Update app.py

app.py

@@ -1,9 +1,32 @@
+import gradio as gr
+from transformers import pipeline
+import PyPDF2
+
+# 📌 Load syllabus from PDF
+def read_pdf(file_path):
+    try:
+        with open(file_path, "rb") as file:
+            reader = PyPDF2.PdfReader(file)
+            text = "\n".join([page.extract_text() for page in reader.pages if page.extract_text()])
+        return text
+    except Exception as e:
+        return f"Error loading syllabus: {str(e)}"
+
+syllabus_text = read_pdf("syllabus.pdf")
+
+# 📌 Load AI Model
+chatbot = pipeline("text-generation", model="facebook/blenderbot-400M-distill")
+
+# 📌 Define Chat Function
 def chat_response(message):
     if "syllabus" in message.lower():
-        chunk_size = 500  # Ek baar me 500 characters
-        chunks = [syllabus_text[i:i+chunk_size] for i in range(0, len(syllabus_text), chunk_size)]
-        return "\n\n".join(chunks[:3])  # Sirf pehle 3 chunks dikhayega (1500 characters)
-    
+        return syllabus_text
     response = chatbot(message, max_length=100, do_sample=True)
     return response[0]['generated_text']
+
+# 📌 Create Gradio Interface
+iface = gr.Interface(fn=chat_response, inputs="text", outputs="text", title="Bit GPT 0.2.8")
+
+# 📌 Launch App
+if __name__ == "__main__":
     iface.launch()