id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 115 |
|---|---|---|
0f0963dfb1f3-1 | answer = agent.run("What's the main title on langchain.com?")
print(answer)
The main title of langchain.com is "LANG CHAIN 🦜️🔗 Official Home Page"
agent.run("What's the main title on google.com?")
---------------------------------------------------------------------------
ValidationError Tra... | https://python.langchain.com/en/latest/modules/agents/tools/tool_input_validation.html |
0f0963dfb1f3-2 | 112 try:
--> 113 outputs = self._call(inputs)
114 except (KeyboardInterrupt, Exception) as e:
115 self.callback_manager.on_chain_error(e, verbose=self.verbose)
File ~/code/lc/lckg/langchain/agents/agent.py:792, in AgentExecutor._call(self, inputs)
790 # We now enter the agent loop (until it returns ... | https://python.langchain.com/en/latest/modules/agents/tools/tool_input_validation.html |
0f0963dfb1f3-3 | 103 tool_input: Union[str, Dict],
(...)
107 **kwargs: Any,
108 ) -> str:
109 """Run the tool."""
--> 110 run_input = self._parse_input(tool_input)
111 if not self.verbose and verbose is not None:
112 verbose_ = verbose
File ~/code/lc/lckg/langchain/tools/base.py:71, in... | https://python.langchain.com/en/latest/modules/agents/tools/tool_input_validation.html |
2bcb8ae48bea-0 | .ipynb
.pdf
Multi-Input Tools
Multi-Input Tools#
This notebook shows how to use a tool that requires multiple inputs with an agent.
The difficulty in doing so comes from the fact that an agent decides its next step from a language model, which outputs a string. So if that step requires multiple inputs, they need to be ... | https://python.langchain.com/en/latest/modules/agents/tools/multi_input_tool.html |
2bcb8ae48bea-1 | )
]
mrkl = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
mrkl.run("What is 3 times 4")
> Entering new AgentExecutor chain...
I need to multiply two numbers
Action: Multiplier
Action Input: 3,4
Observation: 12
Thought: I now know the final answer
Final Answer: 3 times 4 is 12
>... | https://python.langchain.com/en/latest/modules/agents/tools/multi_input_tool.html |
3ec510c6c763-0 | .md
.pdf
Getting Started
Contents
List of Tools
Getting Started#
Tools are functions that agents can use to interact with the world.
These tools can be generic utilities (e.g. search), other chains, or even other agents.
Currently, tools can be loaded with the following snippet:
from langchain.agents import load_tool... | https://python.langchain.com/en/latest/modules/agents/tools/getting_started.html |
3ec510c6c763-1 | Requires LLM: No
wolfram-alpha
Tool Name: Wolfram Alpha
Tool Description: A wolfram alpha search engine. Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Input should be a search query.
Notes: Calls the Wolfram Alpha API and then parses results.
Requires ... | https://python.langchain.com/en/latest/modules/agents/tools/getting_started.html |
3ec510c6c763-2 | Requires LLM: Yes
open-meteo-api
Tool Name: Open Meteo API
Tool Description: Useful for when you want to get weather information from the OpenMeteo API. The input should be a question in natural language that this API can answer.
Notes: A natural language connection to the Open Meteo API (https://api.open-meteo.com/), ... | https://python.langchain.com/en/latest/modules/agents/tools/getting_started.html |
3ec510c6c763-3 | For more information on this, see this page
searx-search
Tool Name: Search
Tool Description: A wrapper around SearxNG meta search engine. Input should be a search query.
Notes: SearxNG is easy to deploy self-hosted. It is a good privacy friendly alternative to Google Search. Uses the SearxNG API.
Requires LLM: No
Extra... | https://python.langchain.com/en/latest/modules/agents/tools/getting_started.html |
3ec510c6c763-4 | Notes: A connection to the OpenWeatherMap API (https://api.openweathermap.org), specifically the /data/2.5/weather endpoint.
