EuroPython2022/Write-Stories-Using-Bloom
22
1import gradio as gr2import requests3import os 4 5##Bloom Inference API6API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"7HF_TOKEN = os.environ["HF_TOKEN"]8headers = {"Authorization": f"Bearer {HF_TOKEN}"}9 10 11def text_generate(prompt, generated_txt): 12 #Prints to debug the code13 print(f"*****Inside text_generate - Prompt is :{prompt}")14 json_ = {"inputs": prompt,15 "parameters":16 {17 "top_p": 0.9,18 "temperature": 1.1,19 #"max_new_tokens": 64,20 "return_full_text": True,21 "do_sample":True,22 }, 23 "options": 24 {"use_cache": True,25 "wait_for_model": True,26 },}27 response = requests.post(API_URL, headers=headers, json=json_)28 print(f"Response is : {response}")29 output = response.json()30 print(f"output is : {output}") 31 output_tmp = output[0]['generated_text']32 print(f"output_tmp is: {output_tmp}")33 solution = output_tmp.split("\nQ:")[0] 34 print(f"Final response after splits is: {solution}")35 if '\nOutput:' in solution:36 final_solution = solution.split("\nOutput:")[0] 37 print(f"Response after removing output is: {final_solution}")38 elif '\n\n' in solution:39 final_solution = solution.split("\n\n")[0] 40 print(f"Response after removing new line entries is: {final_solution}")41 else:42 final_solution = solution43 44 45 if len(generated_txt) == 0 :46 display_output = final_solution47 else:48 display_output = generated_txt[:-len(prompt)] + final_solution49 new_prompt = final_solution[len(prompt):]50 print(f"new prompt for next cycle is : {new_prompt}")51 print(f"display_output for printing on screen is : {display_output}")52 if len(new_prompt) == 0:53 temp_text = display_output[::-1]54 print(f"What is the last character of sentence? : {temp_text[0]}")55 if temp_text[1] == '.':56 first_period_loc = temp_text[2:].find('.') + 157 print(f"Location of last Period is: {first_period_loc}")58 new_prompt = display_output[-first_period_loc:-1]59 print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")60 else:61 print("HERE")62 first_period_loc = temp_text.find('.')63 print(f"Location of last Period is : {first_period_loc}")64 new_prompt = display_output[-first_period_loc:-1]65 print(f"Not sending blank as prompt so new prompt for next cycle is : {new_prompt}")66 display_output = display_output[:-1]67 68 return display_output, new_prompt 69 70 71demo = gr.Blocks()72 73with demo:74 gr.Markdown("<h1><center>Write Stories Using Bloom</center></h1>")75 gr.Markdown(76 """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."""77 )78 with gr.Row():79 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.") 80 81 with gr.Row():82 generated_txt = gr.Textbox(lines=7, visible = True)83 84 b1 = gr.Button("Generate Your Story")85 86 b1.click(text_generate, inputs=[input_prompt, generated_txt], outputs=[generated_txt, input_prompt]) 87 88demo.launch(enable_queue=True, debug=True)