Add quickstarts to docs (#1583)

* drafting

* update titles, add quickstarts to docs

* title

* nb icon in title

* remove unintended file

---------

Co-authored-by: Josh Reini <[email protected]>

examples/quickstart/add_dataframe_quickstart.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 📓 TruLens with Outside Logs in a Dataframe\n",
+    "# 📓 Add Dataframe Quickstart\n",
     "\n",
     "If your application was run (and logged) outside of TruLens, TruVirtual can be used to ingest and evaluate the logs.\n",
     "\n",

examples/quickstart/custom_stream.ipynb

@@ -5,7 +5,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Evaluate Streaming Apps\n",
+    "# 📓 Evaluate Streaming Apps\n",
     "\n",
     "This notebook shows how to evaluate a custom streaming app.\n",
     "\n",

examples/quickstart/groundtruth_dataset_persistence.ipynb

@@ -4,9 +4,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Ground truth dataset persistence and evaluation in TruLens\n",
+    "# 📓 Persist Groundtruth Datasets\n",
     "\n",
-    "In this notebook, we give a quick walkthrough of how you can prepare your own ground truth dataset, as well as utilize our utility function to load preprocessed BEIR (Benchmarking IR) datasets to take advantage of its unified format.\n"
+    "In this notebook, we give a quick walkthrough of how you can prepare your own ground truth dataset, as well as utilize our utility function to load preprocessed BEIR (Benchmarking IR) datasets to take advantage of its unified format.\n",
+    "\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/truera/trulens/blob/main/examples/quickstart/groundtruth_dataset_persistence.ipynb)\n"
    ]
   },
   {

examples/quickstart/groundtruth_evals_for_retrieval_systems.ipynb

@@ -4,8 +4,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Ground-truth based evaluation on information retrieval componenet \n",
-    "When developing a RAG application, the retrieval component plays a critical role in the entire system. Thus, we need to be able to quickly measure the search quality, where directly affects an end-to-end LLM powered application's ability to accurately answer queries based on contextualized knowledge. In this notebook, we walkthrough how you can leverage your curated ground truth datasets containing golden contexts that are relevant to a query to perform evalaution using well established information retrieval (IR) metrics of your app. The key different from this ground-truth-based workflow than RAG triad is that RAG triad is reference free, and is mostly suitable for cases when ground truth data are not available.     "
+    "# 📓 Groundtruth Evaluations for Retrieval Systems\n",
+    "\n",
+    "When developing a RAG application, the retrieval component plays a critical role in the entire system. Thus, we need to be able to quickly measure the search quality, where directly affects an end-to-end LLM powered application's ability to accurately answer queries based on contextualized knowledge. In this notebook, we walkthrough how you can leverage your curated ground truth datasets containing golden contexts that are relevant to a query to perform evalaution using well established information retrieval (IR) metrics of your app. The key different from this ground-truth-based workflow than RAG triad is that RAG triad is reference free, and is mostly suitable for cases when ground truth data are not available.\n",
+    "\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/truera/trulens/blob/main/examples/quickstart/groundtruth_evals_for_retrieval_systems.ipynb)"
    ]
   },
   {

mkdocs.yml

@@ -218,20 +218,24 @@ nav:
           # Title labels of these notebooks come from within the notebooks
           # themselves and will be overridden if specified here.
           - getting_started/quickstarts/quickstart.ipynb
+          - getting_started/quickstarts/add_dataframe_quickstart.ipynb
           - getting_started/quickstarts/existing_data_quickstart.ipynb
           - getting_started/quickstarts/langchain_quickstart.ipynb
           - getting_started/quickstarts/llama_index_quickstart.ipynb
           - getting_started/quickstarts/text2text_quickstart.ipynb
           - getting_started/quickstarts/groundtruth_evals.ipynb
           - getting_started/quickstarts/human_feedback.ipynb
+          - getting_started/quickstarts/groundtruth_evals_for_retrieval_systems.ipynb
+          - getting_started/quickstarts/groundtruth_dataset_persistence.ipynb
+          - getting_started/quickstarts/custom_stream.ipynb
       - ⭐ Core Concepts:
           - getting_started/core_concepts/index.md
           - ☔ Feedback Functions: getting_started/core_concepts/feedback_functions.md
           - ⟁ RAG Triad: getting_started/core_concepts/rag_triad.md
           - 🏆 Honest, Harmless, Helpful Evals: getting_started/core_concepts/honest_harmless_helpful_evals.md
       - 🎈Viewing Results:
           - getting_started/dashboard/index.md
-  - Component Guides:
+  - 🗺️ Component Guides:
     - Instrumentation:
         - component_guides/instrumentation/index.md
         # Titles set inside notebooks and will be overridden if provider here.
@@ -273,7 +277,7 @@ nav:
     - Other:
       - Moving from TruLens Eval: component_guides/other/trulens_eval_migration.md
       - Uninstalling TruLens: component_guides/other/uninstalling.md
-  - API Reference: reference/
+  - 📚 API Reference: reference/
   - 🧑‍🍳 Cookbook: cookbook/
   - 🤝 Contributing:
       - contributing/index.md
@@ -284,7 +288,7 @@ nav:
       - ⛅ Optional Packages: contributing/optional.md
       - ✨ Database Migration: contributing/migration.md
       - 🏁 Release History: contributing/release_history.md
-  - Blog:
+  - ✍️ Blog:
       - blog/index.md
 
 #  - Resources: