Add my use case - personal finance assistant

tool_use/personal-finance-assistant/README.md

@@ -0,0 +1,25 @@
+# Personal Finance Assistant
+
+This use case demonstrates how to build a personal finance assistant using Anthropic's language models. The assistant can help users track their expenses, create budgets, calculate investment returns, and provide personalized financial advice.
+
+## Features
+
+- Expense Tracking: Users can input their expenses, categorize them, and get insights into their spending habits.
+- Budgeting: The assistant can help users create and stick to a monthly or yearly budget based on their income and expenses.
+- Investment Calculations: Users can input their investment details, and the assistant will calculate potential returns, risks, and provide recommendations.
+- Financial Advice: Based on the user's financial situation, the assistant can offer personalized advice on saving, investing, and managing debt.
+
+## Examples
+
+The `examples/` folder contains sample code for implementing different features of the personal finance assistant:
+
+- `budget_tracker.py`: A Python script that demonstrates how to track expenses and create budgets using Anthropic's language models.
+- `investment_calculator.js`: A JavaScript file that shows how to calculate investment returns and provide recommendations based on user inputs.
+
+## Usage
+
+To use this use case, you'll need to have access to Anthropic's language models and follow the setup instructions in the main repository. Once set up, you can run the example scripts or integrate the functionality into your own applications.
+
+## Contributing
+
+Contributions to this use case are welcome! If you have ideas for additional features, improvements, or bug fixes, please open an issue or submit a pull request.

tool_use/personal-finance-assistant/examples/budget_tracker.py

@@ -0,0 +1,24 @@
+import anthropic
+
+# Set up the Anthropic API client
+client = anthropic.Client("YOUR_API_KEY")
+
+# Define a function to track expenses
+def track_expense(description, amount, category):
+    # Use the Anthropic language model to categorize the expense
+    response = client.completion(
+        prompt=f"Categorize the following expense: {description}",
+        max_tokens=50,
+        stop_sequences=[],
+    )
+    categorized_category = response.result["choice"]
+
+    # Store the expense in a database or file
+    with open("expenses.txt", "a") as f:
+        f.write(f"{description},{amount},{categorized_category}\n")
+
+    print(f"Expense '{description}' of ${amount} categorized as '{categorized_category}'")
+
+# Example usage
+track_expense("Grocery shopping at Whole Foods", 75.25, "Food")
+track_expense("Paid rent for May", 1200.00, "Housing")

tool_use/personal-finance-assistant/examples/investment_calculator.js

@@ -0,0 +1,24 @@
+const anthropic = require("@anthropic/client");
+
+// Set up the Anthropic API client
+const client = new anthropic.Client("YOUR_API_KEY");
+
+// Define a function to calculate investment returns
+async function calculateInvestmentReturns(initialInvestment, years, expectedReturn) {
+  const prompt = `
+    Calculate the potential returns for an initial investment of ${initialInvestment} over ${years} years with an expected annual return of ${expectedReturn}%.
+
+    Provide the calculation steps and the final amount in a clear and easy-to-understand format.
+  `;
+
+  const response = await client.complete({
+    prompt,
+    maxTokens: 500,
+    stopSequences: [],
+  });
+
+  console.log(response.result.choice);
+}
+
+// Example usage
+calculateInvestmentReturns(10000, 10, 7);