From af64e253f57b3375a4dae2ab1da0227d2f5820f6 Mon Sep 17 00:00:00 2001
From: zmtomorrow <zmt534885880@gmail.com>
Date: Fri, 22 Aug 2025 09:57:01 +0100
Subject: [PATCH] fix image

---
 cookbook/pageindex_RAG_simple.ipynb | 38 ++++++++++++++---------------
 1 file changed, 19 insertions(+), 19 deletions(-)

diff --git a/cookbook/pageindex_RAG_simple.ipynb b/cookbook/pageindex_RAG_simple.ipynb
index 2d53c3b..0bf4b29 100644
--- a/cookbook/pageindex_RAG_simple.ipynb
+++ b/cookbook/pageindex_RAG_simple.ipynb
@@ -40,7 +40,11 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "PageIndex generates a searchable tree structure of documents, enabling reasoning-based retrieval through tree search — without vectors.\n",
+        "PageIndex generates a searchable tree structure of documents, enabling reasoning-based retrieval through tree search. \n",
+        "\n",
+        "<div align=\"center\">\n",
+        "  <img src=\"https://pageindex.ai/static/images/vectorless_rag_workflow.png\" width=\"100%\">\n",
+        "</div>\n",
         "\n",
         "- **No Vectors Needed**: Uses document structure and LLM reasoning for retrieval.\n",
         "- **No Chunking Needed**: Documents are organized into natural sections rather than artificial chunks.\n",
@@ -57,11 +61,7 @@
         "This notebook demonstrates a simple example of **vectorless RAG** with PageIndex through the following steps:\n",
         "- [x] Build a PageIndex tree structure of a document\n",
         "- [x] Perform reasoning-based retrieval with tree search\n",
-        "- [x] Generate answers based on the retrieved context\n",
-        "\n",
-        "The figure below shows an overview of the workflow:\n",
-        "\n",
-        "<img src=\"https://pageindex.ai/static/images/vectorless_rag_workflow.png\" width=\"70%\">"
+        "- [x] Generate answers based on the retrieved context"
       ]
     },
     {
@@ -85,7 +85,7 @@
         "id": "edTfrizMFK4c"
       },
       "source": [
-        "#### Install dependencies"
+        "### Install dependencies"
       ]
     },
     {
@@ -106,7 +106,7 @@
         "id": "WVEWzPKGcG1M"
       },
       "source": [
-        "#### Setup environment"
+        "### Setup environment"
       ]
     },
     {
@@ -134,7 +134,7 @@
         "id": "AR7PLeVbcG1N"
       },
       "source": [
-        "#### Define utility functions"
+        "### Define utility functions"
       ]
     },
     {
@@ -198,7 +198,7 @@
         "id": "Mzd1VWjwMUJL"
       },
       "source": [
-        "#### Submit a document for PageIndex tree generation"
+        "### Submit a document with PageIndex SDK"
       ]
     },
     {
@@ -222,7 +222,7 @@
         }
       ],
       "source": [
-        "# You can also use our GitHub repo to generate PageIndex tree\n",
+        "# You can also use our GitHub repo to generate PageIndex structure\n",
         "# https://github.com/VectifyAI/PageIndex\n",
         "\n",
         "pdf_url = \"https://arxiv.org/pdf/2501.12948.pdf\"\n",
@@ -244,7 +244,7 @@
         "id": "4-Hrh0azcG1N"
       },
       "source": [
-        "#### Get the generated PageIndex tree structure"
+        "### Get the generated PageIndex tree structure"
       ]
     },
     {
@@ -356,7 +356,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "#### Use LLM for tree search and identify nodes that might contain relevant context"
+        "### Use LLM for tree search and identify nodes that might contain relevant context"
       ]
     },
     {
@@ -396,7 +396,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "#### Print retrieved nodes and reasoning process"
+        "### Print retrieved nodes and reasoning process"
       ]
     },
     {
@@ -455,7 +455,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "#### Extract relevant context from retrieved nodes"
+        "### Extract relevant context from retrieved nodes"
       ]
     },
     {
@@ -507,12 +507,12 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "#### Generate answer based on retrieved context"
+        "### Generate answer based on retrieved context"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 59,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
@@ -564,7 +564,7 @@
         "id": "_1kaGD3GcG1O"
       },
       "source": [
-        "## 🎯 What's Next\n",
+        "# 🎯 What's Next\n",
         "\n",
         "This notebook has demonstrated a basic, minimal example of **reasoning-based**, **vectorless** RAG with PageIndex. The workflow illustrates the core idea:\n",
         "> *Generating a hierarchical tree structure from a document, reasoning over that tree structure, and extracting relevant context, without relying on a vector database or top-k similarity search*.\n",
@@ -581,7 +581,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## 🔎 Learn More About PageIndex\n",
+        "# 🔎 Learn More About PageIndex\n",
         "  <a href=\"https://vectify.ai\">🏠 Homepage</a>&nbsp; • &nbsp;\n",
         "  <a href=\"https://dash.pageindex.ai\">🖥️ Dashboard</a>&nbsp; • &nbsp;\n",
         "  <a href=\"https://docs.pageindex.ai/quickstart\">📚 API Docs</a>&nbsp; • &nbsp;\n",