prepare space.

Dockerfile

@@ -17,4 +17,11 @@ RUN git clone https://github.com/mzimm003/Chess /app/Chess
 RUN pip install /app/Chess
 
 COPY --chown=user . /app
-CMD ["uvicorn", "app:main", "--host", "0.0.0.0", "--port", "7860"]
+# CMD ["uvicorn", "app:main", "--host", "0.0.0.0", "--port", "7860"]
+
+EXPOSE 7860
+CMD streamlit run app.py \
+    --server.headless true \
+    --server.enableCORS false \
+    --server.enableXsrfProtection false \
+    --server.fileWatcherType none

app.py

@@ -2,9 +2,10 @@ from my_chess.scripts.scripts import HumanVsBot
 from my_chess.learner.environments import Chess
 
 from chessmodels import DCMinMax
+import streamlit as st
 
-def main(kwargs=None):
-    modelminmax = DCMinMax.from_pretrained("mzimm003/DeepChessReplicationMinMax")
+def play(bot_select):
+    modelminmax = DCMinMax.from_pretrained("mzimm003/{}".format(bot_select))
     play = HumanVsBot(
         model=modelminmax,
         environment=Chess(render_mode="rgb_array"),
@@ -12,5 +13,11 @@ def main(kwargs=None):
     )
     play.run()
 
+def main(kwargs=None):
+    bot_select = st.selectbox(
+        options=["DeepChessReplicationMinMax"]
+    )
+    st.button("Play bot!", on_click=play, args=bot_select)
+
 if __name__ == "__main__":
     main()

requirements.txt

@@ -11,4 +11,6 @@ posix_ipc==1.1.1
 torchvision==0.14.1
 huggingface_hub==0.24.0
 lz4==4.3.3
-safetensors==0.4.3
+safetensors==0.4.3
+streamlit==1.36.0
+streamlit-image-coordinates==0.1.9