by sierra-research · LLM 插件 · ★ 2.2k
$\tau$-Bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains 🚀 τ³-bench is here! From text-only to multimodal, knowledge-aware agent evaluation. Voice full-duplex · Knowledge retrieval · 75+ task fixes τ-Voice paper · τ-Knowledge paper · Task fixes paper · Release notes How do you say $\tau^3$-bench? We just say "tau three," but you do you! What's New in $\tau^3$-bench Knowledge Domain () — A knowledge-retrieval-based customer service domain with configurable RAG pipelines, document search, embeddings, and agentic shell-based search.
| Stars | 2,245 |
| Forks | 583 |
| Language | Python |
| Category | LLM 插件 |
| License | MIT |
| Quality Score | 73.8759201914111/100 |
| Open Issues | 269 |
| Last Updated | 2026-10-16 |
| Created | 2025-06-09 |
| Platforms | python |
| Est. Tokens | ~15k |
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tau2-bench is τ-Bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains. It is categorized as a LLM 插件 with 2.2k GitHub stars.
tau2-bench is primarily written in Python. It covers topics such as ai, benchmark, conversational-agents.
You can find installation instructions and usage details in the tau2-bench GitHub repository at github.com/sierra-research/tau2-bench. The project has 2.2k stars and 583 forks, indicating an active community.
tau2-bench is released under the MIT license, making it free to use and modify according to the license terms.