
bifrost
The Fastest LLM Gateway with built in OTel observability and MCP gateway
Stars: 525

Bifrost is a high-performance AI gateway that unifies access to multiple providers through a single OpenAI-compatible API. It offers features like automatic failover, load balancing, semantic caching, and enterprise-grade functionalities. Users can deploy Bifrost in seconds with zero configuration, benefiting from its core infrastructure, advanced features, enterprise and security capabilities, and developer experience. The repository structure is modular, allowing for maximum flexibility. Bifrost is designed for quick setup, easy configuration, and seamless integration with various AI models and tools.
README:
Bifrost is a high-performance AI gateway that unifies access to 12+ providers (OpenAI, Anthropic, AWS Bedrock, Google Vertex, and more) through a single OpenAI-compatible API. Deploy in seconds with zero configuration and get automatic failover, load balancing, semantic caching, and enterprise-grade features.
Go from zero to production-ready AI gateway in under a minute.
Step 1: Start Bifrost Gateway
# Install and run locally
npx -y @maximhq/bifrost
# Or use Docker
docker run -p 8080:8080 maximhq/bifrost
Step 2: Configure via Web UI
# Open the built-in web interface
open http://localhost:8080
Step 3: Make your first API call
curl -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-4o-mini",
"messages": [{"role": "user", "content": "Hello, Bifrost!"}]
}'
That's it! Your AI gateway is running with a web interface for visual configuration, real-time monitoring, and analytics.
Complete Setup Guides:
- Gateway Setup - HTTP API deployment
- Go SDK Setup - Direct integration
- Unified Interface - Single OpenAI-compatible API for all providers
- Multi-Provider Support - OpenAI, Anthropic, AWS Bedrock, Google Vertex, Azure, Cohere, Mistral, Ollama, Groq, and more
- Automatic Fallbacks - Seamless failover between providers and models with zero downtime
- Load Balancing - Intelligent request distribution across multiple API keys and providers
- Model Context Protocol (MCP) - Enable AI models to use external tools (filesystem, web search, databases)
- Semantic Caching - Intelligent response caching based on semantic similarity to reduce costs and latency
- Multimodal Support - Support for text,images, audio, and streaming, all behind a common interface.
- Custom Plugins - Extensible middleware architecture for analytics, monitoring, and custom logic
- Governance - Usage tracking, rate limiting, and fine-grained access control
- Budget Management - Hierarchical cost control with virtual keys, teams, and customer budgets
- SSO Integration - Google and GitHub authentication support
- Observability - Native Prometheus metrics, distributed tracing, and comprehensive logging
- Vault Support - Secure API key management with HashiCorp Vault integration
- Zero-Config Startup - Start immediately with dynamic provider configuration
- Drop-in Replacement - Replace OpenAI/Anthropic/GenAI APIs with one line of code
- SDK Integrations - Native support for popular AI SDKs with zero code changes
- Configuration Flexibility - Web UI, API-driven, or file-based configuration options
Bifrost uses a modular architecture for maximum flexibility:
bifrost/
├── npx/ # NPX script for easy installation
├── core/ # Core functionality and shared components
│ ├── providers/ # Provider-specific implementations (OpenAI, Anthropic, etc.)
│ ├── schemas/ # Interfaces and structs used throughout Bifrost
│ └── bifrost.go # Main Bifrost implementation
├── framework/ # Framework components for data persistence
│ ├── configstore/ # Configuration storages
│ ├── logstore/ # Request logging storages
│ └── vectorstore/ # Vector storages
├── transports/ # HTTP gateway and other interface layers
│ └── bifrost-http/ # HTTP transport implementation
