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Update app.py
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app.py
CHANGED
@@ -37,6 +37,8 @@ def generate_input(input_type, image=None, text=None, response_amount=3):
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# If no input, fallback
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if not combined_input:
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combined_input = "No input provided."
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return vector_search(combined_input,response_amount)
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@@ -48,6 +50,8 @@ metadata = pd.read_csv("netflix_metadata.csv") #created using sentence_transform
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def vector_search(query,top_n=3):
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query_embedding = sentence_model.encode(query)
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similarities = cosine_similarity([query_embedding], embeddings)[0]
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top_indices = similarities.argsort()[-top_n:][::-1]
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results = metadata.iloc[top_indices]
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result_text=""
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@@ -90,6 +94,8 @@ with gr.Blocks() as demo:
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submit_button = gr.Button("Submit")
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output = gr.Textbox(label="Recommendations")
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submit_button.click(fn=generate_input, inputs=[input_type,image_input, text_input,selected_response_amount], outputs=output)
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demo.launch()
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# If no input, fallback
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if not combined_input:
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combined_input = "No input provided."
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if response_amount is None:
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response_amount=3
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return vector_search(combined_input,response_amount)
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def vector_search(query,top_n=3):
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query_embedding = sentence_model.encode(query)
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similarities = cosine_similarity([query_embedding], embeddings)[0]
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if top_n is None:
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top_n=3
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top_indices = similarities.argsort()[-top_n:][::-1]
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results = metadata.iloc[top_indices]
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result_text=""
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submit_button = gr.Button("Submit")
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output = gr.Textbox(label="Recommendations")
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if selected_response_amount is None:
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selected_response_amount=3
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submit_button.click(fn=generate_input, inputs=[input_type,image_input, text_input,selected_response_amount], outputs=output)
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demo.launch()
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