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| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/merlin-quix/bdbf7fac4a4da5eb417e7acc7efd8cfa/ingestion_viakafka_using_quix-qdrant.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# This notebook shows you how to continously ingest documents into a Vector Database using Apache Kaflka for message transport\n", | |
| "\n", | |
| "We use Qdrant for the DB and similarity search, and Quix Streams to interact with Kafka." | |
| ], | |
| "metadata": { | |
| "id": "rT1cmV4qCa2X" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### 1. Install the main dependencies\n", | |
| "\n", | |
| "Dependencies include:\n", | |
| "\n", | |
| "- The Quix Streams library for managing interactions with Apache Kafka (or Kafka-like tools such as Redpanda) in a Pandas-like way.\n", | |
| "- The Qdrant library for ingesting vectors and performing similarity search." | |
| ], | |
| "metadata": { | |
| "id": "UPYtfAR_9YxZ" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!pip install quixstreams==2.1.2a qdrant-client>=1.1.1 sentence-transformers pandas" | |
| ], | |
| "metadata": { | |
| "id": "bPbus2gi61ze", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "c8c012fb-60cd-4e56-f0cf-2a8f168c7ceb" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", | |
| "tensorboard 2.15.1 requires protobuf<4.24,>=3.19.6, but you have protobuf 4.25.2 which is incompatible.\n", | |
| "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 4.25.2 which is incompatible.\n", | |
| "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n", | |
| "\u001b[0m" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### 3. Download and setup Kafka and Zookeeper instances\n", | |
| "\n", | |
| "Using the default configurations (provided by Apache Kafka) for spinning up the instances." | |
| ], | |
| "metadata": { | |
| "id": "5_vjVIAh9rLl" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!curl -sSOL https://dlcdn.apache.org/kafka/3.6.1/kafka_2.13-3.6.1.tgz\n", | |
| "!tar -xzf kafka_2.13-3.6.1.tgz" | |
| ], | |
| "metadata": { | |
| "id": "O4R_5Q3FWtdS" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!./kafka_2.13-3.6.1/bin/zookeeper-server-start.sh -daemon ./kafka_2.13-3.6.1/config/zookeeper.properties\n", | |
| "!./kafka_2.13-3.6.1/bin/kafka-server-start.sh -daemon ./kafka_2.13-3.6.1/config/server.properties\n", | |
| "!echo \"Waiting for 10 secs until kafka and zookeeper services are up and running\"\n", | |
| "!sleep 10" | |
| ], | |
| "metadata": { | |
| "id": "Uf7NR_UZ9wye", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "fdaea359-54fd-4241-fc95-3fc7a67dc207" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Waiting for 10 secs until kafka and zookeeper services are up and running\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### 4. Check that the Kafka Daemons are running\n", | |
| "\n", | |
| "Show the running daemon processes by filtering the list for the keyword \"java\" while excluding the grep process itself" | |
| ], | |
| "metadata": { | |
| "id": "H3SafFuS94p1" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "!ps aux | grep -E '[j]ava'" | |
| ], | |
| "metadata": { | |
| "id": "CZDC2lQP99yp", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "02966b5d-ca61-4b64-9526-7adcc72c2073" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "root 2404 0.3 0.7 3082772 93856 ? Sl 11:29 0:02 java -Xmx512M -Xms512M -server -X\n", | |
| "root 2806 1.4 2.7 3715768 367152 ? Sl 11:29 0:09 java -Xmx1G -Xms1G -server -XX:+U\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Import all the libraries\n", | |
| "\n", | |
| "Import the required libraries including Quix and Qdrant." | |
| ], | |
| "metadata": { | |
| "id": "AXlah0ioounL" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "import json\n", | |
| "import time\n", | |
