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84ab24a8de5f-2 | h=this||self;function l(){return void 0!==window.google&&void 0!==window.google.kOPI&&0!==window.google.kOPI?window.google.kOPI:null};var m,n=[];function p(a){for(var b;a&&(!a.getAttribute||!(b=a.getAttribute("eid")));)a=a.parentNode;return b||m}function q(a){for(var b=null;a&&(!a.getAttribute||!(b=a.getAttribute("leid... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
84ab24a8de5f-3 | 8px 0}td{line-height:.8em}.gac_m td{line-height:17px}form{margin-bottom:20px}.h{color:#1558d6}em{font-weight:bold;font-style:normal}.lst{height:25px;width:496px}.gsfi,.lst{font:18px arial,sans-serif}.gsfs{font:17px arial,sans-serif}.ds{display:inline-box;display:inline-block;margin:3px 0 4px;margin-left:4px}input{font-... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
84ab24a8de5f-4 | id="mngb"><div id=gbar><nobr><b class=gb1>Search</b> <a class=gb1 href="https://www.google.com/imghp?hl=en&tab=wi">Images</a> <a class=gb1 href="https://maps.google.com/maps?hl=en&tab=wl">Maps</a> <a class=gb1 href="https://play.google.com/?hl=en&tab=w8">Play</a> <a class=gb1 href="https://www.youtube.com/?tab=w1">YouT... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
84ab24a8de5f-5 | XMLHttpRequest)b="2";else if("undefined"!=typeof ActiveXObject){var c,d,e=["MSXML2.XMLHTTP.6.0","MSXML2.XMLHTTP.3.0","MSXML2.XMLHTTP","Microsoft.XMLHTTP"];for(c=0;d=e[c++];)try{new ActiveXObject(d),b="2"}catch(h){}}a=b;if("2"==a&&-1==location.search.indexOf("&gbv=2")){var f=google.gbvu,g=document.getElementById("gbv");... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
84ab24a8de5f-6 | this.g+""};var l={};\nfunction p(){var c=u,g=function(){};google.lx=google.stvsc?g:function(){google.timers&&google.timers.load&&google.tick&&google.tick("load","xjsls");var a=document;var b="SCRIPT";"application/xhtml+xml"===a.contentType&&(b=b.toLowerCase());b=a.createElement(b);a=null===c?"null":void 0===c?"undefine... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
84ab24a8de5f-7 | previous
Python REPL
next
SceneXplain
Contents
Inside the tool
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 08, 2023. | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/requests.html |
4d437b81694d-0 | .ipynb
.pdf
Wikipedia
Wikipedia#
Wikipedia is a multilingual free online encyclopedia written and maintained by a community of volunteers, known as Wikipedians, through open collaboration and using a wiki-based editing system called MediaWiki. Wikipedia is the largest and most-read reference work in history.
First, you... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/wikipedia.html |
4d437b81694d-1 | 'Page: Hunter × Hunter\nSummary: Hunter × Hunter (stylized as HUNTER×HUNTER and pronounced "hunter hunter") is a Japanese manga series written and illustrated by Yoshihiro Togashi. It has been serialized in Shueisha\'s shōnen manga magazine Weekly Shōnen Jump since March 1998, although the manga has frequently gone on ... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/wikipedia.html |
4d437b81694d-2 | sung by Japanese duo Yuzu in episodes 59 to 75, "Nagareboshi Kirari" also sung by Yuzu from episode 76 to 98, which was originally from the anime film adaptation, Hunter × Hunter: Phantom Rouge, and "Hyōri Ittai" by Yuzu featuring Hyadain from episode 99 to 146, which was also used in the film Hunter × Hunter: The Last... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/wikipedia.html |
4d437b81694d-3 | previous
Twilio
next
Wolfram Alpha
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 08, 2023. | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/wikipedia.html |
cf40366cfd2b-0 | .ipynb
.pdf
Google Places
Google Places#
This notebook goes through how to use Google Places API
#!pip install googlemaps
import os
os.environ["GPLACES_API_KEY"] = ""
from langchain.tools import GooglePlacesTool
places = GooglePlacesTool()
places.run("al fornos")
"1. Delfina Restaurant\nAddress: 3621 18th St, San Franc... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_places.html |
2e1ee50303de-0 | .ipynb
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IFTTT WebHooks
Contents
Creating a webhook
Configuring the “If This”
Configuring the “Then That”
Finishing up
IFTTT WebHooks#
This notebook shows how to use IFTTT Webhooks.
