Datasets:
Initial upload: 175 traces with subagents, v5-only + ≥20 main turns + CC ≥ 2.1.139
Browse files- .gitattributes +1 -0
- README.md +183 -0
- plots/distributions_linear.png +3 -0
- plots/distributions_log.png +3 -0
- plots/subagent_distributions_linear.png +3 -0
- plots/subagent_distributions_log.png +3 -0
- traces.jsonl +3 -0
.gitattributes
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# Video files - compressed
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.webm filter=lfs diff=lfs merge=lfs -text
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# Video files - compressed
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.webm filter=lfs diff=lfs merge=lfs -text
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traces.jsonl filter=lfs diff=lfs merge=lfs -text
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README.md
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+
---
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license: apache-2.0
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pretty_name: CC Traces — Weka, With Subagents, v5 only (May 19 2026)
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task_categories:
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- text-generation
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tags:
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- llm
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- inference
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- benchmarking
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- kv-cache
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- agentic
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- multi-turn
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- claude
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- subagents
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size_categories:
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- n<1K
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configs:
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- config_name: default
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data_files:
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- split: train
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path: traces.jsonl
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---
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# CC Traces — Weka, With Subagents, v5 only (May 19 2026)
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A collection of **175 multi-turn agentic traces** drawn from real production
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traffic against the Claude Code CLI ≥ 2.1.139. Each trace captures the full
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request/response sequence of a single agent session, including per-request
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KV block hashes AND the original sub-agent fan-out structure (Task-tool
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spawned sub-agents grouped into `WekaSubagentEntry` blocks).
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Use this dataset when you want to:
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- Simulate the full agentic-coding workload including parallel Task-tool
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sub-agent fan-out
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- Study sub-agent dispatch patterns, instance counts, durations
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- Replay against an inference engine that should see the same concurrent-
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request structure a real Claude Code session generates
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Filters:
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1. **v5 only.** Every replayable request in every included session has
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`trace_version = 5` (the latest proxy schema, o200k_base tokenizer).
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Sessions containing any earlier-format request are excluded entirely.
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2. **≥ 20 main-agent turns.** Per-trace main-agent stream (the would-be
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no-subagents stream) must have at least 20 turns. Sub-agent fan-out
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is on top of that.
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3. **CC ≥ 2.1.139.** Every replayable request in every included session
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originated from a Claude Code CLI build at version 2.1.139 or newer.
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- **Traces:** 175
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- **Top-level entries:** 39,370 (38,368 main turns + 1,002 subagent groups)
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- **Sub-agent inner requests:** 35,458
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- **Total individual model requests:** 73,826
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- **Models:** `claude-opus-4-7` (70,643 req), `claude-opus-4-6` (2,138 req), `claude-haiku-4-5-20251001` (949 req), `claude-sonnet-4-6` (96 req)
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- **KV block size:** 64 tokens
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- **Hash scope:** `local` — block hash IDs are only comparable *within*
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a single trace; they are not a global content-addressable identity.
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## Important: tokenizer caveat
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The `in` field on each request and the `hash_ids` array are both
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measured in **the proxy's tokenizer** (`o200k_base`, GPT-4o family).
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Anthropic typically reports ~60 % of the o200k token count for the same
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content. So the ISL numbers below are larger than what the Anthropic
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API would have billed for the same prompt — but they're self-consistent
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between `in` and `hash_ids`, which is what matters for KV-cache replay
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simulation.
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## What's in each trace
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Top-level trace fields:
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| field | type | description |
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|-----------------|------------------|-----------------------------------------------------|
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| `id` | str | Trace identifier (the proxy session id) |
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| `models` | list[str] | Models used by the trace |
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| `block_size` | int | KV block size used to derive `hash_ids` (64) |
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| `hash_id_scope` | str | `local` — hash IDs are per-trace, not global |
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| `requests` | list[object] | Ordered list of per-request records OR `WekaSubagentEntry` groups |
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Each entry in `requests` is one of two shapes:
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### Main-agent request (`type: "n"` or `"s"`)
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| field | type | description |
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|---------------|-----------|--------------------------------------------------------------------------|
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| `t` | float | Seconds since start of trace |
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| `type` | str | `n` (non-streaming) or `s` (streaming) |
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| `model` | str | Target model for this request |
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| `in` | int | Effective prompt tokens covered by `hash_ids` (proxy tokenizer) |
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| `out` | int | Output tokens (Anthropic-reported) |
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| `hash_ids` | list[int] | Per-trace local block-hash IDs for the input, one per 64-token block |
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| `api_time` | float | End-to-end server time for this call (seconds) |
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| `think_time` | float? | Wall-clock gap from previous request's end (seconds) |
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| `ttft` | float? | Time to first token (streaming requests only) |
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### Sub-agent group (`type: "subagent"`)
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| field | type | description |
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|-----------------|----------------|--------------------------------------------------------|
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| `t` | float | Start time (seconds since trace start) |
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| `type` | str | Always `"subagent"` |
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| `agent_id` | str | Stable per-trace sub-agent instance id (slug + suffix) |
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| `subagent_type` | str | Sub-agent label (`"Subagent"` for Claude Code ≥ 2.1.139, else the original proxy label) |
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| `duration_ms` | int | Wall-clock span first→last inner request |
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| `total_tokens` | int | Sum of `in + out` across inner requests |
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| `tool_use_count`| null | Not tracked in the proxy DB |
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| `status` | str | Always `"completed"` |
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| `requests` | list[object] | Inner main-shape entries (type `n` — sub-agents are non-streaming) |
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| `models` | list[str] | Distinct models used inside this sub-agent run |
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Sub-agent groups are emitted at the position of the first inner request
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in the chronological stream. Their inner requests have absolute `t`
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values (not relative to the group start), making sub-agent and main-
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agent timelines directly interleavable for replay.
