I Analyzed My Finance With Local LLMs

Step-by-Step Tutorial: Analyzing Your Finances with Local LLMs

1. Downloading and Installing AMA:

• Visit the AMA website and download the tool for your operating system (available for Mac OS and Linux, with Windows support coming soon).
• Install AMA on your laptop by following the installation instructions provided on the website.

2. Installing and Running LLM Models:

• Use AMA to install the desired LLM model by running the command AMA pull [model_name].
• Start using the installed model by running AMA run [model_name] in the terminal.

3. Classifying Expenses from Bank Statements:

• Use the LLM model to classify expenses in your bank statement into categories such as groceries, rent, travel, etc.
• Analyze the categorized data in Python and create visualizations to gain insights.

4. Customizing LLM Models:

• Create a custom LLM model by specifying a model file that suits your specific use case.
• Use AMA to create the custom model and start using it for expense classification.

5. Interacting with LLMs in Python:

• Install the Langchain community library using pip install langchain.
• Access the LLM models installed through AMA in Python environment, such as Jupyter notebook or Visual Studio Code.

6. Processing Transaction Data:

• Read and preprocess your transaction data in a format that can be fed to the LLM model for classification.
• Handle large datasets by breaking them into smaller groups to optimize the model's response.

7. Creating a Personal Finance Dashboard:

• Use Plotly Express to visualize income and expense breakdowns for different years.
• Utilize Panel library to create interactive data dashboards easily and efficiently.

8. Organizing Dashboard Layout:

• Combine various charts and graphs to display income breakdown, expense breakdown, and monthly earnings/spending for each year.
• Use a template like Fastless template from Panel to structure and present the dashboard effectively.

9. Review and Customize:

• Review the dashboard to gain insights into your finances, including income sources, expense categories, and monthly trends.
• Customize the dashboard further by adding elements like assets, investments, or mortgage payments to get a comprehensive overview of your financial status.

10. Continuous Learning and Exploration:

• Explore other data science projects and experiment with open-source language models to enhance your financial analysis skills.
• Stay updated on the latest trends in using LLMs for personal finance management and data analytics.

By following these steps, you can effectively analyze your finances using local LLMs and create insightful visualizations to track your income, expenses, and financial trends over time.