Update cv_quality.py

cv_quality.py

@@ -1,31 +1,52 @@
 import os
-from langchain_community.document_loaders import CSVLoader, PyMuPDFLoader, Docx2txtLoader
+import requests
+from io import BytesIO
+from langchain_community.document_loaders import PyPDFLoader, Docx2txtLoader, UnstructuredFileLoader
 from dotenv import load_dotenv
 from yolo_text_extraction import pdf_to_text
 
 load_dotenv()
 
 class CV:
-    def __init__(self, file_path):
-        self.file_path = file_path
+    def __init__(self, file_url):
+        self.file_url = file_url
         self.doc_loader = {
-            ".csv": CSVLoader,
-            ".pdf": PyMuPDFLoader,
-            ".docx": Docx2txtLoader
+            ".pdf": PyPDFLoader,
+            ".docx": Docx2txtLoader,
+            ".txt": UnstructuredFileLoader
         }
 
     def get_cv_text(self):
-        _, ext = os.path.splitext(self.file_path)
-        if ext in self.doc_loader:
-            loader = self.doc_loader[ext](self.file_path)
+        # Download the file from Supabase
+        response = requests.get(self.file_url)
+        file_content = BytesIO(response.content)
+        
+        # Determine file extension
+        _, ext = os.path.splitext(self.file_url.split("?")[0])  # Remove query parameters
+        
+        if ext.lower() in self.doc_loader:
+            if ext.lower() == '.pdf':
+                loader = self.doc_loader[ext.lower()](file_content)
+            else:
+                # For non-PDF files, save temporarily and use the appropriate loader
+                with tempfile.NamedTemporaryFile(delete=False, suffix=ext) as temp_file:
+                    temp_file.write(file_content.getvalue())
+                    temp_file_path = temp_file.name
+                
+                loader = self.doc_loader[ext.lower()](temp_file_path)
+            
             data = loader.load()
+            
+            if ext.lower() != '.pdf':
+                os.unlink(temp_file_path)  # Delete the temporary file
+            
             if data:
                 text = "\n".join([page.page_content for page in data])
-                return text if text.strip() else pdf_to_text(self.file_path)
+                return text if text.strip() else pdf_to_text(file_content)
             else:
-                return pdf_to_text(self.file_path)
+                return pdf_to_text(file_content)
         else:
-            return pdf_to_text(self.file_path)
+            return pdf_to_text(file_content)
 
     def analyse_cv_quality(self):
         from cv_analyzer import analyze_cv