From https://github.com/SidU/teams-langchain-js/wiki/Connecting-IFTTT-Services.
Creating a webhook#
Go to https://ifttt.com/create
Co... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/ifttt.html |
d2e833c6e3e7-0 | .ipynb
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Human as a tool
Contents
Configuring the Input Function
Human as a tool#
Human are AGI so they can certainly be used as a tool to help out AI agent
when it is confused.
from langchain.chat_models import ChatOpenAI
from langchain.llms import OpenAI
from langchain.agents import load_tools, initialize_agent
... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/human_tools.html |
d2e833c6e3e7-1 | Action Input: "Who said 'Veni, vidi, vici'?"
Observation: Updated on September 06, 2019. "Veni, vidi, vici" is a famous phrase said to have been spoken by the Roman Emperor Julius Caesar (100-44 BCE) in a bit of stylish bragging that impressed many of the writers of his day and beyond. The phrase means roughly "I came,... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/human_tools.html |
c9c12c6b42e5-0 | .ipynb
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OpenWeatherMap API
Contents
Use the wrapper
Use the tool
OpenWeatherMap API#
This notebook goes over how to use the OpenWeatherMap component to fetch weather information.
First, you need to sign up for an OpenWeatherMap API key:
Go to OpenWeatherMap and sign up for an API key here
pip install pyowm
Then w... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/openweathermap.html |
9bdce3217bfb-0 | .ipynb
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SceneXplain
Contents
Usage in an Agent
SceneXplain#
SceneXplain is an ImageCaptioning service accessible through the SceneXplain Tool.
To use this tool, you’ll need to make an account and fetch your API Token from the website. Then you can instantiate the tool.
import os
os.environ["SCENEX_API_KEY"] = "<Y... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/sceneXplain.html |
21b6e6eede13-0 | .ipynb
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Wolfram Alpha
Wolfram Alpha#
This notebook goes over how to use the wolfram alpha component.
First, you need to set up your Wolfram Alpha developer account and get your APP ID:
Go to wolfram alpha and sign up for a developer account here
Create an app and get your APP ID
pip install wolframalpha
Then we wil... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/wolfram_alpha.html |
90773ffc0447-0 | .ipynb
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Python REPL
Python REPL#
Sometimes, for complex calculations, rather than have an LLM generate the answer directly, it can be better to have the LLM generate code to calculate the answer, and then run that code to get the answer. In order to easily do that, we provide a simple Python REPL to execute command... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/python.html |
cb9f80144748-0 | .ipynb
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Shell Tool
Contents
Use with Agents
Shell Tool#
Giving agents access to the shell is powerful (though risky outside a sandboxed environment).
The LLM can use it to execute any shell commands. A common use case for this is letting the LLM interact with your local file system.
from langchain.tools import Sh... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/bash.html |
5d7707a36db2-0 | .ipynb
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Twilio
Contents
Setup
Sending a message
Twilio#
This notebook goes over how to use the Twilio API wrapper to send a text message.
Setup#
To use this tool you need to install the Python Twilio package twilio
# !pip install twilio
You’ll also need to set up a Twilio account and get your credentials. You’ll ... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/twilio.html |
c919a3bd9c11-0 | .ipynb
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GraphQL tool
GraphQL tool#
This Jupyter Notebook demonstrates how to use the BaseGraphQLTool component with an Agent.
GraphQL is a query language for APIs and a runtime for executing those queries against your data. GraphQL provides a complete and understandable description of the data in your API, gives cl... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/graphql.html |
22d4b1d3274e-0 | .ipynb
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Zapier Natural Language Actions API
Contents
Zapier Natural Language Actions API
Example with Agent
Example with SimpleSequentialChain
Zapier Natural Language Actions API#
Full docs here: https://nla.zapier.com/api/v1/docs
Zapier Natural Language Actions gives you access to the 5k+ apps, 20k+ actions on Z... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/zapier.html |
22d4b1d3274e-1 | Action: Gmail: Find Email
Action Input: Find the latest email from Silicon Valley Bank
Observation: {"from__name": "Silicon Valley Bridge Bank, N.A.", "from__email": "sreply@svb.com", "body_plain": "Dear Clients, After chaotic, tumultuous & stressful days, we have clarity on path for SVB, FDIC is fully insuring all dep... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/zapier.html |
22d4b1d3274e-2 | ## step 2. generate draft reply
template = """You are an assisstant who drafts replies to an incoming email. Output draft reply in plain text (not JSON).