Requires LLM: No
Extra Parameters: openweathermap_api_key (your API key to access this endpoint)
previous
Tools
next
Defining Custom Tools
Contents
List of Tools
By Harrison Chase
... | https://python.langchain.com/en/latest/modules/agents/tools/getting_started.html |
6ebb6b52647b-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-1 | def get_input() -> str:
print("Insert your text. Enter 'q' or press Ctrl-D (or Ctrl-Z on Windows) to end.")
contents = []
while True:
try:
line = input()
except EOFError:
break
if line == "q":
break
contents.append(line)
return "\n".joi... | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-2 | Action: DuckDuckGo Search
Action Input: "Who said 'Veni, vidi, vici'?" | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-3 | 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, I saw, I conquered" and it could be pronounc... | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-4 | Caesar ve· ni, vi· di, vi· ci ˌwā-nē ˌwē-dē ˈwē-kē ˌvā-nē ˌvē-dē ˈvē-chē : I came, I saw, I conquered Articles Related to veni, vidi, vici 'In Vino Veritas' and Other Latin... Dictionary Entries Near veni, vidi, vici Venite veni, vidi, vici Venizélos See More Nearby Entries Cite this Entry Style The simplest explanatio... | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-5 | expression of triumph. The words are said to have been used by Caesar as he was enjoying a triumph. | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
6ebb6b52647b-6 | Thought:I now know the final answer
Final Answer: Julius Caesar said the quote "Veni, vidi, vici" which means "I came, I saw, I conquered".
> Finished chain.
'Julius Caesar said the quote "Veni, vidi, vici" which means "I came, I saw, I conquered".'
previous
Gradio Tools
next
IFTTT WebHooks
Contents
Configuring the... | https://python.langchain.com/en/latest/modules/agents/tools/examples/human_tools.html |
3ef879fcc16e-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/sceneXplain.html |
3ef879fcc16e-1 | Observation: In a charmingly whimsical scene, a young girl is seen braving the rain alongside her furry companion, the lovable Totoro. The two are depicted standing on a bustling street corner, where they are sheltered from the rain by a bright yellow umbrella. The girl, dressed in a cheerful yellow frock, holds onto t... | https://python.langchain.com/en/latest/modules/agents/tools/examples/sceneXplain.html |
3ef879fcc16e-2 | By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/modules/agents/tools/examples/sceneXplain.html |
35f2271ab73e-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
35f2271ab73e-1 | 'Thanks to the flexibility of <b>Python</b> and the powerful ecosystem of packages, the Azure CLI supports features such as autocompletion (in shells that support it), persistent credentials, JMESPath result parsing, lazy initialization, network-less unit tests, and more. Building an open-source and cross-platform Azur... | https://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
35f2271ab73e-2 | assignment operator.It adds two values and assigns the sum to a variable (left operand). W3Schools offers free online tutorials, references and exercises in all the major languages of the web. Covering popular subjects like HTML, CSS, JavaScript, <b>Python</b>, SQL, Java, and many, many more. This tutorial introduces t... | https://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
35f2271ab73e-3 | To install <b>Python</b> using the Microsoft Store: Go to your Start menu (lower left Windows icon), type "Microsoft Store", select the link to open the store. Once the store is open, select Search from the upper-right menu and enter "<b>Python</b>". Select which version of <b>Python</b> you would l... | https://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
35f2271ab73e-4 | Number of results#
You can use the k parameter to set the number of results
search = BingSearchAPIWrapper(k=1)
search.run("python")
'Thanks to the flexibility of <b>Python</b> and the powerful ecosystem of packages, the Azure CLI supports features such as autocompletion (in shells that support it), persistent credentia... | https://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
35f2271ab73e-5 | {'snippet': '<b>Apples</b> boast many vitamins and minerals, though not in high amounts. However, <b>apples</b> are usually a good source of vitamin C. Vitamin C. Also called ascorbic acid, this vitamin is a common ...',
'title': 'Apples 101: Nutrition Facts and Health Benefits',
'link': 'https://www.healthline.com... | https://python.langchain.com/en/latest/modules/agents/tools/examples/bing_search.html |
ba10ce9019b3-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/ifttt.html |
ba10ce9019b3-1 | service, and you’re ready to start receiving data and triggering actions 🎉
Finishing up#
To get your webhook URL go to https://ifttt.com/maker_webhooks/settings
Copy the IFTTT key value from there. The URL is of the form
https://maker.ifttt.com/use/YOUR_IFTTT_KEY. Grab the YOUR_IFTTT_KEY value.
