| --- |
| language: |
| - en |
| license: apache-2.0 |
| library_name: datasets |
| tags: |
| - agentic |
| - tool-use |
| - function-calling |
| - curated |
| - high-quality |
| - conversations |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # Acta |
|
|
| *Acta* (Latin: "acts, deeds, records") - A premium curated sample of high-quality agentic tool-use conversations, filtered using an 8-factor quality model based on statistical correlation analysis of diversity metrics. |
|
|
| ## Overview |
|
|
| This public sample contains **5,000 conversations** from the full 37K Acta dataset. It was created by analyzing 5 major agentic datasets (FlameFox, Hermes Reasoning, Hermes Multi-turn, Smolagents, SWE Agent) and applying evidence-based quality filters to maximize training signal density. |
|
|
| **Key Statistics:** |
| - **Train:** 4,500 samples |
| - **Validation:** 500 samples |
| - **Avg semantic diversity:** 0.53 |
| - **Avg lexical diversity:** 0.47 |
| - **Sources:** 5 datasets harmonized |
|
|
| ## The 8-Factor Quality Model |
|
|
| Each sample was scored using 8 factors weighted by their correlation with training quality: |
|
|
| | Factor | Weight | Threshold | Rationale | |
| |--------|--------|-----------|-----------| |
| | Lexical Diversity | 0.25 | >=0.35 | unique_words / total_words (r=+0.967 with quality) | |
| | Semantic Diversity | 0.20 | >=0.40 | content richness excluding stopwords (r=+0.947) | |
| | Verb Uniqueness | 0.15 | >=0.01 | unique_verbs / total_verbs (r=+0.852) | |
| | Turn Efficiency | 0.15 | 2-12 turns | Optimal conversation length (longer = repetitive) | |
| | Tool Pattern Novelty | 0.10 | - | Penalty for over-represented tool sequences | |
| | Reasoning Density | 0.08 | - | Thinking blocks per assistant turn | |
| | Role Balance | 0.05 | - | User/assistant turn ratio | |
| | Content Brevity | 0.02 | - | Information density (shorter = denser signal) | |
|
|
| ## Source Distribution |
|
|
| | Source | Samples | Avg Quality | Characteristics | |
| |--------|---------|-------------|-----------------| |
| | FlameFox Agentic | ~2,600 | 0.819 | Highest diversity, balanced tools | |
| | Hermes Reasoning | ~1,400 | 0.598 | Good semantic diversity | |
| | Hermes Multi-turn | ~450 | 0.534 | Multi-turn, deduplicated | |
| | Smolagents Code | ~70 | 0.592 | Low redundancy | |
| | SWE Agent GLM | ~20 | 0.433 | Shortest, least repetitive traces | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load the curated sample |
| dataset = load_dataset("DJLougen/Acta") |
| |
| # Access quality metrics |
| sample = dataset["train"][0] |
| print(sample["quality_score"]) # 0.0 - 1.0 |
| print(sample["semantic_diversity"]) # 0.546 |
| print(sample["lexical_diversity"]) # 0.400 |
| ``` |
|
|
| ## Key Findings |
|
|
| 1. **Quality ≠ Quantity** - 37K curated samples > 200K raw samples |
| 2. **Lexical diversity is the strongest quality predictor** (r=+0.967) |
| 3. **More content ≠ better signal** - SWE Agent has 5x more text but 3x lower quality |
| 4. **4-10 turns optimal** - longer conversations become repetitive (r=-0.982) |
| 5. **Tool redundancy is rampant** - some patterns repeat 3000+ times in raw data |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{acta_2026, |
| title = {Acta: A Quality-Curated Agentic Tool-Use Dataset}, |
| author = {Lougen, Daniel}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/DJLougen/Acta} |
| } |
| ``` |
|
|
| ## License |
|
|
| Apache 2.0 |
|
|
| ## Acknowledgments |
|
|
| Source datasets: |
| - [FlameF0X/agentic-code](https://huggingface.co/datasets/FlameF0X/agentic-code) |
| - [interstellarninja/hermes_reasoning_tool_use](https://huggingface.co/datasets/interstellarninja/hermes_reasoning_tool_use) |
| - [interstellarninja/tool-use-multiturn-reasoning](https://huggingface.co/datasets/interstellarninja/tool-use-multiturn-reasoning) |
| - [smolagents/codeagent-traces](https://huggingface.co/datasets/smolagents/codeagent-traces) |
| - [DCAgent/neulab-nebius-swe-agent-trajectories-sandboxes_glm_4.7_traces_jupiter](https://huggingface.co/datasets/DCAgent/neulab-nebius-swe-agent-trajectories-sandboxes_glm_4.7_traces_jupiter) |
|
|
| --- |
|
|
| **Full 37K proprietary dataset:** [DJLougen/Acta-Proprietary](https://huggingface.co/datasets/DJLougen/Acta-Proprietary) |
|
|
