Skip to main content

This is my tools package

Project description

Agent-Connector

PyPI version Build Status License Python Version Issues Pull Requests Code Size

Downloads

The Agent Connector is a cutting-edge Prompt Flow plugin that establishes a direct connection to GPT Nexus, a sophisticated agent development and testing platform. This innovation is highlighted in the book GPT Agents In Action by Manning Publications, showcasing its importance in the realm of AI-driven solutions.

Background

In the rapidly evolving field of artificial intelligence, the development and testing of AI agents remain paramount. Agent Connector serves as a bridge to GPT Nexus, enabling developers to seamlessly integrate and interact with AI agents within their applications. This tool is designed to enhance the efficiency of AI agent deployment, offering a streamlined workflow for developers seeking to leverage the capabilities of GPT Nexus.

Installation

Installing Agent Connector is a straightforward process that can be accomplished with a simple pip command. Ensure you have Python installed on your system, and then run the following command in your terminal:

pip install agent-connector

This command will fetch and install the latest version of Agent Connector from PyPI, along with its dependencies.

Setup

After installation, integrating Agent Connector into your Prompt Flow involves a few simple steps:

  1. Add Agent Connector as a tool to your Prompt Flow. This step typically involves updating your Prompt Flow configuration to include Agent Connector as an available plugin.

  2. Create a custom connection by setting the base_url parameter to the URL of your GPT Nexus instance. This is crucial for ensuring that Agent Connector can communicate with GPT Nexus.

  3. Configure the connection parameters including agent_name, agent_profile, agent_actions, and user_input. These parameters are essential for defining how Agent Connector interacts with AI agents through GPT Nexus.

Usage

With Agent Connector set up, you can start leveraging the power of GPT Nexus within your applications. Here's a quick overview of how to use it:

  1. Initialize the Agent Connector with your custom configuration, specifying the connection details and agent parameters.

  2. Invoke Agent Connector within your Prompt Flow, passing in user_input and any other relevant parameters defined during setup.

  3. Receive and process the response from GPT Nexus, utilizing the output from your AI agents in your application's workflow.

Agent Connector simplifies the process of connecting to and utilizing GPT Nexus, making it an indispensable tool for developers working with AI agents.

For more detailed examples and advanced configurations, please refer to the documentation or explore the examples directory in this repository.


We welcome contributions and feedback on Agent Connector! If you encounter any issues or have suggestions for improvements, please file an issue on this GitHub repository.

Happy coding!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agent_connector-0.0.4.tar.gz (4.9 kB view details)

Uploaded Source

Built Distribution

agent_connector-0.0.4-py3-none-any.whl (10.2 kB view details)

Uploaded Python 3

File details

Details for the file agent_connector-0.0.4.tar.gz.

File metadata

  • Download URL: agent_connector-0.0.4.tar.gz
  • Upload date:
  • Size: 4.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.11

File hashes

Hashes for agent_connector-0.0.4.tar.gz
Algorithm Hash digest
SHA256 d4313bf40b89b447ab5c8e2203950a2c9f772444dbb3e64f9d41f3e3b311d23c
MD5 5c836556b92a32215fd6b86bc2b474e5
BLAKE2b-256 130df95f0a348efc4b73a8d6b771be37141022d5438d07ab505962235c4ce9a7

See more details on using hashes here.

File details

Details for the file agent_connector-0.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for agent_connector-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 7e15f9c5a32fd971f770ccfc7b953e1eeb9a370df85e606b82a041d781d72596
MD5 2d764872262301d134b36fa0ee3e2a9e
BLAKE2b-256 a974073795457b3ef7f7d5d42159d3f6db2c6affd2d2208957af701304c05860

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page