Tune cognee's performance

The LLM is the bottleneck. Building the graph costs two LLM calls per chunk (graph extraction and summarization), and almost every other tuning question comes down to how many of those calls run, how fast, and on which model. Database and embedding work is small next to that.

Use it

1. Estimate before you ingest

estimate = await cognee.remember("./docs", dry_run=True)
print(estimate)  # per-stage token counts and approximate cost; no LLM calls

The estimate covers graph extraction and summarization only, not improve(), embeddings, or contradiction detection. Not available with GLiNER or a remote instance.