add init files

src/app.py

@@ -13,7 +13,7 @@ def predict(message, history):
     for human, assistant in history:
         history_messages.append(HumanMessage(content=human))
         history_messages.append(AIMessage(content=assistant))
-    history_messages.append(HumanMessage(content=message))
+    history_messages.append(HumanMessage(content=message.text))
 
     response_message = ''
     for chunk in chat.stream(history_messages):
@@ -23,7 +23,7 @@ def predict(message, history):
 
 css = """
 .container {
-    height: 100vh;
+    # min-height: calc(100vh - 300px);
 }
 """
 
@@ -31,27 +31,43 @@ with gr.Blocks(css=css) as app:
     with gr.Tab('Chat'):
         with gr.Row():
             with gr.Column(scale=2, min_width=600):
-                gr.ChatInterface(predict)
+                gr.ChatInterface(
+                    predict,
+                    multimodal=True,
+                    chatbot=gr.Chatbot(elem_id="chatbot", height=600),
+                    textbox=gr.MultimodalTextbox(),
+                )
             with gr.Column(scale=1, min_width=300):
                 with gr.Accordion('Select Model', open=True):
-                    gr.CheckboxGroup(
-                        choices=deep_seek_llm.support_models,
-                        type="value",
-                        label="Model",
-                        key="model",
-                    )
-                    gr.CheckboxGroup(
-                        choices=deep_seek_llm.support_models,
-                        type="value",
-                        label="Model",
-                        key="model",
-                    )
-                    gr.CheckboxGroup(
-                        choices=deep_seek_llm.support_models,
-                        type="value",
-                        label="Model",
-                        key="model",
-                    )
-
-
-app.launch(server_name='0.0.0.0')
+                    with gr.Column():
+                        gr.Dropdown(
+                            choices=deep_seek_llm.support_models,
+                            type="value",
+                            label="Model",
+                            key="model",
+                        )
+                        gr.Slider(
+                            minimum=0.0,
+                            maximum=1.0,
+                            step=0.1,
+                            label="Temperature",
+                            key="temperature",
+                        )
+                        gr.Number(
+                            minimum=1024,
+                            maximum=1024 * 20,
+                            step=128,
+                            value=4096,
+                            label="Max Tokens",
+                            key="max_tokens",
+                        )
+
+    with gr.Tab('Text to Image'):
+        with gr.Row():
+            with gr.Column(scale=2, min_width=600):
+                gr.Image(label="Input Image")
+            with gr.Column(scale=1, min_width=300):
+                gr.Textbox(label="LoRA")
+
+
+app.launch(debug=True)