Update app.py

app.py

@@ -1,69 +1,69 @@
-import gradio as gr
-from chatllm import (
-    chat_response, get_llm_model, set_llm_model, get_llm_model_info,
-    get_llm_language, set_llm_language, get_llm_sysprompt, get_llm_sysprompt_mode,
-    set_llm_sysprompt_mode, 
-)
-
-# Custom CSS for Gradio app
-css = '''
-.gradio-container{max-width: 1000px !important}
-h1{text-align:center}
-footer { visibility: hidden }
-'''
-
-# Create Gradio interface
-with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as app:
-    with gr.Column():
-        with gr.Group():
-            chatbot = gr.Chatbot(likeable=False, show_copy_button=True, show_share_button=False, layout="bubble", container=True)
-            with gr.Row():
-                chat_query = gr.Textbox(label="Search Query", placeholder="hatsune miku", value="", scale=3)
-                chat_clear = gr.Button("🗑️ Clear", scale=1)
-            with gr.Row():
-                chat_msg = gr.Textbox(label="Message", placeholder="Input message with or without query and press Enter or click Sumbit.", value="", scale=3)
-                chat_submit = gr.Button("Submit", scale=1)
-            with gr.Accordion("Additional inputs", open=False):
-                chat_model = gr.Dropdown(choices=get_llm_model(), value=get_llm_model()[0], allow_custom_value=True, label="Model")
-                chat_model_info = gr.Markdown(value=get_llm_model_info(get_llm_model()[0]), label="Model info")
-                with gr.Row():
-                    chat_mode = gr.Dropdown(choices=get_llm_sysprompt_mode(), value=get_llm_sysprompt_mode()[0], allow_custom_value=False, label="Mode")
-                    chat_lang = gr.Dropdown(choices=get_llm_language(), value="language same as user input", allow_custom_value=True, label="Output language")
-                chat_tokens = gr.Slider(minimum=1, maximum=4096, value=2000, step=1, label="Max tokens")
-                chat_temp = gr.Slider(minimum=0.1, maximum=4.0, value=0.9, step=0.1, label="Temperature")
-                chat_topp = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
-                chat_fp = gr.Slider(minimum=0.0, maximum=2.0, value=0.0, step=0.1, label="Frequency penalty")
-                chat_sysmsg = gr.Textbox(value=get_llm_sysprompt(), interactive=True, label="System message")
-        examples = gr.Examples(
-            examples = [
-                ["Describe this person.", "Kafuu Chino from Gochiusa"],
-                ["Hello", ""],
-            ],
-            inputs=[chat_msg, chat_query],
-        )
-        gr.Markdown(
-            f"""This demo was created in reference to the following demos.<br>
-    [prithivMLmods/WEB-DAC](https://huggingface.co/spaces/prithivMLmods/WEB-DAC), 
-    [featherless-ai/try-this-model](https://huggingface.co/spaces/featherless-ai/try-this-model), 
-                """
-        )
-        gr.DuplicateButton(value="Duplicate Space")
-        gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
-        gr.on(
-            triggers=[chat_msg.submit, chat_query.submit, chat_submit.click],
-            fn=chat_response,
-            inputs=[chat_msg, chatbot, chat_query, chat_tokens, chat_temp, chat_topp, chat_fp],
-            outputs=[chatbot],
-            queue=True,
-            show_progress="full",
-            trigger_mode="once",
-        )
-        chat_clear.click(lambda: (None, None, None), None, [chatbot, chat_msg, chat_query], queue=False)
-        chat_model.change(set_llm_model, [chat_model], [chat_model, chat_model_info], queue=True, show_progress="full")\
-        .success(lambda: None, None, chatbot, queue=False)
-        chat_mode.change(set_llm_sysprompt_mode, [chat_mode], [chat_sysmsg], queue=False)
-        chat_lang.change(set_llm_language, [chat_lang], [chat_sysmsg], queue=False)
-
-if __name__ == "__main__":
-    app.queue()
