prompt stringlengths 43 25.9k | completion stringlengths 7 362 | api stringlengths 18 90 |
|---|---|---|
from langchain_community.llms import DeepSparse
llm = | DeepSparse(
model="zoo:nlg/text_generation/codegen_mono-350m/pytorch/huggingface/bigpython_bigquery_thepile/base-none"
) | langchain_community.llms.DeepSparse |
from langchain.prompts import PromptTemplate
prompt = (
PromptTemplate.from_template("Tell me a joke about {topic}")
+ ", make it funny"
+ "\n\nand in {language}"
)
prompt
prompt.format(topic="sports", language="spanish")
from langchain.chains import LLMChain
from langchain_openai import ChatOpenAI... | ChatOpenAI() | langchain_openai.ChatOpenAI |
from langchain.chains import HypotheticalDocumentEmbedder, LLMChain
from langchain.prompts import PromptTemplate
from langchain_openai import OpenAI, OpenAIEmbeddings
base_embeddings = OpenAIEmbeddings()
llm = OpenAI()
embeddings = HypotheticalDocumentEmbedder.from_llm(llm, base_embeddings, "web_search")
result ... | OpenAI(n=4, best_of=4) | langchain_openai.OpenAI |
from langchain.evaluation import load_evaluator
evaluator = | load_evaluator("embedding_distance") | langchain.evaluation.load_evaluator |
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... | load_tools(["serpapi", "llm-math"], llm=llm) | langchain.agents.load_tools |
get_ipython().run_line_magic('pip', 'install --quiet pypdf chromadb tiktoken openai')
get_ipython().run_line_magic('pip', 'uninstall -y langchain-fireworks')
get_ipython().run_line_magic('pip', 'install --editable /mnt/disks/data/langchain/libs/partners/fireworks')
import fireworks
print(fireworks)
import fireworks.... | RunnablePassthrough() | langchain_core.runnables.RunnablePassthrough |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet spacy')
from langchain_community.embeddings.spacy_embeddings import SpacyEmbeddings
embedder = | SpacyEmbeddings(model_name="en_core_web_sm") | langchain_community.embeddings.spacy_embeddings.SpacyEmbeddings |
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... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
from typing import List
from langchain.output_parsers import PydanticOutputParser
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_openai import ChatOpenAI
class Actor(BaseModel):
name: str = | Field(description="name of an actor") | langchain_core.pydantic_v1.Field |
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... | RunnableLambda(format_docs_with_id) | langchain_core.runnables.RunnableLambda |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from typing import Iterator, List
from langchain.prompts.chat import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_openai import ChatOpenAI
prompt = ChatPromptTemplate.from_temp... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet clearml')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pandas')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet textstat')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet spacy')
get_ipython().system('pyth... | OpenAI(temperature=0, callbacks=callbacks) | langchain_openai.OpenAI |
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
import dspy
colbertv2 = dspy.ColBERTv2(url="http://20.102.90.50:2017/wiki17_abstracts")
from langchain.cache import SQLiteCache
from langchain.globals import set_llm_cache
from langchain_openai import OpenAI
set_llm_cache(SQLiteCache(data... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
from langchain.evaluation import ExactMatchStringEvaluator
evaluator = ExactMatchStringEvaluator()
from langchain.evaluation import load_evaluator
evaluator = | load_evaluator("exact_match") | langchain.evaluation.load_evaluator |
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"]... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
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.BasedOn(["Vegetarian", "regular dairy is ok"]) | langchain_experimental.rl_chain.BasedOn |
from langchain_community.llms.fake import FakeListLLM
from langchain.agents import AgentType, initialize_agent, load_tools
tools = load_tools(["python_repl"])
responses = ["Action: Python REPL\nAction Input: print(2 + 2)", "Final Answer: 4"]
llm = | FakeListLLM(responses=responses) | langchain_community.llms.fake.FakeListLLM |
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... | op.desanitize(x["response"], x["secure_context"]) | langchain_community.utilities.opaqueprompts.desanitize |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet GitPython')
from git import Repo
repo = Repo.clone_from(
"https://github.com/langchain-ai/langchain", to_path="./example_data/test_repo1"
)
branch = repo.head.reference
from langchain_community.document_loaders import GitLoader
