# abstract Server
## Table of Contents
- [Introduction](#Introduction)
- [Installation](#Installation)
- [Getting Started](#Getting-Started)
- [Documentation](#Documentation)
- [Contact](#Contact)
- [License](#License)
## 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:
```sh
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](#overview)
- [Installation](#installation)
- [Usage](#usage)
- [Classes and Functions](#classes-and-functions)
- [PromptManager](#promptmanager-class)
- [hard_request](#hard_request-function)
- [quick_request](#quick_request-function)
- [Examples](#examples)
- [Contributing](#contributing)
- [License](#license)
## 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
1. Install the required Python packages:
```bash
pip install openai
```
2. 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](CONTRIBUTING.md).
## License
This module is licensed under the [MIT License](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](https://github.com/AbstractEndeavors/abstract_essentials/abstract_ai).
## License
`abstract_server` is released under the [MIT License](https://opensource.org/licenses/MIT).
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"description": "# abstract Server\n\n## Table of Contents\n- [Introduction](#Introduction)\n- [Installation](#Installation)\n- [Getting Started](#Getting-Started)\n- [Documentation](#Documentation)\n- [Contact](#Contact)\n- [License](#License)\n\n## Introduction\n\n---\n\n## Installation of `abstract-server`\n\nTo install `abstract_server`, you can either use pip or manually set it up by cloning the repository:\n\n### Using pip:\n\n```sh\npip install abstract-server\n```\n\n**Note**: `abstract_server` requires Python 3.6 or later. Ensure you meet this requirement before proceeding with the installation.\n\n---\n\n## Getting Started\n\nHere is a basic example of using `abstract_server`:\n\n## Documentation\n\n`abstract_server` consists of the following Python files and their corresponding functionalities:\n\n### 1. `response_handling.py`:\n\n### 2. `api_call.py`:\n\nSure, here's an exhaustive `readme.md` for the `api_calls.py` component of the `abstract_ai` module:\n\n# `api_calls.py` - Abstract AI Module\n\n`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.\n\n## Table of Contents\n- [Overview](#overview)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Classes and Functions](#classes-and-functions)\n - [PromptManager](#promptmanager-class)\n - [hard_request](#hard_request-function)\n - [quick_request](#quick_request-function)\n- [Examples](#examples)\n- [Contributing](#contributing)\n- [License](#license)\n\n## Overview\n\n`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.\n\n## Installation\n\n\n1. Install the required Python packages:\n\n ```bash\n pip install openai\n ```\n\n2. 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.\n\n## Usage\n\n## Classes and Functions\n\n### PromptManager Class\n\n\n### hard_request Function\n\nThe `hard_request` function sends a hard request to the OpenAI API with the provided parameters. It is a simplified way to make API calls.\n\n### quick_request Function\n\nThe `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.\n\n## Examples\n\nFor 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.\n\n## Contributing\n\nIf you'd like to contribute to the development of the `abstract_server` module or report issues, please refer to the [Contributing Guidelines](CONTRIBUTING.md).\n\n## License\n\nThis module is licensed under the [MIT License](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.\n\nFeel free to use `api_calls.py` to enhance your interactions with OpenAI's GPT-3 model in your projects.\n### 3. `endpoints.py`:\n\n### 4. `tokenization.py`\n\n\n\n## Contact\n\nShould you have any issues, suggestions or contributions, please feel free to create a new issue on our [Github repository](https://github.com/AbstractEndeavors/abstract_essentials/abstract_ai).\n\n## License\n\n`abstract_server` is released under the [MIT License](https://opensource.org/licenses/MIT).\n\n\n",
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