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## Description of changes Base PR to release sqlite refactor, which spans many stacked PRs. Remaining - [x] Merge this to main - [x] Layered Persistent Index #761 - [x] Remove old impls (In #781 ) - [x] Remove persist() API (In #787) - [x] Add telemetry to SegmentAPI, it was not included. (#788) - [x] New clients #805 - [x] locking and soak tests for thread-safety - [x] Migration tool - [x] Fix #739 - [x] Fix metadata None vs empty - [x] Fix persist directory (addressed in #761) - [x] Leave files open in #761 (merge stacked PR) Post Release - [ ] Un xfail cross version tests once we cut the release - [x] Documentation updates for new silent ADD failure. - [x] Update all documentation for new API instantiation - [x] Update all documentation for settings changes - [ ] Update terraform deployment - [ ] Update cloudformation deployment --------- Co-authored-by: Luke VanderHart <luke@vanderhart.net> Co-authored-by: Jeffrey Huber <jeff@trychroma.com> Co-authored-by: Anton Troynikov <atroyn@users.noreply.github.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Sebastian Sosa <37946988+CakeCrusher@users.noreply.github.com> Co-authored-by: Russell Pollari <russell@sharpestminds.com> Co-authored-by: russell-pollari <pollarir@mgail.com>
189 lines
5.2 KiB
Plaintext
189 lines
5.2 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Local Peristence Demo\n",
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"This notebook demonstrates how to configure Chroma to persist to disk, then load it back in. "
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import chromadb"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create a new Chroma client with persistence enabled. \n",
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"persist_directory = \"db\"\n",
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"\n",
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"client = chromadb.PersistentClient(path=persist_directory)\n",
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"\n",
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"# Create a new chroma collection\n",
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"collection_name = \"peristed_collection\"\n",
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"collection = client.get_or_create_collection(name=collection_name)"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Add some data to the collection\n",
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"collection.add(\n",
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" embeddings=[\n",
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" [1.1, 2.3, 3.2],\n",
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" [4.5, 6.9, 4.4],\n",
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" [1.1, 2.3, 3.2],\n",
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" [4.5, 6.9, 4.4],\n",
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" [1.1, 2.3, 3.2],\n",
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" [4.5, 6.9, 4.4],\n",
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" [1.1, 2.3, 3.2],\n",
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" [4.5, 6.9, 4.4],\n",
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" ],\n",
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" metadatas=[\n",
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" {\"uri\": \"img1.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img2.png\", \"style\": \"style2\"},\n",
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" {\"uri\": \"img3.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img4.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img5.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img6.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img7.png\", \"style\": \"style1\"},\n",
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" {\"uri\": \"img8.png\", \"style\": \"style1\"},\n",
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" ],\n",
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" documents=[\"doc1\", \"doc2\", \"doc3\", \"doc4\", \"doc5\", \"doc6\", \"doc7\", \"doc8\"],\n",
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" ids=[\"id1\", \"id2\", \"id3\", \"id4\", \"id5\", \"id6\", \"id7\", \"id8\"],\n",
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")"
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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": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create a new client with the same settings\n",
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"client = chromadb.PersistentClient(path=persist_directory)\n",
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"\n",
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"# Load the collection\n",
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"collection = client.get_collection(collection_name)"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'ids': [['id1']], 'distances': [[5.1159076593562386e-15]], 'metadatas': [[{'style': 'style1', 'uri': 'img1.png'}]], 'embeddings': None, 'documents': [['doc1']]}\n"
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]
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}
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],
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"source": [
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"# Query the collection\n",
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"results = collection.query(\n",
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" query_embeddings=[[1.1, 2.3, 3.2]],\n",
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" n_results=1\n",
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")\n",
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"\n",
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"print(results)"
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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": 6,
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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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"{'ids': ['id1', 'id2', 'id3', 'id4', 'id5', 'id6', 'id7', 'id8'],\n",
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" 'embeddings': [[1.100000023841858, 2.299999952316284, 3.200000047683716],\n",
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" [4.5, 6.900000095367432, 4.400000095367432],\n",
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" [1.100000023841858, 2.299999952316284, 3.200000047683716],\n",
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" [4.5, 6.900000095367432, 4.400000095367432],\n",
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" [1.100000023841858, 2.299999952316284, 3.200000047683716],\n",
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" [4.5, 6.900000095367432, 4.400000095367432],\n",
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" [1.100000023841858, 2.299999952316284, 3.200000047683716],\n",
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" [4.5, 6.900000095367432, 4.400000095367432]],\n",
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" 'metadatas': [{'style': 'style1', 'uri': 'img1.png'},\n",
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" {'style': 'style2', 'uri': 'img2.png'},\n",
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" {'style': 'style1', 'uri': 'img3.png'},\n",
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" {'style': 'style1', 'uri': 'img4.png'},\n",
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" {'style': 'style1', 'uri': 'img5.png'},\n",
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" {'style': 'style1', 'uri': 'img6.png'},\n",
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" {'style': 'style1', 'uri': 'img7.png'},\n",
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" {'style': 'style1', 'uri': 'img8.png'}],\n",
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" 'documents': ['doc1', 'doc2', 'doc3', 'doc4', 'doc5', 'doc6', 'doc7', 'doc8']}"
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]
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},
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"execution_count": 6,
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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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"collection.get(include=[\"embeddings\", \"metadatas\", \"documents\"])"
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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": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Clean up\n",
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"! rm -rf db"
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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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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "chroma",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.10.8"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "88f09714c9334832bac29166716f9f6a879ee2a4ed4822c1d4120cb2393b58dd"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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