loader = | GitLoader(repo_path="./example_data/test_repo1/", branch=branch) | langchain_community.document_loaders.GitLoader |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet apify-client langchain-openai langchain chromadb tiktoken')
from langchain.indexes import VectorstoreIndexCreator
from langchain_community.document_loaders.base import Document
from langchain_community.utilities import ApifyWrapper
import os
os.envi... | ApifyWrapper() | langchain_community.utilities.ApifyWrapper |
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... | OpenAI(temperature=0.9, callbacks=callbacks) | langchain_openai.OpenAI |
get_ipython().system('pip3 install tcvectordb')
from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings.fake import FakeEmbeddings
from langchain_community.vectorstores import TencentVectorDB
from langchain_community.vectorstores.tencentvectordb import ConnectionParams
from lan... | TencentVectorDB(embeddings, conn_params) | langchain_community.vectorstores.TencentVectorDB |
from langchain.agents import AgentExecutor, Tool, ZeroShotAgent
from langchain.chains import LLMChain
from langchain.memory import ConversationBufferMemory
from langchain_community.chat_message_histories import RedisChatMessageHistory
from langchain_community.utilities import GoogleSearchAPIWrapper
from langchain_opena... | ZeroShotAgent(llm_chain=llm_chain, tools=tools, verbose=True) | langchain.agents.ZeroShotAgent |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pygithub')
import os
from langchain.agents import AgentType, initialize_agent
from langchain_community.agent_toolkits.github.toolkit import GitHubToolkit
from langchain_community.utilities.github import GitHubAPIWrapper
from langchain_openai import Ch... | tracing_v2_enabled(project_name="Github_Demo_PR", tags=["PR_bot"]) | langchain_core.tracers.context.tracing_v2_enabled |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet semanticscholar')
from langchain import hub
from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain_openai import ChatOpenAI
instructions = """You are an expert researcher."""
base_prompt = hub.pull("langchain-ai/openai... | create_openai_functions_agent(llm, tools, prompt) | langchain.agents.create_openai_functions_agent |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet yfinance')
import os
os.environ["OPENAI_API_KEY"] = "..."
from langchain.agents import AgentType, initialize_agent
from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool
from langchain_openai import ChatOpenAI
llm = ChatOpenAI... | YahooFinanceNewsTool() | langchain_community.tools.yahoo_finance_news.YahooFinanceNewsTool |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pymysql')
from langchain.chains import RetrievalQA
from langchain_community.document_loaders import (
DirectoryLoader,
UnstructuredMarkdownLoader,
)
from langchain_community.vectorstores import StarRocks
from langchain_community.vectorstores.sta... | StarRocks.from_documents(split_docs, embeddings, config=settings) | langchain_community.vectorstores.StarRocks.from_documents |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet google-cloud-translate')
from langchain_community.document_transformers import GoogleTranslateTransformer
from langchain_core.documents import Document
sample_text = """[Generated with Google Bard]
Subject: Key Business Process Updates
Date: Friday, ... | Document(page_content=sample_text) | langchain_core.documents.Document |
from langchain_community.document_loaders import NewsURLLoader
urls = [
"https://www.bbc.com/news/world-us-canada-66388172",
"https://www.bbc.com/news/entertainment-arts-66384971",
]
loader = | NewsURLLoader(urls=urls) | langchain_community.document_loaders.NewsURLLoader |
from langchain.chains import RetrievalQA
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
loader = TextLoader("../../state_of_the_union.txt", encoding... | ChatPromptTemplate(messages=prompt_messages) | langchain.prompts.chat.ChatPromptTemplate |
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[... | PromptTemplate.from_template(template=PROMPT_TEMPLATE) | langchain.prompts.PromptTemplate.from_template |
import warnings
warnings.filterwarnings("ignore")
import os
from langchain.agents.agent_toolkits import create_conversational_retrieval_agent
from langchain_community.agent_toolkits import CogniswitchToolkit
from langchain_openai import ChatOpenAI
cs_token = "Your CogniSwitch token"
OAI_token = "Your OpenAI API t... | create_conversational_retrieval_agent(llm, tool_lst, verbose=False) | langchain.agents.agent_toolkits.create_conversational_retrieval_agent |
import getpass
import os
os.environ["TAVILY_API_KEY"] = getpass.getpass()