from langchain.tools.if... | https://python.langchain.com/en/latest/modules/agents/tools/examples/ifttt.html |
565ae3e1fc8a-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/wolfram_alpha.html |
8b7b15b43f7e-0 | .ipynb
.pdf
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
Requirement already satisfied: arxiv in /Users/wfh/code/lc/lckg/.venv/lib/python3.11/site-packages (1.4.7)
Requirement a... | https://python.langchain.com/en/latest/modules/agents/tools/examples/arxiv.html |
8b7b15b43f7e-1 | allowed moves of arbitrary length. We show that the diameter of these graphs on
fibers of a fixed integer matrix can be bounded from above by a constant. We
then study the mixing behaviour of heat-bath random walks on these graphs. We
also state explicit conditions on the set of moves so that the heat-bath random
walk,... | https://python.langchain.com/en/latest/modules/agents/tools/examples/arxiv.html |
8b7b15b43f7e-2 | docs = arxiv.run("1605.08386")
docs
'Published: 2016-05-26\nTitle: Heat-bath random walks with Markov bases\nAuthors: Caprice Stanley, Tobias Windisch\nSummary: Graphs on lattice points are studied whose edges come from a finite set of\nallowed moves of arbitrary length. We show that the diameter of these graphs on\nfi... | https://python.langchain.com/en/latest/modules/agents/tools/examples/arxiv.html |
8b7b15b43f7e-3 | 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://python.langchain.com/en/latest/modules/agents/tools/examples/arxiv.html |
8b7b15b43f7e-4 | Now, we are trying to find information about non-existing article. In this case, the response is “No good Arxiv Result was found”
docs = arxiv.run("1605.08386WWW")
docs
'No good Arxiv Result was found'
previous
Apify
next
AWS Lambda API
Contents
The ArXiv API Wrapper
By Harrison Chase
© Copyright 2023, H... | https://python.langchain.com/en/latest/modules/agents/tools/examples/arxiv.html |
c520b713ba7a-0 | .ipynb
.pdf
OpenWeatherMap API
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 we will need to set some environment vari... | https://python.langchain.com/en/latest/modules/agents/tools/examples/openweathermap.html |
b5e71a5eaa2d-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-1 | %autoreload 2
import os
# get from https://platform.openai.com/
os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "")
# get from https://nla.zapier.com/demo/provider/debug (under User Information, after logging in):
os.environ["ZAPIER_NLA_API_KEY"] = os.environ.get("ZAPIER_NLA_API_KEY", "")
Example with ... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-2 | 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://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-3 | Observation: {"message__text": "Silicon Valley Bank has announced that Tim Mayopoulos is the new CEO. FDIC is fully insuring all deposits and they have an ask for clients and partners as they rebuild.", "message__permalink": "https://langchain.slack.com/archives/C04TSGU0RA7/p1678859932375259", "channel": "C04TSGU0RA7",... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-4 | from langchain.tools.zapier.tool import ZapierNLARunAction
from langchain.utilities.zapier import ZapierNLAWrapper
## step 0. expose gmail 'find email' and slack 'send direct message' actions
# first go here, log in, expose (enable) the two actions: https://nla.zapier.com/demo/start -- for this example, can leave all f... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-5 | SLACK_HANDLE = "@Ankush Gola"
def nla_slack(inputs):
action = next((a for a in actions if a["description"].startswith("Slack: Send Direct Message")), None)
instructions = f'Send this to {SLACK_HANDLE} in Slack: {inputs["draft_reply"]}'
return {"slack_data": ZapierNLARunAction(action_id=action["id"], zapier_... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-6 | overall_chain.run(GMAIL_SEARCH_INSTRUCTIONS)
> Entering new SimpleSequentialChain chain...
{"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 deposits & h... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-7 | Best regards,
[Your Name]
{"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[... | https://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
b5e71a5eaa2d-8 | > 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://python.langchain.com/en/latest/modules/agents/tools/examples/zapier.html |
82f7bcc8f9ab-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/python.html |
414916d2e352-0 | .ipynb
.pdf
Google Serper API
Contents
As part of a Self Ask With Search Chain
Google Serper API#
This notebook goes over how to use the Google Serper component to search the web. First you need to sign up for a free account at serper.dev and get your api key.
