topaLE
/
ghostfolio
mirror of https://github.com/ghostfolio/ghostfolio
1
0
Fork 0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
4727 Commits
19 Branches
688 Tags
297 MiB
 
 
 
 
 
Tree: 20268ee78f
Branches Tags
${ item.name }
Create tag ${ searchTerm }
Create branch ${ searchTerm }
from '20268ee78f'
${ noResults }
ghostfolio/BOUNTY.md

9.6 KiB
Raw Blame History

AgentForge Bounty — $500 Submission

The Customer

A 32-year-old software engineer who uses Ghostfolio to track their $94k investment portfolio and is trying to figure out:

  1. Whether their portfolio can fund a down payment on a home
  2. Whether to accept a $180k job offer in Seattle (is it actually a raise after cost of living?)
  3. What their retirement looks like if they start buying rental properties now

...all in one conversation, without switching between a portfolio app, a real estate site, a COL calculator, a spreadsheet, and a financial advisor.

The specific pain: "I have $94k in my Ghostfolio portfolio, I got a job offer in Seattle, I'm thinking about buying a house, and I want to know if any of this makes sense together — but every tool I use only knows about one piece."

This person needs a financial co-pilot that knows about their whole picture — investments, real estate equity, and major life decisions — and can reason about all three in one place.

The Features

1. Portfolio → Down Payment Bridge

Reads the user's live Ghostfolio portfolio and calculates exactly which housing markets they can afford at 20% down. Compares conservative (60%), full (100%), and safe (80%) scenarios. Includes monthly payment estimates and rent vs. buy verdict.

2. Job Offer Affordability Calculator

Takes any salary offer and destination city, adjusts for cost of living difference, and tells the user whether it is a real raise in purchasing power. Compares state income tax. Works for 200+ cities worldwide. Example: $180k Seattle vs $120k Austin = NOT a real raise (-$5,593 purchasing power loss after COL adjustment).

3. Property Tracker — Full CRUD

Users log owned properties, track equity, monitor appreciation over time. The agent supports all four CRUD operations via natural language:

  • CREATE: add_property(address, purchase_price, current_value, mortgage_balance) → stores in SQLite, returns equity
  • READ: get_properties() → lists all active properties with equity, appreciation, mortgage balance
  • UPDATE: update_property(id, current_value=490000) → recalculates equity after market changes
  • DELETE: remove_property(id) → soft-delete preserving audit trail, property no longer in active list

Persists across sessions in agent/data/properties.db (SQLite).

4. Unified Net Worth View

Combines live investment portfolio from Ghostfolio API + real estate equity from SQLite into one complete financial picture. Single conversation turn: "What is my total net worth?" returns portfolio + all property equity + total.

5. Relocation Runway Calculator

Calculates month-by-month timeline until the user rebuilds emergency fund, reaches down payment, and feels financially stable after any relocation. Works for any two cities globally.

6. Wealth Gap Visualizer

Compares actual net worth against Federal Reserve median wealth by age group. Projects retirement income at current savings rate. Source: Federal Reserve SCF 2022.

7. Life Decision Advisor

Orchestrates all tools into one complete recommendation for job offers, relocations, home purchases, and rent vs. buy decisions. Returns verdict, tradeoffs, confidence level, and next steps.

8. Equity Unlock Advisor

For homeowners: models three 10-year scenarios for home equity — keep untouched, cash-out refi and invest, or use as rental property down payment.

9. Real Estate Strategy Simulator

Simulates buying a home every N years for M years and renting previous ones. Uses the user's own appreciation/rent assumptions, not guesses. Returns year-by-year net worth projection.

10. Family Financial Planner

Models the financial impact of having children for any city. Covers 25+ US cities and international cities. Shows income needed, childcare cost breakdown, and international comparisons (Berlin $333/month vs Austin $1,500/month).