from langchain.retrievers.tavily_search_api import TavilySearchAPIRetriever
retriever = | TavilySearchAPIRetriever(k=3) | langchain.retrievers.tavily_search_api.TavilySearchAPIRetriever |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from langchain.prompts import PromptTemplate
from langchain_core.runnables import ConfigurableField
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0).configurable_fields(
temperature=ConfigurableF... | ChatOpenAI() | langchain_openai.ChatOpenAI |
get_ipython().system('pip3 install clickhouse-sqlalchemy InstructorEmbedding sentence_transformers openai langchain-experimental')
import getpass
from os import environ
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.utilities import SQLDatabase
from langch... | StdOutCallbackHandler() | langchain.callbacks.StdOutCallbackHandler |
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... | RequestsWrapper(headers=headers) | langchain.requests.RequestsWrapper |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet tiledb-vector-search')
from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import TileDB
from langchain_text_splitters import CharacterTextSpl... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
import os
import chromadb
from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors import DocumentCompressorPipeline
from langchain.retrievers.merger_retriever import MergerRetriever
from langchain_community.document_transformers import (
EmbeddingsClusteringFi... | DocumentCompressorPipeline(transformers=[filter, reordering]) | langchain.retrievers.document_compressors.DocumentCompressorPipeline |
import pprint
from typing import Any, Dict
import pandas as pd
from langchain.output_parsers import PandasDataFrameOutputParser
from langchain.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0)
def format_parser_output(parser_output: Dict[str, Any]) -> None:
... | PandasDataFrameOutputParser(dataframe=df) | langchain.output_parsers.PandasDataFrameOutputParser |
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"... | Field(..., description="+,-,*,/") | langchain_core.pydantic_v1.Field |
from langchain.tools import ShellTool
shell_tool = | ShellTool() | langchain.tools.ShellTool |
from typing import List
from langchain.output_parsers import PydanticOutputParser
from langchain.prompts import PromptTemplate
from langchain_core.pydantic_v1 import BaseModel, Field, validator
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0)
class Joke(BaseModel):
setup: str = Field(d... | Field(description="list of names of films they starred in") | langchain_core.pydantic_v1.Field |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet python-gitlab')
import os
from langchain.agents import AgentType, initialize_agent
from langchain_community.agent_toolkits.gitlab.toolkit import GitLabToolkit
from langchain_community.utilities.gitlab import GitLabAPIWrapper
from langchain_openai impo... | GitLabAPIWrapper() | langchain_community.utilities.gitlab.GitLabAPIWrapper |
from typing import List, Optional
from langchain.chains.openai_tools import create_extraction_chain_pydantic
from langchain_core.pydantic_v1 import BaseModel
from langchain_openai import ChatOpenAI
model = ChatOpenAI(model="gpt-3.5-turbo-1106")
class Person(BaseModel):
"""Information about people to extract.""... | create_extraction_chain_pydantic([Person, Class], model) | langchain.chains.openai_tools.create_extraction_chain_pydantic |
from langchain.memory import ConversationKGMemory
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
memory = ConversationKGMemory(llm=llm)
memory.save_context({"input": "say hi to sam"}, {"output": "who is sam"})
memory.save_context({"input": "sam is a friend"}, {"output": "okay"})
memory.load_memory_... | PromptTemplate(input_variables=["history", "input"], template=template) | langchain.prompts.prompt.PromptTemplate |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet dashvector dashscope')
import getpass
import os
os.environ["DASHVECTOR_API_KEY"] = getpass.getpass("DashVector API Key:")
os.environ["DASHSCOPE_API_KEY"] = getpass.getpass("DashScope API Key:")
from langchain_community.embeddings.dashscope import Da... | DashVector.from_documents(docs, embeddings) | langchain_community.vectorstores.DashVector.from_documents |
get_ipython().system('pip3 install clickhouse-sqlalchemy InstructorEmbedding sentence_transformers openai langchain-experimental')
import getpass
from os import environ
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.utilities import SQLDatabase
from langch... | OpenAI(openai_api_key=OPENAI_API_KEY, temperature=0) | langchain_openai.OpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet yfinance')
import os
os.environ["OPENAI_API_KEY"] = "..."