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`hash_ids` make the dataset unusually useful for KV-cache work: the
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contiguous common prefix between turn *t* and turn *t − 1* exactly
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measures the portion of the input that a local prefix cache would be
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able to reuse. The same accounting applies to sub-agent inner requests
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within their group, and to the dispatching parent request that
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triggered them.
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## Summary statistics
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Across **all** requests (main + sub-agent inner = 37,766 requests):
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| | p50 | p75 | p90 | p95 | p99 | mean |
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|------------------------------|---------:|---------:|---------:|---------:|---------:|---------:|
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| ISL (tokens) | 100,902 | 229,982 | 443,856 | 580,438 | 803,019 | 172,848 |
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| OSL (tokens) | 224 | 478 | 1,150 | 1,907 | 5,461 | 530 |
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| Top entries/trace | 115 | — | — | 678 | 1,141 | 231 |
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## Plots
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### Main-agent stream
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Histograms across all 21,566 main-agent turns (sub-agent groups skipped).
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Same view as the [no-subagents sibling](https://huggingface.co/datasets/semianalysisai/cc-traces-weka-no-subagents-051826) — the two datasets share an identical main-agent stream.
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### Sub-agent fan-out analysis
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Histograms across all 618 sub-agent groups (and their 16,200 inner requests). Companion to the main-stream plots — answers questions about how often sub-agents are spawned, how deep their tool-loops go, how long they take, and how much intra-group prefix cache reuse exists.
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Six panels:
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1. **Sub-agent groups per trace** — distribution of how many distinct sub-agent invocations each session spawns
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2. **Inner requests per group** — depth of each sub-agent's tool-use loop
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3. **Group wall-clock duration** — first→last inner span (seconds)
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4. **Group total tokens** — `Σ(in + out)` across each group's inner requests
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5. **Inner-request ISL** — per-call input length INSIDE sub-agent loops (smaller than main-agent turns because sub-agents work on focused sub-problems with trimmed context)
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6. **Intra-group cache hit rate** — for each non-first inner request, fraction of `hash_ids` already seen in earlier inners of the SAME group. Captures how much KV-cache reuse a local prefix cache would get out of a sub-agent's tool-use loop (typically high — sub-agents iterate on a stable prompt)
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## Model composition
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| model | requests (main + subagent inner) |
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|-------|---------:|
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| `claude-opus-4-7` | 36,637 |
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| `claude-haiku-4-5-20251001` | 702 |
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| `claude-opus-4-6` | 343 |
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| `claude-sonnet-4-6` | 84 |
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## Source
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Same proxy → weka pipeline as the
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[no-subagents sibling](https://huggingface.co/datasets/semianalysisai/cc-traces-weka-no-subagents-051826),
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just without the post-step that strips `WekaSubagentEntry` blocks.
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1. `utils/sample_proxy_traces.py --min-trace-version 5 --min-main-turns 20 --privacy-mode anon`
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2. `utils/proxy_to_weka.py` (subagent grouping per the dashboard's
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algorithm)
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3. Concatenate the resulting weka JSONs into `traces.jsonl` — one trace
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per line.
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The same-96-trace contract with the no-subagents sibling makes the two
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variants safe to A/B compare for any benchmark that cares about
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sub-agent fan-out's impact on cache-hit-rate or throughput.
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plots/distributions_linear.png
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Git LFS Details
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plots/distributions_log.png
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Git LFS Details
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plots/subagent_distributions_linear.png
ADDED
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Git LFS Details
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plots/subagent_distributions_log.png
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Git LFS Details
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traces.jsonl
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version https://git-lfs.github.com/spec/v1
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oid sha256:23f45691d854b364f2fb960d570fa60083ee3a63442d767201158534f9325536
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size 1115513148
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