Update app.py

app.py

@@ -1,3 +1,40 @@
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+Duplicate from ysharma/ChatGPTwithAPI
+659118f
+about 10 hours ago
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 import gradio as gr
 import os 
 import json 
@@ -6,8 +43,9 @@ import requests
 #Streaming endpoint 
 API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
 
+#Testing with my Open AI Key 
+#OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") 
 
-openai_api_key = "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"
 def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[], history=[]):  #repetition_penalty, top_k
 
     payload = {
@@ -91,22 +129,35 @@ def predict(inputs, top_p, temperature, openai_api_key, chat_counter, chatbot=[]
 def reset_textbox():
     return gr.update(value='')
 
-title = """<h1 align="center"> ChatGPT API</h1>"""
+title = """<h1 align="center">🔥ChatGPT API 🚀Streaming🚀</h1>"""
 description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
-
+```
+User: <utterance>
+Assistant: <utterance>
+User: <utterance>
+Assistant: <utterance>
+...
+```
+In this app, you can explore the outputs of a gpt-3.5-turbo LLM.
+"""
                 
 with gr.Blocks(css = """#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
                 #chatbot {height: 520px; overflow: auto;}""") as demo:
-        with gr.Column(elem_id = "col_container"):
+    gr.HTML(title)
+    gr.HTML('''<center><Lisa's Chatbot></center>''')
+    with gr.Column(elem_id = "col_container"):
         openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here")
         chatbot = gr.Chatbot(elem_id='chatbot') #c
-        inputs = gr.Textbox(placeholder= "Type here!", label= "Type an input and press Enter") #t
+        inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
         state = gr.State([]) #s
         b1 = gr.Button()
     
+        #inputs, top_p, temperature, top_k, repetition_penalty
         with gr.Accordion("Parameters", open=False):
             top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
             temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
+            #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
+            #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
             chat_counter = gr.Number(value=0, visible=False, precision=0)
 
     inputs.submit( predict, [inputs, top_p, temperature, openai_api_key, chat_counter, chatbot, state], [chatbot, state, chat_counter],)
@@ -114,5 +165,6 @@ with gr.Blocks(css = """#col_container {width: 1000px; margin-left: auto; margin
     b1.click(reset_textbox, [], [inputs])
     inputs.submit(reset_textbox, [], [inputs])
                     
+    #gr.Markdown(description)
     demo.queue().launch(debug=True)