Incoming email:
{email_data}
Draft email reply:"""
prompt_template = PromptTemplate(input_variables=["email_data"], template=template)
reply_chain = LLMChain(llm=Open... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/zapier.html |
22d4b1d3274e-3 | > Finished chain.
'{"message__text": "Dear Silicon Valley Bridge Bank, \\n\\nThank you for your email and the update regarding your new CEO Tim Mayopoulos. We appreciate your dedication to keeping your clients and partners informed and we look forward to continuing our relationship with you. \\n\\nBest regards, \\n[You... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/zapier.html |
a17ad4cea117-0 | .ipynb
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Metaphor Search
Contents
Metaphor Search
Call the API
Use Metaphor as a tool
Metaphor Search#
This notebook goes over how to use Metaphor search.
First, you need to set up the proper API keys and environment variables. Request an API key [here](Sign up for early access here).
Then enter your API key as an... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/metaphor_search.html |
a17ad4cea117-1 | 'date_created': '2023-03-08'},
{'title': 'Extinction Risk from Artificial Intelligence',
'url': 'https://aisafety.wordpress.com/',
'author': None,
'date_created': '2013-10-08'},
{'title': 'The simple picture on AI safety - LessWrong',
'url': 'https://www.lesswrong.com/posts/WhNxG4r774bK32GcH/the-simple-pictur... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/metaphor_search.html |
a17ad4cea117-2 | "action_input": {
"query": "interesting tweet AI safety",
"num_results": 1
}
}
```
{'results': [{'url': 'https://safe.ai/', 'title': 'Center for AI Safety', 'dateCreated': '2022-01-01', 'author': None, 'score': 0.18083244562149048}]}
Observation: [{'title': 'Center for AI Safety', 'url': 'https://safe.ai/', '... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/metaphor_search.html |
747dc35f93a6-0 | .ipynb
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SerpAPI
Contents
Custom Parameters
SerpAPI#
This notebook goes over how to use the SerpAPI component to search the web.
from langchain.utilities import SerpAPIWrapper
search = SerpAPIWrapper()
search.run("Obama's first name?")
'Barack Hussein Obama II'
Custom Parameters#
You can also customize the SerpAPI... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/serpapi.html |
aff12cf17a21-0 | .ipynb
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Bing Search
Contents
Number of results
Metadata Results
Bing Search#
This notebook goes over how to use the bing search component.
First, you need to set up the proper API keys and environment variables. To set it up, follow the instructions found here.
Then we will need to set some environment variables.... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/bing_search.html |
aff12cf17a21-1 | search = BingSearchAPIWrapper()
search.results("apples", 5)
[{'snippet': 'Lady Alice. Pink Lady <b>apples</b> aren’t the only lady in the apple family. Lady Alice <b>apples</b> were discovered growing, thanks to bees pollinating, in Washington. They are smaller and slightly more stout in appearance than other varieties... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/bing_search.html |
76fdaf178f27-0 | .ipynb
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ArXiv API Tool
Contents
The ArXiv API Wrapper
ArXiv API Tool#
This notebook goes over how to use the arxiv component.
First, you need to install arxiv python package.
!pip install arxiv
from langchain.chat_models import ChatOpenAI
from langchain.agents import load_tools, initialize_agent, AgentType
llm = ... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/arxiv.html |
76fdaf178f27-1 | docs = arxiv.run("Caprice Stanley")
docs
'Published: 2017-10-10\nTitle: On Mixing Behavior of a Family of Random Walks Determined by a Linear Recurrence\nAuthors: Caprice Stanley, Seth Sullivant\nSummary: We study random walks on the integers mod $G_n$ that are determined by an\ninteger sequence $\\{ G_n \\}_{n \\geq 1... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/arxiv.html |
342068283d1d-0 | .ipynb
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AWS Lambda API
AWS Lambda API#
This notebook goes over how to use the AWS Lambda Tool component.
AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS), designed to allow developers to build and run applications and services without the need for provisioning or managing servers. ... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/awslambda.html |
65f0acf62ac1-0 | .ipynb
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Google Serper API
Contents
As part of a Self Ask With Search Chain
Obtaining results with metadata
Searching for Google Images
Searching for Google News
Searching for Google Places
Google Serper API#
This notebook goes over how to use the Google Serper component to search the web. First you need to sign u... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-1 | {'title': 'Business',
'link': 'https://www.apple.com/business/'},
{'title': 'Mac',
'link': 'https://www.apple.com/mac/'},
{'title': 'Watch',
'link': 'https://www.apple.com/watch... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-2 | 'markets smartphones, personal\n'
'computers, tablets, wearables and accessories '
'and sells a range of related\n'
'services.',
'title': 'AAPL.O - | Stock Price & Latest News - Reuters',
... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-3 | 'imageWidth': 754,
'imageHeight': 752,
'thumbnailUrl': 'https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcS3fnDub1GSojI0hJ-ZGS8Tv-hkNNloXh98DOwXZoZ_nUs3GWSd&s',
'thumbnailWidth': 225,
'thumbnailHeight': 224,
'source': 'Encyclopedia Britannica',
... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-4 | 'thumbnailWidth': 273,
'thumbnailHeight': 185,
'source': 'Encyclopedia Britannica',
'domain': 'www.britannica.com',
'link': 'https://www.britannica.com/animal/lion',
'position': 6},
{'title': "Where do lions live? Facts about lions' habitats a... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-5 | 'domain': 'virginiazoo.org',
'link': 'https://virginiazoo.org/zoos-new-male-lion-explores-habitat-for-thefirst-time/',
'position': 10}]}
Searching for Google News#
We can also query Google News using this wrapper. For example:
search = GoogleSerperAPIWrapper(type="news")
results = search.resul... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-6 | 'snippet': '(Reuters) -Tesla Inc has resumed taking orders for its '
'Model 3 long-range vehicle in the United States, the '
"company's website showed late on...",
'date': '19 hours ago',
'source': 'Yahoo Finance',
'imageUrl': 'https://encrypt... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-7 | search = GoogleSerperAPIWrapper(type="news", tbs="qdr:h")
results = search.results("Tesla Inc.")
pprint.pp(results)
{'searchParameters': {'q': 'Tesla Inc.',
'gl': 'us',
'hl': 'en',
'num': 10,
'type': 'news',
't... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-8 | 'gl': 'us',
'hl': 'en',
'num': 10,
'type': 'places'},
'places': [{'position': 1,
'title': "L'Osteria",
'address': '1219 Lexington Ave',
'latitude': 40.777154599999996,
'longitude': -73.9571363,
... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
65f0acf62ac1-9 | 'ratingCount': 152,
'category': 'Italian'},
{'position': 8,
'title': 'Piccola Cucina Uptown',
'address': '106 E 60th St',
'latitude': 40.7632468,
'longitude': -73.9689825,
'thumbnailUrl': 'https://lh5.googleusercontent.com/p/AF1Qi... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_serper.html |
7d82f16311f2-0 | .ipynb
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PubMed Tool
PubMed Tool#
This notebook goes over how to use PubMed as a tool
PubMed® comprises more than 35 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full text content from PubMed Central and publisher web sites.
from la... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/pubmed.html |
e33cb777c508-0 | .ipynb
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Google Search
Contents
Number of Results
Metadata Results
Google Search#
This notebook goes over how to use the google search component.
First, you need to set up the proper API keys and environment variables. To set it up, create the GOOGLE_API_KEY in the Google Cloud credential console (https://console.... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/google_search.html |
ef297e423871-0 | .ipynb
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File System Tools
Contents
The FileManagementToolkit
Selecting File System Tools
File System Tools#
LangChain provides tools for interacting with a local file system out of the box. This notebook walks through some of them.
Note: these tools are not recommended for use outside a sandboxed environment!
