Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "google/flan-t5-base"  # Free LLM from Hugging Face
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def solve_math_problem(problem):
+    inputs = tokenizer.encode(problem, return_tensors="pt")
+    outputs = model.generate(inputs, max_length=500)
+    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    # Breaking it down to step-by-step
+    steps = "Step-by-Step: " + result
+    return steps
+
+# Gradio interface
+iface = gr.Interface(
+    fn=solve_math_problem,
+    inputs="text",
+    outputs="text",
+    title="Maths Step-by-Step Solver with LLM",
+    description="Enter a maths problem and get a step-by-step solution using LLM."
+)
+
+iface.launch()