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()
+
+# Function to calculate similarity
+def calculate_similarity(text1, text2):
+    score = wl.similarity(text1, text2)
+    return f"Similarity Score: {score}"
+
+# Function to rank documents
+def rank_documents(query, candidates):
+    candidates_list = candidates.split(";")
+    ranked_docs = wl.rank(query, candidates_list)
+    return ranked_docs
+
+# Function to deduplicate documents
+def deduplicate_docs(candidates, threshold):
+    candidates_list = candidates.split(";")
+    deduplicated_docs = wl.deduplicate(candidates_list, threshold=threshold)
+    return deduplicated_docs
+
+# Function to cluster documents
+def cluster_docs(docs, k, max_iterations, tolerance):
+    docs_list = docs.split(";")
+    clusters = wl.cluster(docs_list, k=k, max_iterations=max_iterations, tolerance=tolerance)
+    return clusters
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# WordLlama Gradio App")
+    
+    # Similarity Interface
+    with gr.Tab("Similarity"):
+        gr.Markdown("### Calculate Similarity between two texts")
+        text1 = gr.Textbox(label="Text 1")
+        text2 = gr.Textbox(label="Text 2")
+        similarity_output = gr.Textbox(label="Similarity Score")
+        similarity_button = gr.Button("Calculate Similarity")
+        similarity_button.click(calculate_similarity, inputs=[text1, text2], outputs=similarity_output)
+    
+    # Ranking Interface
+    with gr.Tab("Rank Documents"):
+        gr.Markdown("### Rank documents based on a query")
+        query = gr.Textbox(label="Query")
+        candidates = gr.Textbox(label="Candidates (separate by semicolons)")
+        rank_output = gr.JSON(label="Ranked Documents")
+        rank_button = gr.Button("Rank Documents")
+        rank_button.click(rank_documents, inputs=[query, candidates], outputs=rank_output)
+    
+    # Deduplication Interface
+    with gr.Tab("Fuzzy Deduplication"):
+        gr.Markdown("### Deduplicate similar documents")
+        candidates = gr.Textbox(label="Candidates (separate by semicolons)")
+        threshold = gr.Slider(0.0, 1.0, value=0.8, label="Threshold")
+        deduplicate_output = gr.JSON(label="Deduplicated Documents")
+        deduplicate_button = gr.Button("Deduplicate")
+        deduplicate_button.click(deduplicate_docs, inputs=[candidates, threshold], outputs=deduplicate_output)
+    
+    # Clustering Interface
+    with gr.Tab("Clustering"):
+        gr.Markdown("### Cluster documents")
+        docs = gr.Textbox(label="Documents (separate by semicolons)")
+        k = gr.Number(label="Number of Clusters", value=5)
+        max_iterations = gr.Number(label="Max Iterations", value=100)
+        tolerance = gr.Number(label="Tolerance", value=1e-4)
+        cluster_output = gr.JSON(label="Clusters")
+        cluster_button = gr.Button("Cluster Documents")
+        cluster_button.click(cluster_docs, inputs=[docs, k, max_iterations, tolerance], outputs=cluster_output)
+
+demo.launch()