Update app.py

app.py

@@ -42,8 +42,8 @@ with gr.Blocks(css=css, title="ViPer Demo", theme=gr.themes.Base()) as demo:
     device = "cuda" if torch.cuda.is_available() else "cpu"
 
 
-    word_list_dataset = load_dataset("EPFL-VILAB/4m-wordlist", data_files="list.txt", use_auth_token=True)
-    word_list = word_list_dataset["train"]['text']
+    #word_list_dataset = load_dataset("EPFL-VILAB/4m-wordlist", data_files="list.txt", use_auth_token=True)
+    #word_list = word_list_dataset["train"]['text']
 
     bnb_config = BitsAndBytesConfig(
         load_in_4bit=True,
@@ -255,6 +255,8 @@ with gr.Blocks(css=css, title="ViPer Demo", theme=gr.themes.Base()) as demo:
 
         clear_botton = gr.Button("Clear comments", interactive=len(comments) != 0)
 
+        print(comments)
+
         return (gr.Image(value=comment_images[0], label=f"image {image_index+1}/{len(comment_images)}", show_label=True),
                 gr.Text(label="Comment", show_label=False, lines=4, max_lines=5, placeholder="Enter your comment. The more detailed the better.", value=next_comment, container=False),
                 gr.Button(f"Extract visual preference from {len(comments)} comments", interactive=len(comments) >= 5, variant="primary"),
@@ -301,9 +303,9 @@ with gr.Blocks(css=css, title="ViPer Demo", theme=gr.themes.Base()) as demo:
         if len(comments) < 8:
             gr.Warning("Fewer than 8 comments may lead to errors.")
 
-        keys =  list(comments.keys())
-        random.shuffle(keys)
-        comments = dict([(key, comments[key]) for key in keys])
+        #keys =  list(comments.keys())
+        #random.shuffle(keys)
+        #comments = dict([(key, comments[key]) for key in keys])
 
         prompt = """I will provide a set of artworks along with accompanying comments from a person. Analyze these artworks and the comments on them and identify artistic features such as present or mentioned colors, style, composition, mood, medium, texture, brushwork, lighting, shadow effects, perspective, and other noteworthy elements.
     Your task is to extract the artistic features the person likes and dislikes based on both the artworks' features and the person's comments. Focus solely on artistic aspects and refrain from considering subject matter.
@@ -344,6 +346,8 @@ with gr.Blocks(css=css, title="ViPer Demo", theme=gr.themes.Base()) as demo:
         generated_ids = vpe_model.generate(**inputs, max_new_tokens=2000, repetition_penalty=0.99, do_sample=False)
         generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
+        print(generated_texts)
+
         if re.match(r"(.|\n)*Assistant: Liked Art Features: (.|\n)*Disliked Art Features: (.|\n)*", generated_texts):
             positive_vp, negative_vp = re.search('.* \nAssistant: Liked Art Features: (.*)\nDisliked Art Features: (.*)', generated_texts).groups()
             positive_vp = positive_vp.split(", ")
@@ -505,11 +509,11 @@ with gr.Blocks(css=css, title="ViPer Demo", theme=gr.themes.Base()) as demo:
         if vp_pos == "" and vp_neg == "":
             slider = 0
 
-        for filter in word_list:
-            if re.search(rf"\b{filter}\b", prompt):
-                raise gr.Error("Please try again with a different prompt")
-            if re.search(rf"\b{filter}\b", vp_pos) or re.search(rf"\b{filter}\b", vp_neg):
-                raise gr.Error("Please try again with a different visual preference")
+        #for filter in word_list:
+        #    if re.search(rf"\b{filter}\b", prompt):
+        #        raise gr.Error("Please try again with a different prompt")
+        #    if re.search(rf"\b{filter}\b", vp_pos) or re.search(rf"\b{filter}\b", vp_neg):
+        #        raise gr.Error("Please try again with a different visual preference")
 
         if vp_pos != "":
             vp_pos = vp_pos.split(", ")