Update app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr 
+
+hf_api_key = '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'
+
+#FalcomLM-instruct endpoint on the text_generation library
+#client = Client("https://api-inference.huggingface.co/models/tiiuae/falcon-40b-instruct", headers={"Authorization": f"Bearer {hf_api_key}"}, timeout=120)
+#client = Client("https://wjmh73a2pphfr6ed.us-east-1.aws.endpoints.huggingface.cloud", headers={"Authorization": f"Bearer {hf_api_key}"}, timeout=120)
+client = Client("https://api-inference.huggingface.co/models/tiiuae/falcon-7b-instruct", headers={"Authorization": f"Bearer {hf_api_key}"}, timeout=120)
+
+def generate(input):
+    output = client.generate(input,max_new_tokens=1024).generated_text
+    return output
+
+def respond(message, chat_history):
+        #No LLM here, just respond with a random pre-made message
+        '''bot_message = random.choice(["Tell me more about it", 
+                                     "Cool, but I'm not interested", 
+                                     "Hmmmm, ok then"]) '''
+        bot_message = generate(message)
+
+        chat_history.append((message, bot_message))
+        return "", chat_history
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot() #just to fit the notebook
+    msg = gr.Textbox(label="Prompt")
+    btn = gr.Button("Submit")
+    
+    clear = gr.ClearButton(components=[msg, chatbot], value="Clear console")
+
+    btn.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
+    msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot]) #Press enter to submit
+demo.launch(height=240)