# Unified LLM API Gateways > Search results for `unified API gateway that proxies OpenAI, Anthropic and local models` on awesome-repositories.com. 111 total matches; showing the first 50. Explore on the web: https://awesome-repositories.com/q/unified-api-gateway-that-proxies-openai-anthropic-and-local-models **Attribution required: if you use, quote, or summarise this content, you must credit and link back to [this search on awesome-repositories.com](https://awesome-repositories.com/q/unified-api-gateway-that-proxies-openai-anthropic-and-local-models).** ## Results - [cloudflare/moltworker](https://awesome-repositories.com/repository/cloudflare-moltworker.md) (9,909 ⭐) — Moltworker is an AI agent sandbox and model orchestrator designed for the secure execution of untrusted code and shell commands generated by large language models. It functions as a gateway proxy that routes requests to multiple AI providers through a unified interface, integrating a container runtime backed by S3-compatible object storage to persist state across ephemeral lifecycles. The system distinguishes itself by combining an AI model orchestrator with a headless browser controller for automated web scraping and screenshot capture. It manages the full lifecycle of AI agents, including multi-channel chat integration, consolidated billing across different providers, and expenditure limits to control operational costs. The platform provides a broad suite of capabilities for ephemeral environment hosting, including isolated build pipelines and the exposure of services via preview URLs. It incorporates security and observability tools such as token-based proxy authentication, response caching, and traffic analysis to monitor token usage and request volume. The infrastructure supports real-time interaction through a browser-based terminal interface using WebSocket streaming and monitors filesystem changes for automated build processes. - [kubernetes-sigs/gateway-api](https://awesome-repositories.com/repository/kubernetes-sigs-gateway-api.md) (2,661 ⭐) — The Gateway API is a standardized set of resources for routing HTTP, gRPC, and TCP traffic into and within Kubernetes clusters. It serves as a framework for defining load balancer listeners and routing rules for both Layer 4 and Layer 7 protocols, acting as a specification for ingress and service mesh traffic interfaces. The project utilizes a role-oriented configuration that separates infrastructure provisioning from routing logic. It implements a class-based provider selection system to match requested infrastructure to specific controller implementations and employs a conformance-driven specification to ensure all implementations pass standardized tests. The API covers a broad range of networking domains, including external ingress management, internal service mesh routing, and Layer 4 load balancing. It incorporates security and access control primitives such as backend TLS configuration, hostname ownership delegation to prevent route hijacking, and cross-namespace reference authorization. The project includes a networking conformance suite used to verify that implementations adhere to the official API specifications. - [mastra-ai/mastra](https://awesome-repositories.com/repository/mastra-ai-mastra.md) (21,221 ⭐) — Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execution. It features a built-in telemetry pipeline that captures structured execution traces, logs, and performance metrics, allowing for real-time debugging and evaluation of agent behavior. Furthermore, it utilizes sandboxed environments to isolate code execution and filesystem operations, ensuring that agent interactions remain secure and reproducible. Mastra covers a broad capability surface, including multi-agent delegation hierarchies, schema-validated tool execution, and real-time voice interaction. It supports advanced orchestration patterns such as human-in-the-loop approvals, persistent state management for long-running workflows, and retrieval-augmented generation using vector-based semantic memory. These features are designed to work together to support the entire lifecycle of AI-powered applications, from initial development and testing to production deployment. The project is built for TypeScript environments and provides a modular architecture that integrates with existing web stacks and infrastructure. It includes a client SDK for interacting with remote agents and supports various authentication providers to secure API endpoints and agent resources. - [kilo-org/kilocode](https://awesome-repositories.com/repository/kilo-org-kilocode.md) (15,616 ⭐) — Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which enable secure, collaborative development across independent instances. By maintaining semantic codebase indexing and a centralized model gateway, it ensures that AI agents have context-aware retrieval of project structures while managing authentication, rate limits, and automatic service failover across multiple AI providers. Beyond its core orchestration capabilities, the platform supports a wide range of functional areas including automated code review, security vulnerability triage, and multi-stage workflow planning. It provides granular control over agent permissions and tool execution, allowing teams to define custom operational modes and integrate external services through standardized protocols. The system is designed for extensibility, offering a framework to register custom tools and manage environment configurations through natural language commands. It includes robust monitoring and observability features to track agent performance, token consumption, and organizational adoption metrics. - [apache/apisix](https://awesome-repositories.com/repository/apache-apisix.md) (16,767 ⭐) — This project is a high-performance, distributed API gateway designed to manage, secure, and observe traffic for microservices, serverless functions, and artificial intelligence model providers. It functions as a dynamic service proxy and cloud-native ingress controller, centralizing policy enforcement and traffic routing through a unified configuration interface that synchronizes state across multiple nodes in real time. The platform distinguishes itself through a highly extensible architecture that utilizes a high-performance scripting engine to execute modular logic directly within the request lifecycle. It provides specialized capabilities for modern AI workflows, including model request proxying, token-based budget enforcement, content moderation, and agentic workflow tracing. Furthermore, it supports complex multi-protocol environments by bridging diverse communication standards, including