Create app.py

app.py

@@ -0,0 +1,22 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "UrFavB0i/Fine-tuned-Falcon7B-skincare-chatbot"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def predict(history, input_text):
+    history.append({"role": "user", "content": input_text})
+    inputs = tokenizer(" ".join([item["content"] for item in history if item["role"] == "user"]), return_tensors="pt")
+    outputs = model.generate(**inputs)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    history.append({"role": "bot", "content": response})
+    return history, history
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=[gr.inputs.State(), gr.inputs.Textbox(lines=2, placeholder="Enter text here...")],
+    outputs=["state", "chatbot"]
+)
+
+iface.launch()