import gradio as gr import requests import os from screenshot import BG_COMP, BOX_COMP, GENERATION_VAR, PROMPT_VAR, main from pathlib import Path title = "JAX / Flax BLOOM 🌸" description = """Gradio Demo for BLOOM. To use it, simply add your text, or click one of the examples to load them. Tips: - Do NOT talk to BLOOM as an entity, it's not a chatbot but a webpage/blog/article completion model. - For the best results: MIMIC a few sentences of a webpage similar to the content you want to generate. Start a paragraph as if YOU were writing a blog, webpage, math post, coding article and BLOOM will generate a coherent follow-up. Longer prompts usually give more interesting results. Options: - sampling: imaginative completions (may be not super accurate e.g. math/history) - greedy: accurate completions (may be more boring or have repetitions) """ wip_description = """Gradio Demo for JAX / Flax BLOOM. The 176B BLOOM model running on a TPU v3-256 pod, with 2D model parallelism and custom mesh axes. Note: rendering of the screenshot is currently not optimised. To experience the true speed of JAX / Flax, tick 'just output raw text'. Tips: - Do NOT talk to BLOOM as an entity, it's not a chatbot but a webpage/blog/article completion model. - For the best results: MIMIC a few sentences of a webpage similar to the content you want to generate. Start a paragraph as if YOU were writing a blog, webpage, math post, coding article and BLOOM will generate a coherent follow-up. Longer prompts usually give more interesting results. Options: - sampling: imaginative completions (may be not super accurate e.g. math/history) - greedy: accurate completions (may be more boring or have repetitions) """ API_URL = os.getenv("API_URL") examples = [ ['To do a "farduddle" means to jump up and down really fast. An example of a sentence that uses the word farduddle is:', 64, "sampling", True], ['A poem about the beauty of science by Alfred Edgar Brittle\nTitle: The Magic Craft\nIn the old times', 64, "sampling", True], ['استخراج العدد العاملي في لغة بايثون:', 64, "greedy", True], ["Pour déguster un ortolan, il faut tout d'abord", 64, "sampling", True], ['Traduce español de España a español de Argentina\nEl coche es rojo - el auto es rojo\nEl ordenador es nuevo - la computadora es nueva\nel boligrafo es negro -', 64, "sampling", True], ['Estos ejemplos quitan vocales de las palabras\nEjemplos:\nhola - hl\nmanzana - mnzn\npapas - pps\nalacran - lcrn\npapa -', 64, "sampling", True], ["Question: If I put cheese into the fridge, will it melt?\nAnswer:", 64, "greedy", True], ["Math exercise - answers:\n34+10=44\n54+20=", 64, "sampling", True], ["Python - code to compute the factorial of a number:", 64, "greedy", True], ["Question: Where does the Greek Goddess Persephone spend half of the year when she is not with her mother?\nAnswer:", 64, "sampling", True], ["spelling test answers.\nWhat are the letters in « language »?\nAnswer: l-a-n-g-u-a-g-e\nWhat are the letters in « Romanian »?\nAnswer:", 64, "sampling", True], ['A "whatpu" is a small, furry animal native to Tanzania. An example of a sentence that uses the word whatpu is:', 64, "sampling", True], ] def query(payload): print(payload) response = requests.post(API_URL, json=payload) print(response) return response.json() def inference(input_sentence, max_length, sample_or_greedy, raw_text=True): do_sample = sample_or_greedy == "sampling" payload = { "inputs": input_sentence, "do_sample": do_sample, # "max_new_tokens": max_length } data = query( payload ) if raw_text: return None, data[0]['generated_text'][0] width, height = 3326, 3326 assets_path = "assets" font_mapping = { "latin characters (faster)": "DejaVuSans.ttf", "complete alphabet (slower)": "GoNotoCurrent.ttf" } working_dir = Path(__file__).parent.resolve() font_path = str(working_dir / font_mapping["complete alphabet (slower)"]) img_save_path = str(working_dir / "output.jpeg") colors = { BG_COMP: "#000000", PROMPT_VAR: "#FFFFFF", GENERATION_VAR: "#FF57A0", BOX_COMP: "#120F25", } # TODO: fix screenshot new_string = data[0]['generated_text'][0].split(input_sentence, 1)[1] _, img = main( input_sentence, new_string, width, height, assets_path=assets_path, font_path=font_path, colors=colors, frame_to_box_margin=200, text_to_text_box_margin=50, init_font_size=142, right_align=False, ) return img, data[0]['generated_text'][0] gr.Interface( inference, [ gr.inputs.Textbox(label="Input"), gr.inputs.Radio([64], default=64, label="Tokens to generate"), gr.inputs.Radio(["sampling", "greedy"], label="Sample or greedy", default="sampling"), gr.Checkbox(label="Just output raw text", value=True), ], ["image", "text"], examples=examples, # article=article, cache_examples=False, title=title, description=wip_description ).launch()