tutorial adjustment

Author: okhat

docs/docs/tutorials/rag/index.ipynb

@@ -94,7 +94,7 @@
       "\n",
       "\n",
       "\n",
-      "\u001b[34m[2024-11-23T22:12:48.901453]\u001b[0m\n",
+      "\u001b[34m[2024-11-23T23:16:35.966534]\u001b[0m\n",
       "\n",
       "\u001b[31mSystem message:\u001b[0m\n",
       "\n",
@@ -404,7 +404,7 @@
       "\n",
       "\n",
       "\n",
-      "\u001b[34m[2024-11-23T22:12:49.329836]\u001b[0m\n",
+      "\u001b[34m[2024-11-23T23:16:36.149518]\u001b[0m\n",
       "\n",
       "\u001b[31mSystem message:\u001b[0m\n",
       "\n",
@@ -527,14 +527,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average Metric: 125.68 / 300 (41.9%): 100%|██████████| 300/300 [00:00<00:00, 598.18it/s]"
+      "Average Metric: 125.68 / 300 (41.9%): 100%|██████████| 300/300 [00:00<00:00, 666.96it/s]"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024/11/23 22:12:49 INFO dspy.evaluate.evaluate: Average Metric: 125.68228336477591 / 300 (41.9%)\n"
+      "2024/11/23 23:16:36 INFO dspy.evaluate.evaluate: Average Metric: 125.68228336477591 / 300 (41.9%)\n"
      ]
     },
     {
@@ -699,13 +699,24 @@
    "source": [
     "## Set up your system's retriever.\n",
     "\n",
-    "As far as DSPy is concerned, you can plug in any Python code for calling tools or retrievers. Here, we'll just use OpenAI Embeddings and do top-K search locally, just for convenience."
+    "As far as DSPy is concerned, you can plug in any Python code for calling tools or retrievers. Here, we'll just use OpenAI Embeddings and do top-K search locally, just for convenience.\n",
+    "\n",
+    "**Note:** The step below will require that you either do `pip install -U faiss-cpu` or pass `brute_force_threshold=30_000` to `dspy.retrievers.Embeddings` to avoid faiss."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# %pip install -U faiss-cpu  # or faiss-gpu if you have a GPU"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -744,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -767,7 +778,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -779,7 +790,7 @@
        ")"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -791,7 +802,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -802,7 +813,7 @@
       "\n",
       "\n",
       "\n",
-      "\u001b[34m[2024-11-23T22:13:02.348625]\u001b[0m\n",
+      "\u001b[34m[2024-11-23T23:16:49.175612]\u001b[0m\n",
       "\n",
       "\u001b[31mSystem message:\u001b[0m\n",
       "\n",
@@ -879,21 +890,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average Metric: 166.39 / 300 (55.5%): 100%|██████████| 300/300 [00:14<00:00, 20.29it/s]"
+      "Average Metric: 166.54 / 300 (55.5%): 100%|██████████| 300/300 [00:04<00:00, 61.40it/s] "
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024/11/23 22:13:17 INFO dspy.evaluate.evaluate: Average Metric: 166.39410892098812 / 300 (55.5%)\n"
+      "2024/11/23 23:16:54 INFO dspy.evaluate.evaluate: Average Metric: 166.53601368289284 / 300 (55.5%)\n"
      ]
     },
     {
@@ -1008,10 +1019,10 @@
     {
      "data": {
       "text/plain": [
-       "55.46"
+       "55.51"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1057,7 +1068,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1075,7 +1086,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1111,21 +1122,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Average Metric: 183.28 / 300 (61.1%): 100%|██████████| 300/300 [00:13<00:00, 22.20it/s] "
+      "Average Metric: 183.32 / 300 (61.1%): 100%|██████████| 300/300 [00:02<00:00, 104.48it/s]"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024/11/23 22:14:01 INFO dspy.evaluate.evaluate: Average Metric: 183.27658621624977 / 300 (61.1%)\n"
+      "2024/11/23 23:17:21 INFO dspy.evaluate.evaluate: Average Metric: 183.3194433591069 / 300 (61.1%)\n"
      ]
     },
     {
@@ -1240,10 +1251,10 @@
     {
      "data": {
       "text/plain": [
-       "61.09"
+       "61.11"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1263,7 +1274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1283,7 +1294,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -1295,7 +1306,7 @@
        ")"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }