diff --git a/generative-ai/text-summarization-with-langchain/notebooks/register-model.ipynb b/generative-ai/text-summarization-with-langchain/notebooks/register-model.ipynb
index 2b3bc021..d3bba5ea 100644
--- a/generative-ai/text-summarization-with-langchain/notebooks/register-model.ipynb
+++ b/generative-ai/text-summarization-with-langchain/notebooks/register-model.ipynb
@@ -72,7 +72,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 01:04:39 - INFO - Notebook execution started.\n"
+      "2025-11-11 19:28:04 - INFO - Notebook execution started.\n"
      ]
     }
    ],
@@ -101,8 +101,8 @@
      "output_type": "stream",
      "text": [
       "Note: you may need to restart the kernel to use updated packages.\n",
-      "CPU times: user 27.6 ms, sys: 7.98 ms, total: 35.6 ms\n",
-      "Wall time: 1.45 s\n"
+      "CPU times: user 173 ms, sys: 31.4 ms, total: 205 ms\n",
+      "Wall time: 4.75 s\n"
      ]
     }
    ],
@@ -283,13 +283,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025/11/05 01:04:48 INFO mlflow.tracking.fluent: Experiment with name 'Summarization_Service' does not exist. Creating a new experiment.\n"
+      "2025/11/11 19:28:34 INFO mlflow.tracking.fluent: Experiment with name 'Summarization_Service' does not exist. Creating a new experiment.\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4659dbb75ff54aac8d65d97926ac70f5",
+       "model_id": "9a4485f97f0b46a980bc4bd57eccc4ed",
        "version_major": 2,
        "version_minor": 0
       },
@@ -303,7 +303,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "01efb80d6a6648889e546cfa5b0450f0",
+       "model_id": "8adddd13d60d45c7b26c0c7055ed89c0",
        "version_major": 2,
        "version_minor": 0
       },
@@ -317,7 +317,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "996080307bfa491bbb13fe1907e4af7c",
+       "model_id": "bafa74954b9b4294922934ac4fb03a72",
        "version_major": 2,
        "version_minor": 0
       },
@@ -332,7 +332,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 01:08:27,267 - INFO - Model and artifacts successfully registered in MLflow.\n",
+      "2025-11-11 19:36:53,094 - INFO - Model and artifacts successfully registered in MLflow.\n",
       "Successfully registered model 'Text_Summarization_Service'.\n"
      ]
     },
@@ -340,9 +340,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Model registered successfully with run ID: 51182439e0ee4c56ab46a49b0e868f5c\n",
-      "CPU times: user 770 ms, sys: 19.4 s, total: 20.2 s\n",
-      "Wall time: 3min 39s\n"
+      "Model registered successfully with run ID: e2c7fcda9a6742df98167adebd8a402e\n",
+      "CPU times: user 4.24 s, sys: 1min 10s, total: 1min 14s\n",
+      "Wall time: 8min 19s\n"
      ]
     },
     {
@@ -399,8 +399,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 01:08:27 - INFO - ⏱️ Total execution time: 3m 48.55s\n",
-      "2025-11-05 01:08:27 - INFO - ✅ Notebook execution completed successfully.\n"
+      "2025-11-11 19:36:54 - INFO - ⏱️ Total execution time: 8m 50.12s\n",
+      "2025-11-11 19:36:54 - INFO - ✅ Notebook execution completed successfully.\n"
      ]
     }
    ],
@@ -421,6 +421,14 @@
    "source": [
     "Built with ❤️ using [**HP AI Studio**](https://hp.com/ai-studio)."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9b1d7d38-7654-49fe-97d0-a416b12e57c7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/generative-ai/text-summarization-with-langchain/notebooks/run-workflow.ipynb b/generative-ai/text-summarization-with-langchain/notebooks/run-workflow.ipynb
index 7f16d832..92e8b0e6 100644
--- a/generative-ai/text-summarization-with-langchain/notebooks/run-workflow.ipynb
+++ b/generative-ai/text-summarization-with-langchain/notebooks/run-workflow.ipynb
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
    "id": "83818c3c-0efd-49af-a2fc-d4579e4daf7d",
    "metadata": {},
    "outputs": [],
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
    "id": "207d0596-9e36-4956-96eb-79311c1fa63d",
    "metadata": {},
    "outputs": [
@@ -82,7 +82,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 00:26:42 - INFO - Notebook execution started.\n"
+      "2025-11-11 18:53:38 - INFO - Notebook execution started.\n",
+      "2025-11-11 18:53:38 - INFO - Notebook execution started.\n"
      ]
     }
    ],
@@ -110,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 8,
    "id": "023fbdfa",
    "metadata": {},
