Provides verified, model-attested end-to-end agent coding and debugging trajectories (JSONL). Each whole-session trace was produced by moonshotai/kimi-k3 on the pi/openrouter runtime, passed acceptance tests and independent model screening — useful for SFT, distillation, and analyzing tool-use behavior.
[next-mdx-remote-client] error compiling MDX: Unexpected character `1` (U+0031) before name, expected a character that can start a name, such as a letter, `$`, or `_` More information: https://mdxjs.com/docs/troubleshooting-mdx
A public dataset of one million real-world conversations with 25 LLMs, including conversation text, model name, detected language tags, and OpenAI moderation outputs — useful for studying prompt distributions, safety/moderation, and training/evaluating instruction-following models.
Benchmark for evaluating general AI assistants with 466 short, real-world questions that require tool use, multimodality and reasoning; provides a public dev set and a withheld test set used for leaderboard evaluation.
Provides Parquet-backed pretraining subsets of web and synthetic QA text for large-language-model training, including web-high-nltk-qa, web-high-medium, and txt360-qa. Offers streaming access, provenance metadata, and CC BY 4.0 licensing; intended for LM pretraining and research.
