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Solana Clawd Realtime Research Instruct
Instruction-tuning dataset generated by scripts/realtime_dataset_ingest.py
from submitted PDFs, notebooks, parquet QA rows, JSON/JSONL files, and local
reference text.
Contents
- Total examples: 29058
- Train/eval/test: 26152 / 1452 / 1454
- Sources: 28
- Duplicate examples removed: 0
- Duplicate files skipped: 2
- Secret-like records skipped: 296
Format
Each row uses OpenAI/Hugging Face chat messages:
{"messages": [{"role": "system", "content": "..."}, {"role": "user", "content": "..."}, {"role": "assistant", "content": "..."}]}
Rows also include non-training metadata columns: source, source_type,
source_sha256, record_id, example_sha256, tags, and metadata.
Sources
2410.21169v5.pdf(pdf, 57 examples)2412.04913v3.pdf(pdf, 8 examples)2412.07591v2.pdf(pdf, 8 examples)2512.01112v3.pdf(pdf, 104 examples)2512.06505v4.pdf(pdf, 13 examples)2512.19113v2.pdf(pdf, 37 examples)2512.22476v1.pdf(pdf, 68 examples)2601.10812v1.pdf(pdf, 37 examples)2601.17008v1.pdf(pdf, 19 examples)2602.00776v1.pdf(pdf, 29 examples)2602.14860v1.pdf(pdf, 30 examples)2603.10092v1.pdf(pdf, 27 examples)2604.01431v1.pdf(pdf, 19 examples)2605.05089v1.pdf(pdf, 32 examples)2605.05878v1.pdf(pdf, 16 examples)2605.10400v1.pdf(pdf, 87 examples)2605.10428v1.pdf(pdf, 48 examples)2605.12151v2.pdf(pdf, 9 examples)2605.29174v1 (1).pdf(pdf, 24 examples)2605.29174v1.pdf(pdf, 0 examples)2606.08232v1 (1).pdf(pdf, 11 examples)2606.08232v1.pdf(pdf, 0 examples)analysing-crypto-charts-like-pro.ipynb(notebook, 47 examples)analysis-of-smart-contracts-in-blockchain.ipynb(notebook, 22 examples)solana-prediction.ipynb(notebook, 53 examples)test-00000-of-00001.parquet(parquet, 1407 examples)train-00000-of-00001.parquet(parquet, 26843 examples)SKILL.md(text, 3 examples)
Source Inventory
PDF Research Sources
| File | What it contains | Pages | Examples | Identifier |
|---|---|---|---|---|
| 2410.21169v5.pdf | Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction | 46 | 57 | https://arxiv.org/abs/2410.21169v5 |
| 2412.04913v3.pdf | Bridging Culture and Finance: A Multimodal Analysis of Memecoins in the Web3 Ecosystem | 4 | 8 | - |
| 2412.07591v2.pdf | CoinCLIP: A Multimodal Framework for Assessing Viability in Web3 Memecoins | 4 | 8 | - |
| 2512.01112v3.pdf | Autodeleveraging: Impossibilities and Optimization | 103 | 104 | https://arxiv.org/abs/2512.01112v3 |
| 2512.06505v4.pdf | Amortizing Perpetual Options | 12 | 13 | https://arxiv.org/abs/2512.06505v4 |
| 2512.19113v2.pdf | A Unified Framework and Comparative Study of Decentralized Finance Derivatives Protocols | 36 | 37 | https://arxiv.org/abs/2512.19113v2 |
| 2512.22476v1.pdf | AutoQuant: An Auditable Expert-System Framework for Execution-Constrained Auto-Tuning in Cryptocurrency Perpetual Futures | 67 | 68 | https://arxiv.org/abs/2512.22476v1 |
| 2601.10812v1.pdf | Optimal Liquidation of Perpetual Contracts | 36 | 37 | https://arxiv.org/abs/2601.10812v1 |
| 2601.17008v1.pdf | Bayesian Robust Financial Trading with Adversarial Synthetic Market Data | 12 | 19 | https://arxiv.org/abs/2601.17008v1 |
| 2602.00776v1.pdf | Explainable Patterns in Cryptocurrency Microstructure | 28 | 29 | https://arxiv.org/abs/2602.00776v1 |
| 2602.14860v1.pdf | Predicting the success of new crypto-tokens: the Pump.fun case | 29 | 30 | https://arxiv.org/abs/2602.14860v1 |
| 2603.10092v1.pdf | Execution Is the New Attack Surface: Survivability-Aware Agentic Crypto Trading with OpenClaw-Style Local Executors | 26 | 27 | https://arxiv.org/abs/2603.10092v1 |