├── ui/ # Web interface for HTTP gateway
├── plugins/ # Extensible plugin system
│ ├── governance/ # Budget management and access control
│ ├── jsonparser/ # JSON parsing and manipulation utilities
│ ├── logging/ # Request logging and analytics
│ ├── maxim/ # Maxim's observability integration
│ ├── mocker/ # Mock responses for testing and development
│ ├── semanticcache/ # Intelligent response caching
│ └── telemetry/ # Monitoring and observability
├── docs/ # Documentation and guides
└── tests/ # Comprehensive test suites
Choose the deployment method that fits your needs:
Best for: Language-agnostic integration, microservices, and production deployments
# NPX - Get started in 30 seconds
npx -y @maximhq/bifrost
# Docker - Production ready
docker run -p 8080:8080 -v $(pwd)/data:/app/data maximhq/bifrost
Features: Web UI, real-time monitoring, multi-provider management, zero-config startup
Learn More: Gateway Setup Guide
Best for: Direct Go integration with maximum performance and control
go get github.com/maximhq/bifrost/core
Features: Native Go APIs, embedded deployment, custom middleware integration
Learn More: Go SDK Guide
Best for: Migrating existing applications with zero code changes
# OpenAI SDK
- base_url = "https://api.openai.com"
+ base_url = "http://localhost:8080/openai"
# Anthropic SDK
- base_url = "https://api.anthropic.com"
+ base_url = "http://localhost:8080/anthropic"
# Google GenAI SDK
- api_endpoint = "https://generativelanguage.googleapis.com"
+ api_endpoint = "http://localhost:8080/genai"
Learn More: Integration Guides
Bifrost adds virtually zero overhead to your AI requests. In sustained 5,000 RPS benchmarks, the gateway added only 11 µs of overhead per request.
Metric | t3.medium | t3.xlarge | Improvement |
---|---|---|---|
Added latency (Bifrost overhead) | 59 µs | 11 µs | -81% |
Success rate @ 5k RPS | 100% | 100% | No failed requests |
Avg. queue wait time | 47 µs | 1.67 µs | -96% |
Avg. request latency (incl. provider) | 2.12 s | 1.61 s | -24% |
Key Performance Highlights:
- Perfect Success Rate - 100% request success rate even at 5k RPS
- Minimal Overhead - Less than 15 µs additional latency per request
- Efficient Queuing - Sub-microsecond average wait times
- Fast Key Selection - ~10 ns to pick weighted API keys
Complete Benchmarks: Performance Analysis
Complete Documentation: https://docs.getbifrost.ai
- Gateway Setup - HTTP API deployment in 30 seconds
- Go SDK Setup - Direct Go integration
- Provider Configuration - Multi-provider setup
- Multi-Provider Support - Single API for all providers
- MCP Integration - External tool calling
- Semantic Caching - Intelligent response caching
- Fallbacks & Load Balancing - Reliability features
- Budget Management - Cost control and governance
- OpenAI SDK - Drop-in OpenAI replacement
- Anthropic SDK - Drop-in Anthropic replacement
- Google GenAI SDK - Drop-in GenAI replacement
- LiteLLM SDK - LiteLLM integration
- Langchain SDK - Langchain integration
- Custom Plugins - Extend functionality
- Clustering - Multi-node deployment
- Vault Support - Secure key management
- Production Deployment - Scaling and monitoring
Join our Discord for community support and discussions.
Get help with:
- Quick setup assistance and troubleshooting
- Best practices and configuration tips
- Community discussions and support
- Real-time help with integrations
We welcome contributions of all kinds! See our Contributing Guide for:
- Setting up the development environment
- Code conventions and best practices
- How to submit pull requests
- Building and testing locally
For development requirements and build instructions, see our Development Setup Guide.
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Built with ❤️ by Maxim
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for bifrost
Similar Open Source Tools

