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Update app.py
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app.py
CHANGED
@@ -31,6 +31,15 @@ def display_df_as_table(model,top_k,score='score'):
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return df
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#function for generating similarity of query and netflix shows
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def semantic_search(query,top_k):
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'''Encode query and check similarity with embeddings'''
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@@ -61,7 +70,7 @@ def semantic_search(query,top_k):
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return bi_df, cross_df
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title = """<h1 id="title">Netflix Shows Semantic Search</h1>"""
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description = """
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Semantic Search is a way to generate search results based on the actual meaning of the query instead of a standard keyword search. I believe this way of searching provides more meaning results when trying to find a good show to watch on Netflix. For example, one could search for "Success, rags to riches story" as provided in the example below to generate shows or movies with a description that is semantically similar to the query.
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@@ -97,7 +106,7 @@ with demo:
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with gr.Row():
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query = gr.
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with gr.Row():
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return df
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#load ASR model
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def asr(audio):
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asr_model = whisper.load_model("base")
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results = loaded_model.transcribe(audio)
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query = results['text']
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return query
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#function for generating similarity of query and netflix shows
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def semantic_search(query,top_k):
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'''Encode query and check similarity with embeddings'''
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return bi_df, cross_df
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title = """<h1 id="title">Voice Activated Netflix Shows Semantic Search</h1>"""
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description = """
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Semantic Search is a way to generate search results based on the actual meaning of the query instead of a standard keyword search. I believe this way of searching provides more meaning results when trying to find a good show to watch on Netflix. For example, one could search for "Success, rags to riches story" as provided in the example below to generate shows or movies with a description that is semantically similar to the query.
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with gr.Row():
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query = gr.Audio(source='microphone',type='filepath',label='Describe the Netflix show or movie you would like to watch..')
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with gr.Row():
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