API option

.gitignore

@@ -1,2 +1,5 @@
 myenv/
-.DS_Store
+.DS_Store
+.env
+
+__pycache__/

README.md

@@ -12,18 +12,34 @@ license: mit
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
-
+https://launchdarkly.com/blog/build-sentiment-analysis-app-hugging-face-spaces-with-ai-model-feature-flags/
 
 ## Run on docker
 
 ### UI
 
 docker run -it -p 8501:8501 --platform=linux/amd64 \
-	-e LAUNCHDARKLY_SDK_KEY="<LAUNCHDARKLY_SDK_KEY>" \
-	registry.hf.space/asgface-sentimentai:latest streamlit run app.py
+ -e LAUNCHDARKLY_SDK_KEY="<LAUNCHDARKLY_SDK_KEY>" \
+ registry.hf.space/asgface-sentimentai:latest streamlit run app.py
 
 ### API
 
 docker run -it -p 5001:5000 --platform=linux/amd64 \
-	-e LAUNCHDARKLY_SDK_KEY="<LAUNCHDARKLY_SDK_KEY>" \
-	registry.hf.space/asgface-sentimentai:latest python api.py
+ -e LAUNCHDARKLY_SDK_KEY="<LAUNCHDARKLY_SDK_KEY>" \
+ registry.hf.space/asgface-sentimentai:latest python api.py
+
+## Run locally
+
+### API
+
+python3 -m venv myenv  
+source myenv/bin/activate
+
+LAUNCHDARKLY_SDK_KEY=<LAUNCHDARKLY_SDK_KEY> gunicorn -w 4 -b 0.0.0.0:5001 api:app
+
+### UI
+
+python3 -m venv myenv  
+source myenv/bin/activate
+
+LAUNCHDARKLY_SDK_KEY=<LAUNCHDARKLY_SDK_KEY> streamlit run app.py

api.py

@@ -64,4 +64,4 @@ def analyze_sentiment():
 
 
 if __name__ == '__main__':
-    app.run(debug=True)
+    app.run(port=5001)

requirements.txt

@@ -3,4 +3,5 @@ transformers
 launchdarkly-server-sdk
 torch
 Flask
-datasets
+datasets
+gunicorn