Update app.py

app.py

@@ -1,8 +1,5 @@
-
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 import streamlit as st 
 
-
 from selenium import webdriver
 from selenium.webdriver.common.by import By
 from selenium.webdriver.chrome.options import Options
@@ -141,4 +138,155 @@ def scrape_google_reviews(url):
         df = pd.DataFrame(review_data)
         df[df["review_text"].str.contains("No review text")==False]
         st.dataframe(df)
+
         
+        if tokenizer and model:
+            inputs = tokenizer(df['review_text'].tolist(), return_tensors="pt", padding=True, truncation=True)
+            with torch.no_grad():
+                logits = model(**inputs).logits
+            predicted_probabilities = torch.nn.functional.softmax(logits, dim=-1)
+            predicted_labels = predicted_probabilities.argmax(dim=1)
+            results = []
+            for i, label in enumerate(predicted_labels):
+                results.append({'Review Number': i + 1, 'Sentiment': model.config.id2label[label.item()]})
+            sentiment_df = pd.DataFrame(results)
+            value_counts1 = sentiment_df['Sentiment'].value_counts().rename_axis('Sentiment').reset_index(name='count')
+            final_df = value_counts1
+            
+
+            
+
+
+            
+            fig1 = px.pie(final_df, values='count', names='Sentiment', hover_data=['count'], labels={'count': 'count'})
+            fig1.update_traces(textposition='inside', textinfo='percent+label')
+            
+            result = pd.concat([df, sentiment_df], axis=1)
+            result['rating'] = result['rating'].astype(int)
+
+            
+            
+
+            
+            
+            fig2 = px.bar(result, x='Sentiment', y='review_date',
+            hover_data=['rating', 'review_date'], color='rating',
+            labels={'Sentiment':'Sentiment'}, height=400)
+
+            
+
+            fig3 = px.scatter(result, x=df["review_date"], y=df["rating"], color=df["rating"])
+            return sentiment_df, result, fig1, fig2, fig3
+        else:
+            return df, None, None, None, None
+    except Exception as e:
+        st.error(f"An error occurred: {e}")
+        if 'driver' in locals():
+            driver.quit()
+        return None, None, None, None, None
+
+# Streamlit UI
+st.title("Google Maps Reviews Sentiment Analysis")
+
+
+
+
+
+
+if 'url_count' not in st.session_state:
+    st.session_state['url_count'] = 0
+
+max_attempts = 2
+
+def update_url_count():
+    st.session_state['url_count'] += 1
+
+def clear_question():
+    st.session_state["url"] = ""
+
+url = st.text_input("Enter Google Maps Reviews URL:", key="url")
+st.button("Clear question", on_click=clear_question)
+
+
+
+
+
+
+
+if st.button("Sentiment Analysis"):
+    placeholder = st.empty()
+    progress_bar = st.progress(0)
+
+    if st.session_state['url_count'] < max_attempts:
+        if url:
+            sentiment_df, df, fig1, fig2, fig3 = scrape_google_reviews(url)
+            if sentiment_df is not None:
+                st.success("Reviews scraped successfully!")
+                df1 = df[['review_text', 'Sentiment', 'rating', 'review_date']]
+                st.dataframe(df1)
+                
+                tab1, tab2, tab3 = st.tabs(["Pie Chart", "Bar Chart", "Scatter Plot"])
+                if fig1 is not None:
+                    with tab1:
+                        st.plotly_chart(fig1)
+                    if fig2 is not None:
+                        with tab2:
+                            st.plotly_chart(fig2)
+                    if fig3 is not None:
+                        with tab3:
+                            st.plotly_chart(fig3)
+                            placeholder.text("Scrolling complete.")
+                            progress_bar.empty()
+                buf = io.BytesIO()
+                with zipfile.ZipFile(buf, "w") as myzip:
+                    myzip.writestr("Summary of the results.csv", df1.to_csv(index=False))
+                with stylable_container(
+                    key="download_button",
+                    css_styles="""button { background-color: yellow; border: 1px solid black; padding: 5px; color: black; }""",
+                ):
+                        st.download_button(
+                        label="Download zip file",
+                        data=buf.getvalue(),
+                        file_name="zip file.zip",
+                        mime="application/zip",
+                    )
+
+                    
+            else:
+                st.warning("Failed to scrape reviews.")
+            update_url_count()
+        else:
+            st.warning("Please enter a URL.")
+    else:
+        st.warning(f"You have reached the maximum URL attempts ({max_attempts}).")
+
+st.write(f"URL pasted {st.session_state['url_count']} times.")
+
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+       
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