| "import uuid\n", | |
| "import os\n", | |
| "import pandas as pd\n", | |
| "from qdrant_client import models, QdrantClient\n", | |
| "\n", | |
| "# Quix stuff\n", | |
| "from quixstreams.kafka import Producer\n", | |
| "from quixstreams import Application, State, message_key\n", | |
| "from sentence_transformers import SentenceTransformer" | |
| ], | |
| "metadata": { | |
| "id": "7GniNF57dTnj" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Set generic constants for our docs annd vector topics." | |
| ], | |
| "metadata": { | |
| "id": "c_JPP6uOgJ_M" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "docs_topic_name = 'docs_scifibooks'\n", | |
| "vectors_topic_name = 'vectors_all-minilm-l6-v2'" | |
| ], | |
| "metadata": { | |
| "id": "8xwoHQ30xe-w" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Producer" | |
| ], | |
| "metadata": { | |
| "id": "KdiB2qsTblQw" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Set the Producer to output to the docs topic, and create a sample data set of 10 animal facts where each fact is a \"doc\"." | |
| ], | |
| "metadata": { | |
| "id": "BwXkBduOgU3D" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "outputtopicname = docs_topic_name\n" | |
| ], | |
| "metadata": { | |
| "id": "fHio9Lh5Oz12" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Create sample data to produce from and dump it to CSV (so we can learn how to produce from a CSV in subsequent steps)" | |
| ], | |
| "metadata": { | |
| "id": "bijPZjZ5U4t0" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Let's make a semantic search for Sci-Fi books!\n", | |
| "documents = [\n", | |
| " { \"name\": \"The Time Machine\", \"description\": \"A man travels through time and witnesses the evolution of humanity.\", \"author\": \"H.G. Wells\", \"year\": 1895 },\n", | |
| " { \"name\": \"Ender's Game\", \"description\": \"A young boy is trained to become a military leader in a war against an alien race.\", \"author\": \"Orson Scott Card\", \"year\": 1985 },\n", | |
| " { \"name\": \"Brave New World\", \"description\": \"A dystopian society where people are genetically engineered and conditioned to conform to a strict social hierarchy.\", \"author\": \"Aldous Huxley\", \"year\": 1932 },\n", | |
| " { \"name\": \"The Hitchhiker's Guide to the Galaxy\", \"description\": \"A comedic science fiction series following the misadventures of an unwitting human and his alien friend.\", \"author\": \"Douglas Adams\", \"year\": 1979 },\n", | |
| " { \"name\": \"Dune\", \"description\": \"A desert planet is the site of political intrigue and power struggles.\", \"author\": \"Frank Herbert\", \"year\": 1965 },\n", | |
| " { \"name\": \"Foundation\", \"description\": \"A mathematician develops a science to predict the future of humanity and works to save civilization from collapse.\", \"author\": \"Isaac Asimov\", \"year\": 1951 },\n", | |
| " { \"name\": \"Snow Crash\", \"description\": \"A futuristic world where the internet has evolved into a virtual reality metaverse.\", \"author\": \"Neal Stephenson\", \"year\": 1992 },\n", | |
| " { \"name\": \"Neuromancer\", \"description\": \"A hacker is hired to pull off a near-impossible hack and gets pulled into a web of intrigue.\", \"author\": \"William Gibson\", \"year\": 1984 },\n", | |
| " { \"name\": \"The War of the Worlds\", \"description\": \"A Martian invasion of Earth throws humanity into chaos.\", \"author\": \"H.G. Wells\", \"year\": 1898 },\n", | |
| " { \"name\": \"The Hunger Games\", \"description\": \"A dystopian society where teenagers are forced to fight to the death in a televised spectacle.\", \"author\": \"Suzanne Collins\", \"year\": 2008 },\n", | |
| " { \"name\": \"The Andromeda Strain\", \"description\": \"A deadly virus from outer space threatens to wipe out humanity.\", \"author\": \"Michael Crichton\", \"year\": 1969 },\n", | |
