| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: Production AI Observability Monitor Synthetic Evaluation Set |
| size_categories: |
| - n<1K |
| task_categories: |
| - text-classification |
| tags: |
| - synthetic |
| - ai-observability |
| - evaluation |
| - text-classification |
| - token-classification |
| - summarization |
| - zero-shot-classification |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train.jsonl |
| - split: test |
| path: data/test.jsonl |
| --- |
| |
| # Production AI Observability Monitor Synthetic Dataset |
|
|
| ## Summary |
|
|
| This dataset contains 14 training examples and 4 |
| held-out examples for **Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.** |
|
|
| Every record is synthetic and includes: |
|
|
| - `input`: query, event, or feature description |
| - `label`: expected class, route, relation, or evidence category |
| - `context`: synthetic supporting context |
| - `source`: fictional source identifier |
| - `variant`: generation pattern |
| - `synthetic`: always `true` |
|
|
| ## Uses |
|
|
| - Reproducible unit and integration tests |
| - Baseline model training |
| - Evaluation harness development |
| - Schema and architecture demonstrations |
|
|
| ## Limitations |
|
|
| Thresholds are demonstration defaults and need calibration against each production workload. |
|
|
| This dataset does not represent real users, patients, customers, production |
| traffic, or licensed media. It must not be presented as real-world evidence. |
|
|
| ## Related Model |
|
|
| [RKB109/production-ai-observability-20260810-model](https://huggingface.co/RKB109/production-ai-observability-20260810-model) |
|
|