import os
os.environ["SERPER_API_KEY"] = ""
from langchai... | https://python.langchain.com/en/latest/modules/agents/tools/examples/google_serper.html |
414916d2e352-1 | 'El Palmar, Spain'
previous
Google Search
next
Gradio Tools
Contents
As part of a Self Ask With Search Chain
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/modules/agents/tools/examples/google_serper.html |
1dd8102acb99-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-1 | search.run("large language model ", engines=['wiki'])
'Large language models (LLMs) represent a major advancement in AI, with the promise of transforming domains through learned knowledge. LLM sizes have been increasing 10X every year for the last few years, and as these models grow in complexity and size, so do their ... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-2 | search.run("deep learning", language='es', engines=['wiki'])
'Aprendizaje profundo (en inglés, deep learning) es un conjunto de algoritmos de aprendizaje automático (en inglés, machine learning) que intenta modelar abstracciones de alto nivel en datos usando arquitecturas computacionales que admiten transformaciones no... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-3 | 'title': 'Promptchainer: Chaining large language model prompts through '
'visual programming',
'link': 'https://dl.acm.org/doi/abs/10.1145/3491101.3519729',
'engines': ['google scholar'],
'category': 'science'},
{'snippet': '… can introspect the large prompt model. We derive the view '
'ϕ... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-4 | 'link': 'https://arxiv.org/abs/2204.02329',
'engines': ['google scholar'],
'category': 'science'}]
Get papers from arxiv
results = search.results("Large Language Model prompt", num_results=5, engines=['arxiv'])
pprint.pp(results)
[{'snippet': 'Thanks to the advanced improvement of large pre-trained language '
... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-5 | 'development of real-world AES systems, yet it remains an '
'under-explored area of research. Models designed for '
'prompt-specific AES rely heavily on prompt-specific knowledge '
'and perform poorly in the cross-prompt setting, whereas current '
'approaches to cross... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-6 | 'example selection. We further explore the use of monolingual '
'data and the feasibility of cross-lingual, cross-domain, and '
'sentence-to-document transfer learning in prompting. Extensive '
'experiments with GLM-130B (Zeng et al., 2022) as the testbed '
'show that... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-7 | 'effective, especially when the prompts are natural language. In '
'this paper, we investigate common attributes shared by effective '
'prompts. We first propose a human readable prompt tuning method '
'(F LUENT P ROMPT) based on Langevin dynamics that incorporates a '
... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-8 | 'In this work, we discuss methods of prompt programming, '
'emphasizing the usefulness of considering prompts through the '
'lens of natural language. We explore techniques for exploiting '
'the capacity of narratives and cultural anchors to encode '
'nuanced intentio... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-9 | 'scripts and screenplays.',
'title': 'dramatron',
'link': 'https://github.com/deepmind/dramatron',
'engines': ['github'],
'category': 'it'}]
We could also directly query for results from github and other source forges.
results = search.results("large language model", num_results = 20, engines=['github', 'gitlab... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-10 | 'engines': ['github'],
'category': 'it'},
{'snippet': 'Code for loralib, an implementation of "LoRA: Low-Rank '
'Adaptation of Large Language Models"',
'title': 'LoRA',
'link': 'https://github.com/microsoft/LoRA',
'engines': ['github'],
'category': 'it'},
{'snippet': 'Code for the paper "Evalua... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-11 | 'engines': ['github'],
'category': 'it'},
{'snippet': 'Optimus: the first large-scale pre-trained VAE language model',
'title': 'Optimus',
'link': 'https://github.com/ChunyuanLI/Optimus',
'engines': ['github'],
'category': 'it'},
{'snippet': 'Seminar on Large Language Models (COMP790-101 at UNC Chapel '
... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-12 | 'link': 'https://github.com/bigscience-workshop/biomedical',
'engines': ['github'],
'category': 'it'},
{'snippet': 'ChatGPT @ Home: Large Language Model (LLM) chatbot application, '
'written by ChatGPT',
'title': 'ChatGPT-at-Home',
'link': 'https://github.com/Sentdex/ChatGPT-at-Home',
'engines':... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
1dd8102acb99-13 | 'engines': ['github'],
'category': 'it'},
{'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 Lingu... | https://python.langchain.com/en/latest/modules/agents/tools/examples/searx_search.html |
62c0d8f901be-0 | .ipynb
.pdf
Gradio Tools
Contents
Using a tool
Using within an agent
Gradio Tools#
There are many 1000s of Gradio apps on Hugging Face Spaces. This library puts them at the tips of your LLM’s fingers 🦾
Specifically, gradio-tools is a Python library for converting Gradio apps into tools that can be leveraged by a lar... | https://python.langchain.com/en/latest/modules/agents/tools/examples/gradio_tools.html |
62c0d8f901be-1 | from langchain.agents import initialize_agent
from langchain.llms import OpenAI
from gradio_tools.tools import (StableDiffusionTool, ImageCaptioningTool, StableDiffusionPromptGeneratorTool,
TextToVideoTool)
from langchain.memory import ConversationBufferMemory
llm = OpenAI(temperature=0)... | https://python.langchain.com/en/latest/modules/agents/tools/examples/gradio_tools.html |
62c0d8f901be-2 | Thought: Do I need to use a tool? Yes
Action: StableDiffusion
Action Input: A dog riding a skateboard, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha
Job Status: Status.STARTING eta: None
Job Status: Status.PROCESSING eta: None
Observat... | https://python.langchain.com/en/latest/modules/agents/tools/examples/gradio_tools.html |
62c0d8f901be-3 | Job Status: Status.IN_QUEUE eta: 42.49370198879602
Job Status: Status.IN_QUEUE eta: 21.314297944849187
Observation: /var/folders/bm/ylzhm36n075cslb9fvvbgq640000gn/T/tmp5snj_nmzf20_cb3m.mp4
Thought: Do I need to use a tool? No
AI: Here is a video of a painting of a dog sitting on a skateboard.
