id stringlengths 14 16 | text stringlengths 36 2.73k | source stringlengths 49 117 |
|---|---|---|
3245048eed24-3 | You’ll have to set up an application in the Spotify developer console, documented here, to get credentials: CLIENT_ID, CLIENT_SECRET, and REDIRECT_URI.
To get an access tokens (and keep them fresh), you can implement the oauth flows, or you can use spotipy. If you’ve set your Spotify creedentials as environment variabl... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-4 | from langchain.agents.agent_toolkits.openapi import planner
llm = OpenAI(model_name="gpt-4", temperature=0.0)
/Users/jeremywelborn/src/langchain/langchain/llms/openai.py:169: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain.chat_mo... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-5 | Thought:I have the plan, now I need to execute the API calls.
Action: api_controller
Action Input: 1. GET /search to search for the album "Kind of Blue"
2. GET /albums/{id}/tracks to get the tracks from the "Kind of Blue" album
3. GET /me to get the current user's information
4. POST /users/{user_id}/playlists to creat... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-6 | Thought:Action: requests_post
Action Input: {"url": "https://api.spotify.com/v1/users/22rhrz4m4kvpxlsb5hezokzwi/playlists", "data": {"name": "Machine Blues"}, "output_instructions": "Extract the id of the created playlist"}
Observation: 7lzoEi44WOISnFYlrAIqyX
Thought:Action: requests_post
Action Input: {"url": "https:/... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-7 | user_query = "give me a song I'd like, make it blues-ey"
spotify_agent.run(user_query)
> Entering new AgentExecutor chain...
Action: api_planner
Action Input: I need to find the right API calls to get a blues song recommendation for the user
Observation: 1. GET /me to get the current user's information
2. GET /recommen... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-8 | 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://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-9 | Observation: [
{
id: '03lXHmokj9qsXspNsPoirR',
name: 'Get Away Jordan'
}
]
Thought:I am finished executing the plan.
Final Answer: The recommended blues song for user Jeremy Welborn (ID: 22rhrz4m4kvpxlsb5hezokzwi) is "Get Away Jordan" with the track ID: 03lXHmokj9qsXspNsPoirR.
> Finished chain.
Observation:... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-10 | > Entering new AgentExecutor chain...
Action: api_planner
Action Input: I need to find the right API calls to generate a short piece of advice
Observation: 1. GET /engines to retrieve the list of available engines
2. POST /completions with the selected engine and a prompt for generating a short piece of advice
Thought:... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-11 | Action: requests_post
Action Input: {"url": "https://api.openai.com/v1/completions", "data": {"engine": "davinci", "prompt": "Give me a short piece of advice on how to be more productive."}, "output_instructions": "Extract the text from the first choice"}
Observation: "you must provide a model parameter"
Thought:!! Cou... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-12 | Observation: babbage, davinci, text-davinci-edit-001, babbage-code-search-code, text-similarity-babbage-001, code-davinci-edit-001, text-davinci-edit-001, ada
Thought:Action: requests_post
Action Input: {"url": "https://api.openai.com/v1/completions", "data": {"model": "davinci", "prompt": "Give me a short piece of adv... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-13 | Action: api_controller
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 AgentE... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-14 | Takes awhile to get there!
2nd example: “json explorer” agent#
Here’s an agent that’s not particularly practical, but neat! The agent has access to 2 toolkits. One comprises tools to interact with json: one tool to list the keys of a json object and another tool to get the value for a given key. The other toolkit compr... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-15 | Thought: I should look at the servers key to see what the base url is
Action: json_spec_list_keys
Action Input: data["servers"][0]
Observation: ValueError('Value at path `data["servers"][0]` is not a dict, get the value directly.')
