Documentation Index
Fetch the complete documentation index at: https://docs.cirron.com/llms.txt
Use this file to discover all available pages before exploring further.
Initial Release
The Cirron Python SDK is now generally available on PyPI. It is a profiler that attaches to the running process with one line, captures what’s happening inside training and inference, and writes open artifacts that work standalone or stream to the platform.ci.profile(): one line, no scope wrapping
- Auto-detects PyTorch, TensorFlow / Keras, and HuggingFace Transformers and installs hooks without scope wrappers or callbacks
- Same zero-touch experience for
Trainer.train(),model.fit(), and plain training loops
What gets captured automatically
- Per-epoch and per-batch wall time, GPU seconds, and memory peak
- Weight and gradient statistics (mean, std, norm, histogram) per epoch
- DataLoader stall time broken out from compute time
ci.mark()for user metrics alongside the auto-captured signals
ci.load(): unified data loader
- Returns pandas, polars, Arrow, or
datasets.Datasetbased on the optional extras installed - Reads from local files, object storage (S3, GCS, Azure Blob), and SQL warehouses (Postgres, MySQL, Databricks, Snowflake)
@ci.inference: serving instrumentation
- Decorator-based capture of p50 / p95 / p99 latency, throughput, error rate, and cost-per-request
- Token counts and time-to-first-token surface automatically for LLM endpoints
Local-first, platform-optional
- Writes structured JSON spans and safetensors snapshots to
./.cirron/with no credentials required - Set
CIRRON_API_KEYto stream to the platform; pipeline, deployment, and run context are injected automatically inside Cirron-managed environments - Snapshot modes for full, sampled, and stats-only captures