABASE_URL"] = getpass.getpass("Supabase URL:")
os.environ["SUPABASE_SERVICE_KEY"] = getpass.getpass("Supabase Service Key:")
fro... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet marqo')
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Marqo
from langchain_text_splitters import CharacterTextSplitter
from langchain_community.document_loaders import TextLoader
loader = Text... | OpenAI(temperature=0) | langchain_openai.OpenAI |
get_ipython().run_line_magic('pip', 'install laser_encoders')
from langchain_community.embeddings.laser import LaserEmbeddings
embeddings = | LaserEmbeddings(lang="eng_Latn") | langchain_community.embeddings.laser.LaserEmbeddings |
get_ipython().run_line_magic('pip', 'install -qU langchain-text-splitters')
from langchain_text_splitters import HTMLHeaderTextSplitter
html_string = """
<!DOCTYPE html>
<html>
<body>
<div>
<h1>Foo</h1>
<p>Some intro text about Foo.</p>
<div>
<h2>Bar main section</h2>
... | HTMLHeaderTextSplitter(headers_to_split_on=headers_to_split_on) | langchain_text_splitters.HTMLHeaderTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet usearch')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import USearch
from langchain_openai import OpenAIE... | TextLoader("../../../extras/modules/state_of_the_union.txt") | langchain_community.document_loaders.TextLoader |
get_ipython().system(' pip install langchain replicate')
from langchain_community.chat_models import ChatOllama
llama2_chat = ChatOllama(model="llama2:13b-chat")
llama2_code = ChatOllama(model="codellama:7b-instruct")
from langchain_community.llms import Replicate
replicate_id = "meta/llama-2-13b-chat:f4e2de70d66... | ConversationBufferMemory(return_messages=True) | langchain.memory.ConversationBufferMemory |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet opencv-python scikit-image')
import os
from langchain_openai import OpenAI
os.environ["OPENAI_API_KEY"] = "<your-key-here>"
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.utilities.dalle_i... | OpenAI(temperature=0.9) | langchain_openai.OpenAI |
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