Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load Model & Tokenizer
+MODEL_NAME = "tezodipta/MindEase-Assistant-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16, device_map="auto")
+
+# Function to Generate Response
+def generate_response(prompt):
+    input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(model.device)
+    output = model.generate(input_ids, max_length=200, temperature=0.7, do_sample=True, top_p=0.9)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+# Gradio UI
+interface = gr.Interface(
+    fn=generate_response,
+    inputs="text",
+    outputs="text",
+    title="MindEase AI Assistant",
+    description="Chat with a Mental Health AI Assistant",
+)
+
+interface.launch(server_name="0.0.0.0", server_port=7860, share=True)