LiteLLM
An open-source Python SDK and proxy server for managing authentication, load balancing, and spend tracking across 100+ LLMs using a unified OpenAI format.
Aperçu
Cas d’usage
Unified Multi-LLM Integration
Call 100+ LLM providers through a single OpenAI-compatible interface, simplifying code and enabling easy switching between models without rewriting integrations.
Load Balancing Across Providers
Distribute requests across multiple LLM endpoints to improve reliability and performance, with automatic failover when providers experience downtime or rate limits.
Centralized Authentication Management
Manage API keys and authentication for many LLM providers from one proxy server, reducing credential sprawl and simplifying access control.
LLM Spend Tracking
Monitor and track spending across different LLM providers in one place, helping teams control costs and analyze usage patterns.
Avis
Moyenne sur 5 avis.
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Rina Desai
Use it every day
Honestly didn't expect to like it this much. The dashboard is exactly what I needed, and it is genuinely easy to set up. I do wish pricing gets steep at scale, but I reach for it almost every day now and it just clicks.
Victor Nguyen
Does the job
Pretty happy overall. The dashboard just works and it saves real time. but no dealbreakers — I'd recommend it to a friend without hesitating.
Mei-Ling Wong
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on the onboarding, and support is responsive caught me off guard. still, I'd recommend giving it a real trial.
Tariq Aziz
Solid for our team
We rolled this out across the team last quarter and it saves real time. The automation fits neatly into how we already work, and the onboarding removed a step we used to do by hand. The mobile experience lags, which is the main caveat, but it has held up under daily use.
Fatima Zahra
Years in this space
I've evaluated a lot of these over the years. What stands out here is the API — handled better than most — and it is genuinely easy to set up. Worth the time if this is your use case.
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