feat(Update):

msoedov · msoedov · commit d29df0357681 · 2025-02-25T08:39:58.000+02:00
diff --git a/LICENSE b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 Alexander Miasoiedov/Myasoedov
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/Readme.md b/Readme.md
@@ -1,18 +1,104 @@
-# Meta Agent
 
+<p align="center"> <h1 align="center">Meta Agent</h1> <p align="center"> An automatic agent optimization framework for generating, evaluating, and selecting top-performing agents.<br /> Define your task, and let Meta Agent discover the perfect solution.<br /> <a href="#">Explore the Docs »</a> · <a href="#">Report a Bug »</a> </p> </p> <p align="center"> <a href="#"> <img alt="GitHub Last Commit" src="https://img.shields.io/github/last-commit/msoedov/meta_agent?style=for-the-badge&logo=git&labelColor=000000&color=6A35FF" /> </a> <a href="#"> <img alt="GitHub Repo Size" src="https://img.shields.io/github/repo-size/msoedov/meta_agent?style=for-the-badge&logo=database&labelColor=000000&color=yellow" /> </a> <a href="#"> <img alt="GitHub License" src="https://img.shields.io/github/license/msoedov/meta_agent?style=for-the-badge&logo=codeigniter&labelColor=000000&color=FFCC19" /> </a> <a href="https://pypi.org/project/meta_agent/"> <img alt="PyPI Version" src="https://img.shields.io/pypi/v/meta_agent?style=for-the-badge&logo=pypi&labelColor=000000&color=00CCFF" /> </a> </p>
 
-Meta agent designed to generate, evaluate, and select the best-performing agents for your tasks. It produces 16 candidate "probes," scores them based on customizable evaluation metrics, and identifies the optimal agent configuration.
+Meta Agent is a powerful, imperative, define-by-run framework designed to simplify agent development. It generates 16 candidate "probes" with varied configurations, evaluates them against customizable metrics, and selects the best-performing agent for your task. Whether you're analyzing data, predicting outcomes, or automating workflows, Meta Agent optimizes the process for you.
+## ✨ Features
 
-## Features
+- Automated Agent Generation
+- Creates 16 unique agent "probes" with diverse configurations tailored to your task.
+- Customizable Evaluation
+- Scores probes using built-in metrics (e.g., accuracy, speed) or your own custom evaluation function.
+- Framework Flexibility
+- Built with Pydantic-AI by default, with seamless support for frameworks like AutoGen or CrewAI.
+- Extensible Design
+- Easily adapt agent roles, tools, and evaluation criteria to suit your specific needs.
 
-- **Natural Language Input**: Describe your desired agent in plain English, and Meta Agent will translate it into a functional agent.
-- **Agent Generation**: Automatically builds 16 unique agent "probes" with varied configurations.
-- **Evaluation & Scoring**: Scores each probe based on performance metrics (e.g., accuracy, speed, task completion) and selects the best one.
-- **Framework Flexibility**: Built with Pydantic-AI by default, but adaptable to frameworks like AutoGen or crewAI.
-- **Extensible**: Easily customize agent roles, tools, and evaluation criteria.
 
-## Installation
+## 📦 Installation
 
+Install Meta Agent with a single command:
 ```shell
+pip install meta_agent
 
 ```
+## 🚀 Quick Start
+
+Get started in just a few lines of code. Below are examples to showcase Meta Agent’s capabilities.
+Basic Usage
+
+Generate an agent to analyze customer reviews and predict sentiment:
+```python
+import meta_agent
+
+# Build and optimize an agent
+best_agent = meta_agent.build_agent(
+    input_text="Create an agent to analyze customer reviews and predict sentiment.",
+    probe_count=16,
+    framework="crewai"
+)
+
+# View the selected agent's details
+print(best_agent.details)
+```
+### Custom Evaluation Function
+
+Define your own scoring logic to evaluate probes:
+```python
+import meta_agent
+import random
+
+# Custom evaluation function
+def custom_eval(trial: meta_agent.Trial) -> float:
+    return random.random()  # Replace with your own metric
+
+# Build an agent with custom evaluation
+best_agent = meta_agent.build_agent(
+    input_text="Create an agent to analyze customer reviews and predict sentiment.",
+    probe_count=16,
+    framework="crewai",
+    eval_fn=custom_eval
+)
+
+print(best_agent.details)
+```
+### Using a Test Dataset
+
+Provide a dataset to evaluate agents against specific inputs and expected outputs:
+```python
+import meta_agent
+
+# Build an agent with a test dataset
+best_agent = meta_agent.build_agent(
+    input_text="Create an agent to analyze customer reviews and predict sentiment.",
+    probe_count=16,
+    framework="crewai",
+    test_dataset=meta_agent.dataset(
+        ("Great product, love it!", 0.9),  # (input, expected_score)
+        ("Terrible service, very disappointed.", 0.2),
+        ("It's okay, nothing special.", 0.5)
+    )
+)
+
+print(best_agent.details)
+```
+
+## 🛠️ How It Works
+
+- Define Your Task: Provide a task description (e.g., "analyze customer reviews").
+- Generate Probes: Meta Agent creates 16 agent configurations with varying parameters.
+- Evaluate Performance: Each probe is scored based on your chosen metrics or dataset.
+- Select the Best: The top-performing agent is returned, ready for use.
+
+## 📚 Documentation
+
+For more details, check out the official documentation (coming soon!).
+## 🤝 Contributing
+
+We welcome contributions! Please see our contribution guidelines and feel free to submit issues or pull requests.
+
+## 📬 Get in Touch
+
+Have questions? Join our community or reach out:
+
+- Discord (coming soon!)
+- GitHub Issues
diff --git a/pyproject.toml b/pyproject.toml
@@ -7,7 +7,7 @@ maintainers = ["Alexander Miasoiedov <msoedov@gmail.com>"]
 repository = "https://github.com/msoedov/meta_agent" # Adjust if different
 homepage = "https://github.com/msoedov/meta_agent"
 documentation = "https://github.com/msoedov/meta_agent/blob/main/README.md"
-license = "Apache-2.0"
+license = "MIT"
 readme = "Readme.md"
 keywords = [
     "AI agent creation",