> Finished chain.
previous... | https://python.langchain.com/en/latest/modules/agents/tools/examples/gradio_tools.html |
ca936704127e-0 | .ipynb
.pdf
Wikipedia API
Wikipedia API#
This notebook goes over how to use the wikipedia component.
First, you need to install wikipedia python package.
pip install wikipedia
from langchain.utilities import WikipediaAPIWrapper
wikipedia = WikipediaAPIWrapper()
wikipedia.run('HUNTER X HUNTER') | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-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://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-2 | × Hunter was adapted into a 62-episode anime television series produced by Nippon Animation and directed by Kazuhiro Furuhashi, which ran on Fuji Television from October 1999 to March 2001. Three separate original video animations (OVAs) totaling 30 episodes were subsequently produced by Nippon Animation and released i... | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-3 | × Hunter has been a huge critical and financial success and has become one of the best-selling manga series of all time, having over 84 million copies in circulation by July 2022.\n\nPage: Hunter × Hunter (2011 TV series)\nSummary: Hunter × Hunter is an anime television series that aired from 2011 to 2014 based on Yosh... | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-4 | new Hunter × Hunter anime was announced on July 24, 2011. It is a complete reboot of the anime adaptation starting from the beginning of the manga, with no connections to the first anime from 1999. Produced by Nippon TV, VAP, Shueisha and Madhouse, the series is directed by Hiroshi Kōjina, with Atsushi Maekawa and Tsut... | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-5 | On television, the series began airing on Adult Swim\'s Toonami programming block on April 17, 2016, and ended on June 23, 2019.The anime series\' opening theme is alternated between the song "Departure!" and an alternate version titled "Departure! -Second Version-" both sung by Galneryus\' vocalist Masatoshi Ono. Five... | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-6 | The background music and soundtrack for the series was composed by Yoshihisa Hirano.\n\n\n\nPage: List of Hunter × Hunter characters\nSummary: The Hunter × Hunter manga series, created by Yoshihiro Togashi, features an extensive cast of characters. It takes place in a fictional universe where licensed specialists known... | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
ca936704127e-7 | previous
SerpAPI
next
Wolfram Alpha
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/modules/agents/tools/examples/wikipedia.html |
d852acdf79aa-0 | .ipynb
.pdf
ChatGPT Plugins
ChatGPT Plugins#
This example shows how to use ChatGPT Plugins within LangChain abstractions.
Note 1: This currently only works for plugins with no auth.
Note 2: There are almost certainly other ways to do this, this is just a first pass. If you have better ideas, please open a PR!
from lang... | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-1 | OpenAPI Spec: {'openapi': '3.0.1', 'info': {'version': 'v0', 'title': 'Open AI Klarna product Api'}, 'servers': [{'url': 'https://www.klarna.com/us/shopping'}], 'tags': [{'name': 'open-ai-product-endpoint', 'description': 'Open AI Product Endpoint. Query for products.'}], 'paths': {'/public/openai/v0/products': {'get':... | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-2 | {'schema': {'$ref': '#/components/schemas/ProductResponse'}}}}, '503': {'description': 'one or more services are unavailable'}}, 'deprecated': False}}}, 'components': {'schemas': {'Product': {'type': 'object', 'properties': {'attributes': {'type': 'array', 'items': {'type': 'string'}}, 'name': {'type': 'string'}, 'pric... | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-3 | Thought:I need to use the Klarna Shopping API to search for t shirts.
