Update app.py

app.py

@@ -1,76 +1,21 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
+from interface import create_demo
+from pdfchatbot import PDFChatBot
 
+# Create Gradio interface
+demo, chat_history, show_img, txt, submit_button, uploaded_pdf = create_demo()
 
-title = "🤖AI ChatBot"
-description = "Building open-domain chatbots is a challenging area for machine learning research."
-examples = [["FA 서비스는 어떤 서비스인가요?"], ["풋살 경기장 규격은 어떻게 되나요?"], ["풋살화는 어떤걸 신어야 하나요?"]]
+# Create PDFChatBot instance
+pdf_chatbot = PDFChatBot()
 
+# Set up event handlers
+with demo:
+    # Event handler for uploading a PDF
+    uploaded_pdf.upload(pdf_chatbot.render_file, inputs=[uploaded_pdf], outputs=[show_img])
 
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    title=title,
-    description=description,
-    examples=examples,
-    theme='ParityError/Anime',
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
+    # Event handler for submitting text and generating response
+    submit_button.click(pdf_chatbot.add_text, inputs=[chat_history, txt], outputs=[chat_history], queue=False).\
+        success(pdf_chatbot.generate_response, inputs=[chat_history, txt, uploaded_pdf], outputs=[chat_history, txt]).\
+        success(pdf_chatbot.render_file, inputs=[uploaded_pdf], outputs=[show_img])
 
 if __name__ == "__main__":
     demo.launch()