Search Results for "budget"
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Showing 160 open source projects for "budget"
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Budget
Get a grip on your finances
...It includes tagging systems for categorizing expenses, enabling detailed analysis of spending habits and financial priorities. Budget also provides reporting tools that generate visual insights such as weekly balances and category breakdowns, helping users understand trends over time. Additional features such as receipt uploads and email summaries enhance usability and provide a more complete financial tracking experience. -
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Actual Budget
Fast, privacy-focused personal finance app
Actual Budget is a fast, privacy-focused personal finance app built around the proven envelope budgeting methodology. It keeps you in control of your money with tools designed to help you make thoughtful financial decisions rather than relying on automated guesswork. The app is fully local-first, meaning it works offline and syncs quietly across your devices without ever compromising ownership of your data. -
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Actual Budget
Local-first personal finance app for budgeting, tracking accounts,
Actual Budget is a local-first personal finance app designed for people who want a fast, privacy-focused, and fully user-controlled way to manage their money. It provides a modern platform for budgeting, tracking accounts, recording transactions, and understanding day-to-day finances without giving up ownership of your data. Actual is built around a local-first architecture, meaning your budget data lives on your device, while synchronization can be used to keep changes consistent across devices. ... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
...It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and then experiment with multiple strategies—evolutionary algorithms, Bayesian optimization, bandit methods, genetic algorithms, etc. Nevergrad supports parallelization, budget scheduling, and multiple cost/resource constraints, allowing it to scale to nontrivial optimization problems. It includes visualization tools and diagnostic metrics to compare strategy performance, track parameter evolution, and detect stagnation. -
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I hate money
A simple shared budget manager web application
I hate money is a web application made to ease shared budget management. It keeps track of who bought what, when, and for whom; and helps to settle the bills. I hate money is written in python, using the flask framework. It’s developed with ease of use in mind and is trying to keep things simple. Hope you (will) like it! The code is distributed under a BSD beerware derivative: if you meet the people in person and you want to pay them a craft beer, you are highly encouraged to do so. -
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any-llm
Communicate with an LLM provider using a single interface
...The project is designed to be framework-agnostic, making it easy to integrate into scripts, applications, or production systems without being tied to a specific stack. It includes a core SDK for direct usage as well as an optional gateway layer that adds enterprise features such as budget management, API key control, usage analytics, and multi-tenant support. The gateway exposes an OpenAI-compatible API, allowing existing tools and workflows to connect without modification. The system emphasizes developer experience with clear error handling, strong typing, and minimal configuration overhead. -
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Size Limit
Calculate the real cost to run your JS app or lib
...When integrated with GitHub Actions, CircleCI, or other CI systems, it runs on every commit or pull request, failing the pipeline if a change exceeds the configured budget. It can also annotate pull requests with comments that highlight how the bundle changed, making performance regressions visible to reviewers early. With the --why flag, size-limit can analyze what contributes most to bundle size and show a dependency breakdown (using Statoscope). -
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Komiser
Cloud environment inspector
Stay under budget by uncovering hidden costs, monitoring increases in spending, and making impactful changes based on customer recommendations. Komiser CE is a free and Open Source project with the goal to create an open cloud cost optimization project with the support of all major public cloud providers. In the last months, we’ve more than doubled our OSS downloads and expanded our community footprint. -
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Claude Cognitive
Persistent context and multi-instance coordination
...It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. Additionally, Claude-Cognitive includes a pool coordinator to share state across multiple Claude Code instances, preserving what’s been learned or completed and preventing repetitive debugging or redundant exploration. -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
...OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run automated experiments based on datasets and hyperparameter conditions within the defined infrastructure budget. Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios. With OptScale, users get complete cloud resource usage transparency, anomaly detection, and extensive functionality to avoid budget overruns. -
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jamesob's guide to running SOTA LLMs
Everything I know about running LLMs locally
...It documents one developer’s local LLM setup, including hardware choices, GPU layout, storage, PCIe switches, kernel settings, and serving workflows. The repository compares budget levels ranging from dual RTX 3090 systems to high-end multi-GPU workstations with very large VRAM pools. It includes ready-to-run serving configurations for selected models and local speech-to-text workloads. The guide focuses on real deployment details such as Docker containers, model weight storage, GPU peer-to-peer behavior, and agentic workload performance. ... -
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ERPNext
World's best free and open source ERP
...Win and retain more customers by optimizing the sales process. Track leads, opportunities, and send the quotes on the go. Deliver both internal and external projects on time, budget, and profitability. Track tasks, timesheets, and issues by project. Deliver a better service experience with an intuitive issue tracker and an integrated knowledge base. Maintain and Manage details of assets, their movement, value adjustment, and depreciation. ERPNext comes with fully-featured content management with blogs, web pages, and forms. -
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AgentGuard
AgentGuard is a firewall for AI agents