    "outputs": [
@@ -119,8 +120,8 @@
      "output_type": "stream",
      "text": [
       "Note: you may need to restart the kernel to use updated packages.\n",
-      "CPU times: user 44.6 ms, sys: 30.4 ms, total: 75 ms\n",
-      "Wall time: 4.25 s\n"
+      "CPU times: user 88.6 ms, sys: 61.5 ms, total: 150 ms\n",
+      "Wall time: 2.85 s\n"
      ]
     }
    ],
@@ -132,19 +133,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
+   "id": "96465a7c-75c9-41fc-98d2-3f7d58fc5333",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
    "id": "902fbba0",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/opt/conda/lib/python3.12/site-packages/sentence_transformers/cross_encoder/CrossEncoder.py:11: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
-      "  from tqdm.autonotebook import tqdm, trange\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import os\n",
     "import sys\n",
@@ -201,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 10,
    "id": "426355b0",
    "metadata": {},
    "outputs": [],
@@ -211,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 11,
    "id": "7b055f19",
    "metadata": {},
    "outputs": [],
@@ -255,7 +255,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 12,
    "id": "3d9e832d",
    "metadata": {},
    "outputs": [],
@@ -283,7 +283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 13,
    "id": "713a24f4-01f4-4a33-8124-7d7601ced6ef",
    "metadata": {},
    "outputs": [
@@ -329,7 +329,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 14,
    "id": "4ab31867-255e-489c-810d-42786bde5a18",
    "metadata": {},
    "outputs": [],
@@ -347,7 +347,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 15,
    "id": "54b28d4a",
    "metadata": {},
    "outputs": [
@@ -355,7 +355,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 00:26:55 - INFO - Local Llama model is properly configured. \n"
+      "2025-11-11 18:53:41 - INFO - Local Llama model is properly configured. \n",
+      "2025-11-11 18:53:41 - INFO - Local Llama model is properly configured. \n"
      ]
     }
    ],
@@ -399,7 +400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 16,
    "id": "dc16a213-9f92-4c75-93ff-66adc3133cce",
    "metadata": {},
    "outputs": [
@@ -492,7 +493,7 @@
        "4  00:00:28.740  "
       ]
      },
-     "execution_count": 11,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -536,7 +537,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 17,
    "id": "d1b33cbb-1c2b-404e-ad65-b243c6702308",
    "metadata": {
     "scrolled": true
@@ -624,7 +625,7 @@
        "4                                                      2          "
       ]
      },
-     "execution_count": 12,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -665,14 +666,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 18,
    "id": "62c67feb-11f7-47ad-bdec-3ec252e51797",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "86c96659a6c643398256c7e9077fe2d6",
+       "model_id": "034820ce93634a78956cf438c0e3fa3b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -686,7 +687,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "56edf0dd1f654198ba10da4f6f5dd224",
+       "model_id": "189eca4ef77f420eb813954f39a0e514",
        "version_major": 2,
        "version_minor": 0
       },
@@ -700,7 +701,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "856c034c5cfa4577bd434977813bc066",
+       "model_id": "4720d46ffc364841819dd29a0f1353df",
        "version_major": 2,
        "version_minor": 0
       },
@@ -714,7 +715,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ca5180955987458989daa9b935e93f29",
+       "model_id": "5bc74dae28564395a59d82c15dcf8fa3",
        "version_major": 2,
        "version_minor": 0
       },
@@ -728,7 +729,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "225d40ea79f2464fa9f62499c6596f08",
+       "model_id": "d6895b6fe4c54ea8812bf42f24171cf2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -749,7 +750,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "bf1d17f1d9ae4001a453d133259151ed",
+       "model_id": "52c7ad25a6a1451c835dc52f33b84118",
        "version_major": 2,
        "version_minor": 0
       },
@@ -763,7 +764,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c2348e77519f4e9a84bda11b17dee0c5",
+       "model_id": "44e105d369524e9c87249c78c21a6afd",
        "version_major": 2,
        "version_minor": 0
       },
