Requesty

​LiteLLM is a versatile platform designed to streamline interactions with over 100 Large Language Models (LLMs) through a unified interface. It offers both a Proxy Server (LLM Gateway) and a Python SDK, enabling developers to integrate various LLMs seamlessly into their applications. The Proxy Server facilitates centralized management, allowing for load balancing, cost tracking across projects, and consistent input/output formatting compatible with OpenAI standards. This setup supports multiple providers. It ensures robust observability by generating unique call IDs for each request, aiding in precise tracking and logging across systems. Developers can leverage pre-defined callbacks to log data using various tools. For enterprise users, LiteLLM offers advanced features like Single Sign-On (SSO), user management, and professional support through dedicated channels like Discord and Slack.

TensorZero is an open source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation. It creates a feedback loop for optimizing LLM applications, turning production metrics and human feedback into smarter, faster, and cheaper models and agents. The gateway lets teams integrate once and access every major LLM provider through a single unified API, including API and self-hosted models, with support for tool use, structured outputs, batch inference, embeddings, multimodal inputs, caching, routing, retries, fallbacks, load balancing, granular timeouts, usage tracking, custom rate limits, and provider-key protection. Built for performance in Rust, TensorZero is designed for extreme throughput and low-latency production workloads while still letting teams adopt only the components they need. Its observability layer stores inferences and feedback in the user’s own database, available programmatically or through the open source UI.