from langchain.agents import AgentType, initialize_agent
from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool
from langchain_openai import ChatOpenAI
llm = | ChatOpenAI(temperature=0.0) | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pyvespa')
from vespa.package import ApplicationPackage, Field, RankProfile
app_package = ApplicationPackage(name="testapp")
app_package.schema.add_fields(
Field(
name="text", type="string", indexing=["index", "summary"], index="enable-bm25"... | VespaStore.from_documents(docs, embedding_function, app=vespa_app, **vespa_config) | langchain_community.vectorstores.VespaStore.from_documents |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet jsonformer > /dev/null')
import logging
logging.basicConfig(level=logging.ERROR)
import json
import os
import requests
from langchain.tools import tool
HF_TOKEN = os.environ.get("HUGGINGFACE_API_KEY")
@tool
def ask_star_coder(query: str, temperat... | HuggingFacePipeline(pipeline=hf_model) | langchain_community.llms.HuggingFacePipeline |
from langchain.agents import Tool
from langchain_experimental.utilities import PythonREPL
python_repl = PythonREPL()
python_repl.run("print(1+1)")
repl_tool = | Tool(
name="python_repl",
description="A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...) | langchain.agents.Tool |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet sqlite-vss')
from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings.sentence_transformer import (
SentenceTransformerEmbeddings,
)
from langchain_community.vectorstores import SQLiteVSS
from langchain_text_sp... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet wandb')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pandas')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet textstat')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet spacy')
get_ipython().system('python... | OpenAI(temperature=0, callbacks=callbacks) | langchain_openai.OpenAI |
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."""
... | Field(description="answer to resolve the joke") | langchain_core.pydantic_v1.Field |
import re
from typing import Union
from langchain.agents import (
AgentExecutor,
AgentOutputParser,
LLMSingleActionAgent,
)
from langchain.chains import LLMChain
from langchain.prompts import StringPromptTemplate
from langchain_community.agent_toolkits import NLAToolkit
from langchain_community.tools.plugi... | LLMChain(llm=llm, prompt=prompt) | langchain.chains.LLMChain |
from langchain.chains import RetrievalQAWithSourcesChain
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores.jaguar import Jaguar
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables im... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain pypdf pymongo langchain-openai tiktoken')
import getpass
MONGODB_ATLAS_CLUSTER_URI = getpass.getpass("MongoDB Atlas Cluster URI:")
from pymongo im... | OpenAIEmbeddings(disallowed_special=()) | langchain_openai.OpenAIEmbeddings |
from langchain.indexes import VectorstoreIndexCreator
from langchain_community.document_loaders import ModernTreasuryLoader
modern_treasury_loader = ModernTreasuryLoader("payment_orders")
index = | VectorstoreIndexCreator() | langchain.indexes.VectorstoreIndexCreator |
from langchain_community.embeddings.fake import FakeEmbeddings
from langchain_community.vectorstores import Tair
from langchain_text_splitters import CharacterTextSplitter
from langchain_community.document_loaders import TextLoader
loader = TextLoader("../../modules/state_of_the_union.txt")
documents = loader.load()... | Tair.drop_index(tair_url=tair_url) | langchain_community.vectorstores.Tair.drop_index |
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="baz", metadata={"id": 3}) | langchain.docstore.document.Document |
from IPython.display import SVG
from langchain_experimental.cpal.base import CPALChain
from langchain_experimental.pal_chain import PALChain
from langchain_openai import OpenAI
llm = OpenAI(temperature=0, max_tokens=512)
cpal_chain = | CPALChain.from_univariate_prompt(llm=llm, verbose=True) | langchain_experimental.cpal.base.CPALChain.from_univariate_prompt |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet wikipedia')
from langchain import hub
from langchain.agents import AgentExecutor, create_react_agent
