Search Results for "define"
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Showing 206 open source projects for "define"
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OmniRoute
OmniRoute is an AI gateway for multi-provider LLM
OmniRoute is a routing and orchestration framework designed to simplify the handling of requests, workflows, or data flows across multiple services or endpoints in a unified manner. It focuses on providing a flexible abstraction layer where developers can define routing logic that dynamically directs traffic based on conditions, context, or predefined rules. The project emphasizes modularity and extensibility, allowing users to plug in different services or handlers without tightly coupling components. It is particularly useful in distributed systems where requests need to be intelligently routed between APIs, microservices, or processing pipelines. ... -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. ... -
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Claude Code Plugins
Intelligent automation and multi-agent orchestration for Claude Code
Claude Code Plugins is a lightweight framework designed to define, manage, and execute AI agents in a modular and extensible way, typically focusing on orchestrating tasks using large language models and tool integrations. The project provides abstractions for building agents that can interpret instructions, execute commands, and interact with external systems in a structured workflow. It emphasizes simplicity and composability, allowing developers to define agent behaviors through reusable components rather than monolithic logic. ... -
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Switch
Connect any AI agent to your team in Slack, Teams & Discord
...It connects agents to Slack, Microsoft Teams, Discord, Telegram, and Mattermost instead of replacing those platforms. Teams can combine agents from different providers, frameworks, machines, and hosting environments. Channels can define instructions, roles, permissions, knowledge, and tracked tasks that shape how work is coordinated. Switch Console manages agents, messaging connections, channels, credentials, sessions, and server deployment from a desktop application. The platform is self-hostable and includes a gateway, room management, PostgreSQL-backed state, and infrastructure for connecting local or remote agents. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Hamilton DAGWorks
Helps scientists define testable, modular, self-documenting dataflow
...Your DAG is portable; it runs anywhere Python runs, whether it's a script, notebook, Airflow pipeline, FastAPI server, etc. Your DAG is expressive; Hamilton has extensive features to define and modify the execution of a DAG (e.g., data validation, experiment tracking, remote execution). To create a DAG, write regular Python functions that specify their dependencies with their parameters. As shown below, it results in readable code that can always be visualized. Hamilton loads that definition and automatically builds the DAG for you. ... -
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promptfoo
Evaluate and compare LLM outputs, catch regressions, improve prompts
Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API. -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
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Cog
Package and deploy machine learning models using Docker containers
...It simplifies the process of deploying models by automatically generating Docker images based on a simple configuration file, eliminating the need to manually write complex Dockerfiles. Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best practices. Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. ... -
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Video-subtitle-remover (VSR)
AI tool that removes hardcoded subtitles and text from videos locally
...Video Subtitle Remover analyzes video frames and detects subtitle regions, then replaces the removed areas using an AI algorithm that fills the space with reconstructed visual content. This process aims to maintain the original resolution and visual continuity of the video after subtitle removal. It allows users to define a specific subtitle region so that only text in that area is removed rather than modifying the entire frame. It can also automatically remove text throughout the whole video when a position is not specified. In addition to video processing, the project supports removing text-like watermarks from images through similar techniques. ... -
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Open CoDesign
Open-source Claude Design alternative
...The architecture emphasizes privacy, with all data stored locally and no mandatory accounts or telemetry. It also includes built-in design skill modules and allows users to define custom styles and preferences. Overall, it bridges AI generation and design engineering into a unified, programmable workflow. -
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Simple Evals
Lightweight framework for evaluating large language model performance
...It is designed to help researchers and developers run targeted evaluations without the complexity of large-scale pipelines. By emphasizing simplicity, the framework makes it easy to define new tasks, run evaluations, and interpret results in a reproducible way. It is particularly useful for sanity checks, exploratory research, and comparing performance across different models or configurations. The project provides clear structures for defining datasets, metrics, and evaluation logic, while staying minimal enough to adapt for custom use cases. ... -
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Cline
Autonomous coding agent right in your IDE
Cline is a command-line application building library for Node.js that helps developers easily create interactive CLI applications. Built on Node's readline module, it offers features like history support, auto-completion, and input masking. Cline allows you to define custom commands with argument placeholders, making it versatile for various command structures. Additionally, it supports modes, where different command sets can be dynamically loaded depending on the application's state. -
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Remotion
Make videos programmatically with React
