50 repository-uri
Utilities for running serverless functions locally to verify logic and event handling.
Distinguishing note: Focuses on local execution of cloud-native code.
Explore 50 awesome GitHub repositories matching development tools & productivity · Local Function Execution. Refine with filters or upvote what's useful.
The Serverless Framework is a declarative infrastructure-as-code tool designed to automate the deployment, scaling, and lifecycle management of cloud-native applications. It provides a unified command-line interface that translates high-level configuration files into provider-specific resource templates, enabling developers to orchestrate complex architectures, event-driven functions, and cloud resources within a single project structure. What distinguishes this framework is its focus on developer experience and multi-environment parity. It supports local function invocation and event proxyin
Allows developers to execute serverless code locally to verify logic, event handling, and environment settings without deploying to the cloud.
This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services
Invokes custom functions during a live session, optionally requiring human approval before the model proceeds with the tool output.
Swarm is a framework for building conversational systems that coordinate multi-agent workflows. It functions as an orchestration engine that manages persistent, multi-turn dialogues by routing tasks between specialized agents and executing local functions. The system is designed to handle complex, multi-step processes by maintaining shared state and context across agent interactions. The framework distinguishes itself through its approach to dynamic task delegation and execution control. It enables agents to hand off tasks to one another by returning agent objects, allowing for modular, domai
Enables agents to invoke local code directly to perform data transformations or external actions.
Parse Server is a backend-as-a-service solution and Node.js framework that provides a ready-to-use REST and GraphQL API for mobile and web applications. It functions as a core backend infrastructure for managing database schemas, user authentication, and API routing. The system distinguishes itself with a real-time data engine that pushes database updates to clients via WebSockets and a GraphQL server that automatically generates schemas based on application data models. It also features an adapter-based storage layer that abstracts interactions with various cloud and local backends. The pla
Executes custom server-side JavaScript logic by mapping API requests to user-defined functions at runtime.
LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it
Triggers user-defined functions to perform side effects or interact with external systems during a conversation.
PydanticAI is a Python framework designed for building production-grade autonomous agents. It provides a unified interface for interacting with diverse language models, enabling developers to construct agents that perform complex tasks through structured data validation, tool execution, and multi-turn conversation management. The library centers on type-safe schema enforcement, ensuring that model inputs and outputs remain consistent and reliable throughout the agent's lifecycle. The framework distinguishes itself through a robust architecture that emphasizes modularity and testability. It ut
Executes specific logic immediately upon receiving model output to facilitate complex workflows.
The Gemini Cookbook is a comprehensive collection of implementation patterns, code samples, and development guides designed for building applications with Google Gemini models. It serves as a central resource for developers to integrate multimodal generative artificial intelligence into their software, providing the necessary frameworks to manage model interactions, stateful workflows, and structured data extraction. The repository distinguishes itself by offering specialized toolkits for autonomous agent orchestration, enabling the construction of agents that can execute code, browse the web
Invokes functions to perform data transformations or external actions during a conversational loop.
Quarkus is a Kubernetes-native Java framework designed for building high-performance, memory-efficient applications. It utilizes ahead-of-time native compilation to transform Java code into standalone, optimized binaries that eliminate the need for a virtual machine, enabling rapid startup and reduced memory consumption. By performing code augmentation during the build phase, it shifts heavy processing tasks away from runtime, ensuring that applications are optimized for cloud-native environments. The framework distinguishes itself through a unified approach to reactive and imperative program
Packages and exports application functions for execution within the AWS Lambda environment using standard or native runtimes.
llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang
Implements functions triggered by agents to perform data transformations and external actions during conversational loops.
Floci is a local emulator for AWS services and cloud infrastructure designed for developing and testing applications without a live internet connection. It serves as a containerized cloud emulator and a serverless runtime emulator, allowing users to run high-fidelity replicas of cloud databases, queues, and compute services on a local machine. The project distinguishes itself by using real container images instead of simple mocks to ensure behavioral accuracy. It functions as a local API gateway simulator with proxy-based routing for REST and WebSocket APIs, and provides a serverless environm
Runs serverless functions using local runtimes with support for container images and instant code reloading.
Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag
Implements a mechanism for AI agents to trigger external code execution within a conversational loop.