from langchain_community.tools import WikipediaQueryRun
from langchain_community.utilities import WikipediaAPIWrapper
from langchain_openai import OpenAI... | create_react_agent(llm, tools, prompt) | langchain.agents.create_react_agent |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pymysql')
get_ipython().system('pip install sqlalchemy')
get_ipython().system('pip install langchain')
from langchain.chains import RetrievalQA
from langchain_community.document_loaders import (
DirectoryLoader,
UnstructuredMarkdownLoader,
)
... | TokenTextSplitter(chunk_size=400, chunk_overlap=50) | langchain_text_splitters.TokenTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet sqlite-vss')
from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings.sentence_transformer import (
SentenceTransformerEmbeddings,
)
from langchain_community.vectorstores import SQLiteVSS
from langchain_text_sp... | TextLoader("../../modules/state_of_the_union.txt") | langchain_community.document_loaders.TextLoader |
import requests
def download_drive_file(url: str, output_path: str = "chat.db") -> None:
file_id = url.split("/")[-2]
download_url = f"https://drive.google.com/uc?export=download&id={file_id}"
response = requests.get(download_url)
if response.status_code != 200:
print("Failed to download the ... | convert_messages_for_finetuning(chat_sessions) | langchain.adapters.openai.convert_messages_for_finetuning |
from langchain.retrievers.multi_vector import MultiVectorRetriever
from langchain.storage import InMemoryByteStore
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import Recursiv... | ChatOpenAI(max_retries=0, model="gpt-4") | langchain_openai.ChatOpenAI |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai wikipedia')
from operator import itemgetter
from langchain.agents import AgentExecutor, load_tools
from langchain.agents.format_scratchpad import format_to_openai_function_messages
from langchain.agents.output_parsers import O... | ChatOpenAI(model="gpt-3.5-turbo") | langchain_openai.ChatOpenAI |
from langchain.chains import RetrievalQA
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
loader = TextLoader("../../state_of_the_union.txt", encoding... | HumanMessagePromptTemplate.from_template("{context}") | langchain.prompts.chat.HumanMessagePromptTemplate.from_template |
from langchain_community.document_loaders.blob_loaders.youtube_audio import (
YoutubeAudioLoader,
)
from langchain_community.document_loaders.generic import GenericLoader
from langchain_community.document_loaders.parsers import (
OpenAIWhisperParser,
OpenAIWhisperParserLocal,
)
get_ipython().run_line_mag... | YoutubeAudioLoader(urls, save_dir) | langchain_community.document_loaders.blob_loaders.youtube_audio.YoutubeAudioLoader |
from langchain.prompts import PromptTemplate
prompt = (
PromptTemplate.from_template("Tell me a joke about {topic}")
+ ", make it funny"
+ "\n\nand in {language}"
)
prompt
prompt.format(topic="sports", language="spanish")
from langchain.chains import LLMChain
from langchain_openai import ChatOpenAI... | LLMChain(llm=model, prompt=prompt) | langchain.chains.LLMChain |
from langchain_community.document_loaders import WebBaseLoader
loader_web = WebBaseLoader(
"https://github.com/basecamp/handbook/blob/master/37signals-is-you.md"
)
from langchain_community.document_loaders import PyPDFLoader
loader_pdf = | PyPDFLoader("../MachineLearning-Lecture01.pdf") | langchain_community.document_loaders.PyPDFLoader |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from langchain.evaluation import load_evaluator
evaluator = load_evaluator("trajectory")
import subprocess
from urllib.parse import urlparse
from langchain.agents import AgentType, initialize_agent
from langchain.tools ... | load_evaluator("trajectory", llm=eval_llm) | langchain.evaluation.load_evaluator |
from langchain_community.llms import KoboldApiLLM
llm = | KoboldApiLLM(endpoint="http://192.168.1.144:5000", max_length=80) | langchain_community.llms.KoboldApiLLM |
from langchain.chains import ConversationChain
from langchain.memory import ConversationBufferMemory
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
conversation = ConversationChain(
llm=llm, verbose=True, memory=ConversationBufferMemory()
)
conversation.predict(input="Hi there!")
