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| 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": 0.9, | |
| "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) |