Update app.py

app.py

@@ -132,7 +132,6 @@ with st.container():
             </p> 
         </div>
     """, unsafe_allow_html=True)
-    # st.markdown("<p class='sub-title'>Enter the claim and context to verify its accuracy</p>", unsafe_allow_html=True)
 
     # Sidebar: Global Settings
     with st.sidebar.expander("⚙️ Settings", expanded=True):
@@ -203,29 +202,31 @@ with st.container():
     
                     # Extract evidence
                     evidence_start_time = time.time()
-                    evidence = extract_evidence_tfidf_qatc(
-                        claim, context, model_qatc, tokenizer_qatc,
-                        "cuda" if torch.cuda.is_available() else "cpu",
-                        confidence_threshold=tfidf_threshold,
-                        length_ratio_threshold=length_ratio_threshold
-                    )
+                    with torch.no_grad():
+                        evidence = extract_evidence_tfidf_qatc(
+                            claim, context, model_qatc, tokenizer_qatc,
+                            "cuda" if torch.cuda.is_available() else "cpu",
+                            confidence_threshold=tfidf_threshold,
+                            length_ratio_threshold=length_ratio_threshold
+                        )
                     evidence_time = time.time() - evidence_start_time
 
                     # Classify the claim
                     verdict = "NEI"
                     details = ""
                     verdict_start_time = time.time()
-                    prob2class, pred_bc = 0, "Not used"
-                    prob3class, pred_tc = classify_claim(
-                        claim, evidence, model_tc, tokenizer_tc,
-                        "cuda" if torch.cuda.is_available() else "cpu"
-                    )
-                    if pred_tc != 0:
-                        prob2class, pred_bc = classify_claim(
-                            claim, evidence, model_bc, tokenizer_bc,
+                    with torch.no_grad():
+                        prob2class, pred_bc = 0, "Not used"
+                        prob3class, pred_tc = classify_claim(
+                            claim, evidence, model_tc, tokenizer_tc,
                             "cuda" if torch.cuda.is_available() else "cpu"
                         )
-                        verdict = "SUPPORTED" if pred_bc == 0 else "REFUTED" if prob2class > prob3class else ["NEI", "SUPPORTED", "REFUTED"][pred_tc]
+                        if pred_tc != 0:
+                            prob2class, pred_bc = classify_claim(
+                                claim, evidence, model_bc, tokenizer_bc,
+                                "cuda" if torch.cuda.is_available() else "cpu"
+                            )
+                            verdict = "SUPPORTED" if pred_bc == 0 else "REFUTED" if prob2class > prob3class else ["NEI", "SUPPORTED", "REFUTED"][pred_tc]
                     verdict_time = time.time() - verdict_start_time
                     if show_details:
                         details = f"""
@@ -286,4 +287,4 @@ with st.container():
             for idx, record in enumerate(reversed(st.session_state.history), 1):
                 st.markdown(f"**{idx}. Claim:** {record['claim']}  \n**Result:** {verdict_icons.get(record['verdict'], '')} {record['verdict']}")
         else:
-            st.write("No verification history yet.")
+            st.write("No verification history yet.")