-    app.launch()
+import gradio as gr
+from chatllm import (
+    chat_response, get_llm_model, set_llm_model, get_llm_model_info,
+    get_llm_language, set_llm_language, get_llm_sysprompt, get_llm_sysprompt_mode,
+    set_llm_sysprompt_mode, 
+)
+
+# Custom CSS for Gradio app
+css = '''
+.gradio-container{max-width: 1000px !important}
+h1{text-align:center}
+footer { visibility: hidden }
+'''
+
+# Create Gradio interface
+with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as app:
+    with gr.Column():
+        with gr.Group():
+            chatbot = gr.Chatbot(likeable=False, show_copy_button=True, show_share_button=False, layout="bubble", container=True)
+            with gr.Row():
+                chat_query = gr.Textbox(label="Search Query", placeholder="hatsune miku", value="", scale=3)
+                chat_clear = gr.Button("🗑️ Clear", scale=1)
+            with gr.Row():
+                chat_msg = gr.Textbox(label="Message", placeholder="Input message with or without query and press Enter or click Sumbit.", value="", scale=3)
+                chat_submit = gr.Button("Submit", scale=1)
+            with gr.Accordion("Additional inputs", open=False):
+                chat_model = gr.Dropdown(choices=get_llm_model(), value=get_llm_model()[0], allow_custom_value=True, label="Model")
+                chat_model_info = gr.Markdown(value=get_llm_model_info(get_llm_model()[0]), label="Model info")
+                with gr.Row():
+                    chat_mode = gr.Dropdown(choices=get_llm_sysprompt_mode(), value=get_llm_sysprompt_mode()[0], allow_custom_value=False, label="Mode")
+                    chat_lang = gr.Dropdown(choices=get_llm_language(), value="language same as user input", allow_custom_value=True, label="Output language")
+                chat_tokens = gr.Slider(minimum=1, maximum=4096, value=2000, step=1, label="Max tokens")
+                chat_temp = gr.Slider(minimum=0.1, maximum=4.0, value=0.9, step=0.1, label="Temperature")
+                chat_topp = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
+                chat_fp = gr.Slider(minimum=0.0, maximum=2.0, value=0.0, step=0.1, label="Frequency penalty")
+                chat_sysmsg = gr.Textbox(value=get_llm_sysprompt(), interactive=True, label="System message")
+        examples = gr.Examples(
+            examples = [
+                ["Describe this person.", "Kafuu Chino from Gochiusa"],
+                ["Hello", ""],
+            ],
+            inputs=[chat_msg, chat_query],
+        )
+        gr.Markdown(
+            f"""This demo was created in reference to the following demos.<br>
+    [prithivMLmods/WEB-DAC](https://huggingface.co/spaces/prithivMLmods/WEB-DAC), 
+    [featherless-ai/try-this-model](https://huggingface.co/spaces/featherless-ai/try-this-model), 
+                """
+        )
+        gr.DuplicateButton(value="Duplicate Space")
+        gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
+        gr.on(
+            triggers=[chat_msg.submit, chat_query.submit, chat_submit.click],
+            fn=chat_response,
+            inputs=[chat_msg, chatbot, chat_query, chat_tokens, chat_temp, chat_topp, chat_fp],
+            outputs=[chatbot],
+            queue=True,
+            show_progress="full",
+            trigger_mode="once",
+        )
+        chat_clear.click(lambda: (None, None, None), None, [chatbot, chat_msg, chat_query], queue=False)
+        chat_model.change(set_llm_model, [chat_model], [chat_model, chat_model_info], queue=True, show_progress="full")\
+        .success(lambda: None, None, chatbot, queue=False)
+        chat_mode.change(set_llm_sysprompt_mode, [chat_mode], [chat_sysmsg], queue=False)
+        chat_lang.change(set_llm_language, [chat_lang], [chat_sysmsg], queue=False)
+
+if __name__ == "__main__":
+    app.queue()
+    app.launch()