Update app.py

app.py

@@ -1,5 +1,9 @@
 import gradio as gr
 import openai
+import os
+
+current_dir = os.path.dirname(os.path.abspath(__file__))
+css_file = os.path.join(current_dir, "style.css")
 
 initial_prompt = "You are a helpful assistant."
 
@@ -19,26 +23,23 @@ def parse_text(text):
                 lines[i] = '<br/>'+line.replace(" ", "&nbsp;")
     return "".join(lines)
 
-def get_response(system, context, raw = False):
+def get_response(system, context, raw=False):
     openai.api_key = "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"
     response = openai.Completion.create(
         engine="text-davinci-002",
         prompt=f"{system}\n\n{context}",
-        temperature=0.7,
+        temperature=0.5,
         max_tokens=1024,
         top_p=1,
         frequency_penalty=0,
-        presence_penalty=0,
-        stop=None,
+        presence_penalty=0
     )
+
     if raw:
         return response
     else:
-        statistics = f'This conversation Tokens usage【{response["total_characters"]} / 2048】 （ Question + above {response["prompt"]["length"]}，Answer {response["choices"][0]["length"]} ）'
-        message = response.choices[0].text
-
-        message_with_stats = f'{message}\n\n{statistics}'
-
+        message = response.choices[0].text.strip()
+        message_with_stats = f'{message}'
         return message, parse_text(message_with_stats)
 
 def predict(chatbot, input_sentence, system, context):
@@ -48,26 +49,43 @@ def predict(chatbot, input_sentence, system, context):
 
     message, message_with_stats = get_response(system, context)
 
-    context.append(message)
-
     chatbot.append((input_sentence, message_with_stats))
 
+    context.append(message)
+
     return chatbot, context
 
 def retry(chatbot, system, context):
     if len(context) == 0:
         return [], []
-    message, message_with_stats = get_response(system, context[:-1])
-    context[-1] = message
+    context.pop()
+    chatbot.pop()
 
-    chatbot[-1] = (context[-2], message_with_stats)
     return chatbot, context
 
 def delete_last_conversation(chatbot, context):
     if len(context) == 0:
         return [], []
-    chatbot = chatbot[:-1]
-    context = context[:-2]
+    chatbot.pop()
+    context.pop()
+    context.pop()
+
+    return chatbot, context
+
+def reduce_token(chatbot, system, context):
+    if len(context) == 0:
+        return [], []
+    context.pop()
+
+    context.append("Please help me summarize our conversation to reduce token usage. Don't include this sentence in the summary.")
+    message, message_with_stats = get_response(system, context, raw=True)
+    summary = message.choices[0].text.strip()
+
+    statistics = f'This conversation token usage [{message.total_tokens} / 2048] (Prompt: {message.prompt_length}, Response: {message.choices[0].length})'
+
+    chatbot.append(("Please help me summarize our conversation to reduce token usage.", summary + statistics))
+
+    context.append(f"We talked about {summary}")
     return chatbot, context
 
 def reset_state():
@@ -76,23 +94,32 @@ def reset_state():
 def update_system(new_system_prompt):
     return new_system_prompt
 
-title = """<h1 align="center">Tu întrebi și eu răspund.</h1>"""
+title = """<h1 align="center">You ask, I answer.</h1>"""
 description = """<div align=center>
 
-Will not describe your needs to ChatGPT？You Use [ChatGPT Shortcut](https://newzone.top/chatgpt/)
+Not interested in describing your needs to ChatGPT? Use [ChatGPT Shortcut](https://newzone.top/chatgpt/)
 
 </div>
 """
 
-gr.Interface(
-    predict, 
-    inputs=["textbox", "text", "text", "text"],
-    outputs="text",
-    title=title,
-    description=description,
-    allow_flagging=False,
-    theme="huggingface",
-    layout="vertical",
-    examples=[["What's your name?", "I don't have a name. How can I assist you today?", "", ""]],
-    interpretation="default"
-).launch()
+with gr.blocks() as demo:
+    gr.html(title)
+    chatbot = []
+    context = [initial_prompt]
+    system = initial_prompt
+
+    input_text = gr.inputs.Textbox(lines=1, placeholder="Enter your message here...")
+    chat_history = gr.outputs.HTML(markdown=False)
+
+    gradio_ui = gr.Interface(fn=lambda message: predict(chatbot, message, system, context),
+                             inputs=input_text,
+                             outputs=chat_history,
+                             title=title,
+                             description=description,
+                             theme="compact",
+                             allow_flagging=False,
+                             layout="vertical",
+                             css=css_file,
+                             )
+
+    gradio_ui.launch()