Thought: I should get the value of the servers key
Action: json_spec_get_value
Action In... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-16 | Action: json_spec_list_keys
Action Input: data["paths"]
Observation: ['/engines', '/engines/{engine_id}', '/completions', '/chat/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/audio/transcriptions', '/audio/translations', '/engines/{engine_id}/search', '/files', '... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-17 | Action: json_spec_list_keys
Action Input: data["paths"]
Observation: ['/engines', '/engines/{engine_id}', '/completions', '/chat/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/audio/transcriptions', '/audio/translations', '/engines/{engine_id}/search', '/files', '... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-18 | Action: json_spec_list_keys
Action Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]
Observation: ['schema']
Thought: I should look at the schema key to see what parameters are required
Action: json_spec_list_keys
Action Input: data["paths"]["/completions"]["post"]["requestBody"... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-19 | > Finished chain.
Observation: The required parameters for a POST request to the /completions endpoint are 'model'.
Thought: I now know the parameters needed to make the request.
Action: requests_post
Action Input: { "url": "https://api.openai.com/v1/completions", "data": { "model": "davinci", "prompt": "tell me a joke... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
3245048eed24-20 | > Finished chain.
'The response of the POST request is {"id":"cmpl-70Ivzip3dazrIXU8DSVJGzFJj2rdv","object":"text_completion","created":1680307139,"model":"davinci","choices":[{"text":" with mummy not there”\\n\\nYou dig deep and come up with,","index":0,"logprobs":null,"finish_reason":"length"}],"usage":{"prompt_tokens... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi.html |
8683825c1b6b-0 | .ipynb
.pdf
Python Agent
Contents
Fibonacci Example
Training neural net
Python Agent#
This notebook showcases an agent designed to write and execute python code to answer a question.
from langchain.agents.agent_toolkits import create_python_agent
from langchain.tools.python.tool import PythonREPLTool
from langchain.p... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/python.html |
8683825c1b6b-1 | I need to write a neural network in PyTorch and train it on the given data.
Action: Python REPL
Action Input:
import torch
# Define the model
model = torch.nn.Sequential(
torch.nn.Linear(1, 1)
)
# Define the loss
loss_fn = torch.nn.MSELoss()
# Define the optimizer
optimizer = torch.optim.SGD(model.parameters(), lr... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/python.html |
8683825c1b6b-2 | Thought: I now know the final answer
Final Answer: The prediction for x = 5 is 10.0.
> Finished chain.
'The prediction for x = 5 is 10.0.'
previous
PowerBI Dataset Agent
next
Spark Dataframe Agent
Contents
Fibonacci Example
Training neural net
By Harrison Chase
© Copyright 2023, Harrison Chase.
... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/python.html |
93c91c1d226a-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://python.langchain.com/en/latest/modules/agents/toolkits/examples/json.html |
93c91c1d226a-1 | Thought: I should look at the paths key to see what endpoints exist
Action: json_spec_list_keys
Action Input: data["paths"]
Observation: ['/engines', '/engines/{engine_id}', '/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/engines/{engine_id}/search', '/files', '/... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/json.html |
93c91c1d226a-2 | Action: json_spec_list_keys
Action Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]
Observation: ['application/json']
Thought: I should look at the application/json key to see what parameters are required
Action: json_spec_list_keys
Action Input: data["paths"]["/completions"]["post"]["requestBody"... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/json.html |
93c91c1d226a-3 | Initialization
Example: getting the required POST parameters for a request
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 25, 2023. | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/json.html |
a820c8d588e0-0 | .ipynb
.pdf
Azure Cognitive Services Toolkit
Contents
Create the Toolkit
Use within an Agent
Azure Cognitive Services Toolkit#
This toolkit is used to interact with the Azure Cognitive Services API to achieve some multimodal capabilities.
Currently There are four tools bundled in this toolkit:
AzureCogsImageAnalysisT... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/azure_cognitive_services.html |
a820c8d588e0-1 | toolkit = AzureCognitiveServicesToolkit()
[tool.name for tool in toolkit.get_tools()]
['Azure Cognitive Services Image Analysis',
'Azure Cognitive Services Form Recognizer',
'Azure Cognitive Services Speech2Text',
'Azure Cognitive Services Text2Speech']
Use within an Agent#
from langchain import OpenAI
from langchai... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/azure_cognitive_services.html |
a820c8d588e0-2 | 'You can make pancakes, omelettes, or quiches with these ingredients!'
audio_file = agent.run("Tell me a joke and read it out for me.")
