Update app.py

app.py

@@ -272,11 +272,15 @@ def get_files_with_ingredient_info(ingredient, N=1):
     #Find embedding for title of all files
     global embeddings_titles
     #Apply cosine similarity between embedding of ingredient name and title of all files
-    file_paths = find_relevant_file_paths(ingredient, embeddings_titles)
+    file_paths_abs = find_relevant_file_paths(ingredient, embeddings_titles)
     #Fine top N titles that are the most similar to the ingredient's name
     #Find file names for those titles
-    if len(file_paths) == 0:
+    if len(file_paths_abs) == 0:
         file_paths.append("Ingredients.docx")
+    else:
+        for file_path in file_paths_abs:
+            file_paths.append(f"articles/{file_path}")
+            
     return file_paths
     
 def get_assistant_for_ingredient(ingredient, N=2):
@@ -297,6 +301,8 @@ def get_assistant_for_ingredient(ingredient, N=2):
     
     # Ready the files for upload to OpenAI.     
     file_paths = get_files_with_ingredient_info(ingredient, N)
+    print(f"DEBUG : Creating vector store for files {file_paths}")
+    
     file_streams = [open(path, "rb") for path in file_paths]
     
     # Use the upload and poll SDK helper to upload the files, add them to the vector store,