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| import gradio as gr | |
| from wordllama import WordLlama | |
| # Load the default WordLlama model | |
| wl = WordLlama.load() | |
| def calculate_similarity(sentence1, sentence2): | |
| similarity_score = wl.similarity(sentence1, sentence2) | |
| return similarity_score | |
| def rank_documents(query, candidates): | |
| ranked_docs = wl.rank(query, candidates) | |
| return ranked_docs | |
| def deduplicate_candidates(candidates, threshold): | |
| deduplicated = wl.deduplicate(candidates, threshold) | |
| return deduplicated | |
| def filter_candidates(query, candidates, threshold): | |
| filtered = wl.filter(query, candidates, threshold) | |
| return filtered | |
| def topk_candidates(query, candidates, k): | |
| topk = wl.topk(query, candidates, k) | |
| return topk | |
| def create_gradio_interface(): | |
| with gr.Blocks() as demo: | |
| gr.Markdown("## WordLlama Gradio Demo") | |
| with gr.Tab("Similarity"): | |
| with gr.Row(): | |
| sentence1 = gr.Textbox(label="Sentence 1", placeholder="Enter the first sentence here...") | |
| sentence2 = gr.Textbox(label="Sentence 2", placeholder="Enter the second sentence here...") | |
| similarity_output = gr.Number(label="Similarity Score") | |
| gr.Button("Calculate Similarity").click( | |
| fn=calculate_similarity, | |
| inputs=[sentence1, sentence2], | |
| outputs=[similarity_output] | |
| ) | |
| with gr.Tab("Rank Documents"): | |
| query = gr.Textbox(label="Query", placeholder="Enter the query here...") | |
| candidates = gr.Textbox(label="Candidates (comma separated)", placeholder="Enter candidate sentences here...") | |
| ranked_docs_output = gr.Dataframe(headers=["Document", "Score"]) | |
| gr.Button("Rank Documents").click( | |
| fn=lambda q, c: rank_documents(q, c.split(',')), | |
| inputs=[query, candidates], | |
| outputs=[ranked_docs_output] | |
| ) | |
| with gr.Tab("Deduplicate Candidates"): | |
| candidates_dedup = gr.Textbox(label="Candidates (comma separated)", placeholder="Enter candidate sentences here...") | |
| threshold_dedup = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, step=0.01, value=0.8) | |
| deduplicated_output = gr.Textbox(label="Deduplicated Candidates") | |
| gr.Button("Deduplicate").click( | |
| fn=lambda c, t: deduplicate_candidates(c.split(','), t), | |
| inputs=[candidates_dedup, threshold_dedup], | |
| outputs=[deduplicated_output] | |
| ) | |
| with gr.Tab("Filter Candidates"): | |
| filter_query = gr.Textbox(label="Query", placeholder="Enter the query here...") | |
| candidates_filter = gr.Textbox(label="Candidates (comma separated)", placeholder="Enter candidate sentences here...") | |
| threshold_filter = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, step=0.01, value=0.3) | |
| filtered_output = gr.Textbox(label="Filtered Candidates") | |
| gr.Button("Filter Candidates").click( | |
| fn=lambda q, c, t: filter_candidates(q, c.split(','), t), | |
| inputs=[filter_query, candidates_filter, threshold_filter], | |
| outputs=[filtered_output] | |
| ) | |
| with gr.Tab("Top-k Candidates"): | |
| topk_query = gr.Textbox(label="Query", placeholder="Enter the query here...") | |
| candidates_topk = gr.Textbox(label="Candidates (comma separated)", placeholder="Enter candidate sentences here...") | |
| k = gr.Slider(label="Top-k", minimum=1, maximum=10, step=1, value=3) | |
| topk_output = gr.Textbox(label="Top-k Candidates") | |
| gr.Button("Get Top-k Candidates").click( | |
| fn=lambda q, c, k: topk_candidates(q, c.split(','), k), | |
| inputs=[topk_query, candidates_topk, k], | |
| outputs=[topk_output] | |
| ) | |
| return demo | |
| # Create and launch the Gradio interface | |
| demo = create_gradio_interface() | |
| demo.launch() | |