Update app.py

app.py

@@ -210,10 +210,11 @@ def selectedCorpusForNextQuarterModel(x,quarter):
     chunksAttention_mask=[tokens["attention_mask"][r*splitSize:(r+1)*splitSize] for r in range(math.ceil(len(tokens["attention_mask"])/splitSize))]
     l=[]
     for idx in range(len(chunksInput_ids)):
-        l.append({"input_ids":torch.tensor([list(x[idx])]).to("cuda"),
-         "token_type_ids":torch.tensor([list(y[idx])]).to("cuda"),
-          "attention_mask":torch.tensor([list(z[idx])]).to("cuda")
-        }) 
+        l.append({"input_ids":torch.tensor([list(chunksInput_ids[idx])]).to("cuda"),
+         "token_type_ids":torch.tensor([list(chunksToken_type_ids[idx])]).to("cuda"),
+          "attention_mask":torch.tensor([list(chunksAttention_mask[idx])]).to("cuda")
+        })
+      
     selectedTopics = ["Stock Movement", "Earnings", "IPO", "Stock Commentary", "Currencies", "M&A | Investments", "Financials", "Macro", "Analyst Update", "Company | Product News"]
     result = [tokenizerTopic.decode(x["input_ids"][0], skip_special_tokens=True) for x in l if getTopic(x) in selectedTopics]
     result=[x for x in result if len(x)>10]
@@ -244,7 +245,7 @@ if st.button("Analyze"):
     st.markdown(f'<span style="color:{sentiment_color}">{sentiment}</span>', unsafe_allow_html=True)
     st.subheader("Next Quarter Perdiction", divider='rainbow')
     # increase_decrease = [increase_decrease_model(x)[0]['label'] for x in chunks]
-    
+    increase_decrease=increase_decrease_model(selectedCorpusForNextQuarterModel(mainTranscript,quarter))[0]['label']
     increase_decrease=max(increase_decrease,key=increase_decrease.count)
     increase_decrease_color = "green" if increase_decrease == "Increase" else "red"
     st.markdown(f'<span style="color:{increase_decrease_color}">{increase_decrease}</span>', unsafe_allow_html=True)
@@ -260,7 +261,7 @@ if st.button("Analyze"):
             while idxx<len(ents):
                 if len(ents[idxx]["word"].split())==2:
                     ner_result.append({ents[idxx]["entity_group"]:ents[idxx]["word"]})
-                else:
+                elif len(ents[idxx]["word"].split())==1:
                     try:
                         ner_result.append({ents[idxx]["entity_group"]:ents[idxx]["word"]+ents[idxx+1]["word"]+ents[idxx+2]["word"]})
                         idxx=idxx+2