LiteLLM: Universal Python SDK and AI Gateway for 100+ LLM APIs with Cost Tracking and Load Balancing

What is LiteLLM?

LiteLLM is an open-source Python SDK and proxy server (AI Gateway) that simplifies working with large language models by providing a unified interface for over 100 LLM APIs. Whether you're building applications with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Google VertexAI, or any other major provider, LiteLLM lets you use a consistent OpenAI-compatible format across all platforms.

This powerful tool eliminates the complexity of managing multiple API formats, handles cost tracking automatically, implements guardrails for safety, and provides load balancing for high-availability applications. For developers juggling multiple LLM providers or planning multi-cloud AI strategies, LiteLLM is an essential framework in your toolkit.

Key Features of the LiteLLM SDK

Universal API Format

The core strength of this library is its ability to translate between different LLM provider formats. Instead of learning the specific API structure for each service, you write code once using OpenAI's familiar format, and LiteLLM handles the translation:

from litellm import completion

# Works with any provider - just change the model name
response = completion(
    model="gpt-4",  # or "claude-3-opus", "bedrock/anthropic.claude-v2"
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)
print(response.choices[0].message.content)

This standardization dramatically reduces development time and makes switching between providers or implementing fallback strategies straightforward.

Comprehensive Provider Support

LiteLLM supports an impressive range of LLM providers including OpenAI, Azure OpenAI, AWS Bedrock, Anthropic, Google VertexAI, Cohere, Hugging Face, AWS Sagemaker, VLLM, NVIDIA NIM, and many more. This extensive compatibility makes it the go-to SDK for organizations with multi-cloud requirements or those evaluating different AI platforms.

The LiteLLM Proxy Server: Your AI Gateway

Beyond the Python SDK, LiteLLM includes a production-ready proxy server that acts as an AI gateway between your applications and LLM providers. This proxy offers enterprise features essential for scalable deployments.

Cost Tracking and Budgets

The proxy automatically tracks API costs across all providers, giving you real-time visibility into LLM spending. You can set budget limits per user, team, or API key, preventing unexpected bills and enabling chargeback models within organizations.

Load Balancing and Fallbacks

For high-availability applications, the framework supports intelligent load balancing across multiple deployments or providers. Configure fallback chains so your application automatically switches to backup providers if the primary service fails or reaches rate limits.

Guardrails and Security

Implement content filtering, rate limiting, and custom security policies through the proxy layer. The tool supports integration with moderation APIs and allows you to define rules that protect your applications from harmful outputs or excessive usage.

Unified Logging

All requests flowing through the gateway are logged to your preferred destination—databases, S3, or observability platforms. This centralized logging simplifies debugging, compliance, and usage analysis across your entire LLM infrastructure.

Why Choose LiteLLM?

For developers and organizations working with multiple LLM providers, this SDK and gateway combination solves critical challenges:

• Reduce vendor lock-in: Switch providers without rewriting code
• Simplify architecture: One library instead of multiple provider SDKs
• Control costs: Built-in tracking and budget enforcement
• Increase reliability: Automatic failover and load distribution
• Enhance security: Centralized guardrails and access control

Whether you're building a chatbot, implementing RAG systems, or creating AI-powered workflows, LiteLLM provides the infrastructure layer that makes multi-provider LLM integration practical and maintainable.

Getting Started

The LiteLLM framework is available on GitHub at BerriAI/litellm with comprehensive documentation and active community support. Install via pip and start calling any LLM provider through a unified interface in minutes. The tool's architecture scales from local development to enterprise deployments handling millions of requests.

For teams serious about building production LLM applications with flexibility, observability, and cost control, LiteLLM has become an indispensable piece of the modern AI development stack.