| --- |
| license: other |
| license_name: microtensor-dataset-terms |
| license_link: https://www.microtensor.cloud/terms |
| pretty_name: Microtensor agent sessions |
| language: |
| - en |
| tags: |
| - agents |
| - context-compression |
| - compaction |
| - code |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: dev |
| path: data/dev-*.parquet |
| --- |
| |
| # Microtensor agent sessions |
|
|
| Coding agent sessions for the `ctx_compress` arena on Microtensor (Bittensor testnet netuid 576). Each row is one compaction request in the arena's exact format: the compaction instruction as the system message and the session, rendered canonically inside `<session>` tags, as the user message. The label holds the facts and probe questions the grader checks. |
|
|
| Every session is generated by Microtensor. A seed coins a Python project with one injected bug, and a scripted agent works the task: it lists the tree, searches, reads modules and tests, runs pytest, often tries a wrong fix and reverts it, applies the right fix and adds a regression test. Every tool result is the real output of the real command. Nothing here comes from a public dataset. |
|
|
| | | | |
| |---|---| |
| | Sessions | 2,000 | |
| | Rows | 3,981 (each session cut near its end, and a twin cut near its middle: 1,981 twins) | |
| | Input tokens | 6,381 to 122,704, median 45,439, Granite 4.0 H Micro tokenizer | |
| | Arena input cap | 122,880 tokens | |
| | Output | nine heading markdown summary within `budget_tokens` | |
|
|
| Hidden evaluation items come from the same generator under a secret seed and are never published. |
|
|
| ## Fields |
|
|
| | Field | Meaning | |
| |---|---| |
| | `item_id` | row id; a twin's id ends in `-twin` | |
| | `twin_of` | the full item a twin was cut from, empty otherwise | |
| | `family` | the generated project name | |
| | `system`, `user` | the request exactly as a miner's model receives it | |
| | `input_tokens`, `budget_tokens` | Granite token count of the request and the output budget it states | |
| | `cut`, `steps` | the step the session was cut at and its full length | |
| | `facts` | JSON list of files, errors and symbols the summary must keep | |
| | `probes` | JSON list of continuation questions with accepted answers | |
| | `image` | `synth:<seed>@<scale>`; the arenas package rebuilds the buggy project from it | |
|
|
|
|
| ## Use |
|
|
| ```python |
| from datasets import load_dataset |
| |
| rows = load_dataset("microtensor-io/agent-sessions", split="dev") |
| ``` |
|
|
| There are no reference summaries. Write targets with a teacher model and keep those the arena grader passes; the miner guide shows the loop. Make more sessions with your own seed: |
|
|
| ``` |
| pip install "microtensor-arenas[compress] @ git+https://github.com/microtensor-io/microtensor-arenas" |
| mta dev --arena ctx_compress --count 2000 --seed 7 --out dev/ |
| ``` |
|
|
| ## Licence |
|
|
| Microtensor dataset terms, see https://www.microtensor.cloud/terms. |
|
|