bifrost
Bifrost is a high-performance AI gateway that unifies access to multiple providers through a single OpenAI-compatible API. It offers features like automatic failover, load balancing, semantic caching, and enterprise-grade functionalities. Users can deploy Bifrost in seconds with zero configuration, benefiting from its core infrastructure, advanced features, enterprise and security capabilities, and developer experience. The repository structure is modular, allowing for maximum flexibility. Bifrost is designed for quick setup, easy configuration, and seamless integration with various AI models and tools.

llamafarm
LlamaFarm is a comprehensive AI framework that empowers users to build powerful AI applications locally, with full control over costs and deployment options. It provides modular components for RAG systems, vector databases, model management, prompt engineering, and fine-tuning. Users can create differentiated AI products without needing extensive ML expertise, using simple CLI commands and YAML configs. The framework supports local-first development, production-ready components, strategy-based configuration, and deployment anywhere from laptops to the cloud.

lyraios
LYRAIOS (LLM-based Your Reliable AI Operating System) is an advanced AI assistant platform built with FastAPI and Streamlit, designed to serve as an operating system for AI applications. It offers core features such as AI process management, memory system, and I/O system. The platform includes built-in tools like Calculator, Web Search, Financial Analysis, File Management, and Research Tools. It also provides specialized assistant teams for Python and research tasks. LYRAIOS is built on a technical architecture comprising FastAPI backend, Streamlit frontend, Vector Database, PostgreSQL storage, and Docker support. It offers features like knowledge management, process control, and security & access control. The roadmap includes enhancements in core platform, AI process management, memory system, tools & integrations, security & access control, open protocol architecture, multi-agent collaboration, and cross-platform support.

databend
Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

opcode
opcode is a powerful desktop application built with Tauri 2 that serves as a command center for interacting with Claude Code. It offers a visual GUI for managing Claude Code sessions, creating custom agents, tracking usage, and more. Users can navigate projects, create specialized AI agents, monitor usage analytics, manage MCP servers, create session checkpoints, edit CLAUDE.md files, and more. The tool bridges the gap between command-line tools and visual experiences, making AI-assisted development more intuitive and productive.

agentneo
AgentNeo is a Python package that provides functionalities for project, trace, dataset, experiment management. It allows users to authenticate, create projects, trace agents and LangGraph graphs, manage datasets, and run experiments with metrics. The tool aims to streamline AI project management and analysis by offering a comprehensive set of features.

AgentNeo
AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

J.A.R.V.I.S.2.0
J.A.R.V.I.S. 2.0 is an AI-powered assistant designed for voice commands, capable of tasks like providing weather reports, summarizing news, sending emails, and more. It features voice activation, speech recognition, AI responses, and handles multiple tasks including email sending, weather reports, news reading, image generation, database functions, phone call automation, AI-based task execution, website & application automation, and knowledge-based interactions. The assistant also includes timeout handling, automatic input processing, and the ability to call multiple functions simultaneously. It requires Python 3.9 or later and specific API keys for weather, news, email, and AI access. The tool integrates Gemini AI for function execution and Ollama as a fallback mechanism. It utilizes a RAG-based knowledge system and ADB integration for phone automation. Future enhancements include deeper mobile integration, advanced AI-driven automation, improved NLP-based command execution, and multi-modal interactions.

forge
Forge is a free and open-source digital collectible card game (CCG) engine written in Java. It is designed to be easy to use and extend, and it comes with a variety of features that make it a great choice for developers who want to create their own CCGs. Forge is used by a number of popular CCGs, including Ascension, Dominion, and Thunderstone.

gemini-cli
Gemini CLI is an open-source AI agent that provides lightweight access to Gemini, offering powerful capabilities like code understanding, generation, automation, integration, and advanced features. It is designed for developers who prefer working in the command line and offers extensibility through MCP support. The tool integrates directly into GitHub workflows and offers various authentication options for individual developers, enterprise teams, and production workloads. With features like code querying, editing, app generation, debugging, and GitHub integration, Gemini CLI aims to streamline development workflows and enhance productivity.

DeepSeekAI
DeepSeekAI is a browser extension plugin that allows users to interact with AI by selecting text on web pages and invoking the DeepSeek large model to provide AI responses. The extension enhances browsing experience by enabling users to get summaries or answers for selected text directly on the webpage. It features context text selection, API key integration, draggable and resizable window, AI streaming replies, Markdown rendering, one-click copy, re-answer option, code copy functionality, language switching, and multi-turn dialogue support. Users can install the extension from Chrome Web Store or Edge Add-ons, or manually clone the repository, install dependencies, and build the extension. Configuration involves entering the DeepSeek API key in the extension popup window to start using the AI-driven responses.

kelivo
Kelivo is a Flutter LLM Chat Client with modern design, dark mode, multi-language support, multi-provider support, custom assistants, multimodal input, markdown rendering, voice functionality, MCP support, web search integration, prompt variables, QR code sharing, data backup, and custom requests. It is built with Flutter and Dart, utilizes Provider for state management, Hive for local data storage, and supports dynamic theming and Markdown rendering. Kelivo is a versatile tool for creating and managing personalized AI assistants, supporting various input formats, and integrating with multiple search engines and AI providers.