gRPC and various binary protocols, without requiring additional sidecar processes. Beyond its core proxying functions, the gateway offers a comprehensive suite of traffic management and security tools. It handles authentication and authorization through multiple strategies, including token validation and identity provider integration, while maintaining granular control over TLS policies and secret management. The system also provides robust observability through distributed tracing, metrics exporting, and detailed request logging, ensuring visibility into both standard API traffic and complex AI-driven interactions. The software is designed for containerized environments and can be deployed using standard container images, with full support for translating Kubernetes ingress resources into live routing rules. - [anthropics/courses](https://awesome-repositories.com/repository/anthropics-courses.md) (21,864 ⭐) — This repository serves as an educational resource and technical guide for developers learning to integrate large language models into software applications. It provides practical lessons and code examples focused on building systems that perform automated text generation, data analysis, and interactive chat tasks. The project functions as a framework for understanding how to connect applications to external artificial intelligence services. It covers the implementation of secure authentication, the orchestration of network requests, and the configuration of model parameters such as temperature and output length to control response characteristics. The materials also detail how to handle multimodal inputs, enabling applications to process and interpret visual data alongside text prompts. Additionally, the guide demonstrates how to implement real-time streaming to deliver model responses incrementally, reducing perceived latency in user interfaces. The content is provided as a collection of Jupyter Notebooks designed for direct study and experimentation. - [aider-ai/aider](https://awesome-repositories.com/repository/aider-ai-aider.md) (46,305 ⭐) — Aider is a command-line interface tool that enables large language models to directly edit, refactor, and manage source code within a local repository. It functions as an AI-powered coding assistant that integrates into the developer workflow, allowing users to apply code changes through natural language prompts while maintaining repository context and version control. The tool distinguishes itself through a specialized diff-based patching engine that parses model-generated search-and-replace blocks to modify specific file segments without rewriting entire files. It features a provider-agnostic model abstraction that supports a wide range of cloud-based and local language models, enabling users to switch between them to optimize for performance, cost, and reasoning capabilities. To ensure high-quality results, it employs a repository context engine that analyzes codebase structure and dependencies, dynamically managing the active chat window to provide relevant information within token limits. Beyond basic editing, the project automates the development lifecycle by integrating directly with version control systems to handle commit attribution and history management. It supports multi-stage planning through an architect mode that separates high-level design from low-level implementation, and it can automatically trigger test suites and linting commands to verify code modifications. The system is highly configurable, offering hierarchical settings management and a programmatic interface for scripting complex coding tasks. - [bytebot-ai/bytebot](https://awesome-repositories.com/repository/bytebot-ai-bytebot.md) (10,413 ⭐) — Bytebot is an LLM desktop automation framework and virtual Linux desktop environment. It enables AI agents to plan and execute mouse and keyboard actions on a virtual computer using natural language, allowing for autonomous desktop automation and the integration of legacy systems that lack native APIs. The system operates as an LLM API gateway and a Model Context Protocol server, routing requests across multiple language model providers with integrated load balancing and rate limiting. It provides isolated, containerized environments where agents use visual reasoning to interpret screenshots and translate goals into precise UI actions. The platform includes a comprehensive suite of orchestration tools for managing asynchronous task lifecycles, programmatic desktop control via REST, and real-time state streaming via WebSockets. It supports hybrid control modes, allowing users to monitor agent execution through a browser-based viewer and intervene manually when necessary. Deployment is supported through Docker Compose, Helm charts for Kubernetes orchestration, and one-click cloud templates for private infrastructure hosting. - [portkey-ai/gateway](https://awesome-repositories.com/repository/portkey-ai-gateway.md) (12,091 ⭐) — This project is an artificial intelligence gateway that functions as a centralized middleware layer for managing, securing, and observing interactions with language, vision, and audio models. It provides a unified interface that standardizes requests across multiple providers, enabling teams to integrate AI capabilities into their applications through a consistent set of tools and protocols. The gateway distinguishes itself through its comprehensive infrastructure governance and traffic management capabilities. It allows for policy-driven routing, automated failover, and load balancing across different model providers to ensure high availability. Furthermore, it incorporates real-time security guardrails, sensitive data redaction, and virtual credential management, which abstracts provider-specific keys to facilitate secure access control and usage attribution across organizational units. Beyond its core proxying functions, the platform offers extensive observability and operational tools. It captures detailed telemetry, including performance metrics, request tracing, and cost analytics, while providing a centralized repository for prompt versioning and template management. The system also supports semantic response caching to reduce latency and operational costs, alongside features for auditing, feedback collection, and fine-tuning model outputs. The software is designed for deployment within private networks or cloud environments, ensuring full data ownership and compliance with internal security requirements. - [envoyproxy/gateway](https://awesome-repositories.com/repository/envoyproxy-gateway.md) (0 ⭐) — Envoy Gateway is an open source project for managing Envoy Proxy as a