sierra-research/tau-bench

• highreadme#1

  Reposition README to clearly state archival status and direct to τ³-bench

  原因：

  当前

  # τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
  
  **⚠️ WARNING: The tasks in this repo are not updated.** This repository contains outdated versions of the airline and retail tasks. Please use τ³-bench for the latest fixed tasks and new domains.
  
  **❗News**: The τ²-bench repository has been updated to τ³-bench, which includes a new `banking` domain, a `voice` evaluation modality, as well as fixes to the `airline` and `retail` domain tasks. Please navigate to the τ³-bench repository to use the latest version of this benchmark.
  
  We propose $\tau$-bench, a benchmark emulating dynamic conversations between a user (simulated by language models) and a language agent provided with domain-specific API tools and policy guidelines.

  复制粘贴的修复

  复制

  # τ-bench: Historical Benchmark for Tool-Agent-User Interaction (See τ³-bench for latest)
  
  **This repository contains an outdated version of the τ-bench benchmark.** For the latest tasks, new domains (like `banking`), and fixes to `airline` and `retail` domains, **please navigate to the [τ³-bench repository](https://github.com/sierra-research/tau3-bench) to use the active version of this benchmark.**
  
  This repository serves as an archive for the original $\tau$-bench, which emulated dynamic conversations between a user (simulated by language models) and a language agent provided with domain-specific API tools and policy guidelines.

  待办完成忽略
• mediumabout#2

  Update the repository description to reflect its archival status

  原因：

  当前

  Code and Data for Tau-Bench

  复制粘贴的修复

  复制

  Historical code and data for τ-bench, an outdated benchmark for tool-agent-user interaction. Please use τ³-bench for the latest version.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  What benchmarks exist for evaluating AI agents that interact with users and external tools?

  你：未被推荐
  AI 推荐顺序：

  1. ALFWorld
  2. WebArena
  3. ToolBench
  4. MiniWoB++
  5. HumanEval
  6. GAIA
  7. AgentBench

  AI 推荐了 7 个替代方案，却始终没点名 sierra-research/tau-bench。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  How to assess language models' performance in dynamic, multi-turn conversations using domain APIs?

  你：未被推荐
  AI 推荐顺序：

  1. Rasa NLU/Core
  2. DeepPavlov
  3. ParlAI
  4. Haystack
  5. Appen
  6. Scale AI
  7. Amazon Mechanical Turk
  8. Elastic Stack
  9. Elasticsearch
  10. Logstash
  11. Kibana
  12. Prometheus
  13. Grafana

  AI 推荐了 13 个替代方案，却始终没点名 sierra-research/tau-bench。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of sierra-research/tau-bench?

  pass
  ✓AI 明确点名了 sierra-research/tau-bench

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts sierra-research/tau-bench in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 sierra-research/tau-bench

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo sierra-research/tau-bench solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 sierra-research/tau-bench

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？