Update app.py

app.py

@@ -7,7 +7,6 @@ css_file = os.path.join(current_dir, "style.css")
 
 initial_prompt = "You are a helpful assistant."
 
-
 def parse_text(text):
     lines = text.split("\n")
     for i,line in enumerate(lines):
@@ -24,105 +23,116 @@ 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}{''.join([f'{c['role']}: {c['content']}\n' for c in context])}",
-        max_tokens=1024,
-        n=1,
-        stop=None,
-        temperature=0.5,
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[system, *context],
     )
+    if raw:
+        return response
+    else:
+        statistics = f'This conversation Tokens usage【{response["usage"]["total_tokens"]} / 4096】 （ Question + above {response["usage"]["prompt_tokens"]}，Answer {response["usage"]["completion_tokens"]} ）'
+        message = response["choices"][0]["message"]["content"]
 
-    message = response.choices[0].text
-    message_with_stats = f"{message}"
-    return message, parse_text(message_with_stats)
+        message_with_stats = f'{message}'
+#         message_with_stats = markdown.markdown(message_with_stats)
 
+        return message, parse_text(message_with_stats)
+        #return message
 
-def predict(input_sentence):
+def predict(chatbot, input_sentence, system, context):
     if len(input_sentence) == 0:
         return []
-
-    chatbot.append((input_sentence, message_with_stats))
-
     context.append({"role": "user", "content": f"{input_sentence}"})
 
-    message, message_with_stats = get_response(systemPrompt.value["content"], context)
+    message, message_with_stats = get_response(system, context)
 
     context.append({"role": "assistant", "content": message})
 
-    return chatbot, context
+    chatbot.append((input_sentence, message_with_stats))
 
+    return chatbot, context
 
-def retry():
+def retry(chatbot, system, context):
     if len(context) == 0:
         return [], []
-
-    context[-1]["content"] = "Could you rephrase that?"
-
-    message, message_with_stats = get_response(systemPrompt.value["content"], context[:-1])
-
+    message, message_with_stats = get_response(system, context[:-1])
     context[-1] = {"role": "assistant", "content": message}
 
     chatbot[-1] = (context[-2]["content"], message_with_stats)
-
     return chatbot, context
 
-
-def delete_last_conversation():
+def delete_last_conversation(chatbot, context):
     if len(context) == 0:
         return [], []
-
     chatbot = chatbot[:-1]
     context = context[:-2]
     return chatbot, context
 
+def reduce_token(chatbot, system, context):
+    context.append({"role": "user", "content": "请帮我总结一下上述对话的内容，实现减少tokens的同时，保证对话的质量。在总结中不要加入这一句话。"})
 
-def reduce_token():
-    context.append({"role": "user", "content": "Please summarize our conversation and reduce tokens used. Don't include this prompt."})
-
-    response = get_response(systemPrompt.value["content"], context, raw=True)
+    response = get_response(system, context, raw=True)
 
-    optmz_str = f'Okay, we talked about: {response.choices[0].text}\n\nTotal tokens used this conversation: {response.choices[0].logprobs.top_logprobs[0].tokens}'
-
-    chatbot.append(("Please summarize our conversation and reduce tokens used. Don't include this prompt.", parse_text(optmz_str)))
-    context = [{"role": "assistant", "content": f"Okay, we talked about: {response.choices[0].text}"}]
+    statistics = f'本次对话Tokens用量【{response["usage"]["completion_tokens"]+12+12+8} / 4096】'
+    optmz_str = markdown.markdown( f'好的，我们之前聊了:{response["choices"][0]["message"]["content"]}\n\n================\n\n{statistics}' )
+    chatbot.append(("请帮我总结一下上述对话的内容，实现减少tokens的同时，保证对话的质量。", optmz_str))
+    
+    context = []
+    context.append({"role": "user", "content": "我们之前聊了什么?"})
+    context.append({"role": "assistant", "content": f'我们之前聊了：{response["choices"][0]["message"]["content"]}'})
     return chatbot, context
 
 
 def reset_state():
     return [], []
 
