Update app.py

app.py

@@ -47,12 +47,14 @@ d = 1024
 text_index = faiss.index_factory(d, "Flat", faiss.METRIC_INNER_PRODUCT)
 faiss.read_index("text_index.index")
 
-def T2Isearch(query, k=50):
+def T2Isearch(query,focussed_word, k=50):
     # Encode the text query        
-    inputs = text_tokenizer([query], padding=True, return_tensors="pt")    
+    inputs = text_tokenizer([query,focussed_word], padding=True, return_tensors="pt")    
     outputs = text_model(**inputs)
     query_embedding = outputs.text_embeds
     query_vector = query_embedding.detach().numpy()
+    query_vector = np.concatenate((query_vector[0], query_vector[1]), dtype=np.float32)
+    query_vector = query_vector.reshape(1,1024)
     # query_vector = test_xt[0]
     # query_vector = np.array([query_embedding])
     faiss.normalize_L2(query_vector)
@@ -91,6 +93,7 @@ def T2Isearch(query, k=50):
             st.image(image, width=600)
 
 query = st.text_input("Enter your search query here:")
+focussed_word = st.text_input("Enter focussed word here")
 if st.button("Search"):
     if query:
-        T2Isearch(query)
+        T2Isearch(query, focussed_word)