Tonic commited on
Commit
93b8804
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1 Parent(s): 56e4f3d

Update app.py

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Files changed (1) hide show
  1. app.py +37 -0
app.py CHANGED
@@ -141,6 +141,27 @@ def search_similar_sentences(input_question, corpus_sentences, corpus_embeddings
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  results = [(corpus_sentences[i], top_k_scores[i]) for i in top_k_indices]
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  return results
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  def app_interface():
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  corpus_sentences = []
@@ -211,6 +232,22 @@ def app_interface():
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  outputs=search_results_output
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  )
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  with gr.Row():
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  with gr.Column():
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  input_text_box
 
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  results = [(corpus_sentences[i], top_k_scores[i]) for i in top_k_indices]
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  return results
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+ # openai response object formatting
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+ def format_response(embeddings):
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+ return {
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+ "data": [
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+ {
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+ "embedding": embeddings,
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+ "index": 0,
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+ "object": "embedding"
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+ }
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+ ],
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+ "model": "e5-mistral",
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+ "object": "list",
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+ "usage": {
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+ "prompt_tokens": 17,
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+ "total_tokens": 17
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+ }
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+ }
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+
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+ def generate_and_format_embeddings(selected_task, input_text):
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+ embeddings = compute_embeddings(selected_task, input_text)
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+ return format_response(embeddings)
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  def app_interface():
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  corpus_sentences = []
 
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  outputs=search_results_output
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  )
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+ with gr.Tab("Connector-like Embeddings"):
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+ with gr.Row():
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+ input_text_box_connector = gr.Textbox(label="Input Text", placeholder="Enter text or array of texts")
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+ model_dropdown_connector = gr.Dropdown(label="Model", choices=["ArguAna", "ClimateFEVER", "DBPedia", "FEVER", "FiQA2018", "HotpotQA", "MSMARCO", "NFCorpus", "NQ", "QuoraRetrieval", "SCIDOCS", "SciFact", "Touche2020", "TRECCOVID"], value="text-embedding-ada-002")
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+ encoding_format_connector = gr.Radio(label="Encoding Format", choices=["float", "base64"], value="float")
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+ user_connector = gr.Textbox(label="User", placeholder="Enter user identifier (optional)")
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+ submit_button_connector = gr.Button("Generate Embeddings")
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+
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+ output_display_connector = gr.JSON(label="Embeddings Output")
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+
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+ submit_button_connector.click(
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+ fn=generate_and_format_embeddings,
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+ inputs=[input_text_box_connector, model_dropdown_connector, encoding_format_connector, user_connector],
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+ outputs=output_display_connector
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+ )
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+
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  with gr.Row():
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  with gr.Column():
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  input_text_box