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  1. app.py +38 -0
app.py ADDED
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+ import gensim
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+ import gensim.models
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+ from gensim.models import KeyedVectors
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+ import gensim.downloader as api
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+ import fasttext
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+ import gradio as gr
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+
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+
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+ model = fasttext.load_model("fasttext_model_ina.bin")
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+
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+ # Test Model Locally
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+
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+ #print(model.get_nearest_neighbors("ndalama")) # Example Chichewa word
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+
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+
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+ # Define function for Gradio
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+ def find_similar_words(wordz, top_n=10):
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+ words=model.get_nearest_neighbors(wordz)
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+ try:
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+ text=''
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+ for word in words:
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+ text= text +"\n" +str(word[1]) + " Similarity score : "+ str(word[0])
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+
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+ return text
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+ except KeyError:
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+ return f"'{word}' not found in the vocabulary!"
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+
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+ # Gradio UI
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+ demo = gr.Interface(
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+ fn=find_similar_words,
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+ inputs=gr.Textbox(label="Enter a Word"),
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+ outputs="text",
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+ title="Chichewa Word Embeddings Explorer",
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+ description="Find similar words using a pre-trained word embedding model.",
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+ )
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+
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+ # Launch for local testing
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+ demo.launch()