Fix issue

app.py

@@ -1,15 +1,28 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "internistai/base-7b-v0.2"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+def load_model():
+    try:
+        model_name = "internistai/base-7b-v0.2"
+        tokenizer = AutoTokenizer.from_pretrained(model_name)
+        model = AutoModelForCausalLM.from_pretrained(model_name)
+        return model, tokenizer
+    except Exception as e:
+        print(f"Error loading model: {e}")
+        return None, None
 
-def chat(message):
-    inputs = tokenizer(message, return_tensors="pt")
-    outputs = model.generate(**inputs)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return response
+def chat(message, model, tokenizer):
+    try:
+        inputs = tokenizer(message, return_tensors="pt")
+        outputs = model.generate(**inputs)
+        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return response
+    except Exception as e:
+        return f"Error generating response: {e}"
 
-iface = gr.Interface(fn=chat, inputs="text", outputs="text")
+model, tokenizer = load_model()
+if model is None or tokenizer is None:
+    print("Failed to load model or tokenizer. Please check the configuration.")
+
+iface = gr.Interface(fn=lambda message: chat(message, model, tokenizer), inputs="text", outputs="text")
 iface.launch()