experiment2

app.py

@@ -1,21 +1,7 @@
 import gradio as gr
 from absa_evaluator import AbsaEvaluatorTest
+import evaluate
+from evaluate.utils import launch_gradio_widget
 
-def evaluate_texts(predictions, references):
-    evaluator = AbsaEvaluatorTest()
-    return evaluator.compute(predictions, references)
-
-def main():
-    iface = gr.Interface(
-        fn=evaluate_texts,  # The evaluation function you want to use
-        inputs=[
-            gr.Textbox(lines=2, placeholder="Enter Predictions Here..."),
-            gr.Textbox(lines=2, placeholder="Enter References Here...")
-        ],
-        outputs=gr.Textbox()
-    )
-
-    iface.launch()
-
-if __name__ == "__main__":
-    main()
+module = evaluate.load("absa_evaluator.py")
+launch_gradio_widget(module)

requirements.txt

@@ -1,3 +1,3 @@
 git+https://github.com/huggingface/evaluate@a4bdc10c48a450b978d91389a48dbb5297835c7d
 scikit-learn
-gradio
+gradio==3.50