| " { \"name\": \"The Left Hand of Darkness\", \"description\": \"A human ambassador is sent to a planet where the inhabitants are genderless and can change gender at will.\", \"author\": \"Ursula K. Le Guin\", \"year\": 1969 },\n", | |
| " { \"name\": \"The Time Traveler's Wife\", \"description\": \"A love story between a man who involuntarily time travels and the woman he loves.\", \"author\": \"Audrey Niffenegger\", \"year\": 2003 }\n", | |
| "]\n", | |
| "\n", | |
| "# Convert the list of dictionaries to a DataFrame\n", | |
| "df = pd.DataFrame(documents)\n", | |
| "# Save the DataFrame to a CSV file so that we can practice producing to Kafka from a CSV file in the next step\n", | |
| "df.to_csv('documents.csv')" | |
| ], | |
| "metadata": { | |
| "id": "as_dynOT-fgc" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Initialize the Quix Producer to send the docs to Kafka\n", | |
| "\n", | |
| "Load the CSV file back in again and interate through it with the Quix Producer." | |
| ], | |
| "metadata": { | |
| "id": "hRcfnWUlge76" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "outputtopicname = docs_topic_name\n", | |
| "# Load the CSV file\n", | |
| "df = pd.read_csv('documents.csv')\n", | |
| "\n", | |
| "with Producer(\n", | |
| " broker_address=\"127.0.0.1:9092\",\n", | |
| " extra_config={\"allow.auto.create.topics\": \"true\"},\n", | |
| ") as producer:\n", | |
| " for index, row in df.iterrows():\n", | |
| " doc_id = index\n", | |
| " doc_key = f\"A{'0'*(10-len(str(doc_id)))}{doc_id}\"\n", | |
| " doc_uuid = str(uuid.uuid4())\n", | |
| " value = {\n", | |
| " \"Timestamp\": time.time_ns(),\n", | |
| " \"doc_uuid\": doc_uuid,\n", | |
| " \"doc_name\": row['name'],\n", | |
| " \"doc_descr\": row['description'],\n", | |
| " \"doc_year\": row['year'],\n", | |
| " }\n", | |
| " print(f\"Producing value: {value}\")\n", | |
| " producer.produce(\n", | |
| " topic=outputtopicname,\n", | |
| " headers=[(\"uuid\", doc_uuid)], # a dict is also allowed here\n", | |
| " key=doc_key,\n", | |
| " value=json.dumps(value), # needs to be a string\n", | |
| " )\n", | |
| " time.sleep(0.2)" | |
| ], | |
| "metadata": { | |
| "id": "prJaZqO8Zw6b", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "c2e41a42-6821-4528-ab11-9bd879af7dc9" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Producing value: {'Timestamp': 1706614397128390512, 'doc_uuid': 'df35ce57-549a-4615-88a7-3541c82ac10e', 'doc_name': 'The Time Machine', 'doc_descr': 'A man travels through time and witnesses the evolution of humanity.', 'doc_year': 1895}\n", | |
| "Producing value: {'Timestamp': 1706614397330999614, 'doc_uuid': '1a54aafd-6fcc-40e9-8bca-d4a48f309297', 'doc_name': \"Ender's Game\", 'doc_descr': 'A young boy is trained to become a military leader in a war against an alien race.', 'doc_year': 1985}\n", | |
| "Producing value: {'Timestamp': 1706614397531688800, 'doc_uuid': 'eddca639-ae48-41d1-9906-8df3fe51df8a', 'doc_name': 'Brave New World', 'doc_descr': 'A dystopian society where people are genetically engineered and conditioned to conform to a strict social hierarchy.', 'doc_year': 1932}\n", | |
| "Producing value: {'Timestamp': 1706614397732394191, 'doc_uuid': '612a45c1-568c-40c3-bcf8-3968dff7d235', 'doc_name': \"The Hitchhiker's Guide to the Galaxy\", 'doc_descr': 'A comedic science fiction series following the misadventures of an unwitting human and his alien friend.', 'doc_year': 1979}\n", | |
| "Producing value: {'Timestamp': 1706614397932979300, 'doc_uuid': '8e28a5e5-1e4b-4564-a1fb-b681f3d85069', 'doc_name': 'Dune', 'doc_descr': 'A desert planet is the site of political intrigue and power struggles.', 'doc_year': 1965}\n", | |