...It works by intercepting API calls made by an AI system and continuously monitoring usage, including token consumption and associated costs, allowing developers to enforce strict budget limits. When predefined thresholds are reached, the system can automatically halt execution, trigger alerts, or gracefully terminate processes depending on the configured mode. This makes it particularly valuable in environments where agents operate autonomously and may enter unintended loops or inefficient workflows. The tool integrates directly into existing applications with minimal changes, often requiring only a few lines of code to activate protection. ... -
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Aden Hive
Outcome driven agent development framework that evolves
...Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. Hive is designed for production environments and supports a wide range of large language models, local models, and business system connectivity. -
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Meridian
Meridian is an MMM framework
Meridian is a comprehensive, open source marketing mix modeling (MMM) framework developed by Google to help advertisers analyze and optimize the impact of their marketing investments. Built on Bayesian causal inference principles, Meridian enables organizations to evaluate how different marketing channels influence key performance indicators (KPIs) such as revenue or conversions while accounting for external factors like seasonality or economic trends. The framework provides a robust... -
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Wallos
Open-source, self-hostable personal subscription tracker
...It focuses on turning subscriptions into a clear, organized view of your financial commitments, helping you spot waste, anticipate upcoming charges, and plan your budget with fewer surprises. The app supports subscription management with due dates and payment schedules so you can keep track of what’s active and when it renews. To make analysis more meaningful, Wallos includes category management so you can group expenses and identify spending patterns over time. It also supports multiple currencies, which is especially useful for people paying for services in different billing regions or traveling between countries. -
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VulnClaw
Based on AI Agent + MCP toolchain + penetration Skill orchestration
...Its newer architecture uses a goal-driven solving engine instead of a fixed-round loop, helping the agent stop when the goal is reached, the search space is exhausted, or a safety budget is met. It also includes evidence checks designed to reduce hallucinated conclusions by requiring real tool output before accepting key findings. VulnClaw is intended for authorized testing, CTFs, security education, and controlled red-team environments. -
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OpenSquilla
Token-Efficient AI Agent with same budget, higher intelligence density
OpenSquilla is a token-efficient microkernel AI agent runtime designed for CLI, web UI, and chat-based workflows. It routes each turn through a shared loop that can select lower-cost models when appropriate while preserving tool dispatch, retries, memory, and decision logging. The project supports multiple LLM providers through a pluggable provider layer, making it adaptable to different model ecosystems. It includes persistent memory, built-in web search, on-device embeddings, and... -
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ai-budget-assistant
Budget app with AI chat, voice input, and family purchase voting.
AI Budget Assistant is a mobile app for tracking personal and shared household finances, available on Android and iOS. Expenses can be logged by typing, speaking a voice note, photographing a receipt, or automatically via Android bank push notifications — parsed on-device, no bank credentials required. An AI assistant (GPT-4o) answers financial questions and executes commands through chat: adding expenses, creating budgets, checking debt balances. -
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Personal Budget Tracker
Personal Budget Tracker — Simple Expense Logger
Personal Budget Tracker is a minimal yet functional CLI tool to help users manage their income and expenses. It supports categorization, listing, and CSV export. Great for learning Python or organizing your personal finances. -
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CUDOS Framework
Command Line Interface tool for Cloud Intelligence Dashboards
...It is part of the AWS Solutions Library and includes CloudFormation templates, CLI commands, and pre-built dashboards that collect, process, and visualize data from AWS billing, cost management, budgets, and usage reports in services such as Amazon QuickSight or other BI tools. These dashboards give finance and engineering teams the power to track spending trends, budget forecasts, account utilization patterns, and compliance signals in a unified view, enabling better governance and financial accountability at scale. -
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Harness-1
Ultra Recipe for Training Long-Horizon Search Agents
...It is designed for long-horizon search tasks where the model must search, inspect documents, curate evidence, verify claims, and decide when enough evidence has been gathered. The harness externalizes search state, including candidate documents, evidence links, verification records, and budget-aware context. This lets the policy focus on higher-level decisions instead of trying to keep every detail inside the model context. The repository includes inference utilities, training scripts, evaluation runners, dataset tools, and documentation for running the released checkpoint. Its main value is showing how a smaller open model can approach advanced search-agent behavior through structured retrieval state and reinforcement learning. -
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EZ Bookkeeping
A lightweight, self-hosted personal finance app
Ez Bookkeeping is an open-source personal finance and bookkeeping web application designed to help individuals and small businesses track income, expenses, accounts, and budgets with simplicity and clarity. It provides a clean, modern interface where users can enter transactions, categorize expenses, and visualize financial data through dashboards, charts, and monthly summaries so that users can better understand their cash flow and spending patterns. The system supports multiple account... -
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Pyrra
Making SLOs with Prometheus manageable, accessible, and easy to use
Making SLOs with Prometheus manageable, accessible, and easy to use for everyone. When running Pyrra outside of Kubernetes, the SLO object can be provided through a YAML file read from the file system. For this, one container or binary needs to be started with the API argument and the reconciler with the filesystem argument. Here, Pyrra will save the generated recording rules to disk where they can be picked up by a Prometheus instance. While running Pyrra on its own works, there won't be... -
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Opacus
Training PyTorch models with differential privacy
...It supports training with minimal code changes required on the client, has little impact on training performance, and allows the client to online track the privacy budget expended at any given moment. Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. ...
