Updated data analysys agent (#328)

* enabled Llama Nemotron Super support in data analysis agent

* Delete .DS_Store

Author: katjasrz

community/.DS_Store

@@ -0,0 +1,68 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+
+# Virtual environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Distribution / packaging
+build/
+dist/
+*.egg-info/
+
+# Jupyter Notebook
+.ipynb_checkpoints/
+
+# Streamlit
+.streamlit/
+
+# Model files
+*.pkl
+*.pickle
+*.joblib
+*.h5
+*.hdf5
+*.onnx
+*.pb
+
+# Data files
+*.csv
+
+# Logs
+*.log
+logs/
+
+# API keys and secrets
+.env
+.env.local
+.env.production
+secrets.json
+config.json
+
+# IDE files
+.vscode/
+.idea/
+*.iml
+*.ipr
+*.iws
+
+# OS files
+.DS_Store
+Thumbs.db
+ehthumbs.db
+Desktop.ini
+
+# Temporary files
+*.tmp
+*.temp
+*.swp
+*.swo
+*~ 

community/data-analysis-agent/.gitignore

@@ -1,6 +1,6 @@
 # Data Analysis Agent
 
-An interactive, agentic data analysis application that leverages advanced LLM reasoning to help users explore, visualize, and understand their data using NVIDIA Llama-3.1-Nemotron-Ultra-253B-v1.
+An interactive, agentic data analysis application that leverages advanced LLM reasoning to help users explore, visualize, and understand their data using NVIDIA Llama-3.1-Nemotron-Ultra-253B-v1 and NVIDIA Llama-3.3-Nemotron-Super-49B-v1.5.
 
 ## Overview
 
@@ -10,17 +10,17 @@ This repository contains a Streamlit application that demonstrates a complete wo
 3. **Automated Visualization**: Generate relevant plots and charts
 4. **Transparent Reasoning**: Get detailed explanations of the analysis process
 
-The implementation leverages the powerful Llama-3.1-Nemotron-Ultra-253B-v1 model through NVIDIA's API, enabling sophisticated data analysis and reasoning.
+The implementation leverages the powerful Llama-3.1-Nemotron-Ultra-253B-v1 and Llama-3.3-Nemotron-Super-49B-v1.5 models through NVIDIA's API, enabling sophisticated data analysis and reasoning.
 
-Learn more about the model [here](https://developer.nvidia.com/blog/build-enterprise-ai-agents-with-advanced-open-nvidia-llama-nemotron-reasoning-models/).
+Learn more about the models [here](https://developer.nvidia.com/blog/build-enterprise-ai-agents-with-advanced-open-nvidia-llama-nemotron-reasoning-models/).
 
 ## Features
 
 - **Agentic Architecture**: Modular agents for data insight, code generation, execution, and reasoning
 - **Natural Language Queries**: Ask questions about your data—no coding required
 - **Automated Visualization**: Instantly generate and display relevant plots
 - **Transparent Reasoning**: Get clear, LLM-generated explanations for every result
-- **Powered by NVIDIA Llama-3.1-Nemotron-Ultra-253B-v1**: State-of-the-art reasoning and interpretability
+- **Powered by NVIDIA Llama-3.1-Nemotron-Ultra-253B-v1 and NVIDIA Llama-3.3-Nemotron-Super-49B-v1.5**: State-of-the-art reasoning and interpretability
 
 ![Workflow](./assets/workflow.png)
 
@@ -61,7 +61,7 @@ Learn more about the model [here](https://developer.nvidia.com/blog/build-enterp
 
 1. Run the Streamlit app:
    ```bash
-   streamlit run data_analysis.py
+   streamlit run data_analysis_agent.py
    ```
 
 2. Download example dataset (optional):
@@ -70,6 +70,7 @@ Learn more about the model [here](https://developer.nvidia.com/blog/build-enterp
    ```
 
 3. Use the application:
+   - Select a model from the dropdown menu
    - Upload a CSV file (e.g., the Titanic dataset)
    - Ask questions in natural language
    - View results, visualizations, and detailed reasoning
@@ -78,17 +79,24 @@ Learn more about the model [here](https://developer.nvidia.com/blog/build-enterp
 
 ![App Demo](./assets/data_analysis_agent_demo.png)
 
-## Model Details
+## Models Details
 
 The Llama-3.1-Nemotron-Ultra-253B-v1 model used in this project has the following specifications:
 - **Parameters**: 253B
 - **Features**: Advanced reasoning capabilities
 - **Use Cases**: Complex data analysis, multi-agent systems
 - **Enterprise Ready**: Optimized for production deployment
 
+The Llama-3.3-Nemotron-Super-49B-v1.5 model used in this project has the following specifications:
+- **Parameters**: 49B
+- **Features**: Efficient reasoning and and chat model
+- **Use Cases**: AI Agent systems, chatbots, RAG systems, and other AI-powered applications. Also suitable for typical instruction-following tasks
+- **Enterprise Ready**: Optimized for production deployment
+
 ## Acknowledgments
 
 - [NVIDIA Llama-3.1-Nemotron-Ultra-253B-v1](https://build.nvidia.com/nvidia/llama-3_1-nemotron-ultra-253b-v1)
+- [NVIDIA Llama-3.3-Nemotron-Super-49B-v1.5](https://build.nvidia.com/nvidia/llama-3_3-nemotron-super-49b-v1_5)
 - [Streamlit](https://streamlit.io/)
 - [Pandas](https://pandas.pydata.org/)
 - [Matplotlib](https://matplotlib.org/)