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| import os | |
| import sys | |
| sys.path.append(os.path.dirname(os.path.dirname(__file__))) | |
| import gradio as gr | |
| from words2wisdom import CONFIG_DIR, ROOT | |
| from words2wisdom.config import Config | |
| from words2wisdom.pipeline import Pipeline | |
| from words2wisdom.utils import dump_all | |
| example_file = (os.path.join(ROOT, "demo", "example.txt")) | |
| example_text = "The quick brown fox jumps over the lazy dog. The cat sits on the mat." | |
| def w2w_from_string(openai_api_key: str, input_text: str): | |
| config = Config.read_ini(os.path.join(CONFIG_DIR, "default_config.ini")) | |
| config.llm["openai_api_key"] = openai_api_key | |
| pipeline = Pipeline(config) | |
| text_batches, knowledge_graph = pipeline.run(input_text) | |
| zip_path = dump_all(config, text_batches, knowledge_graph) | |
| return knowledge_graph, zip_path | |
| def w2w_from_file(openai_api_key: str, input_file): | |
| with open(input_file.name) as f: | |
| input_text = f.read() | |
| return w2w_from_string(openai_api_key, input_text) | |
| with gr.Blocks(title="Words2Wisdom") as demo: | |
| gr.Markdown("# 🧞📖 Words2Wisdom") | |
| with gr.Column(variant="panel"): | |
| openai_api_key = gr.Textbox(label="OpenAI API Key", placeholder="sk-...", type="password") | |
| with gr.Row(equal_height=False): | |
| with gr.Column(variant="panel"): | |
| gr.Markdown("## Input (Text or Text File)") | |
| #gr.Markdown("A knowledge graph will be generated for the provided text.") | |
| with gr.Tab("Direct Input"): | |
| text_string = gr.Textbox(lines=2, placeholder="Text Here...", label="Text") | |
| submit_str = gr.Button() | |
| with gr.Tab("File Upload"): | |
| text_file = gr.File(file_types=["text"], label="Text File") | |
| submit_file = gr.Button() | |
| with gr.Column(variant="panel"): | |
| gr.Markdown("## Output (ZIP Archive)") | |
| #gr.Markdown("The ZIP contains the generated knowledge graph, the text batches (indexed), and a configuration file.") | |
| output_zip = gr.File(label="ZIP") | |
| with gr.Accordion(label="Preview of Knowledge Graph", open=False): | |
| output_graph = gr.DataFrame(headers=["batch_id", "subject", "relation", "object"], label="Knowledge Graph") | |
| with gr.Accordion(label="Examples", open=False): | |
| gr.Markdown("### Text Example") | |
| gr.Examples( | |
| examples=[[None, example_text]], | |
| inputs=[openai_api_key, text_string], | |
| outputs=[output_graph, output_zip], | |
| fn=w2w_from_string, | |
| preprocess=False, | |
| postprocess=False | |
| ) | |
| gr.Markdown("### File Example") | |
| gr.Examples( | |
| examples=[[None, example_file]], | |
| inputs=[openai_api_key, text_file], | |
| outputs=[output_graph, output_zip], | |
| fn=w2w_from_file, | |
| preprocess=False, | |
| postprocess=False | |
| ) | |
| submit_str.click(fn=w2w_from_string, inputs=[openai_api_key, text_string], outputs=[output_graph, output_zip]) | |
| submit_file.click(fn=w2w_from_file, inputs=[openai_api_key, text_file], outputs=[output_graph, output_zip]) | |
| demo.launch(inbrowser=True, width="75%") |