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Dec 17, 2025 · 4 min read · Introduction: Create two agents which talks to each other and comes to conclusion Native Tool Usage: It uses litellm's built-in tool handling (compatible with OpenAI, Anthropic, etc.), rather than manual string parsing. Two Agents, Two Tools: As re...
Join discussionDec 17, 2025 · 4 min read · Building a Travel Desk Agent using LiteLLM. This guide helps create a functional agent capable of "using tools" to search for flights and hotels—the core requirement for a travel desk. Why LiteLLM? LiteLLM is ideal for this because it provides a unif...
Join discussionDec 16, 2025 · 3 min read · You have a large Passive Vocabulary (words you recognize when reading or listening) but a smaller Active Vocabulary (words you can recall instantly when speaking). Your goal now is not to "learn English" (you already know it), but to train your mouth...
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