[FEATURE] Implemented Python-Based AI Workflow Visualizer (#87)

advance_ai_agents/advance_ai_agents/ai_workflow_visualizer/README.md

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+# 🧠 AI Workflow Visualizer
+
+**AI Workflow Visualizer** is a powerful tool that automatically **summarizes, parses, and visualizes intelligent agent workflows**.
+It leverages the **Nebius API** to generate structured, human-understandable visual representations of complex AI agent logs.
+
+---
+
+## 🚀 Features
+
+* **Workflow Summarization** – Automatically extracts key steps and decisions from raw agent logs.
+* **Graph Visualization** – Builds clear, interactive graph-based representations of workflows.
+* **Nebius API Integration** – Uses Nebius LLMs for accurate summarization and entity extraction.
+* **Dynamic Parsing** – Flexible parsing logic that adapts to diverse agent log formats.
+* **Sample Logs Included** – Comes with a ready-to-test sample log (`sample_logs/agent_log.json`).
+
+---
+
+## 🧩 Project Structure
+
+```bash
+ai_workflow_visualizer/
+│
+├── assets
+|    └── IM_1.png
+|    └── IM_2.png
+|    └── IM_3.png
+├── app.py                 
+├── graph_builder.py        
+├── nebius_client.py        
+├── parser.py               
+├── requirements.txt        
+└── sample_logs/
+    └── agent_log.json      
+
+
+## ⚙️ Installation & Setup
+### 1. Clone the repository
+
+```bash
+git clone https://github.com/Sanjana-m55/awesome-ai-apps.git
+cd awesome-ai-apps/advance_ai_agents/advance_ai_agents/ai_workflow_visualizer
+```
+
+### 2. Create and activate a virtual environment
+
+```bash
+python -m venv venv
+source venv/bin/activate        # On macOS/Linux
+venv\Scripts\activate           # On Windows
+```
+
+### 3. Install dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### 4. Add your Nebius API key
+
+Create a `.env` file and add:
+
+```
+NEBIUS_API_KEY=your_api_key_here
+```
+
+---
+
+## 🧠 Usage
+
+### Run the Visualizer
+
+```bash
+streamlit run app.py
+```
+
+### Example Input
+
+The visualizer uses logs like this:
+
+```json
+{
+  "agent": "ChatAgent",
+  "steps": [
+    {"action": "Search", "description": "Searching for user query..."},
+    {"action": "Analyze", "description": "Analyzing retrieved data..."},
+    {"action": "Respond", "description": "Generating final response..."}
+  ]
+}
+```
+
+### Output
+
+✅ Clean summary of workflow steps
+✅ Visual graph showing relationships and sequence of actions
+✅ Interactive insights into decision paths
+
+---
+
+## 🧠 Technologies Used
+
+* **Python 3.9+**
+* **Nebius API (LLM)**
+* **Graphviz / NetworkX** (for visualization)
+* **dotenv**
+* **JSON Parsing Libraries**
+
+---
+
+## 🤝 Contributing
+
+Contributions are welcome!
+Please fork the repo, create a branch, and submit a pull request:
+
+```bash
+git checkout -b feature/your-feature-name
+git commit -m "feat: describe your feature"
+git push origin feature/your-feature-name
+```
+
+---
+
+## 🧩 Example Commit
+
+```
+feat: implemented intelligent workflow summarization and visualization using Nebius API
+```
+
+---
+
+## 🪪 License
+
+This project is licensed under the **MIT License**.
+See the [LICENSE](../../LICENSE) file for details.
+
+---
+
+## 💡 Acknowledgments
+
+* [Nebius AI](https://nebius.com/) for providing advanced AI summarization APIs
+* [NetworkX](https://networkx.org/) for visualization support
+* All open-source contributors!
+
+---
+
+✨ *Developed with ❤️ by [Sanjana M](https://github.com/Sanjana-m55)*