> Entering new AgentExecutor chain...
Action:
```
{
"action": "Azure Cognitive Services Text2Speech",
"action_input": "Why did the chicken cross the playground? To get to the other... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/azure_cognitive_services.html |
3542f29a66eb-0 | .ipynb
.pdf
PlayWright Browser Toolkit
Contents
Instantiating a Browser Toolkit
Use within an Agent
PlayWright Browser Toolkit#
This toolkit is used to interact with the browser. While other tools (like the Requests tools) are fine for static sites, Browser toolkits let your agent navigate the web and interact with d... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-1 | tools = toolkit.get_tools()
tools
[ClickTool(name='click_element', description='Click on an element with the given CSS selector', args_schema=<class 'langchain.tools.playwright.click.ClickToolInput'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, sync_browser=None, async_browser=<Browser ty... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-2 | ExtractTextTool(name='extract_text', description='Extract all the text on the current webpage', args_schema=<class 'pydantic.main.BaseModel'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, sync_browser=None, async_browser=<Browser type=<BrowserType name=chromium executable_path=/Users/wfh/L... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-3 | CurrentWebPageTool(name='current_webpage', description='Returns the URL of the current page', args_schema=<class 'pydantic.main.BaseModel'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, sync_browser=None, async_browser=<Browser type=<BrowserType name=chromium executable_path=/Users/wfh/Lib... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-4 | '[{"innerText": "These Ukrainian veterinarians are risking their lives to care for dogs and cats in the war zone"}, {"innerText": "Life in the ocean\\u2019s \\u2018twilight zone\\u2019 could disappear due to the climate crisis"}, {"innerText": "Clashes renew in West Darfur as food and water shortages worsen in Sudan vi... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-5 | "Australian police sift through 3,000 tons of trash for missing woman\\u2019s remains"}, {"innerText": "As US and Philippine defense ties grow, China warns over Taiwan tensions"}, {"innerText": "Don McLean offers duet with South Korean president who sang \\u2018American Pie\\u2019 to Biden"}, {"innerText": "Almost two-... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-6 | to extend Sudan ceasefire"}, {"innerText": "Spanish Leopard 2 tanks are on their way to Ukraine, defense minister confirms"}, {"innerText": "Flamb\\u00e9ed pizza thought to have sparked deadly Madrid restaurant fire"}, {"innerText": "Another bomb found in Belgorod just days after Russia accidentally struck the city"}, ... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-7 | comes from textile dyes. But a shellfish-inspired solution could clean it up"}, {"innerText": "\\u2018People sacrificed their lives for just\\u00a010 dollars\\u2019: At least 78 killed in Yemen crowd surge"}, {"innerText": "Israeli police say two men shot near Jewish tomb in Jerusalem in suspected \\u2018terror attack\... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-8 | from Khartoum prison"}, {"innerText": "WHO warns of \\u2018biological risk\\u2019 after Sudan fighters seize lab, as violence mars US-brokered ceasefire"}, {"innerText": "How Colombia\\u2019s Petro, a former leftwing guerrilla, found his opening in Washington"}, {"innerText": "Bolsonaro accidentally created Facebook po... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-9 | "Inside the Italian village being repopulated by Americans"}, {"innerText": "Strikes, soaring airfares and yo-yoing hotel fees: A traveler\\u2019s guide to the coronation"}, {"innerText": "A year in Azerbaijan: From spring\\u2019s Grand Prix to winter ski adventures"}, {"innerText": "The bicycle mayor peddling a two-wh... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-10 | as millions in Texas could see damaging winds and hail"}, {"innerText": "The South is in the crosshairs of severe weather again, as the multi-day threat of large hail and tornadoes continues"}, {"innerText": "Spring snowmelt has cities along the Mississippi bracing for flooding in homes and businesses"}, {"innerText": ... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-11 | evacuation from Sudan"}, {"innerText": "Girl to get life-saving treatment for rare immune disease"}, {"innerText": "Haiti\\u2019s crime rate more than doubles in a year"}, {"innerText": "Ocean census aims to discover 100,000 previously unknown marine species"}, {"innerText": "Wall Street Journal editor discusses report... