{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generating Knowledge Graphs with LLMs and Structured Outputs\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/meta-llama/llama-cookbook/blob/main/3p-integrations/togetherai/knowledge_graphs_with_structured_outputs.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "In this notebook we show how to generate and visualize knowledge graphs using Large Language Models (LLMs), and how to use JSON mode for structured output generation. We will use [Together AI JSON mode](https://docs.together.ai/docs/json-mode) to access models that will generate JSON structures that represent a knowledge graph (including nodes, edges, labels) for us. \n",
    "\n",
    "We will then pass these knowledge graph components to [GraphViz](https://graphviz.org/) that will help us generate and visualize these graphs.\n",
    "\n",
    "<img src=\"images/cluster.png\" height=\"500\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install relevant libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "DFAjay1FZVrn",
    "outputId": "d4b17b31-c125-4de5-ad54-6d4d08d81eaa"
   },
   "outputs": [],
   "source": [
    "!pip install together\n",
    "!pip install graphviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "5L-bdWL8Zz2B"
   },
   "outputs": [],
   "source": [
    "from together import Together\n",
    "import together\n",
    "import json\n",
    "\n",
    "# Paste in your Together AI API Key\n",
    "TOGETHER_API_KEY = \"YOUR_TOGETHER_API_KEY\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define Knowledge Graph Schema in Pydantic\n",
    "\n",
    "We need a way of telling the LLM what structure a knowledge graph has - including what information the nodes, edges must have and how they come together to create the overall graph structure. We will do this using `pydantic` models.\n",
    "\n",
    "Below we define the required classes. \n",
    "\n",
    "- Each node in our graph needs to have an `id` and a `label`. The `Node` class specifies this.\n",
    "- Each edge in our graph needs to have a `label` and must also connect two nodes from the `source` to `destination` direction. The `Edge` class specified this.\n",
    "- Each Knowledge graph is a combination of multiple `Node` and `Edge` elements. The `KnowledgeGraph` class specifies this. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "ycvtkJdhZ5Zo"
   },
   "outputs": [],
   "source": [
    "from pydantic import BaseModel, Field\n",
    "from typing import List\n",
    "\n",
    "class Node(BaseModel, frozen=True):\n",
    "    id: int\n",
    "    label: str\n",
    "\n",
    "class Edge(BaseModel, frozen=True):\n",
    "    source: int\n",
    "    target: int\n",
    "    label: str\n",
    "\n",
    "class KnowledgeGraph(BaseModel):\n",
    "    nodes: List[Node] = Field(..., default_factory=list)\n",
    "    edges: List[Edge] = Field(..., default_factory=list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5auwyteuadki",
    "outputId": "38fecb4a-5c11-4755-e311-a376bc308bee"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'$defs': {'Edge': {'properties': {'source': {'title': 'Source',\n",
       "     'type': 'integer'},\n",
       "    'target': {'title': 'Target', 'type': 'integer'},\n",
       "    'label': {'title': 'Label', 'type': 'string'}},\n",
       "   'required': ['source', 'target', 'label'],\n",
       "   'title': 'Edge',\n",
       "   'type': 'object'},\n",
       "  'Node': {'properties': {'id': {'title': 'Id', 'type': 'integer'},\n",
       "    'label': {'title': 'Label', 'type': 'string'}},\n",
       "   'required': ['id', 'label'],\n",
       "   'title': 'Node',\n",
       "   'type': 'object'}},\n",
       " 'properties': {'nodes': {'items': {'$ref': '#/$defs/Node'},\n",
       "   'title': 'Nodes',\n",
       "   'type': 'array'},\n",
       "  'edges': {'items': {'$ref': '#/$defs/Edge'},\n",
       "   'title': 'Edges',\n",
       "   'type': 'array'}},\n",
       " 'title': 'KnowledgeGraph',\n",
       " 'type': 'object'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print out the JSON Schema for our knowledge graph\n",
    "KnowledgeGraph.model_json_schema()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function to Generate a Knowledge Graph using LLMs\n",
    "\n",
    "Here we use Together AI to access `Meta-Llama-3.1-70B` in strict JSON mode. We pass in instructions to get the LLM to generate a knowledge that captures the information about a passed in `input` string. \n",
    "\n",