| "Producing value: {'Timestamp': 1706614398133801773, 'doc_uuid': '97dcf4bd-872d-42d5-a898-1bea38ec42b0', 'doc_name': 'Foundation', 'doc_descr': 'A mathematician develops a science to predict the future of humanity and works to save civilization from collapse.', 'doc_year': 1951}\n", | |
| "Producing value: {'Timestamp': 1706614398334592809, 'doc_uuid': 'a2a86f14-1c8d-47a9-82e6-53d158eacc72', 'doc_name': 'Snow Crash', 'doc_descr': 'A futuristic world where the internet has evolved into a virtual reality metaverse.', 'doc_year': 1992}\n", | |
| "Producing value: {'Timestamp': 1706614398535331408, 'doc_uuid': '3e68c35f-716f-471e-a290-7ad26a21ee8b', 'doc_name': 'Neuromancer', 'doc_descr': 'A hacker is hired to pull off a near-impossible hack and gets pulled into a web of intrigue.', 'doc_year': 1984}\n", | |
| "Producing value: {'Timestamp': 1706614398735957997, 'doc_uuid': 'a0b93e36-9dc7-4ee4-a89e-ae62c8fcdb92', 'doc_name': 'The War of the Worlds', 'doc_descr': 'A Martian invasion of Earth throws humanity into chaos.', 'doc_year': 1898}\n", | |
| "Producing value: {'Timestamp': 1706614398936639071, 'doc_uuid': '1440acf7-fe66-40b3-80d5-2f58885173d3', 'doc_name': 'The Hunger Games', 'doc_descr': 'A dystopian society where teenagers are forced to fight to the death in a televised spectacle.', 'doc_year': 2008}\n", | |
| "Producing value: {'Timestamp': 1706614399137363202, 'doc_uuid': '706f79cd-66cd-4ac7-90bd-4172cf65a10d', 'doc_name': 'The Andromeda Strain', 'doc_descr': 'A deadly virus from outer space threatens to wipe out humanity.', 'doc_year': 1969}\n", | |
| "Producing value: {'Timestamp': 1706614399338054493, 'doc_uuid': 'cf497f84-d447-488c-ac3d-68c4681b88be', 'doc_name': 'The Left Hand of Darkness', 'doc_descr': 'A human ambassador is sent to a planet where the inhabitants are genderless and can change gender at will.', 'doc_year': 1969}\n", | |
| "Producing value: {'Timestamp': 1706614399538760049, 'doc_uuid': '3a0fb63d-15b8-4ac7-8fa5-d433aec0e6ae', 'doc_name': \"The Time Traveler's Wife\", 'doc_descr': 'A love story between a man who involuntarily time travels and the woman he loves.', 'doc_year': 2003}\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Consume and Embed" | |
| ], | |
| "metadata": { | |
| "id": "gBwD9LcIb_s1" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "Create a Quix Consumer/Producer to:\n", | |
| " 1. read the docs from the docs topic\n", | |
| " 2. create embeddings for each doc\n", | |
| " 3. enrich the docs data with the embeddings\n", | |
| " 4. write the embeddings to the vectors topic\n" | |
| ], | |
| "metadata": { | |
| "id": "_LSWrG86gr1a" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Set the input/output topics and initialize the embedding model\n", | |
| "inputtopicname = docs_topic_name\n", | |
| "outputtopicname = vectors_topic_name\n", | |
| "encoder = SentenceTransformer('all-MiniLM-L6-v2') # Model to create embeddings" | |
| ], | |
| "metadata": { | |
| "id": "SwmJ7DnRp-Xf", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 479, | |
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| }, | |
| "outputId": "b40101d2-3ea6-4cee-efe0-0d71d20d1077" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", | |
| "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", | |
| "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", | |
| "You will be able to reuse this secret in all of your notebooks.\n", | |
| "Please note that authentication is recommended but still optional to access public models or datasets.\n", | |
| " warnings.warn(\n" | |
| ] | |
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| "output_type": "display_data", | |
| "data": { | |
| "text/plain": [ | |
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| "version_major": 2, | |
| "version_minor": 0, | |
| "model_id": "15a1fb1cba954e359c139599182ce0a2" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
