Update app.py

app.py

@@ -24,7 +24,7 @@ pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
 # 🔐 Lista de topicuri din dataset (poți ajusta manual dacă vrei):
 covered_topics = {
-    "ospf", "bgp", "vxlan", "evpn", "network design", "acl", "routing",
+    "ospf", "bgp", "eigrp", "vxlan", "evpn", "network design", "acl", "routing",
     "spine", "leaf", "underlay", "overlay", "mpls", "qos", "firewall",
     "vpn", "vlan", "subnet", "cidr"
 }
@@ -32,13 +32,13 @@ covered_topics = {
 def chat(user_input):
     # Verificăm dacă întrebarea conține topicuri cunoscute
     if not any(topic in user_input.lower() for topic in covered_topics):
-        return "Îmi pare rău, nu am suficiente date despre acest subiect pentru a răspunde corect."
+        return "I am sorry, I was not fine tuned with this data."
 
     prompt = f"User: {user_input}\nAI:"
-    response = pipe(prompt, max_new_tokens=64, do_sample=True, temperature=0.1)[0]["generated_text"]
+    response = pipe(prompt, max_new_tokens=128, do_sample=True, temperature=0.1)[0]["generated_text"]
     return response[len(prompt):].strip()
 
-iface = gr.Interface(fn=chat, inputs="text", outputs="text", title="Llama3 8B Chat")
+iface = gr.Interface(fn=chat, inputs="text", outputs="text", title="Eduard's 1st virtual Architect")
 
 if __name__ == "__main__":
     iface.launch()