whileai
Datasets
All datasets matching “whileai”agent-simulations
Agent Simulations
Made with the whileai SDK · Collections: Simulation, Start here: foundational post-training datasets
53,971 synthetic agent trajectories generated by simulations
across 34 agent types. The rows include successful and failed
trajectories for supervised fine-tuning, preference work, reinforcement learning, and
evaluation.
NOTE: This is generated test and training data, not curated ground truth. Review and
filter it for your application before training or… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/agent-simulations.text-to-sql-shop
Text-to-SQL on a seeded store schema, with checkpoints
Recipe: recipes/04-train/text-to-sql · Collection: Analyst
A question about an online store's database in, one PostgreSQL query out, graded by
a program: run the query, compare the result set to the gold query's result. The
schema (8 tables, seeded, schema.sql + seed.sql), the verifier, the trainer and
the benchmark runner are the
recipes/04-train/text-to-sql
recipe in the open-source whileai SDK.
Splits
|… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/text-to-sql-shop.identity-behavior
identity-behavior
Recipe: recipes/04-train/identity · Collections: Character, Start here: foundational post-training datasets
Teach an open model who it is.
Identity behavior is the simplest thing every shipped assistant needs and
open models do not have out of the box: a consistent answer to "who are
you?" and "who made you?", in every phrasing and every language, without a
system prompt propping it up. Ask a base Qwen model and it tells you about
Alibaba; put a persona in the… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/identity-behavior.tool-call-efficiency
tool-call-efficiency
Made with the whileai SDK · Collections: Efficiency, Start here: foundational post-training datasets
Teach an agent to make every tool call count.
An agent that calls a tool twice with the same arguments, looks up what
the user just told it, or keeps calling after the task is done is slow,
expensive, and harder to trust. Ask a base Qwen3-4B to work through
1,133 tool-using tasks across six agents and it does this a lot:
only 52% of its 6,681 rollouts finish… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/tool-call-efficiency.airline-voice-concise
airline-voice-concise
Made with the whileai SDK · Used by: recipes/community/airline-voice-concise-under-probe-outcome-filter · Collection: Register
Training data for putting a speaking register into a model's weights. An
airline support agent that leads with the answer and stops, trained so the
register survives with no instruction in the prompt.
Trained on this set, Qwen3-4B goes from 2.2% to 92.1% of held-out replies
in the register, and becomes less likely to omit required… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/airline-voice-concise.airline-resist-jailbreaks
airline-resist-jailbreaks
Made with the whileai SDK · Collection: Robustness
Jailbreak resistance for a customer support agent, trained on simulated
attacks and tested on real ones.
The real attacks come from elder-plinius/L1B3RT4S,
a public library of working jailbreaks. We read it to extract the attack
techniques and never trained on a single string from it. It is the
evaluation set, unseen by the model.
On 165 unseen blocks from a public jailbreak library the agent holds its… See the full description on the dataset page: https://huggingface.co/datasets/while-ai/airline-resist-jailbreaks.