Update src/streamlit_app.py

src/streamlit_app.py

@@ -78,9 +78,12 @@ text_field = "text" if "text" in data.features else list(data.features.keys())[0
 
 # ========== 🧠 Embedding Function ==========
 @st.cache_data(show_spinner=False)
-def embed_texts(_texts):
+def embed_dataset_texts(_texts):
     return text_model.encode(_texts, convert_to_tensor=True)
 
+def embed_query_text(query):
+    return text_model.encode([query], convert_to_tensor=True)[0]
+
 # Pick which text column to use
 TEXT_COLUMN = "complaints"  # or "general_complaint", depending on your needs
 
@@ -91,8 +94,8 @@ query = st.text_input("Enter your medical question or symptom description:")
 
 if query:
     with st.spinner("Searching medical cases..."):
-        text_embeddings = embed_texts(data[TEXT_COLUMN])
-        query_embedding = embed_texts([query])[0]
+        text_embeddings = embed_dataset_texts(data[TEXT_COLUMN])
+        query_embedding = embed_query_text([query])[0]
 
         # Compute similarity
         cos_scores = util.pytorch_cos_sim(query_embedding, text_embeddings)[0]