Update app.py

app.py

@@ -3,6 +3,7 @@ import os
 from cv_analyzer import analyze_cv
 from cv_quality import CV
 from get_supabase import Supabase
+from datetime import datetime
 
 st.set_page_config(page_title="CV Analyzer", layout="wide")
 st.title('CV Analyzer')
@@ -10,61 +11,69 @@ st.title('CV Analyzer')
 # Initialize Supabase client
 supabase_client = Supabase().init_supabase_client()
 
+# Supabase storage details
+BUCKET_NAME = "CVs UX"
+SUPABASE_PROJECT_ID = "abjtqzgnrtsikkqgnqeg"
+
 uploaded_file = st.file_uploader("Choose a CV file", type=['pdf', 'docx', 'txt'])
 
 if uploaded_file is not None:
     with st.spinner('Uploading and analyzing CV...'):
         # Upload file to Supabase storage
-        file_path = f"cvs/{uploaded_file.name}"
-        supabase_client.storage.from_("cvs").upload(file_path, uploaded_file.getvalue())
+        file_path = f"{uploaded_file.name}"
         
-        # Get the public URL of the uploaded file
-        file_url = supabase_client.storage.from_("cvs").get_public_url(file_path)
+        with uploaded_file as f:
+            supabase_client.storage.from_(BUCKET_NAME).upload(
+                file=f,
+                path=file_path,
+                file_options={"cache-control": "3600", "upsert": "true"}
+            )
+
+        # Construct the public URL of the uploaded file
+        timestamp = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%S.%fZ")
+        file_url = f"https://{SUPABASE_PROJECT_ID}.supabase.co/storage/v1/object/public/{BUCKET_NAME}/{file_path}?t={timestamp}"
 
         # Create CV object with the file URL
         cv = CV(file_url)
         result = cv.analyse_cv_quality()
 
-        # Optionally, delete the file after analysis
-        # supabase_client.storage.from_("cvs").remove([file_path])
+        if "error" in result:
+            st.error(result["error"])
+        else:
+            # Display results
+            # Personal Information
+            st.header("Personal Information")
+            personal_info = result["personal_info"]
+            st.json(personal_info)
+            st.write(f"Personal Information Score: {personal_info['personal_info_score']}")
 
-    if "error" in result:
-        st.error(result["error"])
-    else:
-        # Display results (same as before)
-        # Personal Information
-        st.header("Personal Information")
-        personal_info = result["personal_info"]
-        st.json(personal_info)
-        st.write(f"Personal Information Score: {personal_info['personal_info_score']}")
+            # Detected Sections
+            st.header("Detected Sections")
+            st.write(result["detected_sections"])
+            st.write(f"Section Detection Score: {result['section_detection_score']}")
 
-        # Detected Sections
-        st.header("Detected Sections")
-        st.write(result["detected_sections"])
-        st.write(f"Section Detection Score: {result['section_detection_score']}")
+            # Spelling and Grammar
+            st.header("Spelling and Grammar")
+            st.write(f"Error Percentage: {result['spelling_grammar_error_percentage']:.2f}%")
+            st.write(f"Spelling and Grammar Score: {result['spelling_grammar_score']}")
 
-        # Spelling and Grammar
-        st.header("Spelling and Grammar")
-        st.write(f"Error Percentage: {result['spelling_grammar_error_percentage']:.2f}%")
-        st.write(f"Spelling and Grammar Score: {result['spelling_grammar_score']}")
+            # Content Quality Analysis
+            st.header("Content Quality Analysis")
+            for section, evaluation in result['content_analysis'].items():
+                st.subheader(section.capitalize())
+                st.json(evaluation)
 
-        # Content Quality Analysis
-        st.header("Content Quality Analysis")
-        for section, evaluation in result['content_analysis'].items():
-            st.subheader(section.capitalize())
-            st.json(evaluation)
-        
-        st.write(f"Overall Content Quality Score: {result['overall_score']:.2f} / 10")
+            st.write(f"Overall Content Quality Score: {result['overall_score']:.2f} / 10")
 
-        # Total Score
-        st.header("Total CV Score")
-        total_score = (
-            personal_info['personal_info_score'] +
-            result['section_detection_score'] +
-            result['spelling_grammar_score'] +
-            result['overall_score']
-        )
-        st.write(f"Total Score: {total_score:.2f}")
+            # Total Score
+            st.header("Total CV Score")
+            total_score = (
+                personal_info['personal_info_score'] +
+                result['section_detection_score'] +
+                result['spelling_grammar_score'] +
+                result['overall_score']
+            )
+            st.write(f"Total Score: {total_score:.2f}")
 
 if __name__ == "__main__":
     st.sidebar.title("About")