Create app.py

app.py

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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)