Chris Tan

🎉🎉We are excited to release a full package for AI Agent R&D: 1) For Data & Training, 🎙️AgentOhana🎙️: Design Unified Data and Training Pipeline for Effective Agent Learning. 2) For model, 🔥xLAM-v0.1-R🔥: A strong large action model for AI Agent while maintaining abilities on general tasks. 3) For agent inference framework, 🤖AgentLite🤖: a lightweight agent/multi-agent library. AgentOhana aggregated, standardized and unified agent trajectories from distinct environments. xLAM-v0.1-r, fine-tuned on #Mixtral, outperforms #GPT-3.5-Turbo on the benchmarks (WebShop, HotpotQA, ToolBench, and MINT-Bench) and #GPT-4 on several of them. AgentLite is implemented with <1K lines of code, and magically supports quickly building LLM agents, designing new agent reasoning, new agent architectures and multi-agent orchestration. AgentOhana Paper: arxiv.org/abs/2402.15506… xLAM GitHub and Model:github.com/SalesforceAIRe… and huggingface.co/Salesforce/xLA… AgentLite Github: github.com/SalesforceAIRe… AgentLite Paper: arxiv.org/abs/2402.15538