Update app.py

app.py

@@ -9,7 +9,6 @@ import gradio as gr
 import os
 import requests
 
-# Include the HTML code for displaying the image
 html_temp = """
 <div style="position: absolute; top: 0; right: 0;">
     <img src='https://huggingface.co/spaces/NerdN/open-gpt-Image-Prompter/blob/main/_45a03b4d-ea0f-4b81-873d-ff6b10461d52.jpg' alt='Your Image' style='width:100px;height:100px;'>
@@ -25,13 +24,14 @@ def build_input_prompt(message, chatbot, system_prompt):
     """
     Constructs the input prompt string from the chatbot interactions and the current message.
     """
-    input_prompt = "\n" + system_prompt + "</s>\n\n"
+    input_prompt = "<|system|>\n" + system_prompt + "</s>\n<|user|>\n"
     for interaction in chatbot:
-        input_prompt = input_prompt + str(interaction[0]) + "</s>\n\n" + str(interaction[1]) + "\n</s>\n\n"
+        input_prompt = input_prompt + str(interaction[0]) + "</s>\n<|assistant|>\n" + str(interaction[1]) + "\n</s>\n<|user|>\n"
 
-    input_prompt = input_prompt + str(message) + "</s>\n"
+    input_prompt = input_prompt + str(message) + "</s>\n<|assistant|>"
     return input_prompt
 
+
 def post_request_beta(payload):
     """
     Sends a POST request to the predefined Zephyr-7b-Beta URL and returns the JSON response.
@@ -40,6 +40,7 @@ def post_request_beta(payload):
     response.raise_for_status()  # Will raise an HTTPError if the HTTP request returned an unsuccessful status code
     return response.json()
 
+
 def predict_beta(message, chatbot=[], system_prompt=""):
     input_prompt = build_input_prompt(message, chatbot, system_prompt)
     data = {
@@ -67,12 +68,10 @@ def predict_beta(message, chatbot=[], system_prompt=""):
 
 def test_preview_chatbot(message, history):
     response = predict_beta(message, history, SYSTEM_PROMPT)
-    text_start = response.rfind("", ) + len("")
+    text_start = response.rfind("<|assistant|>", ) + len("<|assistant|>")
     response = response[text_start:]
+    return response
 
-    # Include the image HTML code in the response
-    response_with_image = f"{html_temp}\n{response}"
-    return response_with_image
 
 welcome_preview_message = f"""
 Expand your imagination and broaden your horizons with LLM. Welcome to **{TITLE}**!:\nThis is a chatbot that can generate detailed prompts for image generation models based on simple and short user input.\nSay something like: 
@@ -80,10 +79,8 @@ Expand your imagination and broaden your horizons with LLM. Welcome to **{TITLE}
 "{EXAMPLE_INPUT}"
 """
 
-# Use the modified test_preview_chatbot function
 chatbot_preview = gr.Chatbot(layout="panel", value=[(None, welcome_preview_message)])
 textbox_preview = gr.Textbox(scale=7, container=False, value=EXAMPLE_INPUT)
 
-# Use the modified test_preview_chatbot function
 demo = gr.ChatInterface(test_preview_chatbot, chatbot=chatbot_preview, textbox=textbox_preview)
-demo.launch(share=True)
+demo.launch(share=True)