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README.md
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#
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- The Clay model **code** lives on [Github](https://github.com/Clay-foundation/model). License: [Apache](https://github.com/Clay-foundation/model/LICENSE). The latest release is [v0.0.1](https://github.com/Clay-foundation/model/releases/tag/v0.0.1)
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- The Clay model **weights** on [Hugging Face](https://huggingface.co/made-with-clay/Clay/). License: [OpenRAIL-M](https://github.com/Clay-foundation/model/blob/main/LICENSE-MODEL.md).
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- The Clay **documentation** [lives on this site](https://clay-foundation.github.io/model/). License: [CC-BY](http://creativecommons.org/licenses/by/4.0/).
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- *Coming Soon* > We maintain a set of **embeddings** on [Source Cooperative](https://beta.source.coop/clay/). License: [ODC-BY](https://opendatacommons.org/licenses/by/).
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title: Terrasentinels
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emoji: 📚
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colorFrom: pink
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colorTo: yellow
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sdk: streamlit
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sdk_version: 1.38.0
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app_file: app.py
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pinned: false
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# Data Fetcher AI Agent
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This Streamlit app simulates fetching Sentinel-2 satellite imagery data and storing it in a PostgreSQL database. It's designed to demonstrate the process of data collection and storage for further analysis using tools like MindsDB for anomaly detection.
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## Features
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- Input your OpenAI API key securely
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- Input geographical coordinates (latitude and longitude)
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- Specify date range for data collection
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- Simulate data storage in PostgreSQL
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- Prepare data for analysis with MindsDB
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## How to Use
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1. Enter your OpenAI API key in the sidebar (this is required to run the app)
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2. Enter your Earth Engine Project ID (or use the default)
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3. Input the latitude and longitude of your area of interest
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4. Select the start and end dates for your data collection period
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5. Provide a name for your image
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6. Click "Fetch Sentinel-2 Image" to simulate the data collection and storage process
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## Security Note
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Your API key is not stored and is only used for the current session. It's securely handled and not displayed after entry.
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## Note
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This app is a simulation and does not actually connect to Earth Engine or store data in PostgreSQL. It's designed to demonstrate the user interface and workflow of such a system.
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## Future Improvements
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- Implement actual connection to Earth Engine
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- Set up real-time data storage in PostgreSQL
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- Integrate MindsDB for anomaly detection and data analysis
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Feel free to contribute to this project or use it as a starting point for your own data analysis workflows!
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