Add

app.py

@@ -11,6 +11,7 @@ from Scheduler import Schedule
 from Evaluator import InterviewEvaluator
 import json
 import os
+import pandas as pd
 # At the top with imports
 from werkzeug.utils import secure_filename
 
@@ -55,9 +56,28 @@ def allowed_file(filename):
     return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
 
 # Add this endpoint (before /parse)
+@app.route("/test-upload", methods=["POST"])
+def test_upload():
+    try:
+        logging.info(f"Test upload - Content type: {request.content_type}")
+        logging.info(f"Test upload - Files: {list(request.files.keys())}")
+        logging.info(f"Test upload - Form data: {list(request.form.keys())}")
+        
+        return jsonify({
+            "content_type": request.content_type,
+            "files": list(request.files.keys()),
+            "form": list(request.form.keys())
+        })
+    except Exception as e:
+        logging.error(f"Test upload error: {str(e)}")
+        return jsonify({"error": str(e)}), 500
+
 @app.route("/upload-candidate-list", methods=["POST"])
 def upload_candidate_list():
     try:
+        logging.info(f"Received request with content type: {request.content_type}")
+        logging.info(f"Request files: {list(request.files.keys())}")
+        
         if 'candidate_list' not in request.files:
             return jsonify({"error": "No CSV file provided"}), 400
         
@@ -70,9 +90,9 @@ def upload_candidate_list():
             # Save as test.csv for the scheduler to use
             filepath = os.path.join('.', 'test.csv')
             file.save(filepath)
+            logging.info(f"Saved CSV file to: {filepath}")
             
             # Validate CSV format
-            import pandas as pd
             try:
                 df = pd.read_csv(filepath)
                 required_columns = ['Name', 'Email']
@@ -83,12 +103,14 @@ def upload_candidate_list():
                         "found_columns": list(df.columns)
                     }), 400
                 
+                logging.info(f"Successfully validated CSV with {len(df)} candidates")
                 return jsonify({
                     "output": f"Successfully uploaded candidate list with {len(df)} candidates",
                     "candidates": len(df)
                 })
                 
             except Exception as e:
+                logging.error(f"CSV validation error: {str(e)}")
                 return jsonify({"error": f"Invalid CSV format: {str(e)}"}), 400
         else:
             return jsonify({"error": "File must be a CSV"}), 400