[READM]E

README.md

@@ -1,67 +1,93 @@
-[![Multi-Modality](agorabanner.png)](https://discord.com/servers/agora-999382051935506503)
+# AgentScan
 
-# Python Package Template
+**Production-Grade, Enterprise-Ready, and Bleeding-Edge Multi-Agent Observability**
 
-[![Join our Discord](https://img.shields.io/badge/Discord-Join%20our%20server-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/agora-999382051935506503) [![Subscribe on YouTube](https://img.shields.io/badge/YouTube-Subscribe-red?style=for-the-badge&logo=youtube&logoColor=white)](https://www.youtube.com/@kyegomez3242) [![Connect on LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/kye-g-38759a207/) [![Follow on X.com](https://img.shields.io/badge/X.com-Follow-1DA1F2?style=for-the-badge&logo=x&logoColor=white)](https://x.com/kyegomezb)
+[![PyPI version](https://badge.fury.io/py/AgentScan.svg)](https://badge.fury.io/py/AgentScan)
+[![Build Status](https://travis-ci.com/yourusername/AgentScan.svg?branch=main)](https://travis-ci.com/yourusername/AgentScan)
+[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
 
-A easy, reliable, fluid template for python packages complete with docs, testing suites, readme's, github workflows, linting and much much more
+## Overview
 
+AgentScan is a cutting-edge observability framework designed specifically for multi-agent systems. In the rapidly evolving landscape of AI and automation, monitoring, managing, and scaling agent-based systems have become crucial for enterprise success. AgentScan is built to be the best agent monitoring framework, ensuring your agents operate efficiently, securely, and at scale, no matter the complexity of your deployment.
 
-## Installation
+## Key Benefits
 
-You can install the package using pip
+### 🌟 **Production-Grade Observability**
+AgentScan offers unparalleled visibility into your multi-agent systems, providing real-time metrics, alerts, and insights that are crucial for maintaining optimal performance in production environments. It’s built to handle the most demanding enterprise use cases, ensuring that your agents are always functioning as expected.
 
-```bash
-pip install -e .
-```
+### 🚀 **Enterprise-Ready Integration**
+Seamlessly integrate AgentScan into your existing infrastructure. Whether you're using Swarms, LangChain, AutoGen, or any other agent framework, AgentScan is designed to be fully compatible, making it the go-to observability solution for any multi-agent ecosystem.
 
-# Usage
-```python
-print("hello world")
+### ⚡ **Unmatched Speed and Efficiency**
+AgentScan is engineered for speed. With an architecture optimized for low-latency monitoring, you can trust that your agent systems will be observed and analyzed in real time, allowing for immediate detection and resolution of issues.
 
-```
+### 🔧 **Customizable and Extensible**
+Tailor AgentScan to your specific needs with its highly modular design. Add custom metrics, integrate with your existing logging and alerting systems, and build on top of a framework that scales with your enterprise.
 
+## Vision
 
+At AgentScan, our vision is to become the industry standard for multi-agent observability. We aim to provide enterprises with the tools they need to monitor, manage, and optimize their agent systems, ensuring that they can scale their operations with confidence. Our goal is to be the most reliable, flexible, and efficient monitoring solution on the market, empowering businesses to harness the full potential of their multi-agent ecosystems.
 
-### Code Quality 🧹
+## Installation
+
+Installing AgentScan is as simple as running the following command:
+
+```bash
+pip install agentscan
+```
 
-- `make style` to format the code
-- `make check_code_quality` to check code quality (PEP8 basically)
-- `black .`
-- `ruff . --fix`
+## Getting Started
 
-### Tests 🧪
+Once installed, AgentScan can be easily integrated into your agent systems. Here's a quick guide to get you up and running:
 
-[`pytests`](https://docs.pytest.org/en/7.1.x/) is used to run our tests.
+### 1. Import AgentScan into Your Project
 
-### Publish on PyPi 🚀
+```python
+from AgentScan import AgentScan
+```
 
-**Important**: Before publishing, edit `__version__` in [src/__init__](/src/__init__.py) to match the wanted new version.
+### 2. Initialize AgentScan
 
+```python
+# Initialize AgentScan with your preferred configurations
+monitoring = AgentScan(config={
+    'framework': 'Swarms',  # Replace with your agent framework
+    'log_level': 'INFO',
+    'alerts': True,
+    'custom_metrics': ['cpu_usage', 'memory_consumption']
+})
 ```
-poetry build
-poetry publish
+
+### 3. Start Monitoring Your Agents
+
+```python
+# Start monitoring your agents in real time
+monitoring.start()
 ```
 
-### CI/CD 🤖
+### 4. Analyze and Optimize
+
+Leverage AgentScan’ rich dashboard and analytics to gain deep insights into your multi-agent systems, identify bottlenecks, and optimize performance.
+
+## Compatibility
 
-We use [GitHub actions](https://github.com/features/actions) to automatically run tests and check code quality when a new PR is done on `main`.
+AgentScan is designed to be framework-agnostic, meaning it can seamlessly integrate with any agent framework, including but not limited to:
 
-On any pull request, we will check the code quality and tests.
+- Swarms
+- LangChain
+- AutoGen
+- Custom-built agent frameworks
 
-When a new release is created, we will try to push the new code to PyPi. We use [`twine`](https://twine.readthedocs.io/en/stable/) to make our life easier. 
+If your framework is not listed, AgentScan provides a flexible API to ensure smooth integration.
 
-The **correct steps** to create a new realease are the following:
-- edit `__version__` in [src/__init__](/src/__init__.py) to match the wanted new version.
-- create a new [`tag`](https://git-scm.com/docs/git-tag) with the release name, e.g. `git tag v0.0.1 && git push origin v0.0.1` or from the GitHub UI.
-- create a new release from GitHub UI
+## Contributing
 
-The CI will run when you create the new release.
+We welcome contributions from the community. If you have ideas, bug reports, or improvements, feel free to submit an issue or a pull request. For major changes, please open an issue first to discuss what you would like to change.
 
-# Docs
-We use MK docs. This repo comes with the zeta docs. All the docs configurations are already here along with the readthedocs configs.
+## License
 
+AgentScan is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
 
+## Contact
 
-# License
-MIT
+For enterprise support, custom integration services, or any other inquiries, please contact our team at [[email protected]](mailto:[email protected]).