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@ -1084,13 +1084,14 @@
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "ca7e7eb1",
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"id": "eb5848f3",
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"metadata": {},
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"outputs": [],
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"source": [
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"## Batch Embedding Logic\n",
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"\n",
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"# Simple function to take in a list of text objects and return them as a list of embeddings\n",
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"@retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(10))\n",
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"def get_embeddings(input: List):\n",
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" response = openai.Embedding.create(\n",
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" input=input,\n",
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@ -1197,7 +1198,7 @@
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "9e49c881",
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"id": "e3a6fb12",
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"metadata": {},
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"outputs": [
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{
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@ -1222,7 +1223,7 @@
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "2e6ff2f4",
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"id": "83f0231c",
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"metadata": {},
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"outputs": [
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{
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@ -1248,7 +1249,7 @@
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "963170f9",
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"id": "61c204c8",
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"metadata": {},
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"outputs": [
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{
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@ -2649,7 +2650,7 @@
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{
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"cell_type": "code",
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"execution_count": 24,
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"id": "c1b5fad4",
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"id": "ba73ffab",
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"metadata": {},
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"outputs": [],
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"source": [
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@ -2953,7 +2954,7 @@
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "99072e4c",
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"id": "4ee414f1",
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"metadata": {},
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"outputs": [
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{
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