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-12 | stress is huge\\u2019 as she battles to return to tennis following positive drug test"}, {"innerText": "Barcelona reaches third straight Women\\u2019s Champions League final with draw against Chelsea"}, {"innerText": "Wrexham: An intoxicating tale of Hollywood glamor and sporting romance"}, {"innerText": "Shohei Ohtani... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-13 | # If the agent wants to remember the current webpage, it can use the `current_webpage` tool
await tools_by_name['current_webpage'].arun({})
'https://web.archive.org/web/20230428133211/https://cnn.com/world'
Use within an Agent#
Several of the browser tools are StructuredTool’s, meaning they expect multiple arguments. T... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
3542f29a66eb-14 | ```
{
"action": "get_elements",
"action_input": {
"selector": "h1, h2, h3, h4, h5, h6"
}
}
```
Observation: []
Thought: Thought: I need to navigate to langchain.com to see the headers
Action:
```
{
"action": "navigate_browser",
"action_input": "https://langchain.com/"
}
```
Observation: Navigating to http... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/playwright.html |
d196975beab4-0 | .ipynb
.pdf
Gmail Toolkit
Contents
Create the Toolkit
Customizing Authentication
Use within an Agent
Gmail Toolkit#
This notebook walks through connecting a LangChain email to the Gmail API.
To use this toolkit, you will need to set up your credentials explained in the Gmail API docs. Once you’ve downloaded the crede... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/gmail.html |
d196975beab4-1 | toolkit = GmailToolkit(api_resource=api_resource)
tools = toolkit.get_tools()
tools
[GmailCreateDraft(name='create_gmail_draft', description='Use this tool to create a draft email with the provided message fields.', args_schema=<class 'langchain.tools.gmail.create_draft.CreateDraftSchema'>, return_direct=False, verbose... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/gmail.html |
d196975beab4-2 | GmailGetThread(name='get_gmail_thread', description=('Use this tool to search for email messages. The input must be a valid Gmail query. The output is a JSON list of messages.',), args_schema=<class 'langchain.tools.gmail.get_thread.GetThreadSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/gmail.html |
d196975beab4-3 | WARNING:root:Failed to persist run: {"detail":"Not Found"}
"The latest email in your drafts is from hopefulparrot@gmail.com with the subject 'Collaboration Opportunity'. The body of the email reads: 'Dear [Friend], I hope this letter finds you well. I am writing to you in the hopes of rekindling our friendship and to d... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/gmail.html |
5095af3f0aae-0 | .ipynb
.pdf
Pandas Dataframe Agent
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 can be bad if the LLM generated Pyt... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/pandas.html |
5095af3f0aae-1 | Action: python_repl_ast
Action Input: df['Age'].mean()
Observation: 29.69911764705882
Thought: I can now calculate the square root
Action: python_repl_ast
Action Input: math.sqrt(df['Age'].mean())
Observation: name 'math' is not defined
Thought: I need to import the math library
Action: python_repl_ast
Action Input: im... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/pandas.html |
e98cbd4397b3-0 | .ipynb
.pdf
PowerBI Dataset Agent
Contents
Some notes
Initialization
Example: describing a table
Example: simple query on a table
Example: running queries
Example: add your own few-shot prompts
PowerBI Dataset Agent#
This notebook showcases an agent designed to interact with a Power BI Dataset. The agent is designed ... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/powerbi.html |
e98cbd4397b3-1 | toolkit = PowerBIToolkit(
powerbi=PowerBIDataset(dataset_id="<dataset_id>", table_names=['table1', 'table2'], credential=DefaultAzureCredential()),
llm=smart_llm
)
agent_executor = create_pbi_agent(
llm=fast_llm,
toolkit=toolkit,
verbose=True,
)
Example: describing a table#
agent_executor.run("Desc... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/powerbi.html |
e98cbd4397b3-2 | examples=few_shots,
)
agent_executor = create_pbi_agent(
llm=fast_llm,
toolkit=toolkit,
verbose=True,
)
agent_executor.run("What was the maximum of value in revenue in dollars in 2022?")