ComfyUI-Ollama-Describer
ComfyUI-Ollama-Describer is an extension for ComfyUI that enables the use of LLM models provided by Ollama, such as Gemma, Llava (multimodal), Llama2, Llama3, or Mistral. It requires the Ollama library for interacting with large-scale language models, supporting GPUs using CUDA and AMD GPUs on Windows, Linux, and Mac. The extension allows users to run Ollama through Docker and utilize NVIDIA GPUs for faster processing. It provides nodes for image description, text description, image captioning, and text transformation, with various customizable parameters for model selection, API communication, response generation, and model memory management.

llmchat
LLMChat is an all-in-one AI chat interface that supports multiple language models, offers a plugin library for enhanced functionality, enables web search capabilities, allows customization of AI assistants, provides text-to-speech conversion, ensures secure local data storage, and facilitates data import/export. It also includes features like knowledge spaces, prompt library, personalization, and can be installed as a Progressive Web App (PWA). The tech stack includes Next.js, TypeScript, Pglite, LangChain, Zustand, React Query, Supabase, Tailwind CSS, Framer Motion, Shadcn, and Tiptap. The roadmap includes upcoming features like speech-to-text and knowledge spaces.

cia
CIA is a powerful open-source tool designed for data analysis and visualization. It provides a user-friendly interface for processing large datasets and generating insightful reports. With CIA, users can easily explore data, perform statistical analysis, and create interactive visualizations to communicate findings effectively. Whether you are a data scientist, analyst, or researcher, CIA offers a comprehensive set of features to streamline your data analysis workflow and uncover valuable insights.

paelladoc
PAELLADOC is an intelligent documentation system that uses AI to analyze code repositories and generate comprehensive technical documentation. It offers a modular architecture with MECE principles, interactive documentation process, key features like Orchestrator and Commands, and a focus on context for successful AI programming. The tool aims to streamline documentation creation, code generation, and product management tasks for software development teams, providing a definitive standard for AI-assisted development documentation.
For similar tasks

kaito
Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.

zep-python
Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

AI-in-a-Box
AI-in-a-Box is a curated collection of solution accelerators that can help engineers establish their AI/ML environments and solutions rapidly and with minimal friction, while maintaining the highest standards of quality and efficiency. It provides essential guidance on the responsible use of AI and LLM technologies, specific security guidance for Generative AI (GenAI) applications, and best practices for scaling OpenAI applications within Azure. The available accelerators include: Azure ML Operationalization in-a-box, Edge AI in-a-box, Doc Intelligence in-a-box, Image and Video Analysis in-a-box, Cognitive Services Landing Zone in-a-box, Semantic Kernel Bot in-a-box, NLP to SQL in-a-box, Assistants API in-a-box, and Assistants API Bot in-a-box.

NeMo
NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

E2B
E2B Sandbox is a secure sandboxed cloud environment made for AI agents and AI apps. Sandboxes allow AI agents and apps to have long running cloud secure environments. In these environments, large language models can use the same tools as humans do. For example: * Cloud browsers * GitHub repositories and CLIs * Coding tools like linters, autocomplete, "go-to defintion" * Running LLM generated code * Audio & video editing The E2B sandbox can be connected to any LLM and any AI agent or app.

floneum
Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

dify
Dify is an open-source LLM app development platform that combines AI workflow, RAG pipeline, agent capabilities, model management, observability features, and more. It allows users to quickly go from prototype to production. Key features include: 1. Workflow: Build and test powerful AI workflows on a visual canvas. 2. Comprehensive model support: Seamless integration with hundreds of proprietary / open-source LLMs from dozens of inference providers and self-hosted solutions. 3. Prompt IDE: Intuitive interface for crafting prompts, comparing model performance, and adding additional features. 4. RAG Pipeline: Extensive RAG capabilities that cover everything from document ingestion to retrieval. 5. Agent capabilities: Define agents based on LLM Function Calling or ReAct, and add pre-built or custom tools. 6. LLMOps: Monitor and analyze application logs and performance over time. 7. Backend-as-a-Service: All of Dify's offerings come with corresponding APIs for easy integration into your own business logic.
For similar jobs

sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.