hardik-kanzariya commited on
Commit
ebb9003
1 Parent(s): 5ccafa6

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +0 -32
app.py CHANGED
@@ -76,35 +76,3 @@ if text:
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  "confidence": "{:.2f}".format(float(confidence_score[0] * 100)) + "%"} # Adjust as necessary for output formatting
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  st.json(response)
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- # Add a POST endpoint
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- def api_predict(text):
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- prediction, confidence_score = getPrediction(text)
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- return {
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- "prediction": getSentiment(prediction) + " Statement",
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- "confidence": f"{confidence_score * 100:.2f}%"
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- }
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-
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- st.experimental_set_query_params(api_predict=api_predict)
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-
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- # # Streamlit UI
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- # st.title("Sentiment Analysis")
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-
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- # # Use st.query_params to get the 'text' parameter from the URL
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- # query_text = st.query_params.get("text", [""])[0] # Accessing 'text' from query params
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-
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- # if query_text:
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- # # If text is passed in the URL, process it
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- # prediction, confidence_score = getPrediction(query_text)
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- # st.json({
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- # "prediction": getSentiment(prediction) + " Statement",
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- # "confidence": f"{confidence_score * 100:.2f}%"
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- # })
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- # else:
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- # # Normal Streamlit app interface for manual text entry
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- # input_text = st.text_area("Enter Text for Sentiment Analysis")
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- # if input_text:
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- # prediction, confidence_score = getPrediction(input_text)
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- # st.json({
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- # "prediction": getSentiment(prediction) + " Statement",
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- # "confidence": f"{confidence_score * 100:.2f}%"
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- # })
 
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  "confidence": "{:.2f}".format(float(confidence_score[0] * 100)) + "%"} # Adjust as necessary for output formatting
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  st.json(response)
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