previous
PlayWright Browser Toolkit
next
Python Agent
Contents
Some notes
Initialization
Example: describing a table
... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/powerbi.html |
0a4068822d13-0 | .ipynb
.pdf
Jira
Jira#
This notebook goes over how to use the Jira tool.
The Jira tool allows agents to interact with a given Jira instance, performing actions such as searching for issues and creating issues, the tool wraps the atlassian-python-api library, for more see: https://atlassian-python-api.readthedocs.io/jir... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/jira.html |
0a4068822d13-1 | Observation: None
Thought: I now know the final answer
Final Answer: A new issue has been created in project PW with the summary "Make more fried rice" and description "Reminder to make more fried rice".
> Finished chain.
'A new issue has been created in project PW with the summary "Make more fried rice" and descriptio... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/jira.html |
05fe000f7bf8-0 | .ipynb
.pdf
CSV Agent
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 - this can be bad if the LLM gene... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/csv.html |
05fe000f7bf8-1 | Thought: I can now calculate the square root
Action: python_repl_ast
Action Input: math.sqrt(df['Age'].mean())
Observation: name 'math' is not defined
Thought: I need to import the math library
Action: python_repl_ast
Action Input: import math
Observation:
Thought: I can now calculate the square root
Action: python_re... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/csv.html |
7bbb948cc355-0 | .ipynb
.pdf
SQL Database Agent
Contents
Initialization
Example: describing a table
Example: describing a table, recovering from an error
Example: running queries
Recovering from an error
SQL Database Agent#
This notebook showcases an agent designed to interact with a sql databases. The agent builds off of SQLDatabase... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-1 | Action: schema_sql_db
Action Input: "PlaylistTrack"
Observation:
CREATE TABLE "PlaylistTrack" (
"PlaylistId" INTEGER NOT NULL,
"TrackId" INTEGER NOT NULL,
PRIMARY KEY ("PlaylistId", "TrackId"),
FOREIGN KEY("TrackId") REFERENCES "Track" ("TrackId"),
FOREIGN KEY("PlaylistId") REFERENCES "Playlist" ("PlaylistId"... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-2 | Thought: The table is called PlaylistTrack
Action: schema_sql_db
Action Input: "PlaylistTrack"
Observation:
CREATE TABLE "PlaylistTrack" (
"PlaylistId" INTEGER NOT NULL,
"TrackId" INTEGER NOT NULL,
PRIMARY KEY ("PlaylistId", "TrackId"),
FOREIGN KEY("TrackId") REFERENCES "Track" ("TrackId"),
FOREIGN KEY("Playl... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-3 | "Address" NVARCHAR(70),
"City" NVARCHAR(40),
"State" NVARCHAR(40),
"Country" NVARCHAR(40),
"PostalCode" NVARCHAR(10),
"Phone" NVARCHAR(24),
"Fax" NVARCHAR(24),
"Email" NVARCHAR(60) NOT NULL,
"SupportRepId" INTEGER,
PRIMARY KEY ("CustomerId"),
FOREIGN KEY("SupportRepId") REFERENCES "Employee" ("Emplo... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-4 | "BillingCity" NVARCHAR(40),
"BillingState" NVARCHAR(40),
"BillingCountry" NVARCHAR(40),
"BillingPostalCode" NVARCHAR(10),
