Upload app.py

app.py

@@ -1,90 +1,37 @@
-import os
-from gpt_index import SimpleDirectoryReader, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+_A=True
+import os
+from gpt_index import SimpleDirectoryReader,GPTSimpleVectorIndex,LLMPredictor,PromptHelper
 from langchain import OpenAI
-import gradio as gr
-import openai
-
-API_URL = "https://api.openai.com/v1/chat/completions"
-
-openai.api_key = os.environ["OPENAI_API_KEY"]
-top_p_chatgpt = 1.0
-temperature_chatgpt = 1.0
-
-def predict_chatgpt(inputs,chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):
-    if chat_counter_chatgpt != 0:
-        messages = []
-        for data in chatbot_chatgpt:
-            temp1 = {}
-            temp1["role"] = "user"
-            temp1["content"] = data[0]
-            temp2 = {}
-            temp2["role"] = "assistant"
-            temp2["content"] = data[1]
-            messages.append(temp1)
-            messages.append(temp2)
-        temp3 = {}
-        temp3["role"] = "user"
-        temp3["content"] = inputs
-        messages.append(temp3)
-
-    #os.environ['OPENAI_API_KEY'] =  openai.api_key
-    chat_counter_chatgpt += 1
-    history.append("You typed: " + inputs)
-
-    res = openai.Moderation.create(input=inputs)
-    reply = res["results"][0].flagged
-    if reply == True:
-        result= "This content is offensive and needs to be moderated"
-    else:
-        result= "This content doesn't need moderation"
-
-    response = result.split()
-    token_counter = 0
-    partial_words = ""
-    counter = 0
-    for chunk in response:
-                partial_words=partial_words+" "+chunk
-                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_chatgpt  # This resembles {chatbot: chat, state: history}
-
-def reset_textbox():
-    return gr.update(value="")
-
-def reset_chat(chatbot, state):
-    return None, []
-with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
-                #chatgpt {height: 400px; overflow: auto;}} """, theme=gr.themes.Default(primary_hue="slate") ) as ModerationAI:
-    with gr.Row():
-      with gr.Column(scale=14):
-          with gr.Box():
-              with gr.Row():
-                  with gr.Column(scale=13):
-                   inputs = gr.Textbox(label="Type any abusive sentence ⤵️    Try : I will pi** on you" )
-                  with gr.Column(scale=1):
-                      b1 = gr.Button('Submit', elem_id = 'submit').style(full_width=True)
-                      b2 = gr.Button('Clear', elem_id = 'clear').style(full_width=True)
-                  state_chatgpt = gr.State([])
-
-          with gr.Box():
-              with gr.Row():
-                  chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label="Moderation AI")
-    chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
-             
-
-    inputs.submit(reset_textbox, [], [inputs])
-    
-    b1.click( predict_chatgpt, 
-                [ inputs, chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt], 
-                [chatbot_chatgpt, state_chatgpt],)
-
-    b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
-
-    ModerationAI.queue(concurrency_count=16).launch(height= 2500, debug=True)
-
-
-
+import gradio as gr,openai
+API_URL='https://api.openai.com/v1/chat/completions'
+openai.api_key=os.environ['OPENAI_API_KEY']
+top_p_chatgpt=1.0
+temperature_chatgpt=1.0
+def predict_chatgpt(inputs,chat_counter_chatgpt,chatbot_chatgpt=[],history=[]):
+        N='user';J='content';I='role';D=chat_counter_chatgpt;C=inputs;A=history
+        if D!=0:
+                E=[]
+                for K in chatbot_chatgpt:F={};F[I]=N;F[J]=K[0];G={};G[I]='assistant';G[J]=K[1];E.append(F);E.append(G)
+                H={};H[I]=N;H[J]=C;E.append(H)
+        D+=1;A.append('You typed: '+C);O=openai.Moderation.create(input=C);P=O['results'][0].flagged
+        if P==_A:L='This content is offensive and needs to be moderated'
+        else:L="This content doesn't need moderation"
+        Q=L.split();M=0;B='';T=0
+        for R in Q:
+                B=B+' '+R
+                if M==0:A.append(' '+B)
+                else:A[-1]=B
+                S=[(A[B],A[B+1])for B in range(0,len(A)-1,2)];M+=1;yield(S,A,D)
+def reset_textbox():return gr.update(value='')
+def reset_chat(chatbot,state):return None,[]
+with gr.Blocks(css='#col_container {width: 1000px; margin-left: auto; margin-right: auto;}\n                #chatgpt {height: 400px; overflow: auto;}} ',theme=gr.themes.Default(primary_hue='slate'))as ModerationAI:
+        with gr.Row():
+                with gr.Column(scale=14):
+                        with gr.Box():
+                                with gr.Row():
+                                        with gr.Column(scale=13):inputs=gr.Textbox(label='Type any abusive sentence ⤵️    Try : I will pi** on you')
+                                        with gr.Column(scale=1):b1=gr.Button('Submit',elem_id='submit').style(full_width=_A);b2=gr.Button('Clear',elem_id='clear').style(full_width=_A)
+                                        state_chatgpt=gr.State([])
+                        with gr.Box():
+                                with gr.Row():chatbot_chatgpt=gr.Chatbot(elem_id='chatgpt',label='Moderation AI')
+        chat_counter_chatgpt=gr.Number(value=0,visible=False,precision=0);inputs.submit(reset_textbox,[],[inputs]);b1.click(predict_chatgpt,[inputs,chat_counter_chatgpt,chatbot_chatgpt,state_chatgpt],[chatbot_chatgpt,state_chatgpt]);b2.click(reset_chat,[chatbot_chatgpt,state_chatgpt],[chatbot_chatgpt,state_chatgpt]);ModerationAI.queue(concurrency_count=16).launch(height=2500,debug=_A)