    "We pass in the above `KnowledgeGraph` JSON schema to guide the structured output generation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "GHwlq8vuZ9QM"
   },
   "outputs": [],
   "source": [
    "# Call the LLM with the JSON schema\n",
    "def generate_graph(input) -> KnowledgeGraph:\n",
    "    together = Together(api_key = TOGETHER_API_KEY)\n",
    "\n",
    "    extract = together.chat.completions.create(\n",
    "        messages=[\n",
    "            {\n",
    "                \"role\": \"user\",\n",
    "                \"content\": f\"Build a knowledge graph to explain: {input}. Only answer in JSON.\",\n",
    "            }\n",
    "        ],\n",
    "        model=\"meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo\",\n",
    "        response_format={\n",
    "            \"type\": \"json_object\",\n",
    "            \"schema\": KnowledgeGraph.model_json_schema(),\n",
    "        },\n",
    "    )\n",
    "\n",
    "    output = json.loads(extract.choices[0].message.content)\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's use the function above to generate a knowledge graph about the paper Attention Is All You Need,\n",
    "# a landmark in AI which introduced the Transformer architecture, enabling breakthroughs in LLMs.\n",
    "\n",
    "graph = generate_graph(\"The paper Attention Is All You Need\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'nodes': [{'id': 1, 'label': 'Transformer'},\n",
       "  {'id': 2, 'label': 'Attention Mechanism'},\n",
       "  {'id': 3, 'label': 'Encoder-Decoder Architecture'},\n",
       "  {'id': 4, 'label': 'Self-Attention'},\n",
       "  {'id': 5, 'label': 'Vaswani et al.'},\n",
       "  {'id': 6, 'label': 'Sequence-to-Sequence Models'},\n",
       "  {'id': 7, 'label': 'Recurrent Neural Networks (RNNs)'},\n",
       "  {'id': 8, 'label': 'Convolutional Neural Networks (CNNs)'},\n",
       "  {'id': 9, 'label': 'Parallelization'}],\n",
       " 'edges': [{'source': 1, 'target': 2, 'label': 'utilizes'},\n",
       "  {'source': 1, 'target': 3, 'label': 'employs'},\n",
       "  {'source': 2, 'target': 4, 'label': 'includes'},\n",
       "  {'source': 3, 'target': 6, 'label': 'enhances'},\n",
       "  {'source': 5, 'target': 1, 'label': 'proposes'},\n",
       "  {'source': 6, 'target': 7, 'label': 'replaces'},\n",
       "  {'source': 6, 'target': 8, 'label': 'outperforms'},\n",
       "  {'source': 1, 'target': 9, 'label': 'enables'}]}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lets see the knowlege graph components generated!\n",
    "graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use GraphViz to Create and Visualize the Graph\n",
    "\n",
    "Below we write a function that takes the knowledge graph JSON structure above and creates a GraphViz Directed Graph(`Digraph`) and generates a picture of the graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "dso_caYbapzO"
   },
   "outputs": [],
   "source": [
    "from graphviz import Digraph\n",
    "\n",
    "def visualize_knowledge_graph(kg):\n",
    "    dot = Digraph(comment=\"Knowledge Graph\", format='png')\n",
    "\n",
    "    # Add nodes\n",
    "    for node in kg['nodes']:\n",
    "        dot.node(str(node['id']), node['label'])\n",
    "\n",
    "    # Add edges\n",
    "    for edge in kg['edges']:\n",
    "        dot.edge(str(edge['source']), str(edge['target']), label=edge['label'])\n",
    "\n",
    "    # Render the graph to a file and open it\n",
    "    output_path = dot.render(\"knowledge_graph\", view=True)\n",
    "    print(f\"Graph rendered and saved to {output_path}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "q9v0fnk9dgLY",
    "outputId": "668c6e7a-4460-4248-e7af-ed6c5eb54d2b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Graph rendered and saved to knowledge_graph.png\n"
     ]
    }
   ],
   "source": [
    "visualize_knowledge_graph(graph)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 540
    },
    "id": "w8JnsjGaifAx",
    "outputId": "d08dabeb-5777-4aa0-a5a3-9f32917b1dc1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "\n",
    "# Display the image of the knowledge graph\n",
    "display(Image(filename='knowledge_graph.png'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We were able to get a LLM to generate a knowledge graph by telling is the structure that a knowledge graph library, GraphViz, expects the output to be in. We then used GraphViz to create and visualize the knowledge graph above!\n",
    "\n",
    "Learn more about how to use JSON mode in the [docs](https://docs.together.ai/docs/json-mode) here!"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}