"Total" NUMERIC(10, 2) NOT NULL,
PRIMARY KEY ("InvoiceId"),
FOREIGN KEY("CustomerId") REFERENCES "Customer" ("CustomerId")
)
SELECT * FROM 'Invoice' LIMIT 3;
InvoiceId CustomerId Invoice... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-5 | Observation: [('USA', 523.0600000000003), ('Canada', 303.9599999999999), ('France', 195.09999999999994), ('Brazil', 190.09999999999997), ('Germany', 156.48), ('United Kingdom', 112.85999999999999), ('Czech Republic', 90.24000000000001), ('Portugal', 77.23999999999998), ('India', 75.25999999999999), ('Chile', 46.62)]
Th... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-6 | "TrackId" INTEGER NOT NULL,
PRIMARY KEY ("PlaylistId", "TrackId"),
FOREIGN KEY("TrackId") REFERENCES "Track" ("TrackId"),
FOREIGN KEY("PlaylistId") REFERENCES "Playlist" ("PlaylistId")
)
SELECT * FROM 'PlaylistTrack' LIMIT 3;
PlaylistId TrackId
1 3402
1 3389
1 3390
Thought: I can use a SELECT statement to get the... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-7 | Thought: I now know the final answer.
Final Answer: The total number of tracks in each playlist are: '90’s Music' (1477), 'Brazilian Music' (39), 'Classical' (75), 'Classical 101 - Deep Cuts' (25), 'Classical 101 - Next Steps' (25), 'Classical 101 - The Basics' (25), 'Grunge' (15), 'Heavy Metal Classic' (26), 'Music' (... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-8 | CREATE TABLE "Artist" (
"ArtistId" INTEGER NOT NULL,
"Name" NVARCHAR(120),
PRIMARY KEY ("ArtistId")
)
SELECT * FROM 'Artist' LIMIT 3;
ArtistId Name
1 AC/DC
2 Accept
3 Aerosmith
CREATE TABLE "Track" (
"TrackId" INTEGER NOT NULL,
"Name" NVARCHAR(200) NOT NULL,
"AlbumId" INTEGER,
"MediaTypeId" INTEGER NOT NULL... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-9 | "InvoiceId" INTEGER NOT NULL,
"TrackId" INTEGER NOT NULL,
"UnitPrice" NUMERIC(10, 2) NOT NULL,
"Quantity" INTEGER NOT NULL,
PRIMARY KEY ("InvoiceLineId"),
FOREIGN KEY("TrackId") REFERENCES "Track" ("TrackId"),
FOREIGN KEY("InvoiceId") REFERENCES "Invoice" ("InvoiceId")
)
SELECT * FROM 'InvoiceLine' LIMIT 3;... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
7bbb948cc355-10 | Thought: I should double check my query before executing it.
Action: query_checker_sql_db
Action Input: SELECT Artist.Name, SUM(InvoiceLine.Quantity) AS TotalQuantity FROM Artist INNER JOIN Track ON Artist.ArtistId = Track.ArtistId INNER JOIN InvoiceLine ON Track.TrackId = InvoiceLine.TrackId GROUP BY Artist.Name ORDER... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/sql_database.html |
ddff9403b51e-0 | .ipynb
.pdf
Natural Language APIs
Contents
First, import dependencies and load the LLM
Next, load the Natural Language API Toolkits
Create the Agent
Using Auth + Adding more Endpoints
Thank you!
Natural Language APIs#
Natural Language API Toolkits (NLAToolkits) permit LangChain Agents to efficiently plan and combine ... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-1 | Attempting to load an OpenAPI 3.0.1 spec. This may result in degraded performance. Convert your OpenAPI spec to 3.1.* spec for better support.
Attempting to load an OpenAPI 3.0.1 spec. This may result in degraded performance. Convert your OpenAPI spec to 3.1.* spec for better support.
