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50 Repos

Awesome GitHub RepositoriesLocal Function Execution

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.

Awesome Local Function Execution GitHub Repositories

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  • serverless/serverlessAvatar von serverless

    serverless/serverless

    46,917Auf GitHub ansehen↗

    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.

    JavaScriptawsaws-dynamodbaws-lambda
    Auf GitHub ansehen↗46,917
  • openai/openai-agents-pythonAvatar von openai

    openai/openai-agents-python

    27,191Auf GitHub ansehen↗

    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.

    Pythonagentsaiframework
    Auf GitHub ansehen↗27,191
  • openai/swarmAvatar von openai

    openai/swarm

    21,640Auf GitHub ansehen↗

    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.

    Python
    Auf GitHub ansehen↗21,640
  • parse-community/parse-serverAvatar von parse-community

    parse-community/parse-server

    21,403Auf GitHub ansehen↗

    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.

    JavaScriptbaasbackendfile-storage
    Auf GitHub ansehen↗21,403
  • livekit/livekitAvatar von livekit

    livekit/livekit

    19,358Auf GitHub ansehen↗

    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.

    Gogolangmedia-serversfu
    Auf GitHub ansehen↗19,358
  • pydantic/pydantic-aiAvatar von pydantic

    pydantic/pydantic-ai

    17,791Auf GitHub ansehen↗

    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.

    Pythonagent-frameworkgenaillm
    Auf GitHub ansehen↗17,791
  • google-gemini/cookbookAvatar von google-gemini

    google-gemini/cookbook

    17,418Auf GitHub ansehen↗

    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.

    Jupyter Notebookgeminigemini-api
    Auf GitHub ansehen↗17,418
  • quarkusio/quarkusAvatar von quarkusio

    quarkusio/quarkus

    15,479Auf GitHub ansehen↗

    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.

    Javacloud-nativehacktoberfestjava
    Auf GitHub ansehen↗15,479
  • llmware-ai/llmwareAvatar von llmware-ai

    llmware-ai/llmware

    14,838Auf GitHub ansehen↗

    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.

    Python
    Auf GitHub ansehen↗14,838
  • floci-io/flociAvatar von floci-io

    floci-io/floci

    14,168Auf GitHub ansehen↗

    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.

    Javaawsaws-emulationdevops
    Auf GitHub ansehen↗14,168
  • pipecat-ai/pipecatAvatar von pipecat-ai

    pipecat-ai/pipecat

    12,846Auf GitHub ansehen↗

    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.

    Pythonaichatbot-frameworkchatbots
    Auf GitHub ansehen↗12,846
  • firebase/functions-samplesAvatar von firebase

    firebase/functions-samples

    12,238Auf GitHub ansehen↗

    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.

    JavaScriptfaasfaas-platformfirebase
    Auf GitHub ansehen↗12,238
  • ther1d/shell_gptAvatar von TheR1D

    TheR1D/shell_gpt

    12,131Auf GitHub ansehen↗

    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.

    Pythonchatgptcheat-sheetcli
    Auf GitHub ansehen↗12,131
  • nangohq/nangoAvatar von NangoHQ

    NangoHQ/nango

    10,772Auf GitHub ansehen↗

    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.

    TypeScriptaccess-tokenapiapi-client
    Auf GitHub ansehen↗10,772
  • openai/openai-nodeAvatar von openai

    openai/openai-node

    10,643Auf GitHub ansehen↗

    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.

    TypeScriptnodejsopenaitypescript
    Auf GitHub ansehen↗10,643
  • aws/serverless-application-modelAvatar von aws

    aws/serverless-application-model

    9,560Auf GitHub ansehen↗

    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.

    Pythonawsaws-samlambda
    Auf GitHub ansehen↗9,560
  • microsoft/vscode-copilot-chatAvatar von microsoft

    microsoft/vscode-copilot-chat

    9,493Auf GitHub ansehen↗

    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.

    TypeScript
    Auf GitHub ansehen↗9,493
  • awslabs/llrtAvatar von awslabs

    awslabs/llrt

    8,752Auf GitHub ansehen↗

    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.

    Rust
    Auf GitHub ansehen↗8,752
  • modelcontextprotocol/modelcontextprotocolAvatar von modelcontextprotocol

    modelcontextprotocol/modelcontextprotocol

    8,458Auf GitHub ansehen↗

    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.

    TypeScript
    Auf GitHub ansehen↗8,458
  • smartcontractkit/chainlinkAvatar von smartcontractkit

    smartcontractkit/chainlink

    8,222Auf GitHub ansehen↗

    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.

    Goblockchainchainlinkethereum
    Auf GitHub ansehen↗8,222
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Unter-Tags erkunden

  • Agent-Integrated Functions4 Sub-TagsFunctions invoked by agents to perform data transformations or external actions during a conversation. **Distinct from Local Function Execution:** Distinct from generic serverless local execution: specifically focuses on agent-triggered code execution within a conversational loop.
  • Cloud Function Deployers4 Sub-TagsUtilities for packaging and exporting application functions to managed cloud environments. **Distinct from Local Function Execution:** Distinct from Local Function Execution: focuses on the deployment and export process to cloud providers rather than local simulation.
  • Local Automation ProcessingExecuting automation rules and event-driven logic locally on a hub to eliminate cloud reliance. **Distinct from Local Function Execution:** Specifically addresses the execution of automation rules on a hub, whereas local function execution usually refers to simulating serverless functions.
  • Local Endpoint InvocationsTriggering locally running functions via HTTP endpoints using standard API clients. **Distinct from Local Function Execution:** Focuses on the act of triggering a local function via a network request rather than the general execution environment.
  • Local Function DevelopmentsWrites, tests, and deploys TypeScript integration functions from a local project with source control and CI/CD support. **Distinct from Local Function Execution:** Distinct from Local Function Execution: covers the full development lifecycle including writing, testing, and deploying, not just local execution.
  • Local Multimodal TestingLocal execution of functions that process media files, such as PDFs, to verify behavior before deployment. **Distinct from Local Function Execution:** Specializes local execution for multimodal/file-based inputs rather than generic serverless logic
  • Runtime Function Mapping2 Sub-TagsDynamic mapping of API requests to user-defined JavaScript functions at runtime. **Distinct from Local Function Execution:** Focuses on the dynamic runtime mapping of requests to logic rather than local testing of functions.