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https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
Update openai embeddings notebook with correct embedding model in section 2 (#5831)
In second section it looks like a copy/paste from the first section and doesn't include the specific embedding model mentioned in the example so I added it for clarity. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
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@ -12,7 +12,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 6,
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"id": "0be1af71",
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"metadata": {},
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"outputs": [],
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@ -22,7 +22,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 29,
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"id": "2c66e5da",
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"metadata": {},
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"outputs": [],
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@ -32,7 +32,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 30,
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"id": "01370375",
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"metadata": {},
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"outputs": [],
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@ -42,7 +42,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 31,
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"id": "bfb6142c",
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"metadata": {},
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"outputs": [],
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@ -52,7 +52,32 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 32,
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"id": "91bc875d-829b-4c3d-8e6f-fc2dda30a3bd",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[-0.003186025367556387,\n",
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" 0.011071979803637493,\n",
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" -0.004020420763285827,\n",
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" -0.011658221276953042,\n",
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" -0.0010534035786864363]"
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]
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},
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"execution_count": 32,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"query_result[:5]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"id": "0356c3b7",
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"metadata": {},
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"outputs": [],
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@ -60,6 +85,31 @@
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"doc_result = embeddings.embed_documents([text])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "a4b0d49e-0c73-44b6-aed5-5b426564e085",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[-0.003186025367556387,\n",
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" 0.011071979803637493,\n",
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" -0.004020420763285827,\n",
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" -0.011658221276953042,\n",
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" -0.0010534035786864363]"
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]
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},
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"execution_count": 34,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"doc_result[0][:5]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "bb61bbeb",
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@ -70,7 +120,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "c0b072cc",
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"metadata": {},
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"outputs": [],
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@ -80,17 +130,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 23,
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"id": "a56b70f5",
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"metadata": {},
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"outputs": [],
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"source": [
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"embeddings = OpenAIEmbeddings()"
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"embeddings = OpenAIEmbeddings(model=\"text-search-ada-doc-001\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 24,
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"id": "14aefb64",
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"metadata": {},
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"outputs": [],
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@ -100,7 +150,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 25,
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"id": "3c39ed33",
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"metadata": {},
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"outputs": [],
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@ -110,7 +160,32 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 26,
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"id": "2ee7ce9f-d506-4810-8897-e44334412714",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[0.004452846988523035,\n",
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" 0.034550655976098514,\n",
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" -0.015029939040690051,\n",
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" 0.03827273883655212,\n",
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" 0.005785414075152477]"
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]
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},
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"execution_count": 26,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"query_result[:5]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"id": "e3221db6",
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"metadata": {},
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"outputs": [],
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@ -118,6 +193,31 @@
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"doc_result = embeddings.embed_documents([text])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"id": "a0865409-3a6d-468f-939f-abde17c7cac3",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[0.004452846988523035,\n",
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" 0.034550655976098514,\n",
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" -0.015029939040690051,\n",
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" 0.03827273883655212,\n",
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" 0.005785414075152477]"
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]
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},
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"execution_count": 28,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"doc_result[0][:5]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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@ -132,7 +232,7 @@
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.11.1 64-bit",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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@ -146,7 +246,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.1"
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"version": "3.9.1"
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},
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"vscode": {
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"interpreter": {
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