Create the Agent#
# Slightly twe... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-2 | Action: Open_AI_Klarna_product_Api.productsUsingGET
Action Input: Italian clothes
Observation: The API response contains two products from the Alé brand in Italian Blue. The first is the Alé Colour Block Short Sleeve Jersey Men - Italian Blue, which costs $86.49, and the second is the Alé Dolid Flash Jersey Men - Itali... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-3 | llm,
"https://spoonacular.com/application/frontend/downloads/spoonacular-openapi-3.json",
requests=requests,
max_text_length=1800, # If you want to truncate the response text
)
Attempting to load an OpenAPI 3.0.0 spec. This may result in degraded performance. Convert your OpenAPI spec to 3.1.* spec for be... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-4 | Unsupported APIPropertyLocation "header" for parameter Accept. Valid values are ['path', 'query'] Ignoring optional parameter
Unsupported APIPropertyLocation "header" for parameter Content-Type. Valid values are ['path', 'query'] Ignoring optional parameter
Unsupported APIPropertyLocation "header" for parameter Accept.... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-5 | Action: spoonacular_API.searchRecipes
Action Input: Italian
Observation: The API response contains 10 Italian recipes, including Turkey Tomato Cheese Pizza, Broccolini Quinoa Pilaf, Bruschetta Style Pork & Pasta, Salmon Quinoa Risotto, Italian Tuna Pasta, Roasted Brussels Sprouts With Garlic, Asparagus Lemon Risotto, I... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
ddff9403b51e-6 | > Finished chain.
'To present for your Italian language class, you could wear an Italian Gold Sparkle Perfectina Necklace - Gold, an Italian Design Miami Cuban Link Chain Necklace - Gold, or an Italian Gold Miami Cuban Link Chain Necklace - Gold. For a recipe, you could make Turkey Tomato Cheese Pizza, Broccolini Quino... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/openapi_nla.html |
b2e9e3284829-0 | .ipynb
.pdf
Spark Dataframe Agent
Contents
Spark Connect Example
Spark Dataframe Agent#
This notebook shows how to use agents to interact with a Spark dataframe and Spark Connect. It is mostly optimized for question answering.
NOTE: this agent calls the Python agent under the hood, which executes LLM generated Python... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-1 | +-----------+--------+------+--------------------+------+----+-----+-----+----------------+-------+-----+--------+
| 1| 0| 3|Braund, Mr. Owen ...| male|22.0| 1| 0| A/5 21171| 7.25| null| S|
| 2| 1| 1|Cumings, Mrs. Joh...|female|38.0| 1| 0| PC 17599... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-2 | | 7| 0| 1|McCarthy, Mr. Tim...| male|54.0| 0| 0| 17463|51.8625| E46| S|
| 8| 0| 3|Palsson, Master. ...| male| 2.0| 3| 1| 349909| 21.075| null| S|
| 9| 1| 3|Johnson, Mrs. Osc...|female|27.0| 0| 2| 347742... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-3 | | 14| 0| 3|Andersson, Mr. An...| male|39.0| 1| 5| 347082| 31.275| null| S|
| 15| 0| 3|Vestrom, Miss. Hu...|female|14.0| 0| 0| 350406| 7.8542| null| S|
| 16| 1| 2|Hewlett, Mrs. (Ma...|female|55.0| 0| 0| 248706... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-4 | only showing top 20 rows
agent = create_spark_dataframe_agent(llm=OpenAI(temperature=0), df=df, verbose=True)
agent.run("how many rows are there?")
> Entering new AgentExecutor chain...
Thought: I need to find out how many rows are in the dataframe
Action: python_repl_ast
Action Input: df.count()
Observation: 891
Thoug... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-5 | Thought: I now have the math library imported, I can get the square root
Action: python_repl_ast
Action Input: math.sqrt(29.69911764705882)
Observation: 5.449689683556195
Thought: I now know the final answer
Final Answer: 5.449689683556195
> Finished chain.
