Update app.py

app.py

@@ -15,14 +15,15 @@ def get_top_chunks(query):
     query_embedding = model.encode(query, convert_to_tensor=True)
     query_embedding_normalized = query_embedding / query_embedding.norm()
     similarities = torch.matmul(chunk_embeddings, query_embedding_normalized)
-    top_indices = torch.topk(similarities, k=5).indices.tolist()
+    top_indices = torch.topk(similarities, k=20).indices.tolist()
     return [cleaned_chunks[i] for i in top_indices]
 
 client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
 
 def respond(message, history, name, char_class, char_alignment, char_race, campaign, party):
+    
     response = ""
-    top_chunks = get_top_chunks(message)
+    top_chunks = get_top_chunks(f"{char_class}, {char_alignment}, {char_race}, {campaign},{party},{message}")
     context = "\n".join(top_chunks)
 
     messages = [