diff --git a/embedchain/embedchain.py b/embedchain/embedchain.py
index 190d2f55..4be92b3b 100644
--- a/embedchain/embedchain.py
+++ b/embedchain/embedchain.py
@@ -7,7 +7,9 @@ from typing import Any, Dict, List, Optional, Tuple, Union
 from dotenv import load_dotenv
 from langchain.docstore.document import Document
 
-from embedchain.cache import adapt, get_gptcache_session, gptcache_data_convert, gptcache_update_cache_callback
+from embedchain.cache import (adapt, get_gptcache_session,
+                              gptcache_data_convert,
+                              gptcache_update_cache_callback)
 from embedchain.chunkers.base_chunker import BaseChunker
 from embedchain.config import AddConfig, BaseLlmConfig, ChunkerConfig
 from embedchain.config.base_app_config import BaseAppConfig
@@ -17,7 +19,8 @@ from embedchain.embedder.base import BaseEmbedder
 from embedchain.helpers.json_serializable import JSONSerializable
 from embedchain.llm.base import BaseLlm
 from embedchain.loaders.base_loader import BaseLoader
-from embedchain.models.data_type import DataType, DirectDataType, IndirectDataType, SpecialDataType
+from embedchain.models.data_type import (DataType, DirectDataType,
+                                         IndirectDataType, SpecialDataType)
 from embedchain.telemetry.posthog import AnonymousTelemetry
 from embedchain.utils.misc import detect_datatype, is_valid_json_string
 from embedchain.vectordb.base import BaseVectorDB
diff --git a/examples/sadhguru-ai/app.py b/examples/sadhguru-ai/app.py
index 055f68bc..67d4c62d 100644
--- a/examples/sadhguru-ai/app.py
+++ b/examples/sadhguru-ai/app.py
@@ -93,8 +93,9 @@ if prompt := st.chat_input("Ask me anything!"):
         answer, citations = results["answer"], results["citations"]
         if citations:
             full_response += "\n\n**Sources**:\n"
-            for i, citations in enumerate(citations):
-                full_response += f"{i+1}. {citations[1]}\n"
+            sources = list(set(map(lambda x: x[1]["url"], citations)))
+            for i, source in enumerate(sources):
+                full_response += f"{i+1}. {source}\n"
 
         msg_placeholder.markdown(full_response)
         st.session_state.messages.append({"role": "assistant", "content": full_response})