import inspect import json import os import gradio as gr from gradio import routes import spacy from typing import List, Type ONES = [ "zero", "one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten", "eleven", "twelve", "thirteen", "fourteen", "fifteen", "sixteen", "seventeen", "eighteen", "nineteen", ] # token_mapping = json.load(open('str_mapping.json')) CHAR_MAPPING = { "-": " ", "_": " ", } CHAR_MAPPING.update((str(i), word) for i, word in enumerate([" " + s + " " for s in ONES])) TOKEN_MAPPING = dict(enumerate([" " + s + " " for s in ONES])) BQ_JSON = os.environ['BQ_JSON'] def tokenize(text): return text.split() def detokenize(tokens): return ' '.join(tokens) def replace_tokens(tokens, token_mapping=TOKEN_MAPPING): return [token_mapping.get(tok, tok) for tok in tokens] def replace_chars(text, char_mapping=CHAR_MAPPING): return ''.join((char_mapping.get(c, c) for c in text)) def tokens2int(tokens, numwords={}): """ Convert an English str containing number words into an int >>> text2int("nine") 9 >>> text2int("forty two") 42 >>> text2int("1 2 three") 123 """ if not numwords: tens = ["", "", "twenty", "thirty", "forty", "fifty", "sixty", "seventy", "eighty", "ninety"] scales = ["hundred", "thousand", "million", "billion", "trillion"] numwords["and"] = (1, 0) for idx, word in enumerate(ONES): numwords[word] = (1, idx) for idx, word in enumerate(tens): numwords[word] = (1, idx * 10) for idx, word in enumerate(scales): numwords[word] = (10 ** (idx * 3 or 2), 0) current = result = 0 for word in tokens: if word not in numwords: raise Exception("Illegal word: " + word) scale, increment = numwords[word] current = current * scale + increment if scale > 100: result += current current = 0 return str(result + current) def text2int(text): return tokens2int(tokenize(replace_chars(text))) def text2int_preprocessed(text): return tokens2int(replace_tokens(tokenize(replace_chars(text)))) def get_types(cls_set: List[Type], component: str): docset = [] types = [] if component == "input": for cls in cls_set: doc = inspect.getdoc(cls) doc_lines = doc.split("\n") docset.append(doc_lines[1].split(":")[-1]) types.append(doc_lines[1].split(")")[0].split("(")[-1]) else: for cls in cls_set: doc = inspect.getdoc(cls) doc_lines = doc.split("\n") docset.append(doc_lines[-1].split(":")[-1]) types.append(doc_lines[-1].split(")")[0].split("(")[-1]) return docset, types routes.get_types = get_types with gr.Blocks() as html_block: gr.Markdown("# Gradio Blocks (3.0) with REST API") textbox_input = gr.Textbox( value="forty-two", label="Input number words:", ) button_text2int = gr.Button("text2int") button_text2int_preprocessed = gr.Button("text2int with preprocessing") textbox_output = gr.Textbox( value="42", label="Output integer:" ) button_text2int.click(text2int, inputs=[textbox_input], outputs=[textbox_output]) button_text2int_preprocessed.click(text2int_preprocessed, inputs=[textbox_input], outputs=[textbox_output]) gr.Markdown(r""" ## API You can select which function to run using the `fn_index` argument: ```python import requests requests.post( url="https://Hobson-gradio-rest-api.hf.space/api/predict/", json={"data": ["one hundred forty-two"], "fn_index": 0} ).json() ``` Or using `curl`: ```bash curl -X POST https://Hobson-gradio-rest-api.hf.space/api/predict/ -H 'Content-Type: application/json' -d '{"data": ["one hundred forty-two"], "fn_index": 0}' ``` """ + f"{json.loads()['type']}") interface = gr.Interface(lambda: None, inputs=[textbox_input], outputs=[textbox_output]) html_block.input_components = interface.input_components html_block.output_components = interface.output_components html_block.examples = None html_block.predict_durations = [] bapp = html_block.launch()