| --- |
| license: mit |
| task_categories: |
| - question-answering |
| - text-generation |
| language: |
| - en |
| pretty_name: FlowBench |
| size_categories: |
| - n<1K |
| tags: |
| - agents |
| - tool-use |
| - benchmark |
| - harbor |
| - data-orchestration |
| --- |
| |
| # FlowBench |
|
|
| Dataset ID: `jwu323/FlowBench` |
|
|
| FlowBench is a tool-use benchmark for deterministic business operations |
| workflows. Each task asks an agent to compose Python tools over synthetic |
| customers, products, orders, returns, inventory, support tickets, FX rates, and |
| SLA policies. |
|
|
| This repository contains the public `test` split. It is answer-free by design: |
| fixed gold labels, oracle solutions, and strict verifier expected files are not |
| included. The public files are suitable for task inspection, agent integration, |
| and reproducible smoke tests. Official scoring should use a private evaluator |
| pack or a freshly generated held-out split with hidden answers. |
|
|
| ## Splits |
|
|
| `test` contains 300 public task specifications: |
|
|
| | depth | tasks | description | |
| |---:|---:|---| |
| | 1 | 50 | single-step lookups such as region currency or top-selling product id | |
| | 2 | 50 | filtered order and customer counts | |
| | 3 | 50 | revenue and refund-rate aggregations | |
| | 4 | 50 | local-currency conversion and margin-after-refund calculations | |
| | 5 | 50 | replenishment shortfall and delayed-order revenue workflows | |
| | 6 | 50 | delayed fulfillment plus SLA breach burden, and at-risk revenue from breached tickets | |
|
|
| There are 12 task families with 25 tasks per family. The public `test` split is |
| closed-world and deterministic, but it is not a public-answer leaderboard split. |
|
|
| ## Files |
|
|
| - `data/test.jsonl`: answer-free task records. |
| - `tools/flowbench_tools.py`: deterministic tool implementation visible to agents. |
| - `harbor/`: Harbor-compatible public task pack with a smoke verifier. The smoke |
| verifier checks output shape only; it is not official scoring. |
| - `RUN.md`: instructions for wiring the public split to an LLM agent and writing |
| prediction files. |
|
|
| Each JSONL record includes: |
|
|
| - `task_id` |
| - `depth` |
| - `family` |
| - `region`, `category`, `month_start`, `month_end` |
| - `instruction` |
| - `answer_format` |
|
|
| No record contains a gold answer. |
|
|
| ## Where the Data Comes From |
|
|
| There is no separate CSV, database dump, or network service to download. The |
| benchmark data are generated deterministically inside |
| `tools/flowbench_tools.py` and inside each Harbor task's |
| `/app/flowbench_tools.py`. Importing that file builds in-memory tables for 72 |
| customers, 48 products, 720 orders, 180 returns, 260 support tickets, inventory, |
| FX rates, and SLA policies from SHA-256 keyed generators. The same task and tool |
| file therefore produce the same data on every machine. |
|
|
| When running without Harbor, load `tools/flowbench_tools.py` into the agent |
| runtime and expose its functions as the tool API. When running with Harbor, the |
| task container already places the same tool file at `/app/flowbench_tools.py`. |
| Agents should solve tasks by calling the provided tools; the public release does |
| not ship gold answers or a strict answer checker. |
|
|
| ## Running an Agent |
|
|
| For public agent evaluation, give the agent one task record from |
| `data/test.jsonl`, expose only the functions listed in |
| `tools/flowbench_tools.py::TOOLS`, and ask the agent to return only the final |
| answer in the record's `answer_format`. The task record supplies the question |
| and parameters; the tool module is the data source and builds all tables |
| deterministically at import time. |
|
|
| Recommended public prediction format: |
|
|
| ```json |
| {"task_id": "v3_depth1_currency_lookup_t0", "answer": "USD", "model": "your-model-name"} |
| ``` |
|
|
| `RUN.md` has a fuller harness contract, adapter skeleton, prompt template, and a |
| worked tool plan for a depth-6 task. The public split has no labels, so |
| predictions from this repository alone are for inspection, integration testing, |
| or private scoring; do not report them as official FlowBench scores. |
|
|
| ## Running the Harbor Smoke Pack |
|
|
| ```bash |
| harbor run -p harbor -a <agent> -l 1 |
| ``` |
|
|
| The Harbor pack in this repository is a public smoke pack. It verifies that an |
| agent writes an output with the required shape. It deliberately does not contain |
| the private expected answers. |
|
|
| ## Task Families |
|
|
| - `currency_lookup` |
| - `top_product_lookup` |
| - `order_count` |
| - `unique_customer_count` |
| - `net_revenue_usd` |
| - `refund_share_bp` |
| - `local_net_revenue` |
| - `margin_after_refunds` |
| - `reorder_shortfall` |
| - `delayed_net_revenue` |
| - `delay_sla_burden` |
| - `breached_ticket_revenue` |
|
|
| ## Evaluation Notes |
|
|
| FlowBench is designed to compare how agent interfaces express the same tool |
| capabilities: function-calling style, command style, and code/REPL style |
| substrates can all call the same tools. For public release, do not evaluate by |
| matching against labels embedded in this repository; there are none. Use a |
| private evaluator or generate a held-out split with hidden answers. |
|
|
| ## Citation |
|
|
| If you use FlowBench, cite the associated paper or this dataset repository once |
| the paper is released. |
|
|