'5.449689683556195'
spark.stop()
Spark Connect Example#
# in a... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-6 | df = spark.read.csv(csv_file_path, header=True, inferSchema=True)
df.show()
+-----------+--------+------+--------------------+------+----+-----+-----+----------------+-------+-----+--------+
|PassengerId|Survived|Pclass| Name| Sex| Age|SibSp|Parch| Ticket| Fare|Cabin|Embarked|
+-----------+-... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-7 | | 6| 0| 3| Moran, Mr. James| male|null| 0| 0| 330877| 8.4583| null| Q|
| 7| 0| 1|McCarthy, Mr. Tim...| male|54.0| 0| 0| 17463|51.8625| E46| S|
| 8| 0| 3|Palsson, Master. ...| male| 2.0| 3| 1| 349909... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-8 | | 13| 0| 3|Saundercock, Mr. ...| male|20.0| 0| 0| A/5. 2151| 8.05| null| S|
| 14| 0| 3|Andersson, Mr. An...| male|39.0| 1| 5| 347082| 31.275| null| S|
| 15| 0| 3|Vestrom, Miss. Hu...|female|14.0| 0| 0| 350406... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
b2e9e3284829-9 | | 20| 1| 3|Masselmani, Mrs. ...|female|null| 0| 0| 2649| 7.225| null| C|
+-----------+--------+------+--------------------+------+----+-----+-----+----------------+-------+-----+--------+
only showing top 20 rows
from langchain.agents import create_spark_dataframe_agent
from la... | https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html |
df35ff682b7f-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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-1 | Tool(
name = "Summary",
func=summry_chain.run,
description="useful for when you summarize a conversation. The input to this tool should be a string, representing who will read this summary."
)
]
prefix = """Have a conversation with a human, answering the following questions as best you can. ... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-2 | 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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-3 | Thought: I now know the final answer.
Final Answer: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and is optimized for dialogue by using Reinforcement Learning with Human-in-the-Loop. It is also capab... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-4 | Action Input: Who developed ChatGPT
Observation: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large ... Feb 15, 2023 ... Who owns Chat GPT? Chat GPT is owned and developed by AI research and deployment company, OpenAI. Th... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-5 | 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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-6 | print(agent_chain.memory.buffer)
Human: What is ChatGPT?
AI: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and is optimized for dialogue by using Reinforcement Learning with Human-in-the-Loop. It is a... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-7 | Tool(
name = "Summary",
func=summry_chain.run,
description="useful for when you summarize a conversation. The input to this tool should be a string, representing who will read this summary."
)
]
prefix = """Have a conversation with a human, answering the following questions as best you can. ... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-8 | 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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-9 | Thought: I now know the final answer.
Final Answer: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and is optimized for dialogue by using Reinforcement Learning with Human-in-the-Loop. It is also capab... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-10 | Action Input: Who developed ChatGPT
Observation: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large ... Feb 15, 2023 ... Who owns Chat GPT? Chat GPT is owned and developed by AI research and deployment company, OpenAI. Th... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-11 | 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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
df35ff682b7f-12 | print(agent_chain.memory.buffer)
Human: What is ChatGPT?
AI: ChatGPT is an artificial intelligence chatbot developed by OpenAI and launched in November 2022. It is built on top of OpenAI's GPT-3 family of large language models and is optimized for dialogue by using Reinforcement Learning with Human-in-the-Loop. It is a... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/sharedmemory_for_tools.html |
ddaf65259e45-0 | .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://python.langchain.com/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
ddaf65259e45-1 | llm=OpenAI(temperature=0),
prompt=prompt,
verbose=True,
memory=ConversationBufferWindowMemory(k=2),
)
output = chatgpt_chain.predict(human_input="I want you to act as a Linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal o... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
ddaf65259e45-2 | Human: I want you to act as a Linux terminal. I will type commands and you will reply with what the terminal should show. I want you to only reply with the terminal output inside one unique code block, and nothing else. Do not write explanations. Do not type commands unless I instruct you to do so. When I need to tell ... | https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/chatgpt_clone.html |
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