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| import gradio as gr | |
| import openai | |
| import re | |
| import random | |
| import os | |
| openai.api_key = os.environ["OAI_key"] | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| dialog_tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large") | |
| dialog_model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large") | |
| # Latent Diffusion | |
| latent_diff_interface = gr.Interface.load("spaces/multimodalart/latentdiffusion", api_key="secret", enable_queue=True) | |
| # Background Remover | |
| background_remove_interface = gr.Interface.load("spaces/nateraw/background-remover", api_key="secret", enable_queue=True) | |
| def is_generate_image(input): | |
| """ Return True if user wants to generate an image """ | |
| response = openai.Completion.create( | |
| engine="text-davinci-002", | |
| prompt="Prompt: Generate an image of a lion.\nQuestion: Generate an image? True or False?\nAnswer:True.\n\nPrompt: Remove background of the image.\nQuestion: Generate an image? True or False?\nAnswer:False.\n\nPrompt:" + input + "\nQuestion: Generate an image? True or False\nAnswer:", | |
| temperature=0.7, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| response = re.sub(r'[^A-Za-z]', '', response["choices"][-1]["text"]) | |
| return response | |
| def generate_image(input): | |
| """ Generate image using latent diffusion from the input prompt """ | |
| # Find out what image to generate? | |
| input_prompt = openai.Completion.create( | |
| engine="text-davinci-002", | |
| prompt="Input: Generate an image of a \"lion\"\nQuestion: What is the prompt for image generation?\nAnswer: lion\n\nInput: I am feeling good. Please send me an image of the sky with mountains by Greg Rutkowski.\nQuestion: What is the prompt for image generation?\nAnswer: sky with mountains by Greg Rutkowski\n\nInput: " + input + "\nQuestion: What is the prompt for image generation?\nAnswer:", | |
| temperature=0.7, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| text_prompt_for_image = input_prompt["choices"][-1]["text"] | |
| image_output = latent_diff_interface(text_prompt_for_image,45,256,256,1,5) | |
| text_response_for_image = "Generated image for: " + text_prompt_for_image | |
| return image_output[0], text_response_for_image | |
| def remove_background(input, generated_image=None, generate_image_flag="False"): | |
| # Check if user is asking for removing background. | |
| response = openai.Completion.create( | |
| engine="text-davinci-002", | |
| prompt="Prompt: remove background.\nQuestion: Remove the background? True or False?\nAnswer: True\n\nPrompt: Remove the background of image.\nQuestion: Remove the background? True or False?\nAnswer: True\n\nPrompt: " + input + "\nQuestion: Remove the background? True or False?\nAnswer:", | |
| temperature=0.7, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| response = re.sub(r'[^A-Za-z]', '', response["choices"][-1]["text"]) | |
| if response == str(True) and generated_image != None: | |
| # Remove background | |
| rb_image_output = background_remove_interface(generated_image, 100) | |
| else: | |
| rb_image_output = None | |
| return rb_image_output | |
| def random_HF_space(input): | |
| response = openai.Completion.create( | |
| engine="text-davinci-002", | |
| prompt="User: I am feeling bored.\nQuestion: Is the user bored? True or False?\nAnswer: True\n\nUser: " + input + "\nQuestion: Is the user bored? True or False?\nAnswer:", | |
| temperature=0.7, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| spaces_list = ["<a href='https://huggingface.co/spaces/akhaliq/AnimeGANv2' target='_blank'> Click here for a suprise space </a>", | |
| "<a href='https://huggingface.co/spaces/dalle-mini/dalle-mini' target='_blank'> Click here for a suprise space </a>", | |
| "<a href='https://huggingface.co/spaces/lfqa/lfqa' target='_blank'> Click here for a suprise space </a>", | |
| "<a href='https://huggingface.co/spaces/ronvolutional/ai-pokemon-card' target='_blank'> Click here for a suprise space </a>", | |
| "<a href='https://huggingface.co/spaces/flax-community/chef-transformer' target='_blank'> Click here for a suprise space </a>", | |
| "<a href='https://huggingface.co/spaces/osanseviero/draw_to_search' target='_blank'> Click here for a suprise space </a>"] | |
| response = re.sub(r'[^A-Za-z]', '', response["choices"][-1]["text"]) | |
| if response == str(True): | |
| response = spaces_list[random.randint(0,5)] | |
| else: | |
| response = None | |
| return response | |
| def DialogGPT(input, history=[], text_response_for_image = None): | |
| new_user_input_ids = dialog_tokenizer.encode(input + dialog_tokenizer.eos_token, return_tensors='pt') | |
| bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1) | |
| if text_response_for_image != None: | |
| text_response_for_image = dialog_tokenizer.encode(text_response_for_image + dialog_tokenizer.eos_token, return_tensors='pt') | |
| history = torch.cat([bot_input_ids, text_response_for_image], dim=-1).tolist() | |
| else: | |
| history = dialog_model.generate(bot_input_ids, max_length=1000, pad_token_id=dialog_tokenizer.eos_token_id).tolist() | |
| response = dialog_tokenizer.decode(history[0]).split("<|endoftext|>") | |
| response = [(response[i], response[i+1]) for i in range(0, len(response)-1, 2)] | |
| return response, history | |
| def predict(input, history=[]): | |
| rs_output = None | |
| generated_image = None | |
| generated_text = None | |
| if len(history)>1: | |
| previously_generated_image = history[-1][0] | |
| previously_generated_image_flag = history[-2][0] | |
| history = [history[-3]] | |
| # Check if user is asking for removing background | |
| generated_image = remove_background(input, previously_generated_image, previously_generated_image_flag) | |
| if generated_image != None: | |
| # Output as per removed background | |
| text_response_for_image = "Background removed." | |
| generated_text, history = DialogGPT(input, history, text_response_for_image) | |
| else: | |
| # Check if user is asking for generating image | |
| generate_image_flag = is_generate_image(input) | |
| if generate_image_flag == str(True): | |
| # Generate Image | |
| generated_image, text_response_for_image = generate_image(input) | |
| generated_text, history = DialogGPT(input, history, text_response_for_image) | |
| # Append history with generated image and generated image flag | |
| history.append([generate_image_flag]) | |
| history.append([generated_image]) | |
| else: | |
| # Check if user is bored | |
| rs_output = random_HF_space(input) | |
| if rs_output != None: | |
| # Output as per random space | |
| rs_text_input = "Try out the below space" | |
| generated_text, history = DialogGPT(input, history, rs_text_input) | |
| else: | |
| # Dialog GPT output | |
| generated_text, history = DialogGPT(input, history) | |
| return generated_text, history, rs_output, generated_image | |
| examples = [['Who is Elon Musk?'],['Generate an image of horse running in grassland.'], ['Remove the background of the image.'], ['I am bored.']] | |
| description = "Combines the sanity of Langauge models with HF spaces to create a unique experience. The chatbot is capable of understanding the user input for image generation, image background removal & a random space link if you are bored. For other inputs, the space uses DialogGPT-large." | |
| article = " \nHead on to <a href='https://huggingface.co/spaces/Gradio-Blocks/LM_meets_HF/discussions?type=discussion' target='_blank'>discussions</a> if you have any feedback." | |
| gr.Interface(fn=predict, | |
| inputs=["text", "state"], | |
| outputs=["chatbot", "state", gr.outputs.HTML(), gr.outputs.Image()], title="Language Model Meets Hugging Face", | |
| examples= examples, description=description, article=article).launch(debug=True, enable_queue=True) |