Remotion is a cutting-edge library that lets developers create real videos programmatically using React components, transforming familiar UI paradigms into a flexible, code-driven video production workflow. Instead of traditional timeline editors, Remotion leverages HTML, CSS, and JavaScript to define video frames, animations, and transitions, which means developers can use states, props, loops, and component hierarchies to automate complex motion graphics. Because it integrates with the React ecosystem, Remotion fits naturally into modern front-end stacks and tooling, and can produce dynamic content like personalized videos, dashboards, and data-driven animations with the same code used to build interactive web apps. ... -
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TavernAI
Atmospheric adventure chat for AI language models
...It allows users to connect to various AI backends, including local and cloud-based models, enabling flexibility in how conversations are generated and managed. The platform supports advanced character creation, allowing users to define personalities, memory, and behavior patterns that influence how the AI responds during interactions. TavernAI includes features such as persistent chat histories, branching conversations, and contextual memory, making it suitable for long-form storytelling, roleplaying, and creative writing. It also provides a rich interface with support for extensions and plugins, enabling users to expand functionality and tailor the experience to specific use cases. -
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yek
Serialize repositories into LLM-ready context w/ smart prioritization
...Yek supports multiple directories, individual files, and glob patterns, making it flexible for different workflows. It can stream output when piped or save results to a temporary file, depending on usage. Configuration is handled through a yek.yaml file, allowing users to define ignore rules and priority settings. By consolidating code and documents into a single, ordered format, Yek simplifies preparing repositories for AI-driven analysis, debugging, or automation tasks. -
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Nerve
The Simple Agent Development Kit
Define agents using a clean YAML format: system prompt, task, tools, and variables — all in one file. -
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Timbal
Simple, performant, battle-tested framework for building reliable AI
Timbal is an open-source Python framework for building reliable AI applications with a small, transparent architecture. It provides autonomous agents and explicit workflows through the same calling interface and event stream. Developers define behavior with familiar async functions, Pydantic validation, and composable tools instead of relying on hidden orchestration. The framework supports multiple model providers and can automatically fail over between configured models. Human approval gates can pause runs, preserve their state, and resume them after a process restart. ... -
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VT Code
VT Code - semantic AI coding agent
...VTCode operates as an agent rather than a simple autocomplete tool, meaning it can interpret user intent, navigate codebases, and assist with multi-step tasks. It is highly configurable, allowing developers to define behavior, prompts, and workflows tailored to their projects. The tool is especially useful for developers who prefer lightweight, local-first environments but still want advanced AI assistance comparable to modern IDE-based tools. -
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Flow-Next
Plan-first AI workflow plugin for Claude Code, OpenAI Codex
Flow-Next is a workflow orchestration tool designed to manage complex processes by structuring tasks into organized and repeatable pipelines. It focuses on improving productivity by allowing users to define workflows that can be executed step by step or in parallel. The system emphasizes modularity, enabling tasks to be broken down into smaller components that can be reused across different workflows. It supports integration with various tools and services, making it adaptable to different environments. The project is designed to handle both simple and complex workflows, providing flexibility for a wide range of use cases. ... -
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Elkeid
Open source solution that can meet the requirements of workloads
...For container or cloud-native workloads, it also supports gathering audit logs from Kubernetes and correlating events across processes, network, and file activity to detect security threats. The platform packages data collection, event-streaming, and a rule/event engine (called “HUB”) — letting users define detection rules, alerts, baseline checks, and policy enforcement. -
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Instructor
Structured outputs for llms
Instructor is a tool that enables developers to extract structured data from natural language using Large Language Models (LLMs). Integrating with Python's Pydantic library allows users to define desired output structures through type hints, facilitating schema validation and seamless integration with IDEs. Instructor supports various LLM providers, including OpenAI, Anthropic, Litellm, and Cohere, offering flexibility in implementation. Its customizable nature permits the definition of validators and custom error messages, enhancing data validation processes. ... -
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Ruler AI
Centralize and sync AI coding rules across tools and projects
...Instead of maintaining separate configuration files for tools like GitHub Copilot, Claude, or Cursor, it stores all rules in a single .ruler/ directory and distributes them automatically. This reduces duplication, avoids inconsistent outputs, and keeps guidance aligned as projects evolve. Ruler supports nested rule loading, allowing teams to define context-specific instructions for different parts of a codebase. It also manages MCP server settings, automates .gitignore updates, and provides simple commands to initialize, apply, and revert configurations. Designed for teams using multiple AI agents, it improves workflow consistency, simplifies onboarding, and ensures all assistants follow the same standards across projects. -
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Preswald
Python tool for browser-based interactive data apps in one file
...This approach allows developers to create dashboards, reports, notebooks, and data tools that are portable, fast, and capable of running offline. Preswald emphasizes a code-first workflow where users define applications entirely in Python while using built-in UI components such as tables, charts, and forms. It also includes a reactive execution model that only recomputes necessary parts of the app, improving performance and responsiveness. -
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads to scale separately from the serving logic. ...