conversati... | PromptTemplate(input_variables=["history", "input"], template=template) | langchain.prompts.prompt.PromptTemplate |
from langchain.chains import RetrievalQA
from langchain_community.vectorstores import Chroma
from langchain_openai import OpenAI, OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter
llm = OpenAI(temperature=0)
from pathlib import Path
relevant_parts = []
for p in Path(".").absolute().parts:
... | Chroma.from_documents(texts, embeddings, collection_name="state-of-union") | langchain_community.vectorstores.Chroma.from_documents |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
import os
os.environ["OUTLINE_API_KEY"] = "xxx"
os.environ["OUTLINE_INSTANCE_URL"] = "https://app.getoutline.com"
from langchain.retrievers import OutlineRetriever
retriever = OutlineRetriever()
retriever.get_releva... | ConversationalRetrievalChain.from_llm(model, retriever=retriever) | langchain.chains.ConversationalRetrievalChain.from_llm |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet wandb')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet pandas')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet textstat')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet spacy')
get_ipython().system('python... | PromptTemplate(input_variables=["title"], template=template) | langchain.prompts.PromptTemplate |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet banana-dev')
import os
os.environ["BANANA_API_KEY"] = "YOUR_API_KEY"
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.llms import Banana
template = """Question: {question}
Answer: Let's th... | PromptTemplate.from_template(template) | langchain.prompts.PromptTemplate.from_template |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet neo4j')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet tiktoken')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Ke... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
from langchain.chains import HypotheticalDocumentEmbedder, LLMChain
from langchain.prompts import PromptTemplate
from langchain_openai import OpenAI, OpenAIEmbeddings
base_embeddings = OpenAIEmbeddings()
llm = OpenAI()
embeddings = HypotheticalDocumentEmbedder.from_llm(llm, base_embeddings, "web_search")
result ... | CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) | langchain_text_splitters.CharacterTextSplitter |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet networkx')
from langchain.indexes import GraphIndexCreator
from langchain_openai import OpenAI
index_creator = GraphIndexCreator(llm=OpenAI(temperature=0))
with open("../../../modules/state_of_the_union.txt") as f:
all_text = f.read()
text = ... | OpenAI(temperature=0) | langchain_openai.OpenAI |
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... | ModerationPromptSafetyConfig(threshold=0.5) | langchain_experimental.comprehend_moderation.ModerationPromptSafetyConfig |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet duckduckgo-search')
from langchain.tools import DuckDuckGoSearchRun
search = | DuckDuckGoSearchRun() | langchain.tools.DuckDuckGoSearchRun |
import os
import chromadb
from langchain.retrievers import ContextualCompressionRetriever
from langchain.retrievers.document_compressors import DocumentCompressorPipeline
from langchain.retrievers.merger_retriever import MergerRetriever
from langchain_community.document_transformers import (
EmbeddingsClusteringFi... | EmbeddingsRedundantFilter(embeddings=filter_embeddings) | langchain_community.document_transformers.EmbeddingsRedundantFilter |
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0, model="gpt-4-turbo-preview")
from langchain import hub
from langchain_core.prompts import PromptTemplate
select_prompt = hub.pull("hwchase17/self-discovery-select")
select_prompt.pretty_print()
adapt_prompt = | hub.pull("hwchase17/self-discovery-adapt") | langchain.hub.pull |
get_ipython().system('pip install -U openai langchain langchain-experimental')
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_openai import ChatOpenAI
chat = ChatOpenAI(model="gpt-4-vision-preview", max_tokens=256)
chat.invoke(
[
HumanMessage(
content=[
