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title: MaterialScienceGPT | |
colorFrom: purple | |
colorTo: yellow | |
sdk: gradio | |
sdk_version: 5.25.0 | |
app_file: app.py | |
pinned: false | |
license: mit | |
short_description: 'GPT for Materials Science appplications ' | |
# π§ͺ Materials Science Expert Chatbot | |
Welcome to the **Materials Science Expert Chatbot** β an AI-powered assistant specialized in helping you choose the **best materials for specific applications**. | |
This chatbot is powered by the **Groq API (LLaMA 3.1-8B)** and is tailored to only respond to **Materials Science-related queries**. | |
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π§βπ¬ Built For | |
Highschool Student | |
Chemistry & Physics enthusiasts | |
Computational Scientists | |
Materials scientists | |
Engineering students | |
Product designers and R&D teams | |
Anyone interested in smart material selection using AI | |
## π What Can This Chatbot Do? | |
- β Suggest the **top 3 materials** for a given application | |
- β Explain the **required properties** for the application | |
- β Provide a **side-by-side comparison table** of key material properties (mechanical, thermal, chemical) | |
- β Recommend suitable materials based on different scenarios | |
- β Will **not respond** to unrelated questions (e.g., history, general knowledge) | |
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## π¬ Example Questions | |
You can ask things like: | |
- *What are the best corrosion-resistant materials for marine environments (e.g., desalination)?* | |
- *Which materials are ideal for solar panel coatings and desert heat management?* | |
- *What materials are used for aerospace structures in extreme climates?* | |
- *What advanced materials are used in electric vehicles and batteries in the UAE?* | |
- *How can one leverage AI/ML techniques in Materials Science?* | |
The bot will return a clean, structured comparison of the best material options along with their justifications. | |
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## π How to Use | |
1. Type your question in the textbox (e.g., βBest materials for aerospace applicationsβ) | |
2. Click **Submit** (orange button) or press **Enter** | |
3. View the expert response including a **materials comparison table** | |
4. Browse popular questions for inspiration | |
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## π§ Powered By | |
- **[Groq API](https://groq.com/)** β Ultra-fast inference using LLaMA 3.1-8B | |
- **[Gradio](https://gradio.app/)** β Beautiful and interactive UI | |
- **Python** β Backend glue and logic | |
- Optionally expandable with: | |
- CSV/PDF table downloads | |
- CIF/3D material structure viewing | |
- AI/ML integration for predictive material selection | |
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## π Environment Variables | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |