Upload app.py

app.py

@@ -1,13 +1,12 @@
 import gradio as gr
 import os
 import pdfplumber
-from recommender import rank_resumes, summarize_resume_flan, extract_applicant_name
 from docx import Document
+from recommender import rank_resumes, summarize_resume_flan, extract_applicant_name
 
 UPLOAD_FOLDER = "uploads"
 os.makedirs(UPLOAD_FOLDER, exist_ok=True)
 
-
 def process_resumes(job_description, uploaded_files):
     if not job_description.strip():
         return "Please provide a job description.", None
@@ -21,44 +20,54 @@ def process_resumes(job_description, uploaded_files):
 
         ext = filename.lower().split(".")[-1]
 
-        # Save the uploaded file locally first
         file_path = os.path.join(UPLOAD_FOLDER, filename)
-        with open(file_path, "wb") as f:
-            content = uploaded_file.read() if hasattr(uploaded_file, "read") else uploaded_file
-            if isinstance(content, str):
-                content = content.encode("utf-8")
-            f.write(content)
-
-        # Read file content based on extension
-        if ext == "txt":
-            with open(file_path, "r", encoding="utf-8") as f:
-                text = f.read()
-
-        elif ext == "pdf":
-            try:
+        # Save uploaded file to disk
+        try:
+            with open(file_path, "wb") as f:
+                content = uploaded_file.read() if hasattr(uploaded_file, "read") else uploaded_file
+                if isinstance(content, str):
+                    content = content.encode("utf-8")
+                f.write(content)
+        except Exception as e:
+            return f"Failed to save file {filename}: {str(e)}", None
+
+        # Verify file saved correctly
+        if not os.path.exists(file_path):
+            return f"File was not saved correctly: {filename}", None
+        size = os.path.getsize(file_path)
+        print(f"Saved file {filename} size={size} bytes at {file_path}")
+        if size == 0:
+            return f"File {filename} saved but is empty!", None
+
+        # Extract text depending on file type
+        try:
+            if ext == "txt":
+                with open(file_path, "r", encoding="utf-8") as f:
+                    text = f.read()
+
+            elif ext == "pdf":
                 with pdfplumber.open(file_path) as pdf:
                     pages = [page.extract_text() for page in pdf.pages if page.extract_text() is not None]
                     if not pages:
                         return f"No extractable text found in PDF: {filename}. Is it scanned or image-only?", None
                     text = "\n".join(pages)
-            except Exception as e:
-                return f"Failed to process PDF {filename}: {str(e)}", None
 
-        elif ext == "docx":
-            try:
+            elif ext == "docx":
                 doc = Document(file_path)
                 text = "\n".join([p.text for p in doc.paragraphs])
-            except Exception as e:
-                return f"Failed to process DOCX {filename}: {str(e)}", None
 
-        else:
-            return f"Unsupported file format: {filename}", None
+            else:
+                return f"Unsupported file format: {filename}", None
+
+        except Exception as e:
+            return f"Failed to process {ext.upper()} {filename}: {str(e)}", None
 
         resume_texts.append((filename, text))
 
-    # Rank resumes and generate summaries
+    # Rank resumes
     results = rank_resumes(job_description, resume_texts)
 
+    # Generate summaries
     for candidate in results:
         candidate["summary"] = summarize_resume_flan(candidate["text"], job_description)
 
@@ -73,7 +82,6 @@ def process_resumes(job_description, uploaded_files):
 
     return "", table_data
 
-
 with gr.Blocks() as demo:
     gr.Markdown("## Candidate Recommendation Engine")
     with gr.Row():
@@ -88,6 +96,5 @@ with gr.Blocks() as demo:
 
     btn.click(process_resumes, inputs=[job_desc, resumes], outputs=[msg, output_table])
 
-
 if __name__ == "__main__":
     demo.launch()