TEB best_20261111 v2 (protocol 3): web_search / image_search removed (runner 3d0af78d, frozen TEB_best_20261111_v2); teb.sh nettest (web_fetch / poi_search); identifying default User-Agent (Nominatim 403 on placeholder); machine-local settings no longer shipped
65a5d81 verified | pretty_name: TEB (ToolsBench) frozen release best_20261111 v2 | |
| tags: | |
| - agents | |
| - tool-use | |
| - benchmark | |
| # TEB — Tool-use Efficiency Benchmark, frozen release `best_20261111` v2 | |
| > v2 (2026-11-13): same 185 tasks, answers and scoring; `web_search` and `image_search` are no longer offered to | |
| > models (run protocol v3), exactly as in the maintainers' runs. | |
| > **中文使用说明：[README_zh.md](README_zh.md)**。简单说就是：下载整个目录，把 API key 写进 `keys.env`，用 root 在目录里启动 Codex， | |
| > 对它说"按 AGENTS.md 运行，要测的模型是 …"。它会依次完成检查、安装、验收（不调模型）、预检、正式运行和打包结果。 | |
| 185 tasks (162 long-horizon, 23 short) in which a model works with real files and 31 tools, scored on the correctness | |
| of its answer and on how many of its tool calls made progress recognised by each task's evidence graph. Task files, | |
| scoring and labelling are frozen (hashes in `docs/FREEZE.json` inside the code archive). | |
| ## Files | |
| | file | content | | |
| |---|---| | |
| | `README_zh.md` | 中文使用说明（操作步骤、时间、要发回的内容） | | |
| | `AGENTS.md` | the procedure for a coding agent (or a person): every step, its success criterion and failure handling | | |
| | `teb.sh` | one command per step: check, install, nettest, accept, provider, preflight, run, status, stop, package | | |
| | `install.sh` | verifies the archives, unpacks the code into `./teb` and runs its setup | | |
| | `teb_release_best_20261111.tar.zst` | code + 185 tasks (runner, tool server sources, launcher, docs) | | |
| | `teb_images_best_20261111.tar.zst` | every Docker image (one `docker load`; exact image IDs of the release) | | |
| | `teb_tool_weights_best_20261111.tar.zst` | weights of the tool server's local models (Whisper, bge-m3, DePlot, Grounding DINO, MacBERT, beat_this); optional | | |
| | `SHA256SUMS` | checksums | | |
| ## Using a coding agent (Codex, Claude Code) — recommended | |
| Requirements: Linux x86_64, **root**, Docker Engine + Compose v2 with the classic image store (`check` explains how | |
| to switch if Docker uses the containerd store), network access, 40 GB free on Docker's data root and 25 GB in the | |
| download folder. No GPU. | |
| 1. Download the whole dataset folder: | |
| ```bash | |
| hf auth login | |
| hf download Ameame1002/ToolsBench --repo-type dataset --local-dir teb_download | |
| ``` | |
| 2. Put the API keys of the models to evaluate into `teb_download/keys.env` (never paste keys into the chat): | |
| ```bash | |
| cat > teb_download/keys.env <<'EOF' | |
| OPENAI_API_KEY=... | |
| ANTHROPIC_API_KEY=... | |
| GOOGLE_GENERATIVE_AI_API_KEY=... | |
| EOF | |
| chmod 600 teb_download/keys.env | |
| ``` | |
| 3. As root, start the agent in that folder with permission to use Docker and the network, e.g. Codex: | |
| ```bash | |
| cd teb_download && codex --sandbox danger-full-access | |
| ``` | |
| 4. Tell it, for example: | |
| > Follow AGENTS.md. Evaluate: OpenAI `<model-id>`, Anthropic `<model-id>`, Google `<model-id>`. | |
| > Docker on this machine may use <N> CPUs. Report after the acceptance test and the preflights, then run the full | |
| > benchmark and package the results. | |
| `AGENTS.md` is the complete procedure (check → install → network check of web_fetch / poi_search → acceptance test without a model → configure models → | |
| 2-task preflight per model → full run in the background with status checks and retries → package). `teb.sh` | |
| implements each step as one command; long steps run in the background (`bg` / `poll`), so an agent session can end | |
| and a new one continues. | |
| ## Install by hand | |
| ```bash | |
| bash teb.sh check # as root | |
| TEB_CPUS=<cpus> bash teb.sh install # verifies, unpacks ./teb, loads images, starts the tool server | |
| bash teb.sh nettest # live web_fetch / poi_search check through the tool server: must PASS | |
| # (FAIL = containers have no internet: TEB_UPSTREAM_PROXY=<url> bash teb.sh nettest) | |
| bash teb.sh accept --jobs 8 # acceptance test, no model, no API cost: must PASS | |
| bash teb.sh provider openai <model-id> # or anthropic / google / compat (keys from env variables) | |
| bash teb.sh preflight openai/<model-id> # 2 short tasks: must PASS | |
| bash teb.sh run r1 openai/<model-id>=4 --jobs 8 | |
| bash teb.sh status r1 # until "VERDICT: COMPLETE" (INCOMPLETE -> fix the cause, bash teb.sh retry r1) | |
| bash teb.sh package r1 # r1.tar.gz to send back | |
| ``` | |
| Details: `teb/README.md`; 中文说明：`teb/docs/QUICKSTART_zh.md`。 | |