abstract_server
Project description
abstract Server
Table of Contents
Introduction
Installation of abstract-server
To install abstract_server
, you can either use pip or manually set it up by cloning the repository:
Using pip:
pip install abstract-server
Note: abstract_server
requires Python 3.6 or later. Ensure you meet this requirement before proceeding with the installation.
Getting Started
Here is a basic example of using abstract_server
:
Documentation
abstract_server
consists of the following Python files and their corresponding functionalities:
1. response_handling.py
:
2. api_call.py
:
Sure, here's an exhaustive readme.md
for the api_calls.py
component of the abstract_ai
module:
api_calls.py
- Abstract AI Module
api_calls.py
is a component of the Abstract AI module, designed to facilitate API calls to OpenAI's GPT-3 model. This module is intended to simplify the interaction with the GPT-3 API and handle responses in a structured manner.
Table of Contents
Overview
api_calls.py
serves as a bridge between your application and the OpenAI GPT-3 API. It provides a convenient interface to send requests, manage responses, and control the behavior of the API calls. This module is highly customizable, allowing you to define prompts, instructions, and response handling logic.
Installation
-
Install the required Python packages:
pip install openai
-
Set your OpenAI API key as an environment variable. By default, the module looks for an environment variable named
OPENAI_API_KEY
to authenticate API calls.
Usage
Classes and Functions
PromptManager Class
hard_request Function
The hard_request
function sends a hard request to the OpenAI API with the provided parameters. It is a simplified way to make API calls.
quick_request Function
The quick_request
function sends a quick request to the OpenAI API with simple configurations and prints the result. It is a convenient shortcut for quick API interactions.
Examples
For detailed examples and usage scenarios, refer to the examples
directory in this repository. You'll find practical code samples demonstrating how to use the abstract_server.py
module for various tasks.
Contributing
If you'd like to contribute to the development of the abstract_server
module or report issues, please refer to the Contributing Guidelines.
License
This module is licensed under the MIT License, which means you are free to use and modify it as per the terms of the license. Make sure to review the license file for complete details.
Feel free to use api_calls.py
to enhance your interactions with OpenAI's GPT-3 model in your projects.
3. endpoints.py
:
4. tokenization.py
Contact
Should you have any issues, suggestions or contributions, please feel free to create a new issue on our Github repository.
License
abstract_server
is released under the MIT License.
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