Upload app.py

app.py

@@ -1,92 +1,44 @@
-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 asked: " + inputs)
-   
-    # load index from disk
-    index = GPTSimpleVectorIndex.load_from_disk('IPCIndex.json')
-
-    # query the index
-    result = index.query(inputs)
-    response = result.response.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 PLCoversationalAI:
-    with gr.Row():
-      with gr.Column(scale=14):
-          with gr.Box():
-              with gr.Row():
-                  with gr.Column(scale=13):
-                   inputs = gr.Textbox(label="Ask anything about Productization Labs ⤵️    Try : Who is Gopala" )
-                  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="Productization Labs Conversational 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])
-
-    PLCoversationalAI.queue(concurrency_count=16).launch(height= 2500, debug=True)
-
-
-
-
-
+_E='You are a Legal advisor. Do not answer anything other than legal matter queries.'
+_D='system'
+_C=True
+_B='role'
+_A='content'
+import os,gradio as gr,json,requests,openai
+try:openai.api_key=os.environ['OPENAI_API_KEY']
+except KeyError:
+        error_message='System is at capacity right now.Please try again later';print(error_message)
+        def chatbot(input):return error_message
+else:messages=[{_B:_D,_A:_E}]
+messages=[{_B:_D,_A:_E}]
+API_URL='https://api.openai.com/v1/chat/completions'
+top_p_chatgpt=1.0
+temperature_chatgpt=1.0
+def chatbot(inputs,chat_counter_chatgpt,chatbot_chatgpt=[],history=[]):
+        X='delta';W='choices';V='gpt-3.5-turbo';U='frequency_penalty';T='presence_penalty';S='stream';R='top_p';Q='temperature';P='messages';O='model';J='user';F=chat_counter_chatgpt;E=inputs;A=history;K={O:V,P:[{_B:J,_A:f"{E}"}],Q:1.0,R:1.0,'n':1,S:_C,T:0,U:0};Y={'Content-Type':'application/json','Authorization':f"Bearer {openai.api_key}"}
+        if F!=0:
+                C=[]
+                for L in chatbot_chatgpt:G={};G[_B]=J;G[_A]=L[0];H={};H[_B]='assistant';H[_A]=L[1];C.append(G);C.append(H)
+                I={};I[_B]=J;I[_A]=E;C.append(I);K={O:V,P:C,Q:temperature_chatgpt,R:top_p_chatgpt,'n':1,S:_C,T:0,U:0}
+        F+=1;A.append('You asked:  '+E);Z=requests.post(API_URL,headers=Y,json=K,stream=_C);M=0;D='';N=0
+        for B in Z.iter_lines():
+                if N==0:N+=1;continue
+                if B.decode():
+                        B=B.decode()
+                        if len(B)>13 and _A in json.loads(B[6:])[W][0][X]:
+                                D=D+json.loads(B[6:])[W][0][X][_A]
+                                if M==0:A.append(' '+D)
+                                else:A[-1]=D
+                                a=[(A[B],A[B+1])for B in range(0,len(A)-1,2)];M+=1;yield(a,A,F)
+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 ConversationalAILegal:
+        with gr.Row():
+                with gr.Column(scale=14):
+                        with gr.Box():
+                                with gr.Row():
+                                        with gr.Column(scale=13):inputs=gr.Textbox(label='Ask me anything ⤵️ Try: Binary equivalent of 10. Since this query is not related to legal, ChatGPT provides irrelavant response. Try: How to draft a legal notice. It works. ')
+                                        with gr.Column(scale=1):b1=gr.Button('Submit',elem_id='submit').style(full_width=_C);b2=gr.Button('Clear',elem_id='clear').style(full_width=_C)
+                                        state_chatgpt=gr.State([])
+                        with gr.Box():
+                                with gr.Row():chatbot_chatgpt=gr.Chatbot(elem_id='chatgpt',label='Conversational AI Legal')
+        chat_counter_chatgpt=gr.Number(value=0,visible=False,precision=0);inputs.submit(reset_textbox,[],[inputs]);b1.click(chatbot,[inputs,chat_counter_chatgpt,chatbot_chatgpt,state_chatgpt],[chatbot_chatgpt,state_chatgpt]);b2.click(reset_chat,[chatbot_chatgpt,state_chatgpt],[chatbot_chatgpt,state_chatgpt]);ConversationalAILegal.queue(concurrency_count=16).launch(height=2500,debug=_C)