update

app.py

@@ -31,15 +31,18 @@ A: Let’s think step by step.
 """
 
 
-def text_generate(problem, template): #prompt
+def text_generate(problem, template, prompt):
   
   #prints to debug
   print(f"*****Inside text_generate function******")
-  #print(f"Prompt is :{prompt}")
   print(f"Problem is :{problem}")
   print(f"Template is :{template}")
+  print(f"Prompt is :{prompt}")
   
-  p = problem + "A: " + template #+ "\n"
+  if len(problem) == 0 and len(template) == 0:
+    p = prompt
+  else:
+    p = problem + "A: " + template #+ "\n"
   print(f"Final prompt is : {p}")
   json_ = {"inputs": p,
             "parameters":
@@ -66,21 +69,22 @@ demo = gr.Blocks()
 with demo:
   gr.Markdown("<h1><center>Step By Step With Bloom</center></h1>")
   gr.Markdown(
-        """ [BigScienceW Bloom](https://twitter.com/BigscienceW) \n\n Large language models have demonstrated a capability of 'Chain-of-thought reasoning'. A group of amazing researchers( [Jason Wei et al.](https://arxiv.org/abs/2205.11916)) recently found out that by adding **Lets think step by step** it improves the model's zero-shot performance. Some might say — You can get good results out of LLMs if you know how to speak to them. This space is an attempt at inspecting this LLM behavior/capability in the new HuggingFace BigScienceW [Bloom](https://huggingface.co/bigscience/bloom) model. \n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma) for EuroPython 2022 Demo.\nThis Space might sometime fail due to inference queue being full and logs would end up showing error as *queue full, try again later*, don't despair and try again after some time. I would try and improve the app as well over next couple days."""
+        """ APOLOGIES WIP FIXING SOMETHING. [BigScienceW Bloom](https://twitter.com/BigscienceW) \n\n Large language models have demonstrated a capability of 'Chain-of-thought reasoning'. A group of amazing researchers( [Jason Wei et al.](https://arxiv.org/abs/2205.11916)) recently found out that by adding **Lets think step by step** it improves the model's zero-shot performance. Some might say — You can get good results out of LLMs if you know how to speak to them. This space is an attempt at inspecting this LLM behavior/capability in the new HuggingFace BigScienceW [Bloom](https://huggingface.co/bigscience/bloom) model. \n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma) for EuroPython 2022 Demo.\nThis Space might sometime fail due to inference queue being full and logs would end up showing error as *queue full, try again later*, don't despair and try again after some time. I would try and improve the app as well over next couple days."""
         )
   with gr.Row():
 
     #example_prompt = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step.\n", "Q: Roger has 5 tennis balls already. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\nA: Let’s think step by step.\n", "Q: On an average Joe throws 25 punches per minute. His fight lasts 5 rounds of 3 minutes each. How many punches did he throw?\nA:  Let’s think about this logically.\n"], label= "Choose a sample Prompt")
 
-    example_problem = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\n", "Q: Roger has 5 tennis balls already. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\n", "Q: On an average Joe throws 25 punches per minute. His fight lasts 5 rounds of 3 minutes each. How many punches did he throw?\n"], label= "Choose a sample Problem")
+    example_problem = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\n", "Q: Roger has 5 tennis balls already. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\n", "Q: On an average Joe throws 25 punches per minute. His fight lasts 5 rounds of 3 minutes each. How many punches did he throw?\n"], label= "Choose a sample Problem and corresponding Tempplate for Zero-Shot CoT:")
 
-    example_template = gr.Radio( ["Let’s think step by step.\n"," First, ", " Let’s think about this logically.\n", "Let’s solve this problem by splitting it into steps.\n", " Let’s be realistic and think step by step.\n", "Let’s think like a detective step by step.\n", "Let’s think ", "Before we dive into the answer, ", "The answer is after the proof.\n"], label= "Choose a sample Template for Zero-Shot CoT")
+    example_template = gr.Radio( ["Let’s think step by step.\n"," First, ", " Let’s think about this logically.\n", "Let’s solve this problem by splitting it into steps.\n", " Let’s be realistic and think step by step.\n", "Let’s think like a detective step by step.\n", "Let’s think ", "Before we dive into the answer, ", "The answer is after the proof.\n"], label= "Choose a sample Problem and corresponding Template for Zero-Shot CoT:")
 
-    #input_word = gr.Textbox(placeholder="Enter a word here to generate text ...")
     generated_txt = gr.Textbox(lines=10)
- 
+
+  with gr.Row(): 
+    input_prompt = gr.Textbox(placeholder="Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step.\n", label="Or don't select from above examples and just enter your own prompt drawing from the above examples and submit... ")
   
   b1 = gr.Button("Generate Text")
-  b1.click(text_generate,inputs=[example_problem, example_template], outputs=generated_txt) #example_prompt
+  b1.click(text_generate,inputs=[example_problem, example_template, input_prompt], outputs=generated_txt) #example_prompt
  
 demo.launch(enable_queue=True, debug=True)