After the bills are covered, how much is actually safe to spend? monetr organizes an entire budgeting application around that one question. Inspired by the defunct Simple bank, it budgets paycheck by paycheck rather than month by month. Funding schedules encode when you get paid - including multiple schedules per account and a weekend-exclusion option for deposits that land early - and every expense or savings goal is tied to one. monetr then calculates how much of each recurring obligation (rent, car payment, subscriptions, on any repeat interval) to set aside from each paycheck, so a large bill never has to come out of a single check. What remains after allocations is surfaced as Free-To-Use, and a forecasting timeline projects contributions, due dates, and leftover funds forward so low-balance periods are visible before they happen. Transactions arrive either as OFX uploads from your bank or automatically through a Plaid connection using your own API credentials, keeping balances and transactions synced without manual entry. The app is mobile-friendly and installable as a PWA on desktop or phone. Self-hosting via Docker Compose is completely free, with all source code public and your financial data on your own hardware.

Upload a report, ask a "what if" question in plain language, and MiroFish builds a small simulated society that plays out the answer before you commit to a decision. It reads your seed documents, whether news, policy drafts, financial signals, or a novel, and extracts entities and relationships into a GraphRAG knowledge graph. Entities from the graph become agents with a profession, a biography, and interest tags, and the app estimates simulation rounds from the simulated time span, with a custom mode for shorter runs. Agents post and react on two simulated platforms at once, a feed-style plaza and a topic community, while a live monitor tracks rounds, elapsed simulated time, and actions. A ReportAgent then plans an outline and writes the prediction report section by section with the InsightForge, PanoramaSearch, QuickSearch, and InterviewSubAgent tools. Afterward you can keep questioning the ReportAgent, chat with any individual agent, or send a survey question to a selected group and read their answers. Typical uses include rehearsing public relations responses, testing policy drafts against likely reactions, and exploring alternate endings for a story. The interface switches between English and Chinese, and you bring your own model: any OpenAI SDK compatible LLM endpoint works, Zep Cloud stores agent memory, and the project suggests starting under 40 rounds because runs consume many tokens. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

If your money is split across a bank app, a brokerage portal, and a half-abandoned spreadsheet, YAFFA, a self-hosted personal finance application, gathers it into one ledger with budgets, scheduled transactions, and forecasts. Record withdrawals, deposits, and transfers across unlimited accounts, and split a single supermarket receipt across categories so it lands in both Food and Household. Suggestions surface your most-used accounts and payees, and each payee's default category fills in automatically. Define rent, salary, or a loan payment once as a scheduled transaction; it appears on the dashboard calendar, enters with one action or records itself, and feeds the forecast. Import bank history from CSV or QIF files with rules for country- and bank-specific formats, and review every row before it is recorded. Optional AI document processing turns a receipt, invoice, or forwarded email into a draft transaction with payee, date, amount, and line items, using your own OpenAI or Gemini key and self-hosted Tesseract OCR for images. Accounts in different currencies roll up into your default currency using daily rates from the free Frankfurter service. Investments track gain and loss, with optional daily prices from Alpha Vantage. The dashboard summarizes accounts and upcoming schedules, the cash flow report can look ahead with a forecast, and Find Transactions filters history by payee, category, tag, or date. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 400 GitHub stars and growing, Pythia transforms a local LLM into a self-calibrating geopolitical oracle that watches the entire planet and predicts what happens next — no API keys, no cloud, no cost. The Osiris-based Three.js globe frontend streams 30+ concurrent live feeds including GDELT geopolitics, armed conflict events, USGS earthquakes, NWS storm polygons, EONET disasters, FIRMS wildfires, Polymarket crowd odds, cryptocurrency and commodity prices, UNHCR displacement data, WHO disease outbreaks, and WFP food insecurity indicators. The FastAPI backend fuses these heterogeneous sources into a unified world brief, pipes it through Ollama, and generates located predictions across 24-hour, weekly, monthly, and yearly horizons — each carrying a probability, reasoning, and geocoordinates that fly the globe to the event. A council of four specialist swarm agents — Strategist, Economist, Naturalist, and Skeptic — re-scores every forecast, surfacing consensus, dissent, and splits through Brier-weighted voting where historically accurate personas earn louder votes. The engine maintains a persistent ledger graded by an LLM judge against archived world state, producing running Brier scores and calibration charts. Signal rules fire browser notifications and webhooks when conditions match, a morning brief digest summarizes overnight changes, and the agent API at port 8088 delivers the complete world view in a single JSON call compressed to approximately 50 tokens for AI agent consumption. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.