Update app.py

app.py

@@ -19,27 +19,27 @@ from PyPDF2 import PdfReader
 from gliner import GLiNER
 
 txt = st.text_area("Job description")
+data1 = pd.Series(txt, index = ["Job Description"])
+st.dataframe(data1)
 
 uploaded_files = st.file_uploader(
     "Choose a PDF file(s) and job description as pdf", accept_multiple_files=True, type="pdf"
 )
 
-if uploaded_files:
-    all_data = []  # Store dictionaries of text and entities for each PDF
-    for i, uploaded_file in enumerate(uploaded_files):
-        try:
-            pdf_reader = PdfReader(uploaded_file)
-            text_data = ""
-            for page in pdf_reader.pages:
-                text_data += page.extract_text()
+for uploaded_file in uploaded_files:
+    all_data = []  
+    pdf_reader = PdfReader(uploaded_file)
+    text_data = ""
+    for page in pdf_reader.pages:
+        text_data += page.extract_text()
 
-            model = GLiNER.from_pretrained("urchade/gliner_base")
-            labels = ["person", "country", "organization", "time", "role"]
-            entities = model.predict_entities(text_data, labels)
+        model = GLiNER.from_pretrained("urchade/gliner_base")
+        labels = ["person", "country", "organization", "time", "role"]
+        entities = model.predict_entities(text_data, labels)
 
-            entity_dict = {}
-            for label in labels:
-                entity_dict[label] = [entity["text"] for entity in entities if entity["label"] == label]
+        entity_dict = {}
+        for label in labels:
+            entity_dict[label] = [entity["text"] for entity in entities if entity["label"] == label]
 
             data = {"Text": text_data, **entity_dict}
 
@@ -48,17 +48,14 @@ if uploaded_files:
             
             all_data.append(data)
 
-        except Exception as e:
-            st.error(f"Error processing file {uploaded_file.name}: {e}")
+       
 
     
     if all_data:
         df = pd.DataFrame(all_data)
         st.dataframe(df)
         
-        data1 = pd.Series(txt, index = ["Job Description"])
-        result = pd.concat([df, data1], axis=1, ignore_index=True)
-        st.dataframe(result)
+