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| "model_id": "abe41c209cca4b268ab4c1ddbd20a9ca" | |
| } | |
| }, | |
| "metadata": {} | |
| }, | |
| { | |
| "output_type": "display_data", | |
| "data": { | |
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| ], | |
| "application/vnd.jupyter.widget-view+json": { | |
| "version_major": 2, | |
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| "model_id": "be4188c417224a22a68c5dec2238f7c5" | |
| } | |
| }, | |
| "metadata": {} | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Define the embedding function\n", | |
| "def create_embeddings(row):\n", | |
| " text = row['doc_descr']\n", | |
| " embeddings = encoder.encode(text)\n", | |
| " embedding_list = embeddings.tolist() # Conversion step because SentenceTransformer outputs a numpy Array but Qdrant expects a plain list\n", | |
| " print(f'Created vector: \"{embedding_list}\"')\n", | |
| "\n", | |
| " return embedding_list" | |
| ], | |
| "metadata": { | |
| "id": "u86G3vb6dmWV" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Define your application and settings\n", | |
| "app = Application(\n", | |
| " broker_address=\"127.0.0.1:9092\",\n", | |
| " consumer_group=\"vectorizer\",\n", | |
| " auto_offset_reset=\"earliest\",\n", | |
| " consumer_extra_config={\"allow.auto.create.topics\": \"true\"},\n", | |
| ")\n", | |
| "\n", | |
| "# Define an input topic with JSON deserializer\n", | |
| "input_topic = app.topic(inputtopicname, value_deserializer=\"json\")\n", | |
| "\n", | |
| "# Define an output topic with JSON serializer\n", | |
| "output_topic = app.topic(outputtopicname, value_serializer=\"json\")\n", | |
| "\n", | |
| "# Initialize a streaming dataframe based on the stream of messages from the input topic:\n", | |
| "sdf = app.dataframe(topic=input_topic)\n", | |
| "\n", | |
| "# Filter the SDF to include only incoming rows where the roles that dont match the bot's current role\n", | |
| "sdf = sdf.update(lambda val: print(f\"Received update: {val}\"))\n", | |
| "\n", | |
| "# EMBEDDING HAPPENS HERE\n", | |
| "### Trigger the embedding function for any new messages(rows) detected in the filtered SDF\n", | |
| "sdf[\"embeddings\"] = sdf.apply(create_embeddings, stateful=False)\n", | |
| "\n", | |
| "# Update the timestamp column to the current time in nanoseconds\n", | |
| "sdf[\"Timestamp\"] = sdf[\"Timestamp\"].apply(lambda row: time.time_ns())\n", | |
| "\n", | |
| "# Publish the processed SDF to a Kafka topic specified by the output_topic object.\n", | |
| "sdf = sdf.to_topic(output_topic)\n", | |
| "\n", | |
| "app.run(sdf)\n", | |
| "\n", | |
| "# STOP THIS CELL MANUALLY WHEN THE BOOK ENTRIES HAVE BEEN ENRICHED WITH EMBEDDINGS" | |
| ], | |
| "metadata": { | |
| "id": "4HilakLNcFnN", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "8b6859d4-0d93-4681-b7a4-fc4498ef01f4" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "[2024-01-30 11:41:59,740] [INFO] : Initializing processing of StreamingDataFrame\n", | |
| "INFO:quixstreams.app:Initializing processing of StreamingDataFrame\n", | |
| "[2024-01-30 11:41:59,744] [INFO] : Initializing state directory at \"/content/state/vectorizer\"\n", | |
| "INFO:quixstreams.state.manager:Initializing state directory at \"/content/state/vectorizer\"\n", | |
| "[2024-01-30 11:41:59,761] [INFO] : Waiting for incoming messages\n", | |
| "INFO:quixstreams.app:Waiting for incoming messages\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Received update: {'Timestamp': 1706614397128390512, 'doc_uuid': 'df35ce57-549a-4615-88a7-3541c82ac10e', 'doc_name': 'The Time Machine', 'doc_descr': 'A man travels through time and witnesses the evolution of humanity.', 'doc_year': 1895}\n", | |