-
 def update_system(new_system_prompt):
     return {"role": "system", "content": new_system_prompt}
 
-
-title = """<h1 align="center">You Ask, I Answer - Chatbot</h1>"""
-
-description = "This chatbot is designed to assist you with any questions or tasks you may have. Simply type in your query and the chatbot will provide you with a helpful response."
-
-systemPrompt = gr.inputs.Textbox(lines=2, label="Enter the system prompt you would like to use:")
-userInput = gr.inputs.Textbox(lines=2, label="Enter your message:")
-
-chatbot_output = gr.outputs.HTML(type="auto")
-
-chatbot_interface = gr.Interface(
-predict,
-[systemPrompt, userInput],
-chatbot_output,
-title=title,
-description=description,
-theme="compact",
-layout="vertical",
-examples=[
-["Can you help me with my math homework?", "Sure, what do you need help with?"],
-["How can I make pizza from scratch?", "First, you will need to gather the ingredients..."]
-],
-article="https://openai.com/blog/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-learning-2021/"
-)
-
-if name == "main":
-chatbot_interface.launch(debug=True)
+title = """<h1 align="center">Tu întrebi și eu răspund.</h1>"""
+description = """<div align=center>
+
+Will not describe your needs to ChatGPT？You Use [ChatGPT Shortcut](https://newzone.top/chatgpt/)
+
+</div>
+"""
+
+with gr.Blocks() as demo:
+    gr.HTML(title)
+    chatbot = gr.Chatbot().style(color_map=("#A238FF", "#A238FF"))
+    context = gr.State([])
+    systemPrompt = gr.State(update_system(initial_prompt))
+
+    with gr.Row():
+        with gr.Column(scale=12):
+            txt = gr.Textbox(show_label=False, placeholder="Please enter any of your needs here").style(container=False)
+        with gr.Column(min_width=50, scale=1):
+            #submitBtn = gr.Button("🚀 Submit", variant="Primary")
+            submitBtn = gr.Button("🚀 Submit").style(css={"background-color": "#A238FF"})
+    with gr.Row():
+        emptyBtn = gr.Button("🧹 New conversation")
+        retryBtn = gr.Button("🔄 Resubmit")
+        delLastBtn = gr.Button("🗑️ Delete conversation")
+        #reduceTokenBtn = gr.Button("♻️ Optimize Tokens")
+
+    #newSystemPrompt = gr.Textbox(show_label=True, placeholder=f"Setting System Prompt...", label="Change System prompt").style(container=True)
+    #systemPromptDisplay = gr.Textbox(show_label=True, value=initial_prompt, interactive=False, label="Current System prompt").style(container=True)
+    
+    #gr.Markdown(description)
+    
+    txt.submit(predict, [chatbot, txt, systemPrompt, context], [chatbot, context], show_progress=True)
+    txt.submit(lambda :"", None, txt)
+    submitBtn.click(predict, [chatbot, txt, systemPrompt, context], [chatbot, context], show_progress=True)
+    submitBtn.click(lambda :"", None, txt)
+    emptyBtn.click(reset_state, outputs=[chatbot, context])
+    #newSystemPrompt.submit(update_system, newSystemPrompt, systemPrompt)
+    #newSystemPrompt.submit(lambda x: x, newSystemPrompt, systemPromptDisplay)
+    #newSystemPrompt.submit(lambda :"", None, newSystemPrompt)
+    retryBtn.click(retry, [chatbot, systemPrompt, context], [chatbot, context], show_progress=True)
+    delLastBtn.click(delete_last_conversation, [chatbot, context], [chatbot, context], show_progress=True)
+    #reduceTokenBtn.click(reduce_token, [chatbot, systemPrompt, context], [chatbot, context], show_progress=True)
+
+
+demo.launch()