Data Sources

Primary: SQLite Property Database (agent/data/properties.db)

This is the stateful CRUD data the agent uses. Users add their own properties via natural language. The data persists in SQLite across sessions. The agent reads, writes, updates, and soft-deletes property records through 5 tool functions:

add_property      → INSERT into properties table
get_properties    → SELECT all active properties
update_property   → UPDATE specific fields (value, mortgage, etc.)
remove_property   → UPDATE is_active=0 (soft delete)
get_total_net_worth → aggregate equity across all active properties

The agent accesses this data by calling property_tracker.py tool functions through the LangGraph routing layer. The LangGraph graph classifies the user's intent → routes to the property tracker node → executes the appropriate CRUD function → returns structured JSON result → LLM formats into natural language response.

Supporting: Ghostfolio Portfolio API

Live investment portfolio data (holdings, total value, allocation, performance) fetched from http://localhost:3333/api/v1/portfolio using the user's bearer token. This is the existing Ghostfolio data the agent is built on top of.

How accessed: The agent receives the user's Ghostfolio bearer token from the Angular frontend, uses it to call the Ghostfolio REST API, and incorporates the live portfolio data into property-aware calculations (e.g., net worth = portfolio value + real estate equity).

Supporting: Yahoo Finance

Live stock prices for portfolio performance and YTD calculations. The agent fetches current prices from Yahoo Finance when computing gains, allocations, and real-time portfolio value. Used by portfolio_analysis to work around Ghostfolio's local Yahoo feed limitations.

Supporting: Teleport API

Cost of living and housing data for 200+ cities worldwide. Powers the Job Offer Affordability Calculator and Relocation Runway features. Fetched from api.teleport.org for cities outside Austin; Austin areas use ACTRIS instead.

Supporting: ACTRIS/Unlock MLS January 2026

Licensed Austin TX real estate market data for listing search and neighborhood comparisons. Provided by the developer, who is a licensed Austin real estate agent. Embedded in agent/tools/real_estate.py as structured data.

Usage: Powers the Portfolio → Down Payment Bridge feature for Austin markets, and the real estate search/compare features. Cited in agent responses as "ACTRIS/Unlock MLS January 2026".

Supporting: Federal Reserve Survey of Consumer Finances 2022

Public data. Age-group wealth percentiles (25th, median, 75th, 90th) from the Fed's most recent SCF. Hard-coded in agent/tools/wealth_visualizer.py.

Usage: Powers the Wealth Gap Visualizer. Cited in agent responses as "Federal Reserve SCF 2022".

The CRUD Operations (Explicit)

Operation Function What It Does
CREATE add_property(address, purchase_price, current_value, mortgage_balance) Inserts new property into SQLite, calculates equity, returns property dict with ID
READ get_properties() / list_properties() Selects all active properties, returns with equity, appreciation, and summary totals
UPDATE update_property(id, current_value=..., mortgage_balance=...) Updates specified fields, recalculates equity and appreciation_pct
DELETE remove_property(id) Sets is_active=0 (soft delete), property no longer appears in active list but data preserved

Bonus: get_total_net_worth(portfolio_value) aggregates equity across all active properties + adds investment portfolio → returns complete financial picture.

The Impact

The app solves a real problem. Most people with both investments and real estate have no single place to see the complete picture or run scenarios on their own numbers.

A user adds their home (bought $400k, worth $480k, mortgage $310k) and immediately sees $170k equity tracked alongside their $94k investment portfolio — total net worth $264k in one view.

They then ask: "What if I buy a home every 2 years for the next 10 years and rent the previous one?"

The agent asks what appreciation and rent assumptions they want to use — because we do not guess at numbers for markets we cannot verify. The user says "moderate — 4% appreciation." The agent runs the projection using their actual portfolio balance, their income, and their assumptions, and returns a year-by-year picture of what their net worth could look like at retirement.

This is a conversation people pay financial advisors hundreds of dollars per hour to have. This app does it in 30 seconds — honestly, with the user's own numbers, and with clear disclaimers about what is a projection vs. a prediction.

Eval & Verification

  • 182 tests (100% pass rate) covering portfolio logic, CRUD flows, strategy simulation, edge cases, adversarial inputs, and multi-step chains
  • 3 verification systems: confidence scoring, source attribution (citation enforcement), and domain constraint check (no guaranteed-return language)
  • LangSmith tracing active — every request traced at smith.langchain.com
  • All tool failures return structured error codes (e.g., PROPERTY_TRACKER_NOT_FOUND)
  • Conversation history maintained across all turns via AgentState.messages