Fir... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/filesystem.html |
ef297e423871-1 | ListDirectoryTool(name='list_directory', description='List files and directories in a specified folder', args_schema=<class 'langchain.tools.file_management.list_dir.DirectoryListingInput'>, return_direct=False, verbose=False, callback_manager=<langchain.callbacks.shared.SharedCallbackManager object at 0x1156f4350>, ro... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/filesystem.html |
a8ed119ff0f1-0 | .ipynb
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Brave Search
Brave Search#
This notebook goes over how to use the Brave Search tool.
from langchain.tools import BraveSearch
api_key = "..."
tool = BraveSearch.from_api_key(api_key=api_key, search_kwargs={"count": 3})
tool.run("obama middle name")
'[{"title": "Barack Obama - Wikipedia", "link": "https://en.... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/brave_search.html |
742be4620cc6-0 | .ipynb
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HuggingFace Tools
HuggingFace Tools#
Huggingface Tools supporting text I/O can be
loaded directly using the load_huggingface_tool function.
# Requires transformers>=4.29.0 and huggingface_hub>=0.14.1
!pip install --upgrade transformers huggingface_hub > /dev/null
from langchain.agents import load_huggingfac... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/huggingface_tools.html |
205e70c151cd-0 | .ipynb
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SearxNG Search API
Contents
Custom Parameters
Obtaining results with metadata
SearxNG Search API#
This notebook goes over how to use a self hosted SearxNG search API to search the web.
You can check this link for more informations about Searx API parameters.
import pprint
from langchain.utilities import S... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
205e70c151cd-1 | 'title': 'Large language models are human-level prompt engineers',
'link': 'https://arxiv.org/abs/2211.01910',
'engines': ['google scholar'],
'category': 'science'},
{'snippet': '… Large language models (LLMs) have introduced new possibilities '
'for prototyping with AI [18]. Pre-trained on a large ... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
205e70c151cd-2 | 'a multi-step manner. To address these issues, we introduce '
'Prompt Agnostic Essay Scorer (PAES) for cross-prompt AES. Our '
'method requires no access to labelled or unlabelled '
'target-prompt data during training and is a single-stage '
'approach. PAES is easy to... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
205e70c151cd-3 | 'better described as locating an already learned task rather than '
'meta-learning. This analysis motivates rethinking the role of '
'prompts in controlling and evaluating powerful language models. '
'In this work, we discuss methods of prompt programming, '
'emphasiz... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
205e70c151cd-4 | 'Reasoning in Large Language Models".',
'title': 'Chain-of-ThoughtsPapers',
'link': 'https://github.com/Timothyxxx/Chain-of-ThoughtsPapers',
'engines': ['github'],
'category': 'it'},
{'snippet': 'Mistral: A strong, northwesterly wind: Framework for transparent '
'and accessible large-scale languag... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
205e70c151cd-5 | {'snippet': 'This repository contains the code, data, and models of the paper '
'titled "XL-Sum: Large-Scale Multilingual Abstractive '
'Summarization for 44 Languages" published in Findings of the '
'Association for Computational Linguistics: ACL-IJCNLP 2021.',
'title': 'xl-sum... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/searx_search.html |
1895cedd1965-0 | .ipynb
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DuckDuckGo Search
DuckDuckGo Search#
This notebook goes over how to use the duck-duck-go search component.
# !pip install duckduckgo-search
from langchain.tools import DuckDuckGoSearchRun
search = DuckDuckGoSearchRun()
search.run("Obama's first name?")
'Barack Obama, in full Barack Hussein Obama II, (born A... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/ddg.html |
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Apify
Apify#
This notebook shows how to use the Apify integration for LangChain.
Apify is a cloud platform for web scraping and data extraction,
which provides an ecosystem of more than a thousand
ready-made apps called Actors for various web scraping, crawling, and data extraction use cases.
For example, y... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/apify.html |
02ef34806edb-0 | .ipynb
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YouTubeSearchTool
YouTubeSearchTool#
This notebook shows how to use a tool to search YouTube
Adapted from venuv/langchain_yt_tools
#! pip install youtube_search
from langchain.tools import YouTubeSearchTool
tool = YouTubeSearchTool()
tool.run("lex friedman")
"['/watch?v=VcVfceTsD0A&pp=ygUMbGV4IGZyaWVkbWFu',... | https://langchain.readthedocs.io/en/latest/modules/agents/tools/examples/youtube.html |
d7101e9f37a9-0 | .ipynb
.pdf
How to use the async API for Agents
Contents
Serial vs. Concurrent Execution
How to use the async API for Agents#
LangChain provides async support for Agents by leveraging the asyncio library.
Async methods are currently supported for the following Tools: GoogleSerperAPIWrapper, SerpAPIWrapper and LLMMath... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/async_agent.html |
d7101e9f37a9-1 | Action Input: "Who won the US Open men's final in 2019?"