... | Field(description="The city and state, e.g. San Francisco, CA") | langchain_core.pydantic_v1.Field |
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 ... | RunnablePassthrough() | langchain_core.runnables.RunnablePassthrough |
SOURCE = "test" # @param {type:"Query"|"CollectionGroup"|"DocumentReference"|"string"}
get_ipython().run_line_magic('pip', 'install -upgrade --quiet langchain-google-datastore')
PROJECT_ID = "my-project-id" # @param {type:"string"}
get_ipython().system('gcloud config set project {PROJECT_ID}')
from goo... | DatastoreLoader("Collection") | langchain_google_datastore.DatastoreLoader |
from langchain.memory import ConversationKGMemory
from langchain_openai import OpenAI
llm = | OpenAI(temperature=0) | langchain_openai.OpenAI |
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0, model="gpt-4-turbo-preview")
from langchain import hub
from langchain_core.prompts import PromptTemplate
select_prompt = | hub.pull("hwchase17/self-discovery-select") | langchain.hub.pull |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet neo4j')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain-openai')
get_ipython().run_line_magic('pip', 'install --upgrade --quiet tiktoken')
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Ke... | ChatOpenAI(temperature=0) | langchain_openai.ChatOpenAI |
from langchain.chains import RetrievalQAWithSourcesChain
from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores.jaguar import Jaguar
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables im... | TextLoader("../../modules/state_of_the_union.txt") | langchain_community.document_loaders.TextLoader |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet U lark elasticsearch')
import getpass
import os
from langchain_core.documents import Document
from langchain_elasticsearch import ElasticsearchStore
from langchain_openai import OpenAIEmbeddings
os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI AP... | OpenAI(temperature=0) | langchain_openai.OpenAI |
from langchain.callbacks import get_openai_callback
from langchain_openai import ChatOpenAI
llm = ChatOpenAI(model_name="gpt-4")
with | get_openai_callback() | langchain.callbacks.get_openai_callback |
import os
os.environ["OCTOAI_API_TOKEN"] = "OCTOAI_API_TOKEN"
os.environ["ENDPOINT_URL"] = "https://text.octoai.run/v1/chat/completions"
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_community.llms.octoai_endpoint import OctoAIEndpoint
template = """Below is an ... | PromptTemplate.from_template(template) | langchain.prompts.PromptTemplate.from_template |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet opensearch-py')
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 OpenSearchVectorSearch
from langchain_... | OpenAIEmbeddings() | langchain_openai.OpenAIEmbeddings |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet langchain langchain-openai')
from langchain.prompts import PromptTemplate
from langchain_core.runnables import ConfigurableField
from langchain_openai import ChatOpenAI
model = ChatOpenAI(temperature=0).configurable_fields(
temperature=ConfigurableF... | ChatAnthropic(temperature=0) | langchain_community.chat_models.ChatAnthropic |
get_ipython().run_line_magic('pip', 'install --upgrade --quiet wikipedia')
from langchain import hub
from langchain.agents import AgentExecutor, create_react_agent
from langchain_community.tools import WikipediaQueryRun
from langchain_community.utilities import WikipediaAPIWrapper
from langchain_openai import OpenAI... | AgentExecutor(agent=agent, tools=tools, verbose=True) | langchain.agents.AgentExecutor |
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... | OpenAI() | langchain_openai.OpenAI |
get_ipython().run_line_magic('pip', 'install --quiet pypdf chromadb tiktoken openai')
get_ipython().run_line_magic('pip', 'uninstall -y langchain-fireworks')
get_ipython().run_line_magic('pip', 'install --editable /mnt/disks/data/langchain/libs/partners/fireworks')
import fireworks
print(fireworks)
import fireworks.... | StrOutputParser() | langchain_core.output_parsers.StrOutputParser |
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