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| import gradio as gr | |
| import torch | |
| import os | |
| import numpy | |
| from sentence_transformers import SentenceTransformer | |
| #sentence_model = SentenceTransformer("paraphrase-multilingual-mpnet-base-v2") | |
| #sentence_model = SentenceTransformer("all-mpnet-base-v2") | |
| sentence_model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1") | |
| def getText( file ): | |
| return open( file ).read() | |
| def axis(): | |
| global v, a, s | |
| doc = getText( './axis/v' ) | |
| embedding = sentence_model.encode( doc , show_progress_bar=False, normalize_embeddings=True ) | |
| torch.save( embedding , './embeds/v' ) | |
| v = embedding | |
| doc = getText( './axis/a' ) | |
| embedding = sentence_model.encode( doc , show_progress_bar=False, normalize_embeddings=True ) | |
| torch.save( embedding , './embeds/a' ) | |
| a = embedding | |
| doc = getText( './axis/s' ) | |
| embedding = sentence_model.encode( doc , show_progress_bar=False, normalize_embeddings=True ) | |
| torch.save( embedding , './embeds/s' ) | |
| s = embedding | |
| def zxy( doc ): | |
| global v, a, s | |
| if not os.path.exists( './embeds/s' ): | |
| axis() # run this to setup axis embeddings | |
| else: | |
| if not 'v' in globals() : | |
| print( "loading axes from embeds" ) | |
| v = torch.load( './embeds/v' ) | |
| a = torch.load( './embeds/a' ) | |
| s = torch.load( './embeds/s' ) | |
| embedding = sentence_model.encode( doc , show_progress_bar=False , normalize_embeddings=True ) | |
| # torch.save( embedding , './embeds/new' ) | |
| z = ( 1.0 - embedding @ s ) / 2.0 # level 0 on top | |
| x = ( 1.0 - embedding @ a ) / 2.0 # ring 0 in the middle | |
| y = ( embedding @ v + 1.0 ) / 2.0 # sector 0 at twelve oclock | |
| # add one to make positive / divide by two to make range 0-1 | |
| scale = 1 | |
| levels = 44 | |
| rings = 22 | |
| sectors = 44 * 4 | |
| zxy = [ numpy.rint( scale * levels * z ) , numpy.rint( scale * rings * x ) , numpy.rint( scale * sectors * y ) ] | |
| return f"""L{ str( int( zxy[ 0 ] ) ) }/{ str( int( zxy[ 1 ] ) ) }/{ str( int( zxy[ 2 ] ) ) } | |
| es={ embedding @ s } ex={ embedding @ a } ey={ embedding @ v } | |
| z={ z } x={ x } y={ y } | |
| {scale} {levels} {rings} {sectors} | |
| """ | |
| #iface = gr.Interface(fn=zxy, inputs="text", outputs="text") | |
| #iface.launch() | |
| #iface.launch(share=True) # make public | |