Create app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "devNaam/vakilai-llama32-3b-v1"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def generate_response(prompt):
+
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=300,
+        temperature=0.7,
+        top_p=0.9
+    )
+
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    return response
+
+
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(lines=5, placeholder="Ask VakilAI a legal question..."),
+    outputs="text",
+    title="VakilAI Legal Assistant",
+    description="AI Legal assistant trained on Indian legal data."
+)
+
+iface.launch()