updates to 1.4 samples

KxSystems · Oct 25, 2024 · ec0ade9 · ec0ade9
1 parent 04e5de8
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diff --git a/HuggingFace_search/huggingface_inference.ipynb b/HuggingFace_search/huggingface_inference.ipynb
@@ -1117,7 +1117,9 @@
       },
       "source": [
         "## Embed the Query with the Hugging Face Inference API\n",
-        "Use the Hugging Face Inference API to embed the query so that it can be used to search our index"
+        "Use the Hugging Face Inference API to embed the query so that it can be used to search our index\n",
+        "\n",
+        "!! Note that you might need to run this cell a few times as it takes a few seconds for the model to be ready."
       ]
     },
     {

diff --git a/TSS_transformed/Transformed_TSS_pattern_matching.ipynb b/TSS_transformed/Transformed_TSS_pattern_matching.ipynb
@@ -853,7 +853,7 @@
       },
       "outputs": [],
       "source": [
-        "# Create the table called \"metadata_demo\"\n",
+        "# Create the table called \"sensors\"\n",
         "table = database.create_table(\"sensors\",\n",
         "                              schema = sensor_schema,\n",
         "                              indexes = indexes,\n",

diff --git a/multimodal_RAG_ImageBind/multi_modal_ImageBind.ipynb b/multimodal_RAG_ImageBind/multi_modal_ImageBind.ipynb
@@ -839,8 +839,6 @@
       },
       "outputs": [],
       "source": [
-        "os.environ[\"KDBAI_ENDPOINT\"]=\"http://localhost:8082\"\n",
-        "os.environ[\"KDBAI_API_KEY\"]=\"\"\n",
         "#Set up KDB.AI endpoint and API key\n",
         "KDBAI_ENDPOINT = (\n",
         "    os.environ[\"KDBAI_ENDPOINT\"]\n",
@@ -1456,8 +1454,6 @@
         "def mm_search(query):\n",
         "    image_results = table.search(vectors={\"flat_index\":query}, n=2, filter=[(\"like\", \"media_type\", \"image\")])\n",
         "    text_results = table.search(vectors={\"flat_index\":query}, n=1, filter=[(\"like\", \"media_type\", \"text\")])\n",
-        "    #image_results = table.search(query, n=2, filter=[(\"like\", \"media_type\", \"image\")])\n",
-        "    #text_results = table.search(query, n=1, filter=[(\"like\", \"media_type\", \"text\")])\n",
         "    results = [pd.concat([image_results[0], text_results[0]], ignore_index=True)]\n",
         "    viewResults(results)\n",
         "    return(results)"

diff --git a/multimodal_RAG_unified_text/multi_modal_demo.ipynb b/multimodal_RAG_unified_text/multi_modal_demo.ipynb
@@ -755,7 +755,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Create the table called \"metadata_demo\"\n",
+    "# Create the table called \"multi_modal_demo\"\n",
     "table = database.create_table(\"multi_modal_demo\", schema=table_schema, indexes=indexes)"
    ]
   },