Update app.py

app.py

@@ -252,20 +252,26 @@ returns the names, SMILES strings, molecular weights and logP values for the rel
   tool_choices = str(res).replace('smilars', 'smiles').split('<|assistant|>')[1].split('#')[0].strip()
   tool_choices = tool_choices.split(',')
   print(tool_choices)
+
   if len(tool_choices) == 1:
-    if tool_choices[0].strip().lower() == 'none':
+    tool1 = tool_choices[0.strip()
+    if tool1.lower() == 'none':
       tool_choice = (None, None)
     else:
-      tool_choice = (tool_choices[0].strip().lower(), None)
-  elif len(tool_choices) > 1:
-    if tool_choices[0].strip().lower() == 'none':
-      tool_choice = (None, tool_choices[1].strip().lower())
-    elif tool_choices[1].strip().lower() == 'none':
-      tool_choice = (tool_choices[0].strip().lower(), None)
+      tool_choice = (tool1, None)
+  elif len(tool_choices) == 2:
+    tool1 = agents_list[0]
+    tool2 = agents_list[1]
+    if tool1.lower() == 'none' and tool2.lower() == 'none':
+      tool_choice = (None, None)
+    elif tool1.lower() == 'none' and tool2.lower() != 'none':
+      tool_choice = (None, tool2)
+    elif tool2.lower() == 'none' and tool1.lower() != 'none':
+      tool_choice = (tool1, None)
     else:
-      tool_choice = (tool_choices[0].strip().lower(), tool_choices[1].strip().lower())
+      tool_choice = (tool1, tool2)
   else:
-    tool_choice = None
+    tool_choice = (None, None)
 
   state["tool_choice"] = tool_choice
   state["which_tool"] = 0
@@ -358,14 +364,25 @@ def parser_node(state: State) -> State:
     state["loop_again"] = "finish_gracefully"
     return state
 
-  check_prompt = f'Determine if there is enough CONTEXT below to answer the original \
-QUERY TASK. If there is, respond with "PROCEED #" . If there is not enough information \
-to answer the QUERY TASK, respond with "LOOP #" \n \
-QUERY_TASK: {query_task} \n \
+  prompt = f'Using the CONTEXT below, answer the original query, which \
+was to answer the QUERY_TASK. End your answer with a "#" \
 CONTEXT: {props_string}.\n \
-'
+QUERY_TASK: {query_task}.\n '
+
+  res = chat_model.invoke(prompt)
+  trial_answer = str(res).split('<|assistant|>')[1]
+  print('parser 1 ', trial_answer)
+  state["messages"] = res
+
+  check_prompt = f'Determine if the TRIAL ANSWER below answers the original \
+QUERY TASK. If it does, respond with "PROCEED #" . If the TRIAL ANSWER did not \
+answer the QUERY TASK, respond with "LOOP #" \n \
+Only loop again if the TRIAL ANSWER did not answer the QUERY TASK. \
+TRIAL ANSWER: {trial_answer}.\n \
+QUERY_TASK: {query_task}.\n'
 
   res = chat_model.invoke(check_prompt)
+  print('parser, loop again? ', res)
 
   if str(res).split('<|assistant|>')[1].split('#')[0].strip().lower() == "loop":
     state["loop_again"] = "loop_again"
@@ -377,14 +394,7 @@ CONTEXT: {props_string}.\n \
     state["loop_again"] = None
     print('trying to break loop')
 
-    prompt = f'Using the CONTEXT below, answer the original query, which \
-was to answer the QUERY_TASK. End your answer with a "#" \
-CONTEXT: {props_string}.\n \
-QUERY_TASK: {query_task}.\n '
-
-    res = chat_model.invoke(prompt)
-
-    return {"messages": res}
+  return state
 
 def reflect_node(state: State) -> State:
   '''