Developer-Vs-Tester---Agentic-AI

🔄 Reflection Design Pattern in This Project

This project uses Reflection as an agent strategy — where the Developer agent reflects on feedback from the Tester agent, learns from it, and iteratively improves its code.

🧠 How It Works

1. The Developer agent generates initial code.
2. The Tester agent analyzes it, runs test cases, and gives feedback.
3. The Developer uses this feedback to reflect and revise the code.
4. This loop continues until the code passes or meets the criteria.

This emulates the Reflection Design Pattern: the system can inspect, evaluate, and modify its own behavior at runtime based on external feedback — a crucial concept in LLM agent frameworks like LangChain.

🔁 Benefits

• Dynamic learning without manual reprogramming
• Realistic developer-tester simulation
• Supports meta-cognitive behavior in AI agents

Graph

📜 Full Developer–Tester Conversation- for an example ("Write a python code for Tic-Toc-Toe Game")

🌐 Try It Now

This app is currently live at:

👉 Gradio Public Link
(Note: This link will expire in 7 days)

Make sure to enter open Ai api key

🚀 Deploy This Notebook to Hugging Face Spaces

Follow these steps to deploy your Gradio notebook app permanently:

pip install gradio
huggingface-cli login
gradio deploy