weco 0.1.3

A client facing API for interacting with the WeCo AI function builder service.

$f$(👷‍♂️)

A client facing API for interacting with the WeCo AI function builder service!

Use this API to build complex systems fast. We lower the barrier of entry to software engineer, data science and machine learning by providing an interface to prototype difficult solutions quickly in just a few lines of code.

Installation

Install the weco package simply by calling this in your terminal of choice:

pip install weco

Features

• The build function enables quick and easy prototyping of new functions via LLMs through just natural language. We encourage users to do this through our web console for maximum control and ease of use, however, you can also do this through our API as shown in here.
• The query function allows you to test and use the newly created function in your own code.
• We offer asynchronous versions of the above clients.
• We provide a batch_query functions that allows users to batch functions for various inputs as well as multiple inputs for the same function in a query. This is helpful to make a large number of queries more efficiently.

We provide both services in two ways:

• weco.WecoAI client to be used when you want to maintain the same client service across a portion of code. This is better for dense service usage.
• weco.query and weco.build to be used when you only require sparse usage.

Usage

When using the WeCo API, you will need to set the API key: You can find/setup your API key here by navigating to the API key tab. Once you have your API key, you may pass it to the weco client using the api_key argument input or set it as an environment variable such as:

export WECO_API_KEY=<YOUR_WECO_API_KEY>

Example

We create a function on the web console for the following task:

"I want to evaluate the feasibility of a machine learning task. Give me a json object with three keys - 'feasibility', 'justification', and 'suggestions'."

Now, you're ready to query this function anywhere in your code!

from weco import query
response = query(
    fn_name=fn_name,
    fn_input="I want to train a model to predict house prices using the Boston Housing dataset hosted on Kaggle.",
)

For more examples and an advanced user guide, check out our function builder cookbook.

Happy building $f$(👷‍♂️)!