standalone or Kubernetes-based application gateway. Gateway API resources are used to dynamically provision and configure the managed Envoy Proxies. - [fauxpilot/fauxpilot](https://awesome-repositories.com/repository/fauxpilot-fauxpilot.md) (14,732 ⭐) — Fauxpilot is a self-hosted AI coding assistant and local inference server. It functions as a proxy and API gateway that redirects traffic from IDE plugins to a local large language model, allowing for AI-assisted programming without external cloud dependencies. The project provides a specialized API emulation layer that mimics coding assistant protocols and a standardized OpenAI-compatible interface. This enables supported code editors to use local models for completions and suggestions by overriding default proxy URLs. The system includes capabilities for downloading and deploying local models, as well as a format-conversion pipeline to transform model files into optimized versions for specific inference engines. A model-agnostic backend allows for switching between different inference engines while maintaining the same API interfaces. - [openai/consistency_models](https://awesome-repositories.com/repository/openai-consistency-models.md) (6,492 ⭐) — This project is a framework for training and sampling generative models designed to produce high-quality images in few steps. It provides implementations for image generation models that transform random noise into structured visual data through an optimized sampling process. The system specializes in accelerating image generation through consistency distillation and consistency training. It includes tools to transform pre-trained diffusion models into faster versions by distilling knowledge from a teacher model into a student model, as well as methods to train consistency models from scratch. The project covers a broad surface of generative AI development, including text-to-image sampling and image dataset preparation. It also features an evaluation suite for benchmarking generative quality using metrics such as Fréchet Inception Distance, Precision, Recall, and Inception Score. - [eigent-ai/eigent](https://awesome-repositories.com/repository/eigent-ai-eigent.md) (12,557 ⭐) — Eigent is a comprehensive platform for developing, configuring, and orchestrating autonomous AI agents. It functions as an agent development environment and workflow automation engine, enabling users to build modular agents equipped with custom toolsets, domain-specific skill packages, and external API connections to perform targeted operational tasks. The framework distinguishes itself through a robust multi-agent orchestration layer that coordinates teams of specialized agents to execute complex workflows. By utilizing hierarchical task decomposition, the system breaks high-level goals into granular subtasks that can be executed in parallel. It maintains operational reliability through event-driven monitoring and integrated human-in-the-loop protocols, which allow for manual oversight and intervention when agents encounter uncertainty or task failures. The platform provides a model-agnostic backend abstraction, allowing users to connect agents to a variety of local or cloud-based language model providers. This flexibility is supported by a modular tooling interface that connects agents to external software, remote servers, and custom functions. The system also includes mechanisms for persistent artifact storage and local data privacy management, ensuring that generated files and sensitive information are handled securely across different deployment environments. - [berriai/litellm](https://awesome-repositories.com/repository/berriai-litellm.md) (50,579 ⭐) — LiteLLM is a unified gateway and proxy server designed to centralize access to over one hundred language model providers. It provides a standardized API interface that abstracts vendor-specific schemas, allowing developers to interact with diverse models through a single, consistent format. By acting as a central traffic management layer, it enables organizations to route, secure, and govern model interactions across multiple deployments. The platform distinguishes itself through its policy-driven architecture, which uses configuration-based routing to manage traffic distribution, load balancing, and automatic fallbacks without requiring code changes. It incorporates a robust security and compliance layer that enforces content moderation, secret redaction, and fine-grained access control. Additionally, it supports complex operational requirements such as semantic routing, rule-based complexity scoring, and persistent virtual key management for multi-tenant environments. Beyond core routing, the project provides comprehensive governance and observability tools to monitor usage, track spending, and log request metadata across teams. It includes an integrated software development kit for tool calling and agent orchestration, alongside support for advanced features like response caching, batch processing, and structured output configuration. The system is designed for enterprise-wide deployment, offering features for audit logging, single sign-on integration, and granular cost reporting. - [popjane/free_chatgpt_api](https://awesome-repositories.com/repository/popjane-free-chatgpt-api.md) (5,983 ⭐) — This project is an API proxy that provides free and paid access to ChatGPT models through an OpenAI-compatible endpoint. It acts as a reverse proxy, routing requests to ChatGPT while maintaining full compatibility with OpenAI's SDK interface, allowing any application or tool that supports a custom base URL and API key to connect. The service offers a free tier that provides access to ChatGPT models for chat, image generation, and voice dialogue without requiring an official subscription, along with a paid tier that unlocks over 130 OpenAI models including GPT-4 with lower latency and reduced pricing. Both tiers support streaming chat responses, delivering output incrementally as it is generated for real-time display. The proxy integrates with a wide range of clients, including official OpenAI SDKs for Python and Node.js, open-source web chat interfaces, desktop tools, and third-party applications. It also supports connecting knowledge-base-enabled chat applications for context-aware conversations, and enforces rate limiting on the free tier to manage usage. - [langchain-ai/langgraph](https://awesome-repositories.com/repository/langchain-ai-langgraph.md) (34,925 ⭐) — LangGraph is a framework for building stateful, multi-step agentic workflows by modeling application logic as a directed graph. It provides a runtime environment where complex tasks are orchestrated through interconnected nodes and edges, allowing developers to manage state transitions, persistent memory, and control flow across long-running automated processes. The platform distinguishes itself through its native support for human-in-the-loop automation, enabling developers to define breakpoints that pause execution for manual review, modification, or approval. It also features checkpoint-based persistence, which serializes the entire graph state to external storage to facilitate fault tolerance, process recovery, and the ability to inspect or replay historical execution states for debugging. Beyond its core orchestration capabilities, the project functions as a comprehensive agent deployment platform. It includes administrative tools for scaling and monitoring agent instances, enforcing metadata-driven access control, and managing resource consumption through rate and usage limits. The system also provides real-time visibility into internal processes by streaming execution updates from individual nodes as they progress. - [awslabs/api-gateway-secure-pet-store](https://awesome-repositories.com/repository/awslabs-api-gateway-secure-pet-store.md) (307 ⭐) — Amazon API Gateway sample using Amazon Cognito credentials through AWS Lambda - [coaidev/coai](https://awesome-repositories.com/repository/coaidev-coai.md) (9,212 ⭐) — CoAI is an enterprise-grade, self-hostable AI gateway platform that unifies access to over 200 AI models from more than 35 providers through a single OpenAI-compatible API endpoint. It functions as a multi-tenant gateway, routing requests across providers with load balancing, automatic failover, and priority-based routing, while exposing standard OpenAI API endpoints for chat, image generation, model listing, and billing to enable seamless integration with existing tools and clients. The platform distinguishes itself through a comprehensive set of operational capabilities built around the gateway. It includes a content moderation engine that scans AI-generated and user-provided content against custom safety policies, a multi-tenant token metering and billing system supporting subscription and pay-as-you-go plans, and a response caching layer that reduces latency and API costs for repeated requests. CoAI also provides a file parsing pipeline that extracts text from PDF, DOCX, PPTX, Excel, and images using OCR, a plugin-based extension system for adding new capabilities, and workflow automation for chaining AI calls into repeatable sequences. Beyond the core gateway, CoAI offers a conversational AI assistant with knowledge base integration, web search, image generation via DALL-E, Midjourney, or Stable Diffusion, and speech recognition. It supports single sign-on authentication through SAML or OAuth, role-based access control, and real-time usage monitoring with interactive dashboards. The platform synchronizes chat history and settings across devices, and can be deployed via Docker, Kubernetes, or one-click cloud setups with elastic scaling for high availability. - [ericlbuehler/mistral.rs](https://awesome-repositories.com/repository/ericlbuehler-mistral-rs.md) (6,597 ⭐) — mistral.rs is an inference engine for large language models that runs locally and exposes models behind OpenAI and Anthropic-compatible APIs. It serves as a multi-model serving platform, capable of loading several models in a single server process with per-request routing and on-demand loading and unloading. The engine supports multimodal inference, processing text alongside images, video, audio, and speech inputs, and includes a quantized model deployment runtime that reduces memory use and speeds up inference on consumer hardware. The project distinguishes itself through an agentic tool execution framework that runs server-side tools like code execution, shell commands, and web search in an automated loop during model generation, with session state persistence. It provides an in-process inference engine that can be embedded directly into Rust or Python applications without a separate server process, and includes an in-situ quantization engine that converts model weights to lower precision at load time with per-layer tuning. The system supports structured output constraints, forcing model output to conform to JSON Schema or grammar specifications during decoding, and offers automatic architecture detection that identifies model type, quantization format, and chat template from a Hugging Face model ID. The platform includes capabilities for managing LoRA adapters, composing models as mixture-of-experts configurations, and running distributed inference across multiple GPUs or nodes using tensor parallelism and ring transport. It provides a built-in web chat interface, supports speculative decoding with a smaller assistant model, and offers benchmarking, logging, and Prometheus metrics for monitoring. The project can be run from a configuration file, with options for customizing build processes, tuning hardware settings automatically, and managing model caches. - [weirdlabuw/unified-world-model](https://awesome-repositories.com/repository/weirdlabuw-unified-world-model.md) (0 ⭐) — Chuning Zhu 1 , Raymond Yu 1 , Siyuan Feng 2 , Benjamin Burchfiel 2 , Paarth Shah 2 , Abhishek Gupta 1 - [langchain-ai/langchain](https://awesome-repositories.com/repository/langchain-ai-langchain.md) (139,458 ⭐) — LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows that manage state, memory, and tool execution. The project distinguishes itself through a durable execution runtime that maintains persistent state across long-running processes by checkpointing progress to external storage. It models agent workflows as directed graphs, allowing for explicit node-to-node routing and state management. Furthermore, it includes a human-in-the-loop control layer that enables developers to pause execution at defined breakpoints, allowing for manual inspection, modification, and approval of agent actions during runtime. Beyond its core orchestration capabilities, the framework supports a tiered memory architecture that separates short-term conversation context from long-term persistent data. It also provides comprehensive observability tools for tracing and monitoring execution flows, alongside security features for managing authentication and fine-grained access control. The platform is supported by extensive documentation and standardized interfaces for models, embeddings, and data sources to facilitate the development of production-grade agentic systems. - [mozex/anthropic-php](https://awesome-repositories.com/repository/mozex-anthropic-php.md) (47 ⭐) — PHP client for the Anthropic API: messages, streaming, tool