trace_id stringlengths 34 34 | run_id stringclasses 1
value | spans listlengths 3 13 | total_tokens int64 0 11.7k | total_duration_ms float64 36 1.31M | total_cost_usd float64 0 0.02 |
|---|---|---|---|---|---|
0x4727b25249ff3ae35e280da0809473be | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
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... | 0 | 675,639.625654 | 0.008207 |
0xee41f239d87215c734eb169fa4e8f15b | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 11,720 | 1,011,102.040291 | 0.013583 |
0x52628c75666ff6a91576392d9903352a | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 0 | 679,867.550006 | 0.004993 |
0x51cf77a3f823c0edd965cb15958eb675 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 0 | 747,241.832024 | 0.011278 |
0xbabf0ecdf82c8bca36fd019db2f7ff49 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 0 | 1,313,735.738642 | 0.017233 |
0x4a85e3d078d2982277f73de70e52eb16 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 0 | 940,255.757597 | 0.007456 |
0x46f70095f09a583d1a24b17bd57c33e7 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [
{
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... | 0 | 471,604.044807 | 0.004253 |
0x67607c4a7119d6148d2f98038aef0039 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [{"attributes":{"agent.type":null,"gen_ai.operation.name":null,"gen_ai.request.max_tokens":null,"gen(...TRUNCATED) | 0 | 819,676.138256 | 0.005363 |
0x7017d1a85266649a6906aa3ca7aeb7e8 | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [{"attributes":{"agent.type":null,"gen_ai.operation.name":null,"gen_ai.request.max_tokens":null,"gen(...TRUNCATED) | 0 | 164.999299 | 0 |
0xa49cab520994a85f27fc6a3b7691d05b | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 | [{"attributes":{"agent.type":null,"gen_ai.operation.name":null,"gen_ai.request.max_tokens":null,"gen(...TRUNCATED) | 0 | 246.839543 | 0 |
End of preview. Expand in Data Studio
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SMOLTRACE Execution Traces
This dataset contains OpenTelemetry execution traces from a SMOLTRACE benchmark run.
Dataset Information
| Field | Value |
|---|---|
| Model | Nanbeige/Nanbeige4.1-3B |
| Run ID | cf816e4a-1745-4010-a7cb-2bde4dfc02d5 |
| Total Traces | 15 |
| Generated | 2026-03-04 08:08:50 UTC |
| Format | OpenTelemetry-compatible |
Schema
| Column | Type | Description |
|---|---|---|
trace_id |
string | Unique trace identifier |
span_id |
string | Span identifier within trace |
parent_span_id |
string | Parent span for hierarchy |
span_name |
string | Name of the operation |
start_time |
string | ISO timestamp of span start |
end_time |
string | ISO timestamp of span end |
duration_ms |
float | Span duration in milliseconds |
status |
string | Span status (OK, ERROR) |
attributes |
string | JSON with span attributes |
events |
string | JSON with span events |
total_tokens |
int | Tokens used in this span |
input_tokens |
int | Input/prompt tokens |
output_tokens |
int | Output/completion tokens |
total_cost_usd |
float | Cost for this span |
total_duration_ms |
float | Total duration including children |
Understanding Traces
SMOLTRACE uses OpenTelemetry to capture detailed execution traces:
agent.run (root span)
├── agent.step (step 1)
│ ├── llm.call (model inference)
│ └── tool.execute (tool invocation)
├── agent.step (step 2)
│ └── llm.call
└── agent.finalize
Usage
from datasets import load_dataset
import json
# Load traces
ds = load_dataset("YOUR_USERNAME/smoltrace-traces-TIMESTAMP")
# Analyze execution patterns
for trace in ds['train']:
attrs = json.loads(trace['attributes']) if trace['attributes'] else {}
print(f"Trace {trace['trace_id']}: {trace['span_name']} - {trace['duration_ms']}ms")
Related Datasets
This evaluation run also generated:
- Results Dataset: Pass/fail outcomes for each test case
- Metrics Dataset: GPU utilization and environmental metrics
- Leaderboard: Aggregated metrics for model comparison
About SMOLTRACE
SMOLTRACE is a comprehensive benchmarking and evaluation framework for Smolagents - HuggingFace's lightweight agent library.
Key Features
- Automated agent evaluation with customizable test cases
- OpenTelemetry-based tracing for detailed execution insights
- GPU metrics collection (utilization, memory, temperature, power)
- CO2 emissions and power cost tracking
- Leaderboard aggregation and comparison
Quick Links
Installation
pip install smoltrace
Citation
If you use SMOLTRACE in your research, please cite:
@software{smoltrace,
title = {SMOLTRACE: Benchmarking Framework for Smolagents},
author = {Thakkar, Kshitij},
url = {https://github.com/Mandark-droid/SMOLTRACE},
year = {2025}
}
Generated by SMOLTRACE
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