Observation: Rafael Nadal defeated Daniil Medvedev in the final, 7–5, 6–3, 5–7, 4–6, 6–4 to win the men's singles tennis title at the 2019 US Open. It was his fourth US ... Draw: 128 (16 Q / 8 WC). Champion: Rafael Nadal. Runner-up: Daniil Medvedev. Score: 7–5, 6... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/async_agent.html |
d7101e9f37a9-2 | Thought: I need to find out Max Verstappen's age
Action: Google Serper
Action Input: "Max Verstappen age"
Observation: 25 years
Thought: I need to calculate 25 raised to the 0.23 power
Action: Calculator
Action Input: 25^0.23
Observation: Answer: 2.096651272316035
Thought: I now know the final answer
Final Answer: Max ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/async_agent.html |
d7101e9f37a9-3 | Action: Google Serper
Action Input: "US Open women's final 2019 winner"
Observation: Sudeikis and Wilde's relationship ended in November 2020. Wilde was publicly served with court documents regarding child custody while she was presenting Don't Worry Darling at CinemaCon 2022. In January 2021, Wilde began dating singer... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/async_agent.html |
d7101e9f37a9-4 | Thought:
Observation: Lewis Hamilton holds the record for the most race wins in Formula One history, with 103 wins to date. Michael Schumacher, the previous record holder, ... Michael Schumacher (top left) and Lewis Hamilton (top right) have each won the championship a record seven times during their careers, while Seb... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/async_agent.html |
487c1e82dd8c-0 | .ipynb
.pdf
How to add SharedMemory to an Agent and its Tools
How to add SharedMemory to an Agent and its Tools#
This notebook goes over adding memory to both of an Agent and its tools. Before going through this notebook, please walk through the following notebooks, as this will build on top of both of them:
Adding mem... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
487c1e82dd8c-1 | Action: Search
Action Input: "ChatGPT"
Observation: Nov 30, 2022 ... We've trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer ... ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
487c1e82dd8c-2 | Thought: I now know the final answer
Final Answer: ChatGPT was developed by OpenAI.
> Finished chain.
'ChatGPT was developed by OpenAI.'
agent_chain.run(input="Thanks. Summarize the conversation, for my daughter 5 years old.")
> Entering new AgentExecutor chain...
Thought: I need to simplify the conversation for a 5 ye... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
487c1e82dd8c-3 | Action: Search
Action Input: "ChatGPT"
Observation: Nov 30, 2022 ... We've trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer ... ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
487c1e82dd8c-4 | > Finished chain.
'ChatGPT was developed by OpenAI.'
agent_chain.run(input="Thanks. Summarize the conversation, for my daughter 5 years old.")
> Entering new AgentExecutor chain...
Thought: I need to simplify the conversation for a 5 year old.
Action: Summary
Action Input: My daughter 5 years old
> Entering new LLMChai... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
4968ee3b182e-0 | .ipynb
.pdf
How to access intermediate steps
How to access intermediate steps#
In order to get more visibility into what an agent is doing, we can also return intermediate steps. This comes in the form of an extra key in the return value, which is a list of (action, observation) tuples.
from langchain.agents import loa... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/intermediate_steps.html |
a076ed2651c1-0 | .ipynb
.pdf
How to create ChatGPT Clone
How to create ChatGPT Clone#
This chain replicates ChatGPT by combining (1) a specific prompt, and (2) the concept of memory.
Shows off the example as in https://www.engraved.blog/building-a-virtual-machine-inside/
from langchain import OpenAI, ConversationChain, LLMChain, Prompt... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-1 | Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-2 | Human: ls ~
AI:
```
$ ls ~
Desktop Documents Downloads Music Pictures Public Templates Videos
```
Human: cd ~
AI:
```
$ cd ~
$ pwd
/home/user
```
Human: {Please make a file jokes.txt inside and put some jokes inside}
Assistant:
> Finished LLMChain chain.
