Create app.py

app.py

@@ -0,0 +1,89 @@
+import gradio as gr
+import requests
+import os 
+
+##Bloom Inference API
+API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
+HF_TOKEN = os.environ["HF_TOKEN"]
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+
+def text_generate(prompt, generated_txt): 
+  #Prints to debug the code
+  print(f"*****Inside text_generate - Prompt is :{prompt}")
+  
+  json_ = {"inputs": prompt,
+            "parameters":
+            {
+            "top_p": 0.8,
+          "temperature": 1.1,
+          "max_new_tokens": 128,
+          "return_full_text": True,
+          "do_sample":False,
+          }, 
+          "options": 
+          {"use_cache": False,
+          "wait_for_model": True,
+          },}
+  response = requests.post(API_URL, headers=headers, json=json_)
+  print(f"Response  is : {response}")
+  output = response.json()
+  print(f"output is : {output}") 
+  output_tmp = output[0]['generated_text']
+  print(f"output_tmp is: {output_tmp}")
+  solution = output_tmp.split("\nQ:")[0]   
+  print(f"Final response after splits is: {solution}")
+  if '\nOutput:' in solution:
+    final_solution = solution.split("\nOutput:")[0] 
+    print(f"Response after removing output is: {final_solution}")
+  elif '\n\n' in solution:
+    final_solution = solution.split("\n\n")[0] 
+    print(f"Response after removing new line entries is: {final_solution}")
+  else:
+    final_solution = solution
+  
+  
+  if len(generated_txt) == 0 :
+    display_output = final_solution
+  else:
+    display_output = generated_txt[:-len(prompt)] + final_solution
+  new_prompt = final_solution[len(prompt):]
+  print(f"new prompt for next cycle is : {new_prompt}")
+  print(f"display_output for printing on screen is : {display_output}")
+  if len(new_prompt) == 0:
+    temp_text = display_output[::-1]
+    print(f"What is the last character of sentence? : {temp_text[0]}")
+    if temp_text[1] == '.':
+      first_period_loc = temp_text[2:].find('.') + 1
+      print(f"Location of last Period is: {first_period_loc}")
+      new_prompt = display_output[-first_period_loc:-1]
+      print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")
+    else:
+      print("HERE")
+      first_period_loc = temp_text.find('.')
+      print(f"Location of last Period is : {first_period_loc}")
+      new_prompt = display_output[-first_period_loc:-1]
+      print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")
+    display_output = display_output[:-1]
+    
+  return display_output, new_prompt  
+
+
+demo = gr.Blocks()
+
+with demo:
+  gr.Markdown("<h1><center>Write Stories Using Bloom</center></h1>")
+  gr.Markdown(
+        """This is my playground to test Marathi and Hindi Text Generation""
+        )
+  with gr.Row():
+    input_prompt = gr.Textbox(label="Write some text to get started...", lines=3, value="क्षितिजावर नजर जाईल तिथें")  
+    
+  with gr.Row():
+    generated_txt = gr.Textbox(lines=25, visible = True)
+  
+  b1 = gr.Button("Generate Your Story")
+
+  b1.click(text_generate, inputs=[input_prompt, generated_txt], outputs=[generated_txt, input_prompt]) 
+
+demo.launch(enable_queue=True, debug=True)