Update app.py

app.py

@@ -3,10 +3,10 @@ from transformers import pipeline
 import PyPDF2
 
 # ---------------- Load Hugging Face Pipelines ----------------
-# Summarizer (lightweight model that runs on CPU)
-summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
-# Text generation for eco tips
-generator = pipeline("text-generation", model="distilgpt2")
+# Lightweight summarizer
+summarizer = pipeline("summarization", model="sshleifer/distilbart-xsum-12-6")
+# Instruction-tuned generator for eco tips
+generator = pipeline("text2text-generation", model="google/flan-t5-small")
 
 # ---------------- Core Functions ----------------
 def extract_text_from_pdf(pdf_file):
@@ -28,10 +28,10 @@ def eco_tips_generator(problem_keywords):
     if not problem_keywords.strip():
         return "Please enter some keywords (e.g., plastic, solar, energy saving)."
     prompt = (
-        f"Suggest practical and actionable eco-friendly tips for sustainable living "
-        f"related to: {problem_keywords}. Provide clear solutions and suggestions."
+        f"Give practical eco-friendly tips for sustainable living related to: {problem_keywords}. "
+        f"Provide specific, clear, and actionable solutions."
     )
-    result = generator(prompt, max_length=200, num_return_sequences=1, do_sample=True)
+    result = generator(prompt, max_length=150)
     return result[0]["generated_text"]
 
 def policy_summarization(pdf_file, policy_text):
@@ -48,8 +48,8 @@ def policy_summarization(pdf_file, policy_text):
     try:
         summary = summarizer(
             text_to_summarize,
-            max_length=150,
-            min_length=40,
+            max_length=120,
+            min_length=30,
             do_sample=False
         )
         return summary[0]['summary_text']
@@ -97,3 +97,4 @@ with gr.Blocks() as app:
 # ---------------- Run App ----------------
 if __name__ == "__main__":
     app.launch(server_name="0.0.0.0", server_port=7860)
+