revrseai-python 0.1.0

Python RevrseAI client library

RevrseAI Python Library

The RevrseAI Python library provides convenient access to the RevrseAI API from applications written in Python. It allows you to generate APIs for any Android app using natural language and execute those APIs programmatically.

Installation

pip install revrseai-python

Requirements

• Python 3.11+

Usage

The library needs to be configured with your account's API key which is available in your RevrseAI Dashboard. Set it directly or use the REVRSE_AI_API_KEY environment variable:

from revrseai import RevrseAI

client = RevrseAI("your_api_key")

Generate an API

Generate an API for any Android app by describing what you want to do:

from revrseai import RevrseAI

client = RevrseAI("your_api_key")

task = client.generate(
    "Log into Job Today and get the jobs on my feed",
    secrets={
        "username": "your_username",
        "password": "your_password"
    }
)

# Wait for generation to complete
result = task.wait_till_done()

# Print the generated API documentation
result.print_markdown_documentation()

Execute an Endpoint

Execute endpoints using one of three methods:

By endpoint ID:

result = client.execute(
    endpoint_id="<endpoint_id>",
    data={"username": "your_username", "password": "your_password"}
)
print(result.status)
print(result.data)

By task ID and endpoint name:

result = client.execute(
    task_id="<task_id>",
    endpoint="login",
    data={"username": "your_username", "password": "your_password"}
)

By app name and endpoint:

result = client.execute(
    app="Job Today",
    endpoint="login",
    data={"username": "your_username", "password": "your_password"}
)

Get App Info

Retrieve information about existing endpoints for an app:

info = client.info("Job Today")

# Print available endpoints
info.print_markdown_documentation()

# Execute an endpoint directly
endpoint = info.endpoints[0]
result = endpoint.execute(data={"key": "value"})

Export Documentation

Export generated API documentation to a file:

task = client.generate("Natural language instructions to perform the task")
result = task.wait_till_done()

# Export to markdown file
result.export_markdown_documentation("api_docs.md")