Update app.py

app.py

@@ -4,8 +4,8 @@ import torch
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-with open("travel_knowledge_base.txt", "r", encoding="utf-8") as file:
-    travel_text = file.read()
+with open("hindu_yuva_knowledge_base.txt", "r", encoding="utf-8") as file:
+    yuva_knowledge = file.read()
 
 def preprocess_text(text):
     cleaned_text = text.strip()
@@ -17,7 +17,7 @@ def preprocess_text(text):
             cleaned_chunks.append(chunk)
     return cleaned_chunks
 
-cleaned_chunks = preprocess_text(travel_text)
+cleaned_chunks = preprocess_text(yuva_knowledge)
 
 
 model = SentenceTransformer('all-MiniLM-L6-v2')
@@ -44,7 +44,7 @@ client = InferenceClient("Qwen/Qwen2.5-7B-Instruct")
 def respond(message, history):
     top_chunks = get_top_chunks(message, chunk_embeddings, cleaned_chunks)
     context = "\n\n".join(top_chunks)
-    messages = [{"role": "system", "content": f"You are a travel advisor. Cover flights, hotels, food, and itineraries. If the user is just greeting you, greet them back and ask where they want to travel. \n{context}"}]
+    messages = [{"role": "system", "content": f"Always greet the user first by asking 'Hello, how can I help you?'. You are an assistant answering users' questions about Hindu YUVA. You just need to pull information from the website to answer basic questions. \n{context}"}]
     for turn in history:
         if turn["role"] == "user":
             messages.append({"role": "user", "content": turn["content"]})