Create app.py

app.py

@@ -0,0 +1,69 @@
+import streamlit as st
+import json
+from rapidfuzz import process, fuzz
+
+# --- CONFIGURATION ---
+DATA_FILE = "navy_acronyms_clean.json"
+
+# --- PAGE SETUP ---
+st.set_page_config(page_title="Navy Acronym Finder", page_icon="⚓")
+
+st.title("EDQP Acronym Lookup")
+st.markdown("Type an acronym below to find its definition. Uses fuzzy matching to handle typos.")
+
+# --- LOAD DATA ---
+@st.cache_data
+def load_acronyms():
+    try:
+        with open(DATA_FILE, 'r', encoding='utf-8') as f:
+            return json.load(f)
+    except FileNotFoundError:
+        return {"ERROR": "navy_acronyms_clean.json not found!"}
+
+acronym_dict = load_acronyms()
+acronym_keys = list(acronym_dict.keys())
+
+# --- SEARCH BAR ---
+query = st.text_input("Enter Acronym:", placeholder="e.g., ACAT, MDA, ASW...", max_chars=10)
+
+# --- RESULTS ---
+if query:
+    query = query.upper().strip()
+    
+    # 1. Exact Match (The "Right" Answer)
+    if query in acronym_dict:
+        st.success(f"**{query}**")
+        st.markdown(f"### {acronym_dict[query]}")
+        st.divider()
+
+    # 2. Fuzzy / Top 5 Suggestions
+    st.markdown("#### Did you mean?")
+    
+    # Extracts top 5 similar keys based on the user query
+    # scorer=fuzz.ratio gives a simple similarity score
+    matches = process.extract(query, acronym_keys, limit=5, scorer=fuzz.ratio)
+    
+    for match_tuple in matches:
+        # Tuple format: (matched_string, score, index)
+        candidate = match_tuple[0]
+        score = match_tuple[1]
+        
+        # Don't show the exact match again if we already showed the big green box
+        if candidate == query:
+            continue
+            
+        # Only show relevant matches (score > 40)
+        if score > 40:
+            with st.expander(f"**{candidate}** (Match: {int(score)}%)"):
+                st.write(acronym_dict[candidate])
+
+# --- SIDEBAR (Database Stats) ---
+with st.sidebar:
+    st.header("Database Info")
+    st.metric("Total Acronyms", len(acronym_dict))
+    
+    st.divider()
+    
+    # Option to view raw list
+    if st.checkbox("Show Full List"):
+        st.dataframe(acronym_dict, use_container_width=True)