Add a app.py file

app.py

@@ -0,0 +1,58 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+# Load the model and tokenizer
+def load_model_and_tokenizer():
+    model_name = "AIModels24/Indian_Constitution"  # Replace with your model name
+
+    # Define quantization configuration for 4-bit quantization
+    quant_config = BitsAndBytesConfig(load_in_4bit=True)  # 4-bit quantization
+
+    # Load the tokenizer
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+    # Load the model with 4-bit quantization
+    model = AutoModelForCausalLM.from_pretrained(
+        model_name,
+        quantization_config=quant_config,
+        device_map="auto"  # Automatically use available devices (GPU/CPU)
+    )
+
+    return model, tokenizer
+
+# Load model and tokenizer using the function
+model, tokenizer = load_model_and_tokenizer()
+
+## prompt function 
+alpaca_prompt = "### Instruction:\n{}\n\n### Response:\n"
+
+
+# Streamlit User Interface
+st.title("भारतीय कानून व्यवस्था")
+st.subheader("AI-powered responses for legal questions in Indian law")
+
+# Input text box for user question
+instruction = st.text_area("Enter your question:", placeholder="Ask a question about Indian law...")
+
+# Generate response button
+if st.button("Generate Response"):
+    if instruction.strip():
+        with st.spinner("Generating response..."):
+            # Prepare the prompt for the model
+            inputs = tokenizer(
+                [alpaca_prompt.format(instruction)], 
+                return_tensors="pt"
+            ).to("cuda")
+
+            # Generate the response
+            outputs = model.generate(**inputs, max_new_tokens=150, use_cache=True)
+            response = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+            
+            # Extract the clean response
+            response_cleaned = response.split("### Response:\n")[-1].strip()
+
+        # Display the response
+        st.success("Response:")
+        st.write(response_cleaned)
+    else:
+        st.error("Please enter a question to generate a response.")