use, thinking, web search, code execution, batches, and more. - [josstorer/rwkv-runner](https://awesome-repositories.com/repository/josstorer-rwkv-runner.md) (6,219 ⭐) - [danielmiessler/fabric](https://awesome-repositories.com/repository/danielmiessler-fabric.md) (42,408 ⭐) — Fabric is a command-line orchestrator designed to automate complex data processing and content generation tasks by chaining artificial intelligence models with modular prompt templates. It functions as a terminal-based tool that utilizes standard input and output streams, allowing users to pipe data directly into predefined reasoning strategies. By providing a model-agnostic abstraction layer, the system decouples execution logic from specific artificial intelligence vendors, normalizing requests and responses across different service providers. The platform distinguishes itself through its pattern-based orchestration, which enables the organization, storage, and reuse of custom prompt collections for consistent task execution. It includes a built-in server component that exposes these local prompt workflows as standard web endpoints, allowing external software and graphical interfaces to interact with custom logic as if it were a native model. Users can manage these interactions through a dedicated directory for private templates or via a graphical web dashboard, providing flexibility in how automated workflows are configured and monitored. Beyond its core orchestration capabilities, the tool offers a suite of utilities for development tasks, including document analysis, code context generation, and system interaction. It supports advanced reasoning techniques, such as chain-of-thought processing, and allows for specific model-to-pattern mapping to balance performance and operational costs. The system maintains state and configuration through local filesystem storage, ensuring portability across different operating environments. - [nomic-ai/gpt4all](https://awesome-repositories.com/repository/nomic-ai-gpt4all.md) (77,375 ⭐) — GPT4All is a cross-platform runtime environment designed to execute large language models directly on local consumer hardware. By leveraging an optimized C++ inference backend, it enables private, offline AI interactions without requiring an internet connection or external cloud services. The project provides a comprehensive ecosystem for managing the entire model lifecycle, including discovery, downloading, and configuration of local weights. What distinguishes the platform is its integrated retrieval-augmented generation engine, which allows users to index local documents into semantic vector spaces. This capability enables context-aware chat sessions where the model can reference private files, notes, and spreadsheets to provide grounded, relevant responses. The system also features a local HTTP server that exposes an OpenAI-compatible API, allowing developers to integrate these private, self-hosted models into existing applications and workflows. Beyond its core inference and retrieval capabilities, the project includes a graphical desktop interface for end-user interaction and a Python software development kit for programmatic access. These tools support advanced configuration of model parameters, performance monitoring, and the management of local embedding pipelines for custom semantic search tasks. The software is distributed as a unified application package, with documentation available to guide users through installation and local environment setup. - [mozex/anthropic-laravel](https://awesome-repositories.com/repository/mozex-anthropic-laravel.md) (72 ⭐) — Laravel integration for the Anthropic API: facade, config publishing, install command, testing fakes, messages, streaming, tool use, thinking, and batches. - [anthropics/anthropic-sdk-python](https://awesome-repositories.com/repository/anthropics-anthropic-sdk-python.md) (2,795 ⭐) — This is a Python SDK for interacting with large language models via API. It serves as a client library to generate text, process messages, and manage conversational states, while providing a specialized interface for connecting to models hosted across different cloud infrastructure providers. The SDK includes a tool-calling framework that maps Python functions to JSON schemas, allowing models to execute external tools. It also features a built-in token counting utility to estimate input size before transmission and a server-sent events client for receiving model tokens in real time. The library covers a broad range of capabilities, including asynchronous batch processing for large-scale prompt handling, automated pagination of API results, and file upload management. It also implements traffic management through automatic request retries with exponential backoff to handle transient network errors and rate limits. - [mlflow/mlflow](https://awesome-repositories.com/repository/mlflow-mlflow.md) (26,554 ⭐) - [chopratejas/headroom](https://awesome-repositories.com/repository/chopratejas-headroom.md) (29,537 ⭐) — Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential information via a reversible local cache. The project covers a broad capability surface including synchronized agent memory systems, semantic vector storage for context management, and AST-based code indexing. It also provides observability tools for tracking token savings, simulating compression effects, and monitoring pipeline performance. The software is implemented in Python and supports standalone proxy deployment. - [langchain-ai/langchainjs](https://awesome-repositories.com/repository/langchain-ai-langchainjs.md) (17,818 ⭐) — LangChain.js is a framework for building, executing, and monitoring stateful agentic applications. It provides an orchestration engine that models workflows as directed graphs, allowing developers to connect language models, data sources, and external tools into modular, multi-step processes. The platform distinguishes itself through its focus on stateful execution and human-in-the-loop control. It manages agent lifecycles by persisting execution state across threads, enabling fault tolerance and the ability to pause workflows at designated breakpoints for manual review or modification. This architecture supports both autonomous agent orchestration and complex multi-agent systems, with built-in capabilities for streaming real-time execution updates and managing long-term memory. Beyond core orchestration, the project offers a comprehensive suite of tools for the entire application lifecycle. This includes integrated observability for tracing and evaluating agent performance, schema-enforced data serialization for reliable communication, and