From 21cc7c4451a40601b8e9b9f88215f2913bf53bb4 Mon Sep 17 00:00:00 2001 From: Farzad Sunavala <40604067+farzad528@users.noreply.github.com> Date: Sat, 25 Jan 2025 10:52:55 -0600 Subject: [PATCH] docs: added markdown headings to enable TOC in github pages Signed-off-by: Farzad Sunavala <40604067+farzad528@users.noreply.github.com> --- docs/examples/rag_azuresearch.ipynb | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/docs/examples/rag_azuresearch.ipynb b/docs/examples/rag_azuresearch.ipynb index 4350ec2b..08e7c73b 100644 --- a/docs/examples/rag_azuresearch.ipynb +++ b/docs/examples/rag_azuresearch.ipynb @@ -33,6 +33,7 @@ "metadata": {}, "source": [ "\n", + "## A recipe 🧑‍🍳 🐥 💚\n", "\n", "This notebook demonstrates how to build a Retrieval-Augmented Generation (RAG) system using:\n", "- [Docling](https://ds4sd.github.io/docling/) for document parsing and chunking\n", @@ -61,7 +62,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Part 0: Prerequisites\n", + "### Part 0: Prerequisites\n", " - **Azure AI Search** resource\n", " - **Azure OpenAI** resource with a deployed embedding and chat completion model (e.g. `text-embedding-3-small` and `gpt-4o`) \n", " - **Docling 2.12+** (installs `docling_core` automatically) Docling installed (Python 3.8+ environment)\n", @@ -114,7 +115,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Part 1: Parse the PDF with Docling\n", + "### Part 1: Parse the PDF with Docling\n", "\n", "We’ll parse the **Microsoft GraphRAG Research Paper** (~15 pages). Parsing should be relatively quick, even on CPU, but it will be faster on a GPU or MPS device if available.\n", "\n", @@ -235,7 +236,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Part 2: Hierarchical Chunking\n", + "### Part 2: Hierarchical Chunking\n", "We convert the `Document` into smaller chunks for embedding and indexing. The built-in `HierarchicalChunker` preserves structure. " ] }, @@ -382,7 +383,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Embed and Upsert to Azure AI Search\n" + "#### Embed and Upsert to Azure AI Search\n" ] }, { @@ -497,7 +498,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Part 4: RAG Query with Azure OpenAI\n", + "### Part 4: RAG Query with Azure OpenAI\n", "Combine retrieval from Azure Search with Chat Completions (aka. grounding your LLM)" ] },