Update pages/Report_Writer.py

pages/Report_Writer.py

@@ -9,7 +9,7 @@ from llama_index.embeddings.fastembed import FastEmbedEmbedding
 import google.generativeai as genai
 import os
 import PyPDF2
-import streamlit_analytics2 as streamlit_analytics
+#import streamlit_analytics2 as streamlit_analytics
 
 
 # Set up Google API key
@@ -92,40 +92,39 @@ def main():
     st.title("AI Report Writer")
     st.write("Upload your document and our AI will generate a comprehensive report based on its contents!")
 
-    with streamlit_analytics.track():
 
-    # File uploader
-        uploaded_file = st.file_uploader("Choose a file (PDF or TXT)", type=["txt", "pdf"])
-        
-        # Report format input
-        report_format = st.text_area("Enter the desired report format (optional)", height=150, 
-                                     help="Leave blank to use a default template")
-        
-        # Additional information input
-        additional_info = st.text_area("Enter any additional information or context for the report", height=100)
+# File uploader
+    uploaded_file = st.file_uploader("Choose a file (PDF or TXT)", type=["txt", "pdf"])
     
-        if uploaded_file is not None:
-            # Read file contents
-            if uploaded_file.type == "application/pdf":
-                pdf_reader = PyPDF2.PdfReader(uploaded_file)
-                document_text = ""
-                for page in pdf_reader.pages:
-                    document_text += page.extract_text()
-            else:
-                document_text = uploaded_file.getvalue().decode("utf-8")
+    # Report format input
+    report_format = st.text_area("Enter the desired report format (optional)", height=150, 
+                                 help="Leave blank to use a default template")
     
-            if st.button("Generate Report"):
-                st.write("Analyzing document and generating report...")
-    
-                # Load data and generate report
-                doc_list = document_text.split(".")
-                index = load_data(document_text)
-                report = generate_report(index, report_format, additional_info)
-    
-                st.write("## Generated Report")
-                st.write(report)
+    # Additional information input
+    additional_info = st.text_area("Enter any additional information or context for the report", height=100)
+
+    if uploaded_file is not None:
+        # Read file contents
+        if uploaded_file.type == "application/pdf":
+            pdf_reader = PyPDF2.PdfReader(uploaded_file)
+            document_text = ""
+            for page in pdf_reader.pages:
+                document_text += page.extract_text()
         else:
-            st.warning("Please upload a file to generate a report.")
+            document_text = uploaded_file.getvalue().decode("utf-8")
+
+        if st.button("Generate Report"):
+            st.write("Analyzing document and generating report...")
+
+            # Load data and generate report
+            doc_list = document_text.split(".")
+            index = load_data(document_text)
+            report = generate_report(index, report_format, additional_info)
+
+            st.write("## Generated Report")
+            st.write(report)
+    else:
+        st.warning("Please upload a file to generate a report.")
 
 if __name__ == "__main__":
     main()