Upload app.py

app.py

@@ -5,11 +5,11 @@
 # - https://huggingface.co/EnglishVoice/t5-base-keywords-to-headline?text=diabetic+diet+plan
 # - Apache 2.0
 
+# In[7]:
+
 
 import torch
 from transformers import T5ForConditionalGeneration,T5Tokenizer
-import gradio as gr
-
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
@@ -17,26 +17,36 @@ model = T5ForConditionalGeneration.from_pretrained("EnglishVoice/t5-base-keyword
 tokenizer = T5Tokenizer.from_pretrained("EnglishVoice/t5-base-keywords-to-headline", clean_up_tokenization_spaces=True, legacy=False)
 model = model.to(device)
 
-def title_gen(keywords):
 
+
+# In[37]:
+
+
+def title_gen(keywords, diversity, temp):
+
+ if keywords!= "":
     text =  "headline: " + keywords
     encoding = tokenizer.encode_plus(text, return_tensors = "pt")
     input_ids = encoding["input_ids"].to(device)
     attention_masks = encoding["attention_mask"].to(device)
+    
+    if diversity:
+            num_beams = 20,
+            num_beam_groups = 20,
+            diversity_penalty=0.8,
+            early_stopping = True,
+    else:
+             penalty_alpha = 0.8,
+     
     beam_outputs = model.generate(
         input_ids = input_ids,
         attention_mask = attention_masks,
         max_new_tokens = 30,
         do_sample = True,
         num_return_sequences = 5,
-        temperature = 1.2,
-        #num_beams = 20,
-        #num_beam_groups = 20,
-        #diversity_penalty=0.8,
-        no_repeat_ngram_size = 3,
-        penalty_alpha = 0.8,
-        #early_stopping = True,
+        temperature = temp,
         top_k = 15,
+        no_repeat_ngram_size = 3,
         #top_p = 0.60,
     )
 
@@ -44,24 +54,78 @@ def title_gen(keywords):
     
     for i in range(len(beam_outputs)):
         result = tokenizer.decode(beam_outputs[i], skip_special_tokens=True)
-        titles += f"<h3>{result}<br>" #Create string with all the titles and a <br> tag for line break
+        titles += f"<p align=center><b>{result}</b></p>" #Create string with titles and <br> tag for html reading in gradio html
     
     return titles
 
 
+# In[8]:
+
+
+import gradio as gr
+
+
+# In[40]:
+
 
 iface = gr.Interface(fn=title_gen, 
-                     inputs=[gr.Textbox(label="Paste 2 or more keywords searated by a comma.", lines=1), "checkbox", gr.Slider(0.1, 2, 0.8)],
-                     outputs=[gr.HTML(label="Titles:")],
+                     inputs=[gr.Textbox(label="Paste one or more keywords searated by a comma and hit 'Submit'.", lines=1), "checkbox", gr.Slider(0.1, 1.9, 1.2)],
+                     outputs=[gr.HTML(label="Title suggestions:")],
                      title="AI Keywords to Title Generator", 
-                     description="Turn keywords into creative suggestions",
-                     article="<div align=left><h1>AI Creative Title Generator</h1><li>With just keywords, generate a list of creative titles.</li><li>Click on Submit to generate more creative and diverse titles.</li><p>AI Model:<br><li>T5 Model trained on a dataset of titles and related keywords</li><li>Original model id: EnglishVoice/t5-base-keywords-to-headline by English Voice AI Labs</li></p><p>Default parameter details:<br><li>Temperature = 1.2, no_repeat_ngram_size=3, top_k = 15, penalty_alpha = 0.8, max_new_tokens = 30</li></div>",
+                     #description="Turn keywords into creative suggestions",
+                     article="<div align=left><h1>AI Creative Title Generator</h1><li>With just keywords, generate a list of creative titles.</li><li>Click on Submit to generate more title options.</li><li>Tweak slider for less or more creative titles</li><li>Check 'diversity' to turn on diversity beam search</li><p>AI Model:<br><li>T5 Model trained on a dataset of titles and related keywords</li><li>Original model id: EnglishVoice/t5-base-keywords-to-headline by English Voice AI Labs</li></p><p>Default parameter details:<br><li>Temperature = 1.2, no_repeat_ngram_size=3, top_k = 15, penalty_alpha = 0.8, max_new_tokens = 30</li><p>Diversity beam search params:<br><li>num_beams=20, diversity_penalty=0.8, num_beam_groups=20</li></div>",
                      flagging_mode='never'
                     )
 
 iface.launch()
 
 
-
-
+# In[ ]:
+
+
+'''
+#Create a four button panel for changing parameters with one click
+
+def fn(text):
+    return ("Hello gradio!")
+
+with gr.Blocks () as demo:
+
+    with gr.Row(variant='compact') as PanelRow1: #first row: top
+        
+        with gr.Column(scale=0, min_width=180) as PanelCol5:
+            gr.HTML("")
+        with gr.Column(scale=0) as PanelCol4:
+            submit = gr.Button("Temp++", scale=0)
+        with gr.Column(scale=1) as PanelCol5:
+            gr.HTML("")
+        
+       
+    with gr.Row(variant='compact') as PanelRow2: #2nd row: left, right, middle
+
+        with gr.Column(min_width=100) as PanelCol1:
+            submit = gr.Button("Contrastive")
+        with gr.Column(min_width=100) as PanelCol2:
+            submit = gr.Button("Re-generate")
+        with gr.Column(min_width=100) as PanelCol3:
+            submit = gr.Button("Diversity Beam")
+        
+        with gr.Column(min_width=100) as PanelCol5:
+            gr.HTML("")
+        with gr.Column(min_width=100) as PanelCol5:
+            gr.HTML("")
+        with gr.Column(scale=0) as PanelCol5:
+            gr.HTML("")
+            
+    with gr.Row(variant='compact') as PanelRow3: #last row: down
+        with gr.Column(scale=0, min_width=180) as PanelCol7:
+            gr.HTML("")
+        with gr.Column(scale=1) as PanelCol6:
+            submit = gr.Button("Temp--", scale=0)
+            
+        with gr.Column(scale=0) as PanelCol5:
+            gr.HTML("")
+
+demo.launch()
+'''