Life Insurance Coverage Advisor Agent

A Streamlit application that helps users estimate the amount of term life insurance they may need and surfaces currently available policy options. The app is powered by the Agno agent framework, uses OpenAI GPT-5 as the LLM, the E2B sandbox for deterministic coverage calculations, and Firecrawl for live web research.

Highlights

• Minimal intake form (age, income, dependents, debt, assets, existing cover, horizon, location).
• The agent runs Python code inside an E2B sandbox to calculate coverage with a discounted cash-flow style income replacement model.
• Firecrawl search is used to gather the latest term-life products for the user’s geography and coverage needs.
• Returns a concise coverage estimate, calculation breakdown, and up to three product suggestions with source links.

Prerequisites

You will need API keys for each external service:

Installation

1. Clone the GitHub repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git

2. Create and activate a virtual environment (optional but recommended).

3. Install dependencies:

pip install -r requirements.txt

4. Run the Streamlit app:

streamlit run life_insurance_advisor_agent.py

Using the App

1. Enter your OpenAI, Firecrawl, and E2B API keys in the sidebar (keys are kept in the local Streamlit session).
2. Provide the requested financial information and choose an income replacement horizon.
3. Click Generate Coverage & Options to launch the Agno agent workflow.
4. Review the recommended coverage, rationale, and suggested insurers. Raw agent output is available in an expander for debugging.

Disclaimer

This project is for educational and prototyping purposes only and does not provide licensed financial advice. Always validate the output with a qualified professional and confirm details directly with insurance providers.