@@ -777,7 +778,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "de8f29d1da914548bbc13f4dcb7ac22d",
+       "model_id": "c3bae07b63a94683a1a355da17fd9a5d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -791,7 +792,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "16df29f056ea46129b9610e3d362d276",
+       "model_id": "b1f187777c9c421ebb370c3c6f339659",
        "version_major": 2,
        "version_minor": 0
       },
@@ -805,7 +806,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "62c7795d9d414a558ead29264f096eba",
+       "model_id": "181f7d0a6927451ca26130648b83af91",
        "version_major": 2,
        "version_minor": 0
       },
@@ -819,7 +820,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2814d964cc2144df957c6e718226bf25",
+       "model_id": "a879bae564e447b89c7922a63dddae94",
        "version_major": 2,
        "version_minor": 0
       },
@@ -838,7 +839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 19,
    "id": "c5538aee-0233-4b58-a574-879dfa64a792",
    "metadata": {},
    "outputs": [],
@@ -1164,7 +1165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 20,
    "id": "a25ffc2d",
    "metadata": {},
    "outputs": [
@@ -1172,15 +1173,24 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 00:27:01 - INFO - Encoding 250 content items with embedding model\n",
-      "2025-11-05 00:27:01 - INFO - Generated embeddings with shape: (250, 384)\n",
-      "2025-11-05 00:27:01 - INFO - Performing KMeans clustering with 6 clusters\n",
-      "2025-11-05 00:27:02 - INFO - Clustering complete, found 6 clusters\n",
-      "2025-11-05 00:27:02 - INFO - Found 248 raw transitions between clusters\n",
-      "2025-11-05 00:27:02 - INFO - After filtering: using 6 breaks between clusters\n",
-      "2025-11-05 00:27:02 - INFO - Created 6 breaks using clustering method\n",
-      "2025-11-05 00:27:02 - INFO - Created 6 breaks using method 'clustering'\n",
-      "2025-11-05 00:27:02 - INFO - Generated 7 chunks from content\n"
+      "2025-11-11 18:54:00 - INFO - Encoding 250 content items with embedding model\n",
+      "2025-11-11 18:54:00 - INFO - Encoding 250 content items with embedding model\n",
+      "2025-11-11 18:54:00 - INFO - Generated embeddings with shape: (250, 384)\n",
+      "2025-11-11 18:54:00 - INFO - Generated embeddings with shape: (250, 384)\n",
+      "2025-11-11 18:54:00 - INFO - Performing KMeans clustering with 6 clusters\n",
+      "2025-11-11 18:54:00 - INFO - Performing KMeans clustering with 6 clusters\n",
+      "2025-11-11 18:54:01 - INFO - Clustering complete, found 6 clusters\n",
+      "2025-11-11 18:54:01 - INFO - Clustering complete, found 6 clusters\n",
+      "2025-11-11 18:54:01 - INFO - Found 248 raw transitions between clusters\n",
+      "2025-11-11 18:54:01 - INFO - Found 248 raw transitions between clusters\n",
+      "2025-11-11 18:54:01 - INFO - After filtering: using 6 breaks between clusters\n",
+      "2025-11-11 18:54:01 - INFO - After filtering: using 6 breaks between clusters\n",
+      "2025-11-11 18:54:01 - INFO - Created 6 breaks using clustering method\n",
+      "2025-11-11 18:54:01 - INFO - Created 6 breaks using clustering method\n",
+      "2025-11-11 18:54:01 - INFO - Created 6 breaks using method 'clustering'\n",
+      "2025-11-11 18:54:01 - INFO - Created 6 breaks using method 'clustering'\n",
+      "2025-11-11 18:54:01 - INFO - Generated 7 chunks from content\n",
+      "2025-11-11 18:54:01 - INFO - Generated 7 chunks from content\n"
      ]
     }
    ],
@@ -1223,7 +1233,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 21,
    "id": "3137ca2a",
    "metadata": {},
    "outputs": [],
@@ -1233,7 +1243,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 22,
    "id": "539fba44-6a64-40a1-88e6-d5cf1f5cc4b0",
    "metadata": {},
    "outputs": [
@@ -1241,8 +1251,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 1.91 s, sys: 3.44 s, total: 5.35 s\n",
-      "Wall time: 1min 8s\n"
+      "CPU times: user 2min 51s, sys: 5.15 s, total: 2min 56s\n",
+      "Wall time: 5min 10s\n"
      ]
     }
    ],
@@ -1254,7 +1264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 23,
    "id": "043cdb8f-a70a-499a-a2d6-56c14d965169",
    "metadata": {},
    "outputs": [],
@@ -1282,7 +1292,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 24,
    "id": "40e5cde3-b064-4280-8ada-8df68820a2f0",
    "metadata": {},
    "outputs": [],
