100k_Synthetic_LLM_Multiturn_Formatted_Tech_Support
🛠️ Drone Technical Support Dialogue Dataset (Simulated Conversations)
Build smarter UAV assistants with realistic, domain-specific technical support data.
Whether you're training LLMs to handle drone troubleshooting, building a contextual agent for UAV repair workflows, or teaching a model to understand user frustration in technical conversations—this dataset is for you.
🔗 Sample Dataset on Hugging Face: (Https://huggingface.co/datasets/CJJones/100k_Synthetic_LLM_Multiturn_Formatted_Tech_Support)
🚁 Example Use Case:
delivery_service (frustrated):
"I'm extremely annoyed by this camera feed freezing malfunction on my Yuneec H520E."Support Agent (Me):
"Let's troubleshoot that step by step. Start by formatting your SD card to exFAT with a 64KB allocation. Also, check for camera firmware updates (v3.0.8) and calibrate your gimbal under Settings > Sensors > Calibration."Diagnostic Tools:
- Azure Monitor for cloud services
- iOS console logs via Xcode
Error Code:
GEOZONE_SYNC_FAILURE
Outcome: Resolution through structured troubleshooting and metadata analysis.
📦 What's Inside:
- 60+ richly annotated conversations (simulated but realistic)
- Covers DJI, Autel, Skydio, and Yuneec platforms
- Metadata includes:
- Drone model
- Software version
- Mobile OS
- Error codes
- Reproduction steps
- Troubleshooting procedures
- Diagnostic tools and references
🎯 Perfect for:
- Training dialogue models on real-world UAV support scenarios
- Creating technical Q&A agents with layered reasoning
- Modeling user frustration and progressive troubleshooting
- Benchmarking LLM support assistants in hardware/software issue resolution
🔧 Supported Tasks:
- Closed-domain QA
- Dialogue modeling
- Explanation generation
- Troubleshooting flow simulation
Note: This dataset is being sold to fund the development of a 500M -1B, fully transparent GPT community model. All data used in the model will eventually be made open to the public with it's release.
📥 Full version available exclusively here on Gumroad