Datasetpublic

dacorvo/transformers-coding-session-captures

dacorvo/transformers-coding-session-captures HTTP captures of agent ↔ model interactions — one parquet row per /v1/chat/completions call. Produced by agentcap. Native session traces for the same runs live in companion datasets named transformers-coding-session-<agent>-traces. They're all grouped under the transformers-coding-session Collection alongside this dataset. Join on run_id. Loading from datasets import load_dataset ds =… See the full description on the dataset page: https://huggingface.co/datasets/dacorvo/transformers-coding-session-captures.

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Dataset Card

dacorvo/transformers-coding-session-captures

HTTP captures of agent ↔ model interactions — one parquet row per /v1/chat/completions call. Produced by agentcap.

Native session traces for the same runs live in companion datasets named transformers-coding-session-<agent>-traces. They're all grouped under the transformers-coding-session Collection alongside this dataset. Join on run_id.

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python

from datasets import load_dataset

ds = load_dataset("dacorvo/transformers-coding-session-captures", split="train")

Schema

column	description
`run_id`	agentcap run id; matches the per-run folder in the traces dataset
`request_id`	UUID minted by the capture proxy
`model`	Model id from the captured request body
`captured_at`	Epoch seconds when the request was captured
`request`	Raw OpenAI request body, JSON-stringified
`response`	Raw OpenAI response body, JSON-stringified (or `{"stream": true, "raw": ...}` for SSE)
`served_by`	Per-response `X-Served-By` header (HF Router sub-provider routing)
`served_build_info`	Per-response `X-Build-Info` header
`served_model`	Per-response body-echoed `model`
`provider`	Derived from the proxy upstream URL (constant per file)
`upstream_url`	Proxy upstream URL at capture time (constant per file)

request and response are JSON strings; consumers json.loads(...) them. To recover per-message token ranges, render request.messages through the model's chat template yourself — transformers.AutoTokenizer.apply_chat_template.