Update app.py

app.py

@@ -33,4 +33,129 @@ for r in stream:
         break
     # yield the generated token
     print(r.token.text, end = "")
-    # yield r.token.text
+    # yield r.token.text
+
+
+#######################################################################
+#Darstellung mit Gradio
+
+with open("custom.css", "r", encoding="utf-8") as f:
+    customCSS = f.read()
+    
+with gr.Blocks(theme=small_and_beautiful_theme) as demo:
+    history = gr.State([])
+    user_question = gr.State("")
+    gr.Markdown("KIs am LI - wähle aus, was du bzgl. KI-Bots ausprobieren möchtest!")
+    with gr.Tabs():
+        with gr.TabItem("LI-Chat"):
+            with gr.Row():
+                gr.HTML(title)
+                status_display = gr.Markdown("Erfolg", elem_id="status_display")
+            gr.Markdown(description_top)
+            with gr.Row(scale=1).style(equal_height=True):
+                with gr.Column(scale=5):
+                    with gr.Row(scale=1):
+                        chatbotGr = gr.Chatbot(elem_id="LI_chatbot").style(height="100%")
+                    with gr.Row(scale=1):
+                        with gr.Column(scale=12):
+                            user_input = gr.Textbox(
+                                show_label=False, placeholder="Gib deinen Text / Frage ein."
+                            ).style(container=False)
+                        with gr.Column(min_width=100, scale=1):
+                            submitBtn = gr.Button("Absenden")
+                        with gr.Column(min_width=100, scale=1):
+                            cancelBtn = gr.Button("Stoppen")
+                    with gr.Row(scale=1):
+                        emptyBtn = gr.Button(
+                            "🧹 Neuer Chat",
+                        )
+                with gr.Column():
+                    with gr.Column(min_width=50, scale=1):
+                        with gr.Tab(label="Nur zum Testen:"):
+                            gr.Markdown("# Parameter")
+                            top_p = gr.Slider(
+                                minimum=-0,
+                                maximum=1.0,
+                                value=0.95,
+                                step=0.05,
+                                interactive=True,
+                                label="Top-p",
+                            )
+                            temperature = gr.Slider(
+                                minimum=0.1,
+                                maximum=2.0,
+                                value=1,
+                                step=0.1,
+                                interactive=True,
+                                label="Temperature",
+                            )
+                            max_length_tokens = gr.Slider(
+                                minimum=0,
+                                maximum=512,
+                                value=512,
+                                step=8,
+                                interactive=True,
+                                label="Max Generation Tokens",
+                            )
+                            max_context_length_tokens = gr.Slider(
+                                minimum=0,
+                                maximum=4096,
+                                value=2048,
+                                step=128,
+                                interactive=True,
+                                label="Max History Tokens",
+                            )
+            gr.Markdown(description)
+
+        with gr.TabItem("Übersetzungen"):
+            with gr.Row():
+                    gr.Textbox(
+                                show_label=False, placeholder="Ist noch in Arbeit..."
+                            ).style(container=False)
+        with gr.TabItem("Code-Generierungen"):
+            with gr.Row():
+                    gr.Textbox(
+                                show_label=False, placeholder="Ist noch in Arbeit..."
+                            ).style(container=False)
+    
+    predict_args = dict(
+        fn=predict,
+        inputs=[
+            user_question,
+            chatbotGr,
+            history,
+            top_p,
+            temperature,
+            max_length_tokens,
+            max_context_length_tokens,
+        ],
+        outputs=[chatbotGr, history, status_display],
+        show_progress=True,
+    )
+        
+    #neuer Chat
+    reset_args = dict(
+        #fn=reset_chat, inputs=[], outputs=[user_input, status_display]
+        fn=reset_textbox, inputs=[], outputs=[user_input, status_display]
+    )
+            
+    # Chatbot
+    transfer_input_args = dict(
+        fn=transfer_input, inputs=[user_input], outputs=[user_question, user_input, submitBtn], show_progress=True
+    )
+        
+    #Listener auf Start-Click auf Button oder Return
+    predict_event1 = user_input.submit(**transfer_input_args).then(**predict_args)
+    predict_event2 = submitBtn.click(**transfer_input_args).then(**predict_args)
+        
+    #Listener, Wenn reset...
+    emptyBtn.click(
+        reset_state,
+        outputs=[chatbotGr, history, status_display],
+        show_progress=True,
+    )
+    emptyBtn.click(**reset_args)
+
+demo.title = "LI Chat"
+#demo.queue(concurrency_count=1).launch(share=True) 
+demo.queue(concurrency_count=1).launch(debug=True)