Streamlit Data Analysis with PandasAI and Meta Llama 3 Model

This project is a simple web application for data analysis using Streamlit and PandasAI, integrating the Meta Llama 3 language model via Ollama. Users can upload CSV or XLSX files and interact with the data through natural language queries.

Features

• Upload CSV or Excel (XLSX) files.
• View the first few rows of your dataset.
• Ask questions about the data in natural language using the Llama 3 model.
• Receive answers in real-time using the pandasai library.

Installation

1. Clone the repository:

git clone https://github.com/zenklinov/Streamlit-CSV-excel-xlsx-Llama3-Ollama-PandasAI.git
cd Streamlit-CSV-excel-xlsx-Llama3-Ollama-PandasAI

2. Install dependencies: Ensure you have Python installed, then install required packages.

pip install -r requirements.txt

3. Set up Meta Llama 3 with Ollama: Install and configure Ollama to run Llama 3 locally. Ensure the model is running on http://localhost:11434/v1 for this application to connect successfully.

Usage

1. Run the Streamlit application: Open PowerShell (or Terminal), navigate to the project directory, and run:

streamlit run app2.py

2. Upload Data Files:

• After launching, use the "Upload your CSV or XLSX files" button to upload one or more data files.
• Select a file from the dropdown to load its data.

3. Interact with Your Data:

• Type a question about the data into the provided text area.
• Click "Ask" to receive a response generated by Llama 3 through the pandasai library.

Requirements

• Streamlit
• Pandas
• PandasAI
• Meta Llama 3 model (configured via Ollama)

Example

1. Upload your data file (CSV or Excel).
2. Type in queries like:

• "What is the average value in the column 'Price'?"
• "Show the rows where 'Quantity' is greater than 50."