| "Created vector: \"[-0.03813491389155388, 0.04517783224582672, -0.02202131599187851, 0.059235550463199615, 0.006653918419033289, 0.018390029668807983, 0.06810280680656433, -0.0416623130440712, 0.04437771067023277, -0.025251809507608414, -0.009794252924621105, -0.02291647344827652, -0.11903539299964905, 0.03131901100277901, -0.05753288045525551, -0.008934102952480316, -0.10448412597179413, 0.007782086730003357, 0.05709610879421234, -0.05635249614715576, -0.005898033268749714, 0.026749499142169952, -0.047672420740127563, -1.9592926037148573e-06, -0.03601924702525139, 0.0012949593365192413, 0.06238840892910957, 0.0017686388455331326, 0.05468187481164932, 0.02123241126537323, 0.07367485016584396, -0.012031598016619682, -0.032027505338191986, -0.037245869636535645, -0.04593818262219429, 0.007532414514571428, 0.0013578846119344234, 0.0012013301020488143, 0.04790322110056877, -0.0013521654764190316, 0.06363940984010696, -0.03758496791124344, -0.011651739478111267, 0.05344289541244507, 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| "Received update: {'Timestamp': 1706614397330999614, 'doc_uuid': '1a54aafd-6fcc-40e9-8bca-d4a48f309297', 'doc_name': \"Ender's Game\", 'doc_descr': 'A young boy is trained to become a military leader in a war against an alien race.', 'doc_year': 1985}\n", | |
| "Created vector: \"[-0.0637923926115036, 0.0765136256814003, -0.06527190655469894, -0.01625140942633152, -0.028062069788575172, 0.06347545236349106, 0.026289114728569984, -0.00979003868997097, -0.051685623824596405, -0.005895865615457296, 0.010342624969780445, -0.035597458481788635, 0.02774212323129177, 0.09502433985471725, -0.04431113600730896, 0.011122157797217369, 0.010814893990755081, 0.033173639327287674, -0.028435083106160164, -0.06806894391775131, -0.06661729514598846, 0.02648310177028179, 0.09230083972215652, 0.06629398465156555, 0.0022590900771319866, 0.02928309515118599, 0.05818559229373932, 0.003195533063262701, -0.05464857071638107, 0.03564196825027466, 0.10109207034111023, -0.015165401622653008, -0.002449355088174343, 0.049501124769449234, 0.004460382740944624, -0.003589537926018238, 0.08970107138156891, -0.0101315937936306, -0.025876829400658607, 0.04201750457286835, -0.027640076354146004, -0.01911321096122265, 0.007330939639359713, -0.016895221546292305, 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| "Received update: {'Timestamp': 1706614397531688800, 'doc_uuid': 'eddca639-ae48-41d1-9906-8df3fe51df8a', 'doc_name': 'Brave New World', 'doc_descr': 'A dystopian society where people are genetically engineered and conditioned to conform to a strict social hierarchy.', 'doc_year': 1932}\n", | |
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| "Received update: {'Timestamp': 1706614397732394191, 'doc_uuid': '612a45c1-568c-40c3-bcf8-3968dff7d235', 'doc_name': \"The Hitchhiker's Guide to the Galaxy\", 'doc_descr': 'A comedic science fiction series following the misadventures of an unwitting human and his alien friend.', 'doc_year': 1979}\n", | |
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| "Received update: {'Timestamp': 1706614397932979300, 'doc_uuid': '8e28a5e5-1e4b-4564-a1fb-b681f3d85069', 'doc_name': 'Dune', 'doc_descr': 'A desert planet is the site of political intrigue and power struggles.', 'doc_year': 1965}\n", | |
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| "Received update: {'Timestamp': 1706614398133801773, 'doc_uuid': '97dcf4bd-872d-42d5-a898-1bea38ec42b0', 'doc_name': 'Foundation', 'doc_descr': 'A mathematician develops a science to predict the future of humanity and works to save civilization from collapse.', 'doc_year': 1951}\n", | |
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| "Received update: {'Timestamp': 1706614398334592809, 'doc_uuid': 'a2a86f14-1c8d-47a9-82e6-53d158eacc72', 'doc_name': 'Snow Crash', 'doc_descr': 'A futuristic world where the internet has evolved into a virtual reality metaverse.', 'doc_year': 1992}\n", | |