Action: requests_get
Action Input: https://www.klarna.com/us/shopping/public/openai/v0/products?q=t%20shirts | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-4 | Observation: {"products":[{"name":"Lacoste Men's Pack of Plain T-Shirts","url":"https://www.klarna.com/us/shopping/pl/cl10001/3202043025/Clothing/Lacoste-Men-s-Pack-of-Plain-T-Shirts/?utm_source=openai","price":"$26.60","attributes":["Material:Cotton","Target Group:Man","Color:White,Black"]},{"name":"Hanes Men's Ultima... | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-5 | Comfort T-shirts Men's 3-pack","url":"https://www.klarna.com/us/shopping/pl/cl10001/3202640533/Clothing/adidas-Comfort-T-shirts-Men-s-3-pack/?utm_source=openai","price":"$14.99","attributes":["Material:Cotton","Target Group:Man","Color:White,Black","Neckline:Round"]}]} | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
d852acdf79aa-6 | Thought:The available t shirts in Klarna are Lacoste Men's Pack of Plain T-Shirts, Hanes Men's Ultimate 6pk. Crewneck T-Shirts, Nike Boy's Jordan Stretch T-shirts, Polo Classic Fit Cotton V-Neck T-Shirts 3-Pack, and adidas Comfort T-shirts Men's 3-pack.
Final Answer: The available t shirts in Klarna are Lacoste Men's P... | https://python.langchain.com/en/latest/modules/agents/tools/examples/chatgpt_plugins.html |
b71c8080b0ec-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/awslambda.html |
b71c8080b0ec-1 | agent.run("Send an email to test@testing123.com saying hello world.")
previous
ArXiv API Tool
next
Shell Tool
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/modules/agents/tools/examples/awslambda.html |
f9f77e6d99d4-0 | .ipynb
.pdf
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://python.langchain.com/en/latest/modules/agents/tools/examples/google_search.html |
f9f77e6d99d4-1 | tool.run("Obama's first name?")
"STATE OF HAWAII. 1 Child's First Name. (Type or print). 2. Sex. BARACK. 3. This Birth. CERTIFICATE OF LIVE BIRTH. FILE. NUMBER 151 le. lb. Middle Name. Barack Hussein Obama II is an American former politician who served as the 44th president of the United States from 2009 to 2017. A mem... | https://python.langchain.com/en/latest/modules/agents/tools/examples/google_search.html |
f9f77e6d99d4-2 | Number of Results#
You can use the k parameter to set the number of results
search = GoogleSearchAPIWrapper(k=1)
tool = Tool(
name = "I'm Feeling Lucky",
description="Search Google and return the first result.",
func=search.run
)
tool.run("python")
'The official home of the Python Programming Language.'
‘Th... | https://python.langchain.com/en/latest/modules/agents/tools/examples/google_search.html |
4759247e3690-0 | .ipynb
.pdf
Requests
Contents
Inside the tool
Requests#
The web contains a lot of information that LLMs do not have access to. In order to easily let LLMs interact with that information, we provide a wrapper around the Python Requests module that takes in a URL and fetches data from that URL.
