Using OpenAI AgentKit with Anthropic, Gemini and other providers
Learn how to connect OpenAI AgentKit workflows with multiple LLM providers and get observability, guardrails, and reliability controls.
Topic
Multi-LLM
A collection of 4 issues
Load balancing in multi-LLM setups: Techniques for optimal performance
Load balancing is crucial for teams running multi-LLM setups. Learn practical strategies for routing requests efficiently, from usage-based distribution to latency monitoring. Discover how to optimize costs, maintain performance, and handle failures gracefully across your LLM infrastructure.
Why Multi-LLM Provider Support is Critical for Enterprises
Learn why enterprises need multi-LLM provider support to avoid vendor lock-in, ensure redundancy, and optimize costs and performance.
Multi-LLM Text Summarization
The paper introduces a novel framework called Multi-LLM for text summarization, which leverages multiple large language models (LLMs) to generate better summaries, especially for long documents. This framework is designed to overcome the limitations of using a single LLM, which might fail to captur