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| "Received update: {'Timestamp': 1706614398535331408, 'doc_uuid': '3e68c35f-716f-471e-a290-7ad26a21ee8b', 'doc_name': 'Neuromancer', 'doc_descr': 'A hacker is hired to pull off a near-impossible hack and gets pulled into a web of intrigue.', 'doc_year': 1984}\n", | |
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| "Received update: {'Timestamp': 1706614398735957997, 'doc_uuid': 'a0b93e36-9dc7-4ee4-a89e-ae62c8fcdb92', 'doc_name': 'The War of the Worlds', 'doc_descr': 'A Martian invasion of Earth throws humanity into chaos.', 'doc_year': 1898}\n", | |
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| "Received update: {'Timestamp': 1706614398936639071, 'doc_uuid': '1440acf7-fe66-40b3-80d5-2f58885173d3', 'doc_name': 'The Hunger Games', 'doc_descr': 'A dystopian society where teenagers are forced to fight to the death in a televised spectacle.', 'doc_year': 2008}\n", | |
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| "Received update: {'Timestamp': 1706614399137363202, 'doc_uuid': '706f79cd-66cd-4ac7-90bd-4172cf65a10d', 'doc_name': 'The Andromeda Strain', 'doc_descr': 'A deadly virus from outer space threatens to wipe out humanity.', 'doc_year': 1969}\n", | |
| "Created vector: \"[-0.0430397167801857, 0.04119887575507164, 0.03773803636431694, 0.010774866677820683, 0.039475660771131516, -0.0214026290923357, 0.01947275549173355, 0.00783283356577158, 0.025680115446448326, 0.09449644386768341, -0.003302122000604868, 0.047390248626470566, 0.018230438232421875, -0.028012169525027275, -0.0919637531042099, -0.038990966975688934, -0.06219663843512535, -0.032344501465559006, -0.006513610016554594, 0.06071000546216965, 0.024634677916765213, 0.10988171398639679, -0.039423488080501556, -0.00587341608479619, -0.12526513636112213, 0.05369923263788223, 0.0270853154361248, 0.03303862363100052, -0.03036661632359028, -0.010769562795758247, 0.0470658540725708, -0.04685108736157417, 0.06674157083034515, 0.006891841068863869, 0.0012519035954028368, 0.019336596131324768, 0.03658575937151909, -0.08298184722661972, 0.01377305667847395, -0.0011435659835115075, -0.006669668015092611, -0.01683485321700573, -0.010652299970388412, 0.05894438549876213, 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| "Received update: {'Timestamp': 1706614399338054493, 'doc_uuid': 'cf497f84-d447-488c-ac3d-68c4681b88be', 'doc_name': 'The Left Hand of Darkness', 'doc_descr': 'A human ambassador is sent to a planet where the inhabitants are genderless and can change gender at will.', 'doc_year': 1969}\n", | |
| "Created vector: \"[0.06835169345140457, 0.07161106169223785, -0.056116752326488495, 0.00027605294599197805, 0.0031131156720221043, -0.0877617746591568, 0.06292880326509476, -0.15200698375701904, 0.0009341543773189187, 0.09255550801753998, 0.0020934599451720715, -0.054847776889801025, -0.027046097442507744, 0.011097592301666737, 0.027735635638237, 0.005109098274260759, -0.03127167001366615, 0.032389700412750244, 0.013752696104347706, 0.05680043622851372, 0.02019665762782097, -0.03123602643609047, -0.0051191155798733234, -0.0004562011163216084, -0.10110675543546677, -0.08415822684764862, -0.03228821977972984, -0.02196364291012287, -0.049966778606176376, 0.016135646030306816, -0.001226284191943705, 0.03956010565161705, -0.01256280392408371, 0.030542613938450813, -0.0560515858232975, 0.1449931114912033, -0.02628474310040474, -0.049552686512470245, 0.01648689992725849, 0.009251674637198448, 0.051938120275735855, -0.13037605583667755, -0.025233939290046692, -0.04914636164903641, 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| "Received update: {'Timestamp': 1706614399538760049, 'doc_uuid': '3a0fb63d-15b8-4ac7-8fa5-d433aec0e6ae', 'doc_name': \"The Time Traveler's Wife\", 'doc_descr': 'A love story between a man who involuntarily time travels and the woman he loves.', 'doc_year': 2003}\n", | |