```
$ touch jokes.txt
$ echo "Why did the chicken cross... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-3 | AI:
```
$ touch jokes.txt
$ echo "Why did the chicken cross the road? To get to the other side!" >> jokes.txt
$ echo "What did the fish say when it hit the wall? Dam!" >> jokes.txt
$ echo "Why did the scarecrow win the Nobel Prize? Because he was outstanding in his field!" >> jokes.txt
```
Human: echo -e "x=lambda y:y... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-4 | $ docker run -t my_docker_image
Hello from Docker
```
output = chatgpt_chain.predict(human_input="nvidia-smi")
print(output)
> Entering new LLMChain chain...
Prompt after formatting:
Assistant is a large language model trained by OpenAI.
Assistant is designed to be able to assist with a wide range of tasks, from answer... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-5 | Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-6 | Overall, Assistant is a powerful tool that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.
Human: nvidia-smi
AI:
```
$ n... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-7 | 3 packets transmitted, 3 packets received, 0.0% packet loss
round-trip min/avg/max/stddev = 14.945/14.945/14.945/0.000 ms
```
Human: curl -fsSL "https://api.github.com/repos/pytorch/pytorch/releases/latest" | jq -r '.tag_name' | sed 's/[^0-9\.\-]*//g'
AI:
```
$ curl -fsSL "https://api.github.com/repos/pytorch/pytorch/... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-8 | print(output)
> Entering new LLMChain chain...
Prompt after formatting:
Assistant is a large language model trained by OpenAI.
Assistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a languag... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
a076ed2651c1-9 | Assistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based ... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
02d14116f04d-0 | .ipynb
.pdf
How to use a timeout for the agent
How to use a timeout for the agent#
This notebook walks through how to cap an agent executor after a certain amount of time. This can be useful for safeguarding against long running agent runs.
from langchain.agents import load_tools
from langchain.agents import initialize... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/max_time_limit.html |
787929a773e2-0 | .ipynb
.pdf
How to cap the max number of iterations
How to cap the max number of iterations#
This notebook walks through how to cap an agent at taking a certain number of steps. This can be useful to ensure that they do not go haywire and take too many steps.
from langchain.agents import load_tools
from langchain.agent... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/max_iterations.html |
92164dadfd00-0 | .ipynb
.pdf
How to combine agents and vectorstores
Contents
Create the Vectorstore
Create the Agent
Use the Agent solely as a router
Multi-Hop vectorstore reasoning
How to combine agents and vectorstores#
This notebook covers how to combine agents and vectorstores. The use case for this is that you’ve ingested your d... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/agent_vectorstore.html |
92164dadfd00-1 | > Finished chain.
"Biden said that Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence."
agent.run("Why use ruff over flake8?")
> Entering new AgentExecutor chain...
I need to find out the advantages of using ruff over flake8
Action: Ruff QA System
Action Inp... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/agent_vectorstore.html |
92164dadfd00-2 | > Finished chain.
' Ruff can be used as a drop-in replacement for Flake8 when used (1) without or with a small number of plugins, (2) alongside Black, and (3) on Python 3 code. It also re-implements some of the most popular Flake8 plugins and related code quality tools natively, including isort, yesqa, eradicate, and m... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/agent_vectorstore.html |
8896a9762397-0 | .ipynb
.pdf
Handle Parsing Errors
Contents
Setup
Error
Default error handling
Custom Error Message
Custom Error Function
Handle Parsing Errors#
Occasionally the LLM cannot determine what step to take because it outputs format in incorrect form to be handled by the output parser. In this case, by default the agent err... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/handle_parsing_errors.html |
8896a9762397-1 | 957 )
File ~/workplace/langchain/langchain/agents/agent.py:773, in AgentExecutor._take_next_step(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)
771 raise_error = False
772 if raise_error:
--> 773 raise e
774 text = str(e)
775 if isinstance(self.handle_par... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/handle_parsing_errors.html |
8896a9762397-2 | > Finished chain.
'Gigi Hadid.'
Custom Error Function#
You can also customize the error to be a function that takes the error in and outputs a string.
def _handle_error(error) -> str:
return str(error)[:50]
mrkl = initialize_agent(
tools,
ChatOpenAI(temperature=0),
agent=AgentType.CHAT_ZERO_SHOT_REACT... | https://langchain.readthedocs.io/en/latest/modules/agents/agent_executors/examples/handle_parsing_errors.html |
173e3ec5b314-0 | .ipynb
.pdf
Vectorstore Agent
Contents
Create the Vectorstores
Initialize Toolkit and Agent
Examples
Multiple Vectorstores
Examples
Vectorstore Agent#
This notebook showcases an agent designed to retrieve information from one or more vectorstores, either with or without sources.
