Create app.py

app.py

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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
+
+# Define the Gradio interface
+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"], datatype=["str", "float"])
+            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(debug = True)