OpenBMB/ToolBench

• hightopics#1

  Add comprehensive topics to the repository

  原因：

  复制粘贴的修复

  复制

  llm, tool-learning, tool-use, llm-benchmark, api-integration, instruction-tuning, large-language-models, evaluation, training

  待办完成忽略
• mediumreadme#2

  Refine the README's introductory paragraph to emphasize training capabilities

  原因：

  当前

  This project (ToolLLM) aims to construct **open-source, large-scale, high-quality** instruction tuning SFT data to facilitate the construction of powerful LLMs with general **tool-use** capability. We aim to empower open-source LLMs to master thousands of diverse real-world APIs. We achieve this by collecting a high-quality instruction-tuning dataset. It is constructed automatically using the latest ChatGPT (gpt-3.5-turbo-16k), which is upgraded with enhanced function call capabilities. We provide the dataset, the corresponding training and evaluation scripts, and a capable model ToolLLaMA fine-tuned on ToolBench.

  复制粘贴的修复

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  ToolBench is an open platform providing **instruction tuning data, training scripts, and evaluation tools** to empower large language models with general **tool-use** capability, enabling them to master thousands of diverse real-world APIs. We achieve this by collecting a high-quality instruction-tuning dataset, constructed automatically using the latest ChatGPT (gpt-3.5-turbo-16k) with enhanced function call capabilities. We also provide the corresponding training and evaluation scripts, and a capable model ToolLLaMA fine-tuned on ToolBench.

  待办完成忽略
• lowcomparison#3

  Add a 'Comparison' section to the README to differentiate from application frameworks

  原因：

  复制粘贴的修复

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  ## Comparison with LLM Application Frameworks
  
  ToolBench is a comprehensive platform for *training and evaluating* large language models to master real-world APIs, providing datasets, training scripts, and benchmarks. Unlike application frameworks such as LangChain or LlamaIndex, which focus on building LLM-powered applications, ToolBench's primary goal is to advance the LLM's intrinsic tool-use capabilities.

  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

  How can I train a large language model to effectively use external APIs and tools?

  你：未被推荐
  AI 推荐顺序：

  1. LangChain
  2. LlamaIndex
  3. OpenAI Function Calling
  4. Hugging Face Transformers Agents
  5. Microsoft Semantic Kernel
  6. Google Vertex AI Agent Builder
  7. Hugging Face Transformers

  AI 推荐了 7 个替代方案，却始终没点名 OpenBMB/ToolBench。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What open-source platforms exist for evaluating and improving LLM's ability to learn and use tools?

  你：第 1 位
  AI 推荐顺序：

  1. ToolBench ← 你
  2. AgentBench
  3. LlamaIndex
  4. LangChain
  5. OpenAI Evals
  6. AutoGPT
  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 OpenBMB/ToolBench?

  pass
  ✓AI 明确点名了 OpenBMB/ToolBench

  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 OpenBMB/ToolBench in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 OpenBMB/ToolBench

  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 OpenBMB/ToolBench solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 OpenBMB/ToolBench

  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？