BerriAI / litellm

2023-07-27 · Source: Github Trending: All languages · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Cloud Computing & IT Infrastructure · Depth: Intermediate, long

Summary

LiteLLM is an open-source library and AI Gateway that provides a unified interface for interacting with over 100 Large Language Models (LLMs) from various providers, including OpenAI, Anthropic, AWS Bedrock, Azure, and Google Vertex AI. It offers both a Python SDK for direct code integration and an AI Gateway (proxy server) for centralized management, authentication, cost tracking, and load balancing. The platform supports diverse endpoints like `/chat/completions`, `/embeddings`, `/images`, and `/audio`, and extends functionality to A2A (Agent-to-Agent) agents and MCP (Multi-tool Co-operation Protocol) tools. LiteLLM boasts an 8ms P95 latency at 1k RPS and is adopted by companies like Stripe and Netflix, with enterprise features available for enhanced security and support.

Key takeaway

For AI Architects and ML Platform Teams managing diverse LLM deployments, LiteLLM offers a critical solution to standardize API interactions and centralize control. Implementing the LiteLLM AI Gateway can streamline multi-provider LLM access, enforce consistent security policies via virtual keys, and enable granular cost tracking across projects. This approach simplifies infrastructure, reduces integration complexity, and ensures robust, high-performance operations for your generative AI applications.

Key insights

LiteLLM unifies access to 100+ LLMs and agents via a single API, simplifying multi-provider AI integration.

Principles

• Unified API for diverse LLMs
• Centralized AI gateway for control
• High performance and low latency

Method

LiteLLM provides a Python SDK for direct integration or an AI Gateway for centralized proxying, enabling calls to various LLMs, A2A agents, and MCP tools through a consistent OpenAI-compatible interface.

In practice

• Integrate 100+ LLMs with one SDK
• Deploy a proxy for centralized LLM management
• Connect MCP servers to any LiteLLM model

Topics

• LLM Gateway
• Multi-LLM API
• AI Agents
• Tool Calling
• LLM Orchestration

Code references

• BerriAI/litellm
• BerriAI/litellm

Best for: AI Architect, NLP Engineer, CTO, AI Engineer, Machine Learning Engineer, MLOps Engineer

Related on AIssential

• ADK Agents with Amazon Bedrock — LiteLLM unifies access to diverse LLMs, simplifying multi-agent system integration with platforms like Amazon Bedrock.
• How Shopify built an AI stack that doesn't care which models survive — Building model-agnostic AI infrastructure ensures resilience and cost-efficiency amidst evolving LLM landscapes.
• Step-by-Step Guide to Building AI Agents Using LLMs — LLM-powered AI agents enable advanced automation by understanding language, reasoning, and interacting with systems autonomously.
• Meet LiteLLM Agent Platform: A Kubernetes-Based, Self-Hosted Infrastructure Layer for Isolated Agent Sandboxes and Persistent Session Management in Production — The LiteLLM Agent Platform offers self-hosted, Kubernetes-based infrastructure for isolated, persistent AI agent sandboxes.
• Building Aura: An Agentic LLM Gateway in Rust — Agentic LLM workflows demand gateways that natively preserve tool calls and reasoning, not just OpenAI compatibility.
• The Architecture of Modular Intelligence: Project Granite Switch — Modular AI architectures, like Granite-Switch, enable cost-effective LLM deployments by treating adapters as reusable software components.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Github Trending: All languages.