sohoso commited on
Commit
7da78c1
·
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1 Parent(s): 71d15da

Update app.py

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Files changed (1) hide show
  1. app.py +15 -9
app.py CHANGED
@@ -1,4 +1,11 @@
1
- import time, os, multiprocessing, torch, requests, asyncio, json, aiohttp
 
 
 
 
 
 
 
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  from minivectordb.embedding_model import EmbeddingModel
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  from minivectordb.vector_database import VectorDatabase
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  from text_util_en_pt.cleaner import structurize_text, detect_language, Language
@@ -24,12 +31,12 @@ def index_and_search(query, text):
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  # Indexing
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  vector_db = VectorDatabase()
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- sentences = [ s['sentence'] for s in structurize_text(text)]
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  for idx, sentence in enumerate(sentences):
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  sentence_embedding = model.extract_embeddings(sentence)
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  vector_db.store_embedding(idx + 1, sentence_embedding, {'sentence': sentence})
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-
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  embedding_time = time.time() - start
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  # Retrieval
@@ -168,10 +175,9 @@ async def predict(message, history):
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  # Define a custom theme with colors similar to the provided image
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  custom_theme = gr.themes.Default(
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- primary_hue="#6a0dad", # Custom primary color (similar to the purple in the image)
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- secondary_hue="#4b0082", # Custom secondary color
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  font="Roboto", # Custom font
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- font_size="16px", # Custom font size
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  rounded_corners=True, # Enable rounded corners
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  background_color="#1a1a2e", # Custom dark background color
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  text_color="#f0f0f0" # Custom text color for better contrast
@@ -180,13 +186,13 @@ custom_theme = gr.themes.Default(
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  # Apply the custom theme to the Gradio interface
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  gr.ChatInterface(
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  predict,
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- title="Assistant pro",
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  retry_btn=None,
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  undo_btn=None,
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  examples=[
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  'What is the current sentiment of the Brazil election?',
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  'Compare the current economies of China and India?',
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- 'What are new shoe design trends in 2024',
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  ],
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  theme=custom_theme # Apply the custom theme
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- ).launch()
 
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+ import time
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+ import os
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+ import multiprocessing
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+ import torch
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+ import requests
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+ import asyncio
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+ import json
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+ import aiohttp
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  from minivectordb.embedding_model import EmbeddingModel
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  from minivectordb.vector_database import VectorDatabase
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  from text_util_en_pt.cleaner import structurize_text, detect_language, Language
 
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  # Indexing
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  vector_db = VectorDatabase()
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+ sentences = [s['sentence'] for s in structurize_text(text)]
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  for idx, sentence in enumerate(sentences):
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  sentence_embedding = model.extract_embeddings(sentence)
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  vector_db.store_embedding(idx + 1, sentence_embedding, {'sentence': sentence})
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+
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  embedding_time = time.time() - start
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  # Retrieval
 
175
 
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  # Define a custom theme with colors similar to the provided image
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  custom_theme = gr.themes.Default(
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+ primary_hue="purple", # Custom primary color (similar to the purple in the image)
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+ secondary_hue="indigo", # Custom secondary color
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  font="Roboto", # Custom font
 
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  rounded_corners=True, # Enable rounded corners
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  background_color="#1a1a2e", # Custom dark background color
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  text_color="#f0f0f0" # Custom text color for better contrast
 
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  # Apply the custom theme to the Gradio interface
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  gr.ChatInterface(
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  predict,
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+ title="Assistant Pro",
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  retry_btn=None,
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  undo_btn=None,
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  examples=[
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  'What is the current sentiment of the Brazil election?',
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  'Compare the current economies of China and India?',
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+ 'What are new shoe design trends in 2024?',
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  ],
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  theme=custom_theme # Apply the custom theme
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+ ).launch()