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import numpy as np
from sklearn.decomposition import PCA
import gensim.downloader as api
import gradio as gr
import plotly.graph_objects as go
# Load the Word2Vec model
model = api.load("word2vec-google-news-300")
def gensim_analogy(model, word1, word2, word3):
try:
result = model.most_similar(positive=[word2, word3], negative=[word1], topn=1)
return result[0][0] # Return the word
except KeyError as e:
return str(e)
def plot_words_plotly(model, words):
vectors = np.array([model[word] for word in words if word in model.key_to_index])
# Reduce dimensions to 2D for plotting
pca = PCA(n_components=2)
vectors_2d = pca.fit_transform(vectors)
# Create a scatter plot
fig = go.Figure()
# Add scatter points for each word vector
for word, vec in zip(words, vectors_2d):
fig.add_trace(go.Scatter(x=[vec[0]], y=[vec[1]],
text=[word], mode='markers+text',
textposition="bottom center",
name=word))
fig.update_layout(title="Word Vectors Visualization",
xaxis_title="PCA 1",
yaxis_title="PCA 2",
showlegend=True)
return fig
def gradio_interface(choice, custom_input=None):
if choice == "Custom":
if not custom_input or len(custom_input.split(", ")) != 3:
return "Invalid input. Please enter exactly three words, separated by commas.", None, {
"error": "Invalid input"}
words = custom_input.split(", ")
else:
words = choice.split(", ")
word1, word2, word3 = words
word4 = gensim_analogy(model, word1, word2, word3)
plot_fig = plot_words_plotly(model, [word1, word2, word3, word4])
if word4 in model.key_to_index:
vector = model[word4]
vector_display = {word4: [round(num, 2) for num in vector.tolist()]}
else:
vector_display = {"error": "Vector not available for the resulting word"}
return word4, plot_fig, vector_display
choices = [
"man, king, woman",
"Paris, France, London",
"strong, stronger, weak",
"pork, pig, beef",
"Custom"
]
iface = gr.Interface(
fn=gradio_interface,
inputs=[
gr.Dropdown(choices=choices, label="Choose predefined words or enter custom words"),
gr.Textbox(label="Custom words (comma-separated, required for custom choice; use only if 'Custom' is selected)",
placeholder="Enter 3 words separated by commas")
],
outputs=["text", "plot", "json"],
title="Word Analogy and Vector Visualization with Plotly",
description="Select a predefined triplet of words or choose 'Custom' and enter your own (comma-separated) to find a fourth word by analogy, and see their vectors plotted with Plotly."
)
iface.launch(share=True)
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