extensive support for deployment, security, and infrastructure management. The project provides a TypeScript-based software development kit and a command-line interface to facilitate local development, testing, and deployment of agentic workflows. - [windofshadow/that](https://awesome-repositories.com/repository/windofshadow-that.md) (0 ⭐) — This repository contains the Pytorch implementation of the THAT methods in the following paper: - [openai-php/client](https://awesome-repositories.com/repository/openai-php-client.md) (5,805 ⭐) — ⚡️ OpenAI PHP is a supercharged community-maintained PHP API client that allows you to interact with OpenAI API. - [decolua/9router](https://awesome-repositories.com/repository/decolua-9router.md) (17,690 ⭐) — 9router is an AI model gateway designed to route requests from AI coding tools to multiple model providers through a single unified API. It provides administration for self-hosted AI proxy deployments, allowing users to manage API keys and model access on local servers or edge networks. The system differentiates itself through multi-provider API normalization, which translates incompatible request and response formats to ensure compatibility across different AI models. It features AI provider failover management to automatically switch between providers or accounts when quotas are exhausted or errors occur, and implements multi-account rotation to bypass individual provider limits. The gateway covers a broad set of capabilities including token optimization via payload compression, spending analysis and quota tracking, and encrypted configuration synchronization across devices. Traffic management is handled through capability-based routing and outbound proxy support, while security is maintained via API access keys and automated token refreshment. The application supports containerized deployment and can be hosted on local machines, virtual servers, or global edge networks. - [truefoundry/cognita](https://awesome-repositories.com/repository/truefoundry-cognita.md) (4,317 ⭐) — Cognita is a retrieval augmented generation orchestration framework used to build pipelines that connect document stores and language models to provide grounded answers. It functions as a document ingestion pipeline and a vector database integrator, managing the process of loading, parsing, and indexing files into a searchable knowledge base. The system includes a language model gateway proxy that provides a unified API to interact with multiple different model providers. This routing layer decouples the application from specific vendors, allowing requests to be proxied through a provider-agnostic interface. The framework covers contextual information retrieval through similarity search and reranking to generate responses with source citations. It supports incremental document indexing to process new or updated files without re-indexing entire datasets and allows for the integration of various vector store implementations. - [formbricks/formbricks](https://awesome-repositories.com/repository/formbricks-formbricks.md) (12,391 ⭐) — Formbricks is an open-source survey and feedback platform designed to help teams capture and analyze user insights through targeted, in-app, and website-based interactions. It functions as a comprehensive customer experience analytics system that allows organizations to maintain full control over their data, user attributes, and survey workflows. The platform distinguishes itself through its event-driven architecture, which enables precise behavioral targeting by triggering surveys based on specific user actions or application events. It supports deep integration with external ecosystems by automatically synchronizing response data to CRMs, databases, and communication tools, while providing programmatic interfaces for managing resources and automating feedback loops. Beyond core collection, the system includes advanced logic for conditional branching, scoring, and personalized routing to create adaptive survey experiences. It offers extensive customization options, including white-labeling, CSS overrides, and multi-channel distribution across web, mobile, and email environments. The platform is built for self-hosting, supporting containerized deployments with built-in multi-tenant data isolation and enterprise-grade security features like single sign-on and role-based access control. - [openai-php/laravel](https://awesome-repositories.com/repository/openai-php-laravel.md) (3,732 ⭐) — ⚡️ OpenAI PHP for Laravel is a supercharged PHP API client that allows you to interact with OpenAI API - [quantumnous/new-api](https://awesome-repositories.com/repository/quantumnous-new-api.md) (39,722 ⭐) — This project is an AI model API gateway and proxy server designed to provide a unified interface for interacting with diverse artificial intelligence service providers. It functions as a centralized middleware platform that routes, load balances, and translates API requests across multiple models, enabling developers to access text, image, audio, and video generation capabilities through a single, standardized integration. The gateway distinguishes itself through comprehensive administrative and financial controls, including event-driven usage accounting, real-time token consumption tracking, and granular role-based access control. It supports complex traffic management by distributing requests across multiple credential pools and providers to optimize throughput and bypass rate limits. Furthermore, it integrates a robust identity federation system that supports OIDC, OAuth, and hardware-backed passkeys to secure user access and manage multi-tenant environments. Beyond core routing, the platform provides extensive tooling for service maintenance, including automated health checks, model registry synchronization, and content moderation filters. It also features a complete billing and payment infrastructure, allowing administrators to manage user credit balances, process prepaid redemptions, and monitor cost structures across different model vendors. The system is designed for flexible deployment across containerized and distributed infrastructure, with administrative interfaces for auditing usage logs, managing API channels, and configuring global system parameters. - [insforge/insforge](https://awesome-repositories.com/repository/insforge-insforge.md) (11,794 ⭐) — InsForge is a backend-as-a-service platform that provides an integrated suite of tools for managing relational databases, identity provision, object storage, and serverless compute. It functions as an open-source identity provider and a PostgreSQL database manager featuring integrated vector storage