- This project demonstrates the application of Agentic AI in industrial environments, enabling operators to interact with complex systems through natural language. Built using Google ADK and a modular agent architecture, it translates high-level business or operational intents into actionable tasks—such as predictive maintenance and system control.
- 🧠 Intent-based natural language interaction
- 🔍 Query engine status
- 🔧 Predict Remaining Useful Life (RUL)
- 🛑 Simulate engine shutdowns
- 📅 Schedule maintenance actions
- 🤖 Modular multi-agent architecture (root agent + sub-agents)
- 📊 Backed by the CMAPSS aircraft engine degradation dataset
- Python 3.10+
- Google ADK
- (Optional) GitHub Codespaces for cloud-based execution
git clone https://github.com/yourusername/talk-to-your-factory.git
cd talk-to-your-factory
pip install -r requirements.txtBefore running the app, create a .env file in the root directory with the following content:
GOOGLE_GENAI_USE_VERTEXAI=FALSE
GOOGLE_API_KEY=<your-API-key-here>💡 Set
GOOGLE_GENAI_USE_VERTEXAI=FALSEto use the public Gemini API instead of Google Cloud Vertex AI. Make sure you have a valid API key from Google Generative AI.
adk webAccess the ADK web interface and begin interacting using natural language.
I need to maintain all the engines working well according to their predicted RUL, avoiding unexpected stops. Please create a consolidated predictive maintenance plan in table format.
| Engine ID | Recommended Action | Priority | Estimated Cost (USD) | Labor Hours | Assigned Staff | Scheduled Time |
|---|---|---|---|---|---|---|
| 1 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 2 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 3 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 3 days |
| 4 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 5 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 6 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 7 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 8 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 9 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 10 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 11 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 12 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 13 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 14 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 15 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 16 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 17 | REPAIR | high | 6000 | 4 | mechanic, junior_mechanic | Schedule within 3 days |
| 18 | REPAIR | high | 6000 | 4 | mechanic, junior_mechanic | Schedule within 3 days |
| 19 | MONITOR | low | 0 | 0 | junior_mechanic | Schedule within 7 days |
| 20 | STOP | critical | 15000 | 8 | tech_lead, senior_mechanic | IMMEDIATE (0–1 days) |
- CMAPSS Dataset – NASA Prognostics Data Repository
- Saxena, A., et al. “Damage Propagation Modeling for Aircraft Engine Run-to-Failure Simulation.” (2008).
- Google ADK Documentation
Contributions and improvements are welcome! Feel free to fork the repository, submit pull requests, or open issues for suggestions and bugs.
This project is licensed under the MIT License.