Update app.py

app.py

@@ -1,88 +1,16 @@
-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["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"]
-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": 0.9,
-          "temperature": 1.1,
-          #"max_new_tokens": 64,
-          "return_full_text": True,
-          "do_sample":True,
-          }, 
-          "options": 
-          {"use_cache": True,
-          "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(
-        """Bloom is a model by [HuggingFace](https://huggingface.co/bigscience/bloom) and a team of more than 1000 researchers coming together as [BigScienceW Bloom](https://twitter.com/BigscienceW).\n\nLarge language models have demonstrated a capability of producing coherent sentences and given a context we can pretty much decide the *theme* of generated text.\n\nHow to Use this App: Use the sample text given as prompt or type in a new prompt as a starting point of your awesome story! Just keep pressing the 'Generate Text' Button and go crazy!\n\nHow this App works: This app operates by feeding back the text generated by Bloom to itself as a Prompt for next generation round and so on. Currently, due to size-limits on Prompt and Token generation, we are only able to feed very limited-length text as Prompt and are getting very few tokens generated in-turn. This makes it difficult to keep a tab on theme of text generation, so please bear with that. In summary, I believe it is a nice little fun App which you can play with for a while.\n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma) for EuroPython 2022 Demo."""
-        )
-  with gr.Row():
-    input_prompt = gr.Textbox(label="Write some text to get started...", lines=3, value="Dear human philosophers, I read your comments on my abilities and limitations with great interest.")  
-    
-  with gr.Row():
-    generated_txt = gr.Textbox(lines=7, 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)
+async function query(data) {
+	const response = await fetch(
+		"https://api-inference.huggingface.co/models/bigscience/bloom",
+		{
+			headers: { Authorization: "Bhf_RryCjUQHSqwobWXNyvzUWdEYdHxizZDLZlxxxxxx" },
+			method: "POST",
+			body: JSON.stringify(data),
+		}
+	);
+	const result = await response.json();
+	return result;
+}
+
+query({"inputs": "Can you please let us know more details about your "}).then((response) => {
+	console.log(JSON.stringify(response));
+});