Capstone project for ECE496 at the University of Toronto.
- Sebastion Czyrny ([email protected])
 - Danny Ahmad ([email protected])
 - David Marcovitch ([email protected])
 - Mert Okten ([email protected])
 
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Ensure you have Python 3.x installed on your system.
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Clone the repository to your local machine:
git clone https://github.com/ECE496-LLM-Agent-Shareholder-Report-Gen/LLM-Agent.git - 
Navigate to the project directory.
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(Optional) Create and activate a virtual environment to isolate your project dependencies:
python3 -m venv venv source venv/bin/activate # On Linux/Mac .\venv\Scripts\activate # On Windows
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Install the required dependencies using pip:
pip install -r requirements.txt - 
(Optional) Run an Ollama server:
a. Set your Ollama environment variable:
export OLLAMA_MODELS=<path to ollama models>b. Navigate to ollama folder and run Ollama server:
./ollama-linux-amd64 serve& - 
Set folder paths and API Keys (optional) in the
config.pyfile - 
Run streamlit app:
streamlit run streamlit_app.py 
Thank you for considering contributing to our project! Contributions are welcome from everyone.
To contribute to this project, please follow these guidelines:
- Fork the repository and clone it to your local machine.
 - Create a new branch for your contribution: 
git checkout -b feature/new-feature. - Make your changes and test them thoroughly.
 - Commit your changes: 
git commit -m "Add new feature". - Push to your branch: 
git push origin feature/new-feature. - Submit a pull request, describing your changes in detail and mentioning any related issues.
 - After submitting the pull request, our team will review your changes and provide feedback as needed.
 
Please ensure that your contributions adhere to our code of conduct.
If you have any questions or need assistance with the contribution process, feel free to reach out to us by creating an issue.
This project is licensed under the MIT License - see the LICENSE file for details.