Tool steps
Python Tool step
Use the Python Tool step to run a custom API call to another product / service
The Python Tool step allows you to use Python to take outputs from other Tool steps and manipulate data for other Tool steps and LLMs.
You can then access a specific output of that Tool step by adding another variable.
What is Python?
Python is a widely used programming language known for its clarity and simplicity. It’s popular among beginners and experts alike because it’s easy to read, quick to write, and versatile enough for tasks ranging from web development and automation to data analysis and machine learning. With a massive library ecosystem and strong community support, Python is a powerful tool for solving real-world problems efficiently.In order to use this Tool step, we would recommend having a beginner level of understanding of Python programming.
Add the Python Tool step to your Tool
You can add the Python Tool step to your Tool by:- Creating a new Tool, then searching for the ‘Convert PDF to text’ Tool step
- Click ‘Expand’ to see the full Tool step
- Enter your code in the ‘Code’ field
- Click ’+ New item’ under ‘PyPl Packages’ if you need to install any packages
- Click ‘Run step’ to run the Tool step
In order to access the output of this codeblock, you will need to return a value in the return statement.
Accessing variables
You can access Tool input variables, other Tool step outputs, and API keys you’ve created in Relevance in your Python Tool step.Input variables
You can access Input variables by following this syntax, where ‘name’ is the variable for your input.Other Tool step outputs
You can access other Tool step outputs by following this syntax, where ‘tool_step’ is the variable for the Tool step you’re trying to access the output of.API keys
You can access one of your saved API keys by using this syntax, where ‘api_key’ is the variable for the key you’re trying to access.Advanced Settings
Backend
You can choose between two backend services to run the code, ‘Modal Labs’ or ‘e2b.dev’.Runtime Commands
You can include a list of Linux terminal commands to be run before running your code.Session ID
Define a custom session that saves all local variables between Python executions.This setting is only available when the backend is set to ‘Modal Labs’.
Enable ‘Long Output’ Mode
Allow the output to be longer than 127,000 characters, in exchange for 2-4 seconds of extra latency.Number of GPUs
Allows you to specify a number of GPUs for your code to use.This setting is only available when the backend is set to ‘Modal Labs’.
Number of CPU Cores
Allows you to specify a number of CPU cores for your code to use.This setting is only available when the backend is set to ‘Modal Labs’.
Memory Size
Allows you to specify an amount of RAM for your code to use.This setting is only available when the backend is set to ‘Modal Labs’.
Session Timeout
Allows you to specify (in seconds) how long the code should run before timing out.This setting is only available when the backend is set to ‘Modal Labs’.
Raise Error
Allows you to specify how errors are raised:- Error with Full Traceback
- Error
- Print Error to Stderr
Enable fallback
If the selected backend fails, when this is selected, your code will attempt to run via the other backend.Common errors
Code execution timed out
Code execution timed out
This error indicates that the code took longer than the seconds allowed in the ‘Session timeout’ Advanced Setting, or exceeded our hard limit of four hours.
No return statement
No return statement
This error indicates that there is no return statement in the code. You will not be able to access the output of this codeblock unless you pass data in a return statement.