@@ -1356,7 +1366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 25,
    "id": "c27bb40e-7823-490a-af94-0d8aae5e5886",
    "metadata": {
     "scrolled": true
@@ -1366,10 +1376,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 00:28:11 - INFO - Starting text summarization and evaluation...\n",
-      "2025-11-05 00:28:11 - INFO - Processing 7 chunks\n",
-      "2025-11-05 00:28:21 - INFO - ✅ Summarization completed in 10.03 seconds\n",
-      "2025-11-05 00:28:21 - ERROR - Error calculating ROUGE metrics: name 'evaluate' is not defined\n"
+      "2025-11-11 18:59:11 - INFO - Starting text summarization and evaluation...\n",
+      "2025-11-11 18:59:11 - INFO - Starting text summarization and evaluation...\n",
+      "2025-11-11 18:59:11 - INFO - Processing 7 chunks\n",
+      "2025-11-11 18:59:11 - INFO - Processing 7 chunks\n",
+      "2025-11-11 19:05:08 - INFO - ✅ Summarization completed in 356.80 seconds\n",
+      "2025-11-11 19:05:08 - INFO - ✅ Summarization completed in 356.80 seconds\n",
+      "2025-11-11 19:05:08 - ERROR - Error calculating ROUGE metrics: name 'evaluate' is not defined\n",
+      "2025-11-11 19:05:08 - ERROR - Error calculating ROUGE metrics: name 'evaluate' is not defined\n"
      ]
     },
     {
@@ -1381,9 +1395,9 @@
       "SUMMARIZATION RESULTS\n",
       "==================================================\n",
       "Original text length: 6560 characters\n",
-      "Summary length: 1626 characters\n",
-      "Compression ratio: 24.79%\n",
-      "Processing time: 10.03 seconds\n",
+      "Summary length: 1667 characters\n",
+      "Compression ratio: 25.41%\n",
+      "Processing time: 356.80 seconds\n",
       "\n",
       "ROUGE Scores:\n",
       "  ROUGE1: 0.0000\n",
@@ -1397,9 +1411,9 @@
       "\n",
       "The excerpt describes a state of intense heat and injustice, specifically referencing the state of Mississippi.\n",
       "\n",
-      "The excerpt is a passage from Martin Luther King Jr.'s famous \"I Have a Dream\" speech. In the passage, King expresses his vision of a future where people are judged not by the color of their skin but by the content of their character. He envisions a world where children of all colors can join hands and sing together in harmony.\n",
+      "The excerpt appears to be a passage from Martin Luther King Jr.'s famous \"I Have a Dream\" speech. In the passage, King expresses his vision of a future where people are judged not by the color of their skin but by the content of their character. He envisions a world where people can live together in harmony and equality.\n",
       "\n",
-      "The excerpt expresses a desire for freedom to ring and for America to become a great nation.\n",
+      "The excerpt expresses a desire for freedom to ring in America, and suggests that this is necessary for the country to become a great nation.\n",
       "\n",
       "The excerpt is a poetic passage that calls for freedom to ring from various locations. Specifically, it mentions the \"prestigious hilltops of New Hampshire\" and the \"mighty mountains of New York\".\n",
       "\n",
@@ -1476,7 +1490,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 26,
    "id": "60bd4708-d7b4-4928-a9be-48679ef8748d",
    "metadata": {},
    "outputs": [
@@ -1484,8 +1498,10 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2025-11-05 00:28:21 - INFO - ⏱️ Total execution time: 0m 10.04s\n",
-      "2025-11-05 00:28:21 - INFO - ✅ Notebook execution completed successfully.\n"
+      "2025-11-11 19:05:08 - INFO - ⏱️ Total execution time: 5m 56.83s\n",
+      "2025-11-11 19:05:08 - INFO - ⏱️ Total execution time: 5m 56.83s\n",
+      "2025-11-11 19:05:08 - INFO - ✅ Notebook execution completed successfully.\n",
+      "2025-11-11 19:05:08 - INFO - ✅ Notebook execution completed successfully.\n"
      ]
     }
    ],
diff --git a/generative-ai/text-summarization-with-langchain/requirements.txt b/generative-ai/text-summarization-with-langchain/requirements.txt
index b5747171..8b6a0200 100644
--- a/generative-ai/text-summarization-with-langchain/requirements.txt
+++ b/generative-ai/text-summarization-with-langchain/requirements.txt
@@ -6,10 +6,8 @@ langchain-huggingface==0.2.0
 pyyaml
 pandas
 sentence-transformers
-langchain_core
-langchain_huggingface
 tokenizers>=0.13.0
 httpx>=0.24.0
 mlflow==2.21.2
 langchain==0.3.27
-langchain-community==0.3.27
+langchain-community