Update app.py

app.py

@@ -15,11 +15,15 @@ import random
 import requests
 import os
 
-from transformers import pipeline, set_seed
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
-# Load a text generation model locally
-generator = pipeline('text-generation', model='gpt2')
-set_seed(42)
+# Load tokenizer and model for Flan-T5
+model_name = "google/flan-t5-base"
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base")
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
+
+# Create a pipeline
+generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
 # File to store feedback
 FEEDBACK_FILE = "user_feedback.csv"
@@ -29,6 +33,10 @@ def huggingface_chatbot(user_input):
         result = generator(user_input, max_length=150, temperature=0.7, do_sample=True)
         if isinstance(result, list) and "generated_text" in result[0]:
             return result[0]["generated_text"]
+        elif "generated_text" in result:
+            return result["generated_text"]
+        elif "text" in result[0]:
+            return result[0]["text"]
         else:
             return "⚠️ Could not parse model response."
     except Exception as e:
@@ -36,6 +44,7 @@ def huggingface_chatbot(user_input):
 
 
 
+
 # Database setup for user authentication
 def init_db():
     conn = sqlite3.connect("users.db")