added details

examples/evaluation/ragas/openai-ragas-eval-cookbook.ipynb

@@ -27,6 +27,7 @@
    "source": [
     "### Prerequisites\n",
     "- Ragas is a python package and we can install it using pip\n",
+    "- Some documents to build our simple RAG pipeline\n",
     "- Ragas uses model guided techniques underneath to produce scores for each metric. In this tutorial, we will use OpenAI `gpt-3.5-turbo` and `text-embedding-ada-002`. These are the default models used in ragas but you can use any LLM or Embedding of your choice by referring to this [guide](https://docs.ragas.io/en/stable/howtos/customisations/bring-your-own-llm-or-embs.html). I highly recommend that you try this notebook with open-ai so that you get a feel of it with ease."
    ]
   },
@@ -40,6 +41,16 @@
     "! pip install -q ragas"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d0e43825-9c28-417e-a18a-03543383f3bd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!git clone https://huggingface.co/datasets/explodinggradients/prompt-engineering-guide-papers"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 16,
@@ -260,7 +271,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "reader = SimpleDirectoryReader(\"/Users/shahules/Myprojects/ragas/experiments/prompt-engineering-papers/\",num_files_limit=30, required_exts=[\".pdf\"])\n",
+    "reader = SimpleDirectoryReader(\"./prompt-engineering-papers/\",num_files_limit=30, required_exts=[\".pdf\"])\n",
     "documents = reader.load_data()\n"
    ]
   },

examples/evaluation/ragas/openai-ragas-synthetic-test.ipynb

@@ -7,6 +7,10 @@
    "source": [
     "# Introduction\n",
     "\n",
+    "<a target=\"_blank\" href=\"https://colab.research.google.com/github/shahules786/openai-cookbook/blob/ragas/examples/evaluation/ragas/openai-ragas-synthetic-test.ipynb\">\n",
+    "  <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
+    "</a>\n",
+    "\n",
     "Ragas is the de-facto opensource standard for RAG evaluations. Ragas provides features and methods to help evaluate RAG applications. In this notebook we will build a synthetic test dataset using Ragas to evaluate your RAG. \n",
     "\n",
     "### Contents\n",