Update app.py

app.py

@@ -1,23 +1,29 @@
-import openai
+import lightning as L
+from lightning.app.components import ServeGradio
 import gradio as gr
 
-system_content = "You are a travel agent. Be descriptive and helpful."
-user_content = "Tell me about San Francisco"
-
-client = openai.OpenAI(
-    api_key="f722a9f6e3afd6b9999e6aee02aeac9e751ea3a67b124c3667ab50c85c7fa99e",
-    base_url="https://api.together.xyz/v1",
-    )
-
-def chat_completion: client.chat.completions.create(
-    model="mistralai/Mixtral-8x7B-Instruct-v0.1",
-    messages=[
-        {"role": "system", "content": system_content},
-        {"role": "user", "content": user_content},
-    ],
-    temperature=0.7,
-    max_tokens=1024,
-)
-response = chat_completion.choices[0].message.content
-
-gr.ChatInterface(predict).queue().launch()
+class LitGradio(ServeGradio):
+
+    inputs = gr.inputs.Textbox(default='lightning', label='name input')
+    outputs = gr.outputs.Textbox(label='output')
+    examples = [["hello lightning"]]
+
+    def predict(self, input_text):
+        return self.model(input_text)
+
+    def build_model(self):
+        fake_model = lambda x: f"hello {x}"
+        return fake_model
+
+class RootFlow(L.LightningFlow):
+    def __init__(self):
+        super().__init__()
+        self.lit_gradio = LitGradio()
+
+    def run(self):
+        self.lit_gradio.run()
+
+    def configure_layout(self):
+        return [{"name": "home", "content": self.lit_gradio}]
+
+app = L.LightningApp(RootFlow())