| "Created vector: \"[-0.026922030374407768, 0.01746455952525139, 0.03929992392659187, 0.08742781728506088, -0.03379801660776138, 0.027124835178256035, 0.052756428718566895, -0.04150020703673363, 0.0378434993326664, -0.06891652941703796, -0.015587751753628254, 0.0456748865544796, -0.04623468965291977, 0.09151460230350494, 0.016819162294268608, 0.014253911562263966, -0.06783799827098846, 0.023272782564163208, 0.022471753880381584, 0.012675010599195957, 0.03890371695160866, -0.05974509194493294, -0.03808203712105751, -0.0016881820047274232, -0.0742245465517044, -0.030052484944462776, 0.03912728652358055, -0.007236476056277752, -0.047289252281188965, 0.03823164105415344, 0.018973009660840034, 0.012455812655389309, -0.03405575826764107, -0.005593579728156328, -0.0535542331635952, -0.018117817118763924, -0.07677809149026871, 0.06265303492546082, 0.02540847472846508, 0.01577674224972725, 0.03745590150356293, -0.06051455810666084, 0.013040314428508282, 0.03220631927251816, 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| ] | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "[2024-01-30 11:42:29,482] [INFO] : Stop processing of StreamingDataFrame\n", | |
| "INFO:quixstreams.app:Stop processing of StreamingDataFrame\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "#### STOP THE CELL MANUALLY WHEN ALL MESSAGES HAVE BEEN PROCESSED ☝️" | |
| ], | |
| "metadata": { | |
| "id": "Tf-0EEKArJrr" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Consume and Ingest\n", | |
| "\n", | |
| "Create a Quix \"terminus\" Consumer with Qdrant as a data sink.\n", | |
| "\n", | |
| "The consumer:\n", | |
| " 1. reads the embeddings from the vectors topic\n", | |
| " 2. writes each embedding to the vector db along with the original text." | |
| ], | |
| "metadata": { | |
| "id": "qbXFnHBwbp0e" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Initialze the input topic and the name of the vector db\n", | |
| "inputtopicname = vectors_topic_name\n", | |
| "qdrant = QdrantClient(path=\"./scifi-books4\") # persist a Qdrant DB on the filesystem" | |
| ], | |
| "metadata": { | |
| "id": "Wa1FjNyIlLvN" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Create collection to store books\n", | |
| "qdrant.recreate_collection(\n", | |
| " collection_name=\"my_books\",\n", | |
| " vectors_config=models.VectorParams(\n", | |
| " size=encoder.get_sentence_embedding_dimension(), # Vector size is defined by used model\n", | |
| " distance=models.Distance.COSINE\n", | |
| " )\n", | |
| ")" | |
| ], | |
| "metadata": { | |
| "id": "jwAsI3doxFMM", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "b7d963c8-57eb-4fa1-9ace-5a0764750847" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "True" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "execution_count": 15 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Define the ingestion function\n", | |
| "def ingest_vectors(row):\n", | |
| "\n", | |
| " single_record = models.PointStruct(\n", | |
| " id=row['doc_uuid'],\n", | |
| " vector=row['embeddings'],\n", | |
| " payload=row\n", | |
| " )\n", | |
| "\n", | |
| " qdrant.upload_points(\n", | |
| " collection_name=\"my_books\",\n", | |
| " points=[single_record]\n", | |
| " )\n", | |
| "\n", | |
| " print(f'Ingested vector entry id: \"{row[\"doc_uuid\"]}\"...')" | |
| ], | |
| "metadata": { | |
| "id": "r78mkDhNj3uC" | |
| }, | |
| "execution_count": null, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Define the consumer application and settings\n", | |
| "app = Application(\n", | |
| " broker_address=\"127.0.0.1:9092\",\n", | |
| " consumer_group=\"vectorizer3\",\n", | |
| " auto_offset_reset=\"earliest\",\n", | |
| " consumer_extra_config={\"allow.auto.create.topics\": \"true\"},\n", | |
| ")\n", | |
| "\n", | |