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Project description
Climate Foresight
Prototype of a system that answers questions about climate change impacts on planned human activities.
Running with docker
simplest: running prebuild container
You should have Docker installed. Then execute:
docker pull koldunovn/climsight:stable
docker run -p 8501:8501 -e OPENAI_API_KEY=$OPENAI_API_KEY climsight
Then open http://localhost:8501/
in your browser.
Build and run container with the latest code
You should have the following packages installed:
- git
- wget
- docker
As long as you have them, do:
git clone https://github.com/koldunovn/climsight.git
cd climsight
./download_data.sh
docker build -t climsight .
docker run -p 8501:8501 climsight
Then open http://localhost:8501/
in your browser. If you don't want to add OpenAI key every time, you can expose it through:
docker run -p 8501:8501 -e OPENAI_API_KEY=$OPENAI_API_KEY climsight
where $OPENAI_API_KEY
not necessarily should be environment variable, you can insert the key directly.
If you do not have an OpenAI key but want to test Climsight without sending requests to OpenAI, you can run Climsight with the skipLLMCall
argument:
docker run -p 8501:8501 -e STREAMLIT_ARGS="skipLLMCall" climsight
Installation
The easiest way is to install it through conda or mamba. We recommend mamba, as it's faster.
Install mamba if you don't have it.
git clone https://github.com/koldunovn/climsight.git
cd climsight
Create environment and install necessary packages:
mamba env create -f environment.yml
Activate the environment:
conda activate climsight
Before you run
You have to download example climate data and NaturalEarth coastlines. To do it simply run:
./download_data.sh
You also need to download the natural hazard data (for which you have to create a free account). Please download the CSV - Disaster Location Centroids [zip file] and unpack it into the 'data/natural_hazards' folder. Your file should automatically be called 'pend-gdis-1960-2018-disasterlocations.csv'. If not, please change the file name accordingly.
You would also need an OpenAI API key to run the prototype. You can provide it as environment variable:
export OPENAI_API_KEY="???????"
There is a possibility to also provide it in the running app. The cost of each request (status September 2023) is about 6 cents with gpt-4
and about 0.3 cents with gpt-3.5-turbo
(you can change it in the beggining of climsight.py
script).
Running
Change to the climsight
folder:
cd climsight
streamlit run src/climsight/climsight.py
The browser window should pop up, with the app running. Ask the questions and don't forget to press "Generate".
If you do not have an OpenAI key but want to test Climsight without sending requests to OpenAI, you can run Climsight with the skipLLMCall
argument:
streamlit run src/climsight/climsight.py skipLLMCall
Citation
If you use or refer to ClimSight in your work, please cite the following publication:
Koldunov, N., Jung, T. Local climate services for all, courtesy of large language models. Commun Earth Environ 5, 13 (2024). https://doi.org/10.1038/s43247-023-01199-1
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