Update app.py

app.py

@@ -17,6 +17,7 @@ import gradio as gr
 chat_history = []
 nltk.download('punkt_tab')
 token = os.environ.get('HF_TOKEN')
+spc = os.environ.get('SPC')
 dataset_mng = DatasetManager(os.environ.get('DATASET'))
 tokeniz = AutoTokenizer.from_pretrained("iarfmoose/t5-base-question-generator")
 model = AutoModelForSeq2SeqLM.from_pretrained("iarfmoose/t5-base-question-generator")
@@ -353,21 +354,23 @@ with gr.Blocks() as demo:
             generate_qna_button = gr.Button("Find Answer")
             generate_qna_button.click(search_question, inputs=text_input_qna, outputs=text_output_qna)
 
+        # with gr.Tab("Chat"):
+        #     gr.ChatInterface(
+        #         respond,
+        #         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)",
+        #             ),
+        #         ],
+        #     )
         with gr.Tab("Chat"):
-            gr.ChatInterface(
-                respond,
-                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)",
-                    ),
-                ],
-            )
+            gr.HTML(f"<iframe src='{spc}' width='100%' height='80%'></iframe>")
 
 demo.launch()