Update app.py

app.py

@@ -27,27 +27,23 @@ I asked Generative AI Models about their context window. Their response was intr
 The context window for a large language model (LLM) like OpenAI’s GPT refers to the maximum amount of text the model can consider at any one time when generating a response. This includes both the prompt provided by the user and the model’s generated text.
 In practical terms, the context window limits how much previous dialogue the model can “remember” during an interaction. If the interaction exceeds the context window, the model loses access to the earliest parts of the conversation. This limitation can impact the model’s consistency in long conversations or complex tasks.
 """
-
-def assign_val(inp, rng, cnt, limit):
-    if go:            
-        for ea in range(rng):
-            if go:      
-                noun_list[str(noun)].append(f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}')   
-                
-                if json_object[f'{a}{cont_list[b]}{cont_list[c]}{cont_list[d]}']=='ZNNN':
-                    a="Y"
-                    b=0
-                    c=0
-                    d=0
-
-                
-                if cnt == key_cnt-1:
-                    print('done')
-                    go=False
-                    print(list(json_object.keys())[-1])
-                else:
-                    cnt+=1
-
+def get_sen_list(text):
+    sen_list=[]
+    blob = TextBlob(text)
+    for sentence in blob.sentences:
+        sen_list.append(str(sentence))
+    return sen_list
+    
+def proc_sen(sen_list,cnt):
+    blob_n = TextBlob(sen_list[cnt])
+    noun_p=blob_n.noun_phrases
+    noun_box1=[]
+    for ea in blob_n.parse().split(" "):
+        n=ea.split("/")
+        if n[1] == "NN":
+            noun_box1.append(n[0])
+    json_object={'sentence':sen_list[cnt],'noun_phrase':noun_p,'nouns':noun_box}    
+    return json_object
 
 def get_nouns(text=text,steps=1):
     control_len=control_json['leng']-steps
@@ -57,37 +53,25 @@ def get_nouns(text=text,steps=1):
     val_len=len(control_val)
     print(control_char)
     print(control_val)
+    
     json_object={}
-    sen_list=[]
     noun_list={}
-    noun_box=[]
-    #print(text)
-    blob = TextBlob(text)
-    for sentence in blob.sentences:
-        sen_list.append(str(sentence))
-
-
-    noun_box=[]
-    for ea in blob.parse().split(" "):
-        #print(ea)
-        n=ea.split("/")
-        if n[1] == "NN":
-            noun_box.append(n[0])
+    step_list=[]
+    step_cont_box=[]
+    
+    sen_list=get_sen_list(text)
 
-        
-    print(sen_list)
     key_cnt=len(sen_list)
-    noun_cnt=len(noun_box)
     print(key_cnt)
-    print(noun_cnt)
+    #noun_cnt=len(noun_box)
+    #print(noun_cnt)
     
     big_cnt=0
     cnt=0
     go=True
-    a="Z"
 
     n_cnt=0
-    nx=noun_cnt
+    nx=key_cnt
     while True:
         if nx > 1:
             n_cnt+=1
@@ -99,23 +83,7 @@ def get_nouns(text=text,steps=1):
             print("#######")
             steps=n_cnt
             break
-            
-    step_allot=char_len**steps
-    print(step_allot)
-    div_raw=(step_allot/noun_cnt)
-    print(div_raw)
-    div_steps=int(step_allot/noun_cnt)
-    print(div_steps)
-    div_remain=div_raw-div_steps
-    print(div_remain)
-    steps_mult=div_remain*char_len
-    #steps_mult=div_remain*char_len
-    print(steps_mult)
-    print(math.ceil(steps_mult))
-    step_list=[]
 
-    step_control=""
-    step_cont_box=[]
     for ii in range(steps):
         print(ii)
         step_cont_box.append(0)
@@ -123,11 +91,8 @@ def get_nouns(text=text,steps=1):
     mod=0
     pos=len(step_cont_box)-1
     
-    if noun_cnt > step_allot:
-        go=False
-        print("Increase Steps")
     if go:
-        for i, ea in enumerate(noun_box):
+        for i, ea in enumerate(sen_list):
             if go:
                 if cnt > char_len-1:
                     #print(step_cont_box)
@@ -145,20 +110,21 @@ def get_nouns(text=text,steps=1):
                     cnt+=1
                 print(step_cont_box)
                 out_js=""
-                for i,j in enumerate(step_cont_box):
+                for iii,j in enumerate(step_cont_box):
                     print(j)
                     out_js = out_js+control_char[j]
-
-                json_object[out_js]={'nouns':ea}
+                sen_obj=proc_sen(sen_list,i)
+                #json_out[out_js]={'nouns':ea}
+                json_out[out_js]=sen_obj
                 
                 big_cnt+=1
-                if big_cnt==noun_cnt:
+                if big_cnt==key_cnt:
                     print("DONE")
                     go=False
         
     
     
-    return json_object,noun_list
+    return json_out,noun_list