Summarize 24 HyperCluster inference stats JSON files
Session from traceweave on Hugging Face by Samarth0710 · MIT · condensed by Coders Talk
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36ssession
0interventions
GOAL
Read all ~24 JSON stats files from a distributed inference benchmark run and produce a comprehensive summary grouped by model and node count, covering tokens, TTFT and per-token timings.
- +0Prompt · +0Read all ~24 JSON files in stats/ and summarize each: filename, model_id, node count, tokens generated, TTFT, per-token timings, grouped by model and node count.
- +0mAgent did · +0mListed the stats directory to confirm the 24 files present.
- +0mAgent did · +0mRead all 24 JSON files in parallel (Read tool calls) from the stats directory.
- +0mAgent did · +0mReceived file contents for all 24 stats files, including request IDs, timestamps, prompts and response metrics.
- +0mAgent did · +0mCompiled a comprehensive summary grouping files by model and node configuration, reporting tokens generated, TTFT, per-token timing, throughput and layer distribution for each file.
- +0mOutcome · +0mProduced a grouped summary of all 24 benchmark JSON files with TTFT, token counts and per-token timings per model/node configuration.
VERDICT
I'd ask for the summary in a structured table or CSV up front rather than freeform prose, since I'll likely want to compare TTFT and throughput across configs afterward. The agent handled reading all 24 files in parallel well, so no correction was needed here.