Create the Vectorstores#
from langchai... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/vectorstore.html |
173e3ec5b314-1 | from langchain.agents.agent_toolkits import (
create_vectorstore_router_agent,
VectorStoreRouterToolkit,
VectorStoreInfo,
)
ruff_vectorstore_info = VectorStoreInfo(
name="ruff",
description="Information about the Ruff python linting library",
vectorstore=ruff_store
)
router_toolkit = VectorStore... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/vectorstore.html |
1fb7bc252c7d-0 | .ipynb
.pdf
Pandas Dataframe Agent
Contents
Multi DataFrame Example
Pandas Dataframe Agent#
This notebook shows how to use agents to interact with a pandas dataframe. It is mostly optimized for question answering.
NOTE: this agent calls the Python agent under the hood, which executes LLM generated Python code - this ... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/pandas.html |
56ae7579bca5-0 | .ipynb
.pdf
CSV Agent
Contents
Multi CSV Example
CSV Agent#
This notebook shows how to use agents to interact with a csv. It is mostly optimized for question answering.
NOTE: this agent calls the Pandas DataFrame agent under the hood, which in turn calls the Python agent, which executes LLM generated Python code - th... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/csv.html |
a74cbad6f4c9-0 | .ipynb
.pdf
JSON Agent
Contents
Initialization
Example: getting the required POST parameters for a request
JSON Agent#
This notebook showcases an agent designed to interact with large JSON/dict objects. This is useful when you want to answer questions about a JSON blob that’s too large to fit in the context window of... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/json.html |
a74cbad6f4c9-1 | Observation: #/components/schemas/CreateCompletionRequest
Thought: I should look at the CreateCompletionRequest schema to see what parameters are required
Action: json_spec_list_keys
Action Input: data["components"]["schemas"]["CreateCompletionRequest"]
Observation: ['type', 'properties', 'required']
Thought: I should ... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/json.html |
64f40172db7c-0 | .ipynb
.pdf
OpenAPI agents
Contents
1st example: hierarchical planning agent
To start, let’s collect some OpenAPI specs.
How big is this spec?
Let’s see some examples!
Try another API.
2nd example: “json explorer” agent
OpenAPI agents#
We can construct agents to consume arbitrary APIs, here APIs conformant to the Ope... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
64f40172db7c-1 | from langchain.agents.agent_toolkits.openapi.spec import reduce_openapi_spec
with open("openai_openapi.yaml") as f:
raw_openai_api_spec = yaml.load(f, Loader=yaml.Loader)
openai_api_spec = reduce_openapi_spec(raw_openai_api_spec)
with open("klarna_openapi.yaml") as f:
raw_klarna_api_spec = yaml.load(f, Loa... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
64f40172db7c-2 | 3. GET /me to get the current user's information
4. POST /users/{user_id}/playlists to create a new playlist named "Machine Blues" for the current user
5. POST /playlists/{playlist_id}/tracks to add the first song from "Kind of Blue" to the "Machine Blues" playlist
> Entering new AgentExecutor chain...
Action: requests... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
64f40172db7c-3 | Observation: acoustic, afrobeat, alt-rock, alternative, ambient, anime, black-metal, bluegrass, blues, bossanova, brazil, breakbeat, british, cantopop, chicago-house, children, chill, classical, club, comedy, country, dance, dancehall, death-metal, deep-house, detroit-techno, disco, disney, drum-and-bass, dub, dubstep,... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
64f40172db7c-4 | Observation: babbage, davinci, text-davinci-edit-001, babbage-code-search-code, text-similarity-babbage-001, code-davinci-edit-001, text-davinci-001, ada, babbage-code-search-text, babbage-similarity, whisper-1, code-search-babbage-text-001, text-curie-001, code-search-babbage-code-001, text-ada-001, text-embedding-ada... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
64f40172db7c-5 | Action Input: 1. GET /models to retrieve the list of available models
2. Choose a suitable model for generating text (e.g., text-davinci-002)
3. POST /completions with the chosen model and a prompt related to improving communication skills to generate a short piece of advice
> Entering new AgentExecutor chain...
Action... | https://langchain.readthedocs.io/en/latest/modules/agents/toolkits/examples/openapi.html |
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