From 1d6c194a14992db38ed006b1462b353f2d2c32b4 Mon Sep 17 00:00:00 2001
From: Jack Woehr <jwoehr@softwoehr.com>
Date: Sat, 29 Nov 2025 22:30:42 -0700
Subject: [PATCH 1/2] changes required to make the example work

Signed-off-by: Jack Woehr <jwoehr@softwoehr.com>
---
 generative-ai/langchain-rag.ipynb | 24 ++++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/generative-ai/langchain-rag.ipynb b/generative-ai/langchain-rag.ipynb
index a56ae0fb9..23226c367 100644
--- a/generative-ai/langchain-rag.ipynb
+++ b/generative-ai/langchain-rag.ipynb
@@ -107,7 +107,7 @@
     "from ibm_watsonx_ai.foundation_models.utils.enums import EmbeddingTypes\n",
     "\n",
     "from langchain_ibm import WatsonxEmbeddings, WatsonxLLM\n",
-    "from langchain.vectorstores import Chroma\n",
+    "from langchain_chroma import Chroma\n",
     "\n",
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "from langchain_core.output_parsers import StrOutputParser\n",
@@ -284,6 +284,13 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's load our content into a local instance of a vector database, using Chroma."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -291,20 +298,13 @@
    "outputs": [],
    "source": [
     "embeddings = WatsonxEmbeddings(\n",
-    "    model_id=EmbeddingTypes.IBM_SLATE_30M_ENG.value,\n",
+    "    model_id=\"ibm/slate-30m-english-rtrvr-v2\",\n",
     "    url=credentials[\"url\"],# type: ignore\n",
     "    apikey=credentials[\"apikey\"],# type: ignore\n",
     "    project_id=project_id,\n",
     "    )"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Let's load our content into a local instance of a vector database, using Chroma."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -349,7 +349,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model_id = \"ibm/granite-3-8b-instruct\""
+    "model_id = \"ibm/granite-3-3-8b-instruct\""
    ]
   },
   {
@@ -538,7 +538,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -552,7 +552,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.4"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,

From b3e76e602b5e869a19a10dd99e302bc622e3ba93 Mon Sep 17 00:00:00 2001
From: Jack Woehr <jwoehr@softwoehr.com>
Date: Sun, 30 Nov 2025 07:40:20 -0700
Subject: [PATCH 2/2] correct text to refer to the model actually used

Signed-off-by: Jack Woehr <jwoehr@softwoehr.com>
---
 generative-ai/langchain-rag.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/generative-ai/langchain-rag.ipynb b/generative-ai/langchain-rag.ipynb
index 23226c367..e7dddfdf9 100644
--- a/generative-ai/langchain-rag.ipynb
+++ b/generative-ai/langchain-rag.ipynb
@@ -340,7 +340,7 @@
     "\n",
     "Finally, we’ll generate a response. The generative model (like GPT-4 or IBM Granite) uses the retrieved information to produce a more accurate and contextually relevant response to our questions.\n",
     "\n",
-    "First, we'll establish which LLM we're going to use to generate the response. For this tutorial, we'll use IBM's Granite-3.0-8B-Instruct model."
+    "First, we'll establish which LLM we're going to use to generate the response. For this tutorial, we'll use IBM's Granite-3-3-8B-Instruct model."
    ]
   },
   {