update to handle empty chunk values from aPI

app.py

@@ -73,18 +73,20 @@ def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[]
         counter+=1
         # check whether each line is non-empty
         if chunk :
-          # decode each line as response data is in bytes
-          if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
-            break
-          #print(json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"])
-          partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
-          if token_counter == 0:
-            history.append(" " + partial_words)
-          else:
-            history[-1] = partial_words
-          chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
-          token_counter+=1
-          yield chat, history, chat_counter  # resembles {chatbot: chat, state: history}  
+          chunk_str = chunk.decode()[6:]
+          if chunk_str:
+            delta = json.loads(chunk_str)['choices'][0]["delta"]
+            if len(delta) == 0:
+                break
+            # decode each line as response data is in bytes
+            partial_words = partial_words + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
+            if token_counter == 0:
+              history.append(" " + partial_words)
+            else:
+              history[-1] = partial_words
+            chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
+            token_counter+=1
+            yield chat, history, chat_counter  # resembles {chatbot: chat, state: history}