This repository provides a comprehensive library of code examples for implementing event-driven, serverless backend architectures. It serves as a practical guide for building scalable cloud-native applications that execute logic in isolated environments, triggered by infrastructure events or HTTP requests rather than persistent server processes. The collection demonstrates how to leverage managed infrastructure to automate backend workflows, including the use of asynchronous task queuing to maintain system stability during high traffic. It highlights patterns for secure API hosting, enabling
Offers a collection of code examples demonstrating how to implement event-driven logic and serverless backend tasks.
Shell GPT is an AI-powered command-line interface that generates shell commands and source code from natural language prompts. It serves as a terminal-based tool for automating technical tasks, producing executable commands, and generating code snippets directly within the shell. The tool distinguishes itself through a read-eval-print loop for interactive chatting and the ability to maintain stateful conversational history via named sessions. It supports flexible backend routing, allowing users to connect to cloud-based APIs or local language model hosts for offline operation and data privacy
Allows the AI to execute local system functions and analyze the resulting output.
Nango is an open-source platform that connects applications to external APIs by managing authentication, data synchronization, and custom function execution. It provides a managed runtime for TypeScript integration functions, handling OAuth flows, credential storage, and token refresh for hundreds of external APIs while keeping secrets isolated from application code. The platform distinguishes itself by exposing integration functions as discoverable tools for AI agents through an MCP server or API, with per-user credential isolation that keeps provider secrets out of the agent loop. It offers
Uploads TypeScript integration functions to a managed runtime for synchronous or asynchronous execution.
This project is a comprehensive Node.js software development kit designed for integrating large language models into applications. It serves as a foundational client for interacting with REST and WebSocket services, enabling developers to implement chat functionality, multimodal content generation, and autonomous agent orchestration. The library provides a structured framework for defining executable tools and enforcing JSON schemas, ensuring that model outputs remain programmatically compatible with downstream systems. The SDK distinguishes itself through its robust request orchestration and
Registers custom functions with JSON schemas to enable model-triggered execution during conversations.
This is an infrastructure as code tool and serverless deployment orchestrator that provides a shorthand syntax for defining serverless infrastructure. It functions as a framework for transforming concise resource declarations into full AWS CloudFormation templates to automate the provisioning of cloud functions, APIs, and databases. The project distinguishes itself by using a macro-based transformation system to expand simplified resource types into detailed infrastructure components. It includes an automated permission mapping system that translates high-level resource interaction intents in
Provides utilities for running serverless functions locally to verify logic and event handling before cloud deployment.
This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for generating, refactoring, and debugging code. It functions as an AI agent framework and a Model Context Protocol client, connecting AI models to external data sources and tools to automate complex development tasks. The system is distinguished by its use of autonomous AI agents capable of multi-step task execution, including the ability to read files, modify code, and run terminal commands iteratively. It supports recursive agent orchestration through subagent delegation and employ
Enables the creation, testing, and deployment of Python functions from local environments to remote cloud workspaces.
llrt is a low-latency JavaScript runtime based on the QuickJS engine, specifically designed for executing asynchronous functions in serverless environments. It provides a lightweight execution layer optimized for fast startup times and minimal memory usage when running ES2023 workloads. The project differentiates itself by bundling natively optimized cloud service SDKs directly into the runtime binary to eliminate external dependency loading. To further reduce cold start latency, it implements parallel connection warming for TLS and network handshakes during the startup phase. The runtime co
Provides utilities to run serverless functions locally using mock events to emulate cloud environments.
Model Context Protocol is a standardized framework for connecting large language models to external data sources and executable tools. It enables the creation of a universal interface where servers expose tools, resources, and prompts that can be discovered and utilized by various AI clients. The protocol utilizes a JSON-RPC message system that is transport-agnostic, supporting both standard input/output for local processes and HTTP with server-sent events for remote connections. It emphasizes security and control by delegating model sampling to the client to keep API keys secure from servers
Defines how executable functions are mapped to tools that a model can call with user approval.
Chainlink is a decentralized oracle network that connects smart contracts to off-chain data, computation, and real-world systems. It provides a secure and reliable infrastructure for blockchain applications to access external information, execute automated workflows, and interact with other blockchains. The network is secured by a staking-based model where node operators lock LINK tokens as collateral, which can be slashed for poor performance, incentivizing honest and accurate data delivery. The platform distinguishes itself through a comprehensive set of capabilities that extend beyond basi
Triggers core protocol functions like liquidations and interest accrual with reliable real-time automation.