Update bf_trigger.py

bf_trigger.py

@@ -277,23 +277,17 @@ def get_seo_tags(image_url, topical_map, new_imgs, attempts=0, max_attempts=5):
         keys = ['topic', 'description', 'caption', 'seo', 'alt_tag', 'filename']
         json_dict = ast.literal_eval(response.json()['choices'][0]['message']['content'])
         if json_dict['topic'] not in topic_list:
-            st.write(response.json())
-            st.write('wrong_topic')
             return get_seo_tags(image_path, topical_map, new_imgs, attempts=attempts+1)
         if set(json_dict.keys()) != set(keys):
-            st.write(response.json())
-            st.write('incorrect json formatting')
             return get_seo_tags(image_path, topical_map, new_imgs, attempts=attempts+1)
         
         
         return json_dict
     else:
-        st.write(response.json())
         print("API call failed or bad data, retrying...")
         return get_seo_tags(image_url, topical_map, new_imgs, attempts=attempts + 1)
   except Exception as e:
     print("Exception during API call:", str(e))
-    st.write(response.json())
     return get_seo_tags(image_url, topical_map, new_imgs, attempts=attempts + 1)
 
 # creates the asset in the client's brand folder
@@ -552,10 +546,8 @@ def delete_og_asset(asset_id):
 
   return
 
-def run_preprocess_ai(topical_map, client_name, section_type):
+def run_preprocess_ai(topical_map, client_name, section_type, progress=gr.Progress()):
   section_id = section_key_dict[section_type]
-  status_text = st.empty()
-  status_text.text("Getting Images...")
   headers = {
     'Content-Type': 'application/json',
     'Authorization': brandfolder_api
@@ -578,21 +570,13 @@ def run_preprocess_ai(topical_map, client_name, section_type):
         pre_process_ids.append(asset_names)
   asset_names = sum(pre_process_ids, [])
   
-  progress_text = f"Images are being processed."
-  percent_complete = 0
-  status_text.text(f'{progress_text} 0% completed.')
-  my_bar = st.progress(percent_complete)
   new_imgs = []
-  for i in range(len(asset_names)):
+  for asset_id in progress.tqdm(asset_names, desc="Uploading..."):
     time.sleep(2)
-    asset_id = asset_names[i]
     asset_dict = get_asset_info(asset_id)
     new_img = create_ai_asset(asset_dict, topical_map, client_name, new_imgs)
     new_imgs.append(new_img)
     if new_img:
       delete_og_asset(asset_id)
-    prog = float(i+1)/float(len(asset_names))
-    status_text.text(f'{progress_text} {round(prog*100,2)}% completed.')
-    my_bar.progress(prog)
-  status_text.text(f'AI Algorithm successfuly run!')
+  gr.Info('Images have been processed!')
   return