from langchain.agents im... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-1 | RequestsPatchTool(name='requests_patch', description='Use this when you want to PATCH to a website.\n Input should be a json string with two keys: "url" and "data".\n The value of "url" should be a string, and the value of "data" should be a dictionary of \n key-value pairs you want to PATCH to the url.\n B... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-2 | Each requests tool contains a requests wrapper. You can work with these wrappers directly below
# Each tool wrapps a requests wrapper
requests_tools[0].requests_wrapper
TextRequestsWrapper(headers=None, aiosession=None)
from langchain.utilities import TextRequestsWrapper
requests = TextRequestsWrapper()
requests.get("h... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-3 | '<!doctype html><html itemscope="" itemtype="http://schema.org/WebPage" lang="en"><head><meta content="Search the world\'s information, including webpages, images, videos and more. Google has many special features to help you find exactly what you\'re looking for." name="description"><meta content="noodp" name="robots"... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-4 | nonce="MXrF0nnIBPkxBza4okrgPA">(function(){window.google={kEI:\'TA9QZOa5EdTakPIPuIad-Ac\',kEXPI:\'0,1359409,6059,206,4804,2316,383,246,5,1129120,1197768,626,380097,16111,28687,22431,1361,12319,17581,4997,13228,37471,7692,2891,3926,213,7615,606,50058,8228,17728,432,3,346,1244,1,16920,2648,4,1528,2304,29062,9871,3194,136... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-5 | 342,23024,6699,31123,4568,6258,23418,1252,5835,14967,4333,4239,3245,445,2,2,1,26632,239,7916,7321,60,2,3,15965,872,7830,1796,10008,7,1922,9779,36154,6305,2007,17765,427,20136,14,82,2730,184,13600,3692,109,2412,1548,4308,3785,15175,3888,1515,3030,5628,478,4,9706,1804,7734,2738,1853,1032,9480,2995,576,1041,5648,3722,2058... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-6 | 1439,1128,7343,426,249,517,95,1102,14,696,1270,750,400,2208,274,2776,164,89,119,204,139,129,1710,2505,320,3,631,439,2,300,1645,172,1783,784,169,642,329,401,50,479,614,238,757,535,717,102,2,739,738,44,232,22,442,961,45,214,383,567,500,487,151,120,256,253,179,673,2,102,2,10,535,123,135,1685,5206695,190,2,20,50,198,599422... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-7 | ,1,5,1,16,7,2,41,247,4,9,7,9,15,4,4,121,24,23944834,4042142,1964,16672,2894,6250,15739,1726,647,409,837,1411438,146986,23612960,7,84,93,33,101,816,57,532,163,1,441,86,1,951,73,31,2,345,178,243,472,2,148,962,455,167,178,29,702,1856,288,292,805,93,137,68,416,177,292,399,55,95,2566\',kBL:\'hw1A\',kOPI:89978449};google.sn=... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-8 | 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://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-9 | null};google.log=function(a,b,c,d,k,e){e=void 0===e?l:e;c||(c=t(a,b,e,d,k));if(c=r(c)){a=new Image;var g=n.length;n[g]=a;a.onerror=a.onload=a.onabort=function(){delete n[g]};a.src=c}};google.logUrl=function(a,b){b=void 0===b?l:b;return t("",a,b)};}).call(this);(function(){google.y={};google.sy=[];google.x=function(a,b)... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-10 | a}a=!1}a&&b.preventDefault()},!0);}).call(this);</script><style>#gbar,#guser{font-size:13px;padding-top:1px !important;}#gbar{height:22px}#guser{padding-bottom:7px !important;text-align:right}.gbh,.gbd{border-top:1px solid #c9d7f1;font-size:1px}.gbh{height:0;position:absolute;top:24px;width:100%}@media all{.gb1{height:... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-11 | a{color:#1558d6}a:visited{color:#4b11a8}.sblc{padding-top:5px}.sblc a{display:block;margin:2px 0;margin-left:13px;font-size:11px}.lsbb{background:#f8f9fa;border:solid 1px;border-color:#dadce0 #70757a #70757a #dadce0;height:30px}.lsbb{display:block}#WqQANb a{display:inline-block;margin:0 12px}.lsb{background:url(/images... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-12 | null;q++;d=d||{};b=encodeURIComponent;var c="/gen_204?atyp=i&ei="+b(google.kEI);google.kEXPI&&(c+="&jexpid="+b(google.kEXPI));c+="&srcpg="+b(google.sn)+"&jsr="+b(t.jsr)+"&bver="+b(t.bv);var f=a.lineNumber;void 0!==f&&(c+="&line="+f);var g=\na.fileName;g&&(0<g.indexOf("-extension:/")&&(e=3),c+="&script="+b(g),f&&g===win... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-13 | bgcolor="#fff"><script nonce="MXrF0nnIBPkxBza4okrgPA">(function(){var src=\'/images/nav_logo229.png\';var iesg=false;document.body.onload = function(){window.n && window.n();if (document.images){new Image().src=src;}\nif (!iesg){document.f&&document.f.q.focus();document.gbqf&&document.gbqf.q.focus();}\n}\n})();</script... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
4759247e3690-14 | id=gbn class=gbi></span><span id=gbf class=gbf></span><span id=gbe></span><a href="http://www.google.com/history/optout?hl=en" class=gb4>Web History</a> | <a href="/preferences?hl=en" class=gb4>Settings</a> | <a target=_top id=gb_70 href="https://accounts.google.com/ServiceLogin?hl=en&passive=true&continue=https://www... | https://python.langchain.com/en/latest/modules/agents/tools/examples/requests.html |
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