Example notebook

examples/multimodal/multimodal_retrieval.ipynb

@@ -75,7 +75,9 @@
     "## Ingesting multimodal data\n",
     "\n",
     "Chroma supports multimodal collections by referencing external URIs for data types other than text.\n",
-    "All you have to do is specify a data loader when creating the collection, and then provide the URI for each entry. "
+    "All you have to do is specify a data loader when creating the collection, and then provide the URI for each entry. \n",
+    "\n",
+    "For this example, we are only adding images, though you can also add text."
    ]
   },
   {
@@ -476,9 +478,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Next Steps\n",
+    "## What's Next? \n",
+    "\n",
+    "Multi-modal retrieval is powerful extension to basic text retrieval. As AI systems begin to understand more types of data, like images, audio, and video, we can store and query them alongside documents and text to build even more powerful applications. \n",
+    "\n",
+    "Join our community to learn more and get help with your projects: [Discord](https://discord.gg/MMeYNTmh3x) | [Twitter](https://twitter.com/trychroma)\n",
+    "\n",
+    "Contribute to Chroma, including new multi-modal embedding functions and data loaders on [GitHub](https://github.com/chroma-core/chroma)\n",
     "\n",
-    "Multi-modal retrieval is powerful extension to basic text retrieval. As AI systems begin to understand more types of data, like images, audio, and video, we can store and query them alongside documents and text to build even more powerful applications. "
+    "We are [hiring](https://trychroma.notion.site/careers-chroma-9d017c3007c7478ebd85bad854101497?pvs=4)! "
    ]
   }
  ],