| 2604.01431v1.pdf | Do Prediction Markets Forecast Cryptocurrency Volatility? Evidence from Kalshi Macro Contracts | 14 | 19 | https://arxiv.org/abs/2604.01431v1 |
| 2605.05089v1.pdf | Dynamic Collateral Control for Permissionless Spot Perpetual Basis Trading | 23 | 32 | https://arxiv.org/abs/2605.05089v1 |
| 2605.05878v1.pdf | Agentic, Context-Aware Risk Intelligence in the Internet of Value | 15 | 16 | https://arxiv.org/abs/2605.05878v1 |
| 2605.10400v1.pdf | Resolution-Aware Perpetual Futures on Binary Prediction Markets: An Empirical Risk-Design Framework Using Polymarket Data | 86 | 87 | https://arxiv.org/abs/2605.10400v1 |
| 2605.10428v1.pdf | A Taxonomy of Event-Linked Perpetual Futures: Variant Designs Beyond the Single-Market Binary Case | 47 | 48 | https://arxiv.org/abs/2605.10428v1 |
| 2605.12151v2.pdf | RED-2400: A Public Benchmark of Algorithmically-Rejected Trading Events with Outcome Labels | 8 | 9 | - |
| 2605.29174v1 (1).pdf | Paper Agents, Paper Gains: An Empirical Analysis of DeFi Investment Agents | 23 | 24 | https://arxiv.org/abs/2605.29174v1 |
| 2605.29174v1.pdf | duplicate file skipped | - | 0 | - |
| 2606.08232v1 (1).pdf | Hour-Aware Adaptive Risk Management for Autonomous Memecoin Trading: A Multi-Layer Intelligence Framework | 11 | 11 | - |
| 2606.08232v1.pdf | duplicate file skipped | - | 0 | - |
Notebook Sources
| File | Cells | Kernel | Examples |
|---|---|---|---|
| analysing-crypto-charts-like-pro.ipynb | 53 | Python 3 | 47 |
| analysis-of-smart-contracts-in-blockchain.ipynb | 27 | Python 3 | 22 |
| solana-prediction.ipynb | 67 | Python 3 | 53 |
Parquet QA Sources
| File | Rows | Columns | Examples |
|---|---|---|---|
| test-00000-of-00001.parquet | 1426 | question, answer, chunk | 1407 |
| train-00000-of-00001.parquet | 27092 | question, answer, chunk | 26843 |
Text and Skill Sources
| File | Type | Details | Examples |
|---|---|---|---|
| SKILL.md | text | 10506 | 3 |
Google Document Processing
The ingestion script supports Google-backed PDF extraction:
pdf_extractor: autotries Document AI when OAuth/ADC credentials are present, then Gemini whenGEMINI_API_KEYorGOOGLE_API_KEYis present, then localpypdf.- Document AI endpoint:
https://us-documentai.googleapis.com/v1/projects/1013652097839/locations/us/processors/29a612e70aee73e1:process - Document AI field mask:
text,pages.pageNumber,pages.detectedLanguages,pages.imageQualityScores - Document AI billing labels:
pipeline=solana-clawd,dataset=realtime-research,client=clawd - Gemini model:
gemini-2.5-flash
Document AI's ProcessDocument endpoint normally requires Google Cloud OAuth
or Application Default Credentials. API keys are used by the Gemini extractor.
Reproduce
cd /path/to/solana-clawd/ai-training
python3 scripts/realtime_dataset_ingest.py --config configs/realtime_dataset_config.yaml
python3 scripts/realtime_dataset_ingest.py --input my.pdf my.json --push
python3 scripts/realtime_dataset_ingest.py --pdf-extractor gemini --input my.pdf
python3 scripts/realtime_dataset_ingest.py --pdf-extractor documentai --input my.pdf
Use watch mode for drop-folder style updates:
python3 scripts/realtime_dataset_ingest.py --watch-dir data/incoming --watch --push
Safety Notes
The builder filters high-confidence API keys, private keys, and token patterns
before writing rows. It does not publish local absolute paths in dataset rows.
Review data/realtime_research_dataset_manifest.json before public release.
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