Create app2.py

app2.py

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+from transformers import pipeline
+import streamlit as st
+import os
+
+# Load Hugging Face Token from Environment (Set this in Hugging Face Spaces Secrets)
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+# Select model: Use a quantized, smaller model like DistilGPT-2
+MODEL_NAME = "distilgpt2"  # Change to any of the small models mentioned above
+
+# Load Model
+@st.cache_resource
+def load_model():
+    try:
+        return pipeline("text-generation", model=MODEL_NAME, token=HF_TOKEN)
+    except Exception as e:
+        st.error(f"❌ Error loading model: {str(e)}")
+        return None
+
+generator = load_model()
+
+# Function to Generate Functional Requirement Document
+def generate_functional_requirements(topic):
+    if generator is None:
+        return "Error: Model not loaded properly."
+
+    prompt = f"Generate a comprehensive functional requirement document for {topic} in the banking sector."
+    
+    # Generate content
+    output = generator(prompt, max_length=800, do_sample=True, temperature=0.8)
+    return output[0]['generated_text']
+
+# Streamlit UI
+def main():
+    st.title("📄 AI-Powered Functional Requirement Generator for Banking")
+
+    banking_topics = [
+        "Core Banking System",
+        "Loan Management System",
+        "Payment Processing Gateway",
+        "Risk and Fraud Detection",
+        "Regulatory Compliance Management",
+        "Digital Banking APIs",
+        "Customer Onboarding & KYC",
+        "Treasury Management",
+        "Wealth & Portfolio Management"
+    ]
+    
+    topic = st.selectbox("Select a Banking Functional Requirement Topic", banking_topics)
+    
+    if st.button("Generate Functional Requirement Document"):
+        with st.spinner("Generating... This may take a while."):
+            content = generate_functional_requirements(topic)
+            if "Error" in content:
+                st.error(content)
+            else:
+                filename = "functional_requirement.pdf"
+                save_to_pdf(content, filename)
+                st.success("✅ Functional Requirement Document Generated!")
+                st.download_button(label="📥 Download PDF", data=open(filename, "rb"), file_name=filename, mime="application/pdf")
+
+if __name__ == "__main__":
+    main()