Add dropdown autocomplete and autocorrection for searches

app.py

@@ -69,6 +69,16 @@ def search_by_reactant(reactant):
         for _, row in matches.head(5).iterrows():
             results.append(f"**{row['name']}**: {', '.join(row['reactants'])} → {', '.join(row['products'])}")
         return "\n\n".join(results)
+    # Fuzzy match for autocorrection
+    fuzzy_matches = process.extract(reactant, unique_reactants, limit=3)
+    if fuzzy_matches and fuzzy_matches[0][1] > 70:
+        closest = fuzzy_matches[0][0]
+        matches = df[df['reactants'].apply(lambda x: closest.lower() in [r.lower() for r in x])]
+        if not matches.empty:
+            results = [f"Did you mean '{closest}'?\n"]
+            for _, row in matches.head(5).iterrows():
+                results.append(f"**{row['name']}**: {', '.join(row['reactants'])} → {', '.join(row['products'])}")
+            return "\n\n".join(results)
     return "No reactions found with that reactant."
 
 def search_by_product(product):
@@ -80,6 +90,16 @@ def search_by_product(product):
         for _, row in matches.head(5).iterrows():
             results.append(f"**{row['name']}**: {', '.join(row['reactants'])} → {', '.join(row['products'])}")
         return "\n\n".join(results)
+    # Fuzzy match for autocorrection
+    fuzzy_matches = process.extract(product, unique_products, limit=3)
+    if fuzzy_matches and fuzzy_matches[0][1] > 70:
+        closest = fuzzy_matches[0][0]
+        matches = df[df['products'].apply(lambda x: closest.lower() in [p.lower() for p in x])]
+        if not matches.empty:
+            results = [f"Did you mean '{closest}'?\n"]
+            for _, row in matches.head(5).iterrows():
+                results.append(f"**{row['name']}**: {', '.join(row['reactants'])} → {', '.join(row['products'])}")
+            return "\n\n".join(results)
     return "No reactions found with that product."
 
 def get_autocomplete_reactions(query):
@@ -105,23 +125,29 @@ with gr.Blocks(title="Organic Reactions Search") as demo:
     gr.Markdown("Search through the organic reactions dataset by name, reactant, or product.")
 
     with gr.Tab("Search by Reaction Name"):
-        reaction_input = gr.Textbox(label="Reaction Name", placeholder="e.g., appel-reaction")
+        reaction_input = gr.Dropdown(label="Reaction Name", choices=reaction_names, allow_custom_value=True, placeholder="Type or select a reaction name")
         reaction_output = gr.Markdown(label="Result")
         reaction_btn = gr.Button("Search")
         reaction_btn.click(search_by_reaction_name, inputs=reaction_input, outputs=reaction_output)
 
     with gr.Tab("Search by Reactant"):
-        reactant_input = gr.Textbox(label="Reactant", placeholder="e.g., alcohol")
+        reactant_input = gr.Dropdown(label="Reactant", choices=unique_reactants, allow_custom_value=True, placeholder="Type or select a reactant")
         reactant_output = gr.Markdown(label="Results")
         reactant_btn = gr.Button("Search")
         reactant_btn.click(search_by_reactant, inputs=reactant_input, outputs=reactant_output)
 
     with gr.Tab("View Reaction SVG"):
-        svg_input = gr.Textbox(label="Reaction Name", placeholder="e.g., appel-reaction")
+        svg_input = gr.Dropdown(label="Reaction Name", choices=reaction_names, allow_custom_value=True, placeholder="Type or select a reaction name")
         svg_output = gr.HTML(label="Reaction SVG")
         svg_btn = gr.Button("Generate SVG")
         svg_btn.click(generate_reaction_svg, inputs=svg_input, outputs=svg_output)
 
+    with gr.Tab("Search by Product"):
+        product_input = gr.Dropdown(label="Product", choices=unique_products, allow_custom_value=True, placeholder="Type or select a product")
+        product_output = gr.Markdown(label="Results")
+        product_btn = gr.Button("Search")
+        product_btn.click(search_by_product, inputs=product_input, outputs=product_output)
+
     with gr.Tab("API Documentation"):
         gr.Markdown("""
         ## API Endpoints