and row-level security. The platform serves as an LLM orchestration gateway, offering a unified endpoint to route requests across various AI providers through an OpenAI-compatible interface. It enables AI-driven application generation and connects AI agents to backend resources using a standardized context protocol. Broad capabilities include comprehensive OAuth and OIDC identity management, an S3-compatible object storage gateway, and a real-time pub-sub engine for database synchronization. The system also covers automated billing and subscription lifecycles with mirrored payment data, as well as serverless function runtimes triggered by HTTP requests or database events. Infrastructure is managed via a backend command-line interface and declarative configuration files. - [betalgo/openai](https://awesome-repositories.com/repository/betalgo-openai.md) (3,008 ⭐) — .NET library for the OpenAI service API by Betalgo Ranul - [bytebytegohq/system-design-101](https://awesome-repositories.com/repository/bytebytegohq-system-design-101.md) (83,491 ⭐) — This project is a centralized engineering knowledge repository that provides a structured curriculum for mastering system design, architectural patterns, and fundamental software development workflows. It serves as a professional development resource for engineers, offering foundational knowledge and real-world case studies to support the design of scalable, secure, and efficient distributed systems. The repository distinguishes itself through a visual-first approach to knowledge synthesis, distilling complex technical concepts into high-density graphical diagrams and succinct illustrations. By employing cross-domain concept mapping and modular topic decomposition, it connects disparate engineering disciplines—such as infrastructure, security, and application layers—into granular, self-contained modules that facilitate rapid mental modeling and targeted learning. The content covers a broad spectrum of technical domains, including API and web development, database scaling strategies, networking protocols, and DevOps deployment pipelines. These educational assets are organized as a static, version-controlled repository, allowing users to consume technical insights asynchronously at their own pace. - [openai/openai-python](https://awesome-repositories.com/repository/openai-openai-python.md) (31,022 ⭐) — The OpenAI Python library is a generative AI client library designed to simplify communication with large language model services. It functions as a language-specific software development kit that maps local code calls to remote service endpoints, enabling the integration of text generation, data analysis, and reasoning tasks into software applications. The library acts as a structured abstraction layer that manages the complexities of network-based service interactions, including authentication, connection pooling, and header management. It distinguishes itself through built-in request orchestration that handles transient network failures and rate limits via automatic exponential backoff strategies. Developers can further customize the request-response lifecycle through middleware interception and maintain stability across service updates using versioned API routing. The toolkit provides comprehensive support for standardizing data exchange, including type-hinted interface mapping that converts complex response structures into structured objects. It also supports secure configuration through environment variables and includes utilities for debugging requests to assist in development and maintenance. - [musistudio/claude-code-router](https://awesome-repositories.com/repository/musistudio-claude-code-router.md) (35,016 ⭐) — This project is an AI-focused API gateway and proxy system designed to intercept, standardize, and route requests across heterogeneous language model providers. It functions as a middleware layer that normalizes incoming traffic and manages authentication, ensuring consistent integration across diverse service interfaces. The system features a programmable routing engine that executes user-defined scripts to evaluate request content in real-time. This allows for dynamic traffic management, where requests are inspected, transformed, and redirected to specific model endpoints based on custom logic rather than static configurations. Beyond core routing, the project provides a comprehensive suite of tools for configuration and observability. Users can manage gateway settings and environment variables through a command-line interface, export and import configuration presets for consistent environment replication, and monitor operational performance through real-time logging and status indicators. - [iotsharp/gateways](https://awesome-repositories.com/repository/iotsharp-gateways.md) (33 ⭐) — Open source industrial IoT connectivity gateway. - [janhq/jan](https://awesome-repositories.com/repository/janhq-jan.md) (43,043 ⭐) — Jan is a desktop application that functions as a local artificial intelligence model runtime and an open-standard API server. It enables the execution of large language models directly on local hardware, ensuring that data remains private and accessible offline while providing a unified interface for managing model weights and inference runtimes. The platform distinguishes itself by offering a modular inference backend that allows users to swap execution engines based on hardware compatibility and performance needs. It acts as a cross-platform orchestrator, providing the ability to switch between local model files and remote cloud-based AI providers through a single interface. By exposing these capabilities via an open-standard server layer, the application supports the integration of local AI into external software and development tools. Beyond its core runtime capabilities, the software provides an environment for configuring agentic workflows and autonomous task automation. It includes tools for managing server behaviors, such as network access, authentication, and remote tool execution, while maintaining state persistence through a local file-based database. The application is distributed as a cross-platform container to ensure consistent access to local files and system resources across different operating systems. - [agno-agi/agno](https://awesome-repositories.com/repository/agno-agi-agno.md) (40,717 ⭐) — Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It features a shared cultural knowledge layer that enables agents to reflect on interactions and store universal principles across sessions, alongside persistent memory architectures that manage chat history and context retrieval. The system supports a wide range of operational capabilities, including real-time response streaming, asynchronous background task management, and automated performance evaluation. It integrates with external systems through standardized interfaces and provides comprehensive observability tools to trace autonomous decision paths and monitor agent accuracy in production environments. Developers can configure the system using typed classes or YAML files, and the platform exposes agents as secure, scalable web services with built-in middleware for authentication and request validation. - [andreivmaksimov/serverless-framework-aws-lambda-amazon-api-gateway-s3-dynamodb-and-cognito](https://awesome-repositories.com/repository/andreivmaksimov-serverless-framework-aws-lambda-amazon-api-gateway-s3-dynamodb-and-cognito.md) (0 ⭐) — This is Serverless framework code demo for articles: tag v.1.0 - Serverless Framework - Building Web App Using AWS Lambda, Amazon API Gateway S3 DynamoDB And Cognito - Part-1 tag v.2.0 - Serverless Framework - Building Web App Using AWS Lambda, Amazon API Gateway S3 DynamoDB And Cognito - Part-2 - [eyaltoledano/claude-task-master](https://awesome-repositories.com/repository/eyaltoledano-claude-task-master.md) (27,567 ⭐) — This project is an autonomous, multi-model orchestrator designed to manage the full software development lifecycle through a command-line interface. It functions as an intelligent agent that decomposes high-level product goals into actionable, prioritized subtasks, manages dependency graphs, and executes development cycles. By automating requirement parsing, technical research, and task tracking, it maintains project alignment and momentum throughout the implementation process. The system distinguishes itself through a provider-agnostic abstraction layer that allows users to assign specific artificial intelligence models to primary, research, or fallback roles. It supports both cloud-based services for broad reasoning capabilities and local model execution to ensure data privacy and offline functionality. Furthermore, the platform integrates live web research directly into the task management workflow, enabling agents to generate complexity scores and validate technical decisions against current industry patterns before writing code. Beyond core orchestration, the tool provides a comprehensive framework for managing task metadata, parallel workstreams, and team collaboration. It includes features for real-time task monitoring, automated documentation generation, and integration with development environments through standardized communication protocols and editor extensions. The system is configured via local environment files, which handle secure credential management and allow for the optimization of active tools to balance context window usage. - [alishahryar1/free-claude-code](https://awesome-repositories.com/repository/alishahryar1-free-claude-code.md) (34,843 ⭐) — This project is a multi-provider AI gateway and proxy server that intercepts and routes requests between AI clients and various large language model providers. It functions as an API protocol translator and model router, mapping incoming requests to specific upstream providers or local runners to provide a unified interface for multiple models. The system distinguishes itself by bridging chat platforms and command line interfaces, converting messages from chat services into managed command line sessions. It further optimizes traffic by executing certain web search and fetch requests locally and translating message formats, streaming events, and tool schemas between different provider standards. The proxy includes capabilities for voice input and output processing, including audio-to-text transcription. It also provides a local web interface for managing provider keys, validates requests via authorization tokens, and implements a transport-class abstraction to support the integration of custom backend services. - [vercel/vercel](https://awesome-repositories.com/repository/vercel-vercel.md) (15,738 ⭐) — Vercel is a cloud platform for building, deploying, and scaling web applications. It provides a unified infrastructure that automates the build process by detecting project frameworks and distributing static and dynamic content through a global content delivery network. The platform executes application logic using serverless functions that scale automatically based on real-time traffic demand. The platform distinguishes itself through a centralized AI gateway that proxies requests to multiple model providers, enabling standardized authentication, observability, and cost tracking. It supports advanced development workflows by integrating AI coding agents directly into the terminal and version control systems, allowing for automated code analysis, pull request reviews, and infrastructure management. Security is maintained through isolated microVM-based sandboxing for untrusted code and edge-side middleware that handles request routing and personalization before traffic reaches the origin. Beyond its core hosting capabilities, the platform offers a comprehensive suite of tools for monitoring application performance, managing team access via identity providers, and orchestrating durable background tasks. It includes features for incremental content updates, which allow developers to refresh specific pages without requiring full site rebuilds, and provides granular control over traffic management through global configuration and feature flags. The platform is designed to be accessed via a command-line interface and integrates directly with Git repositories to automate the entire deployment lifecycle, from preview environments for every branch commit to production releases. - [dan1471/free-openai-api-keys](https://awesome-repositories.com/repository/dan1471-free-openai-api-keys.md) (3,564 ⭐) — This project is a repository of pre-generated API keys designed to provide shared access to OpenAI models. It serves as a provider of authentication credentials for testing and educational development, allowing users to bypass personal account registration. The system utilizes a static distribution model where credentials are stored as plain text strings within the codebase. These keys are delivered via a public version control platform, enabling client-side retrieval without the need for a dedicated backend server or external database. The provided keys support the prototyping of AI features and the integration of large language models into software projects. This facilitates the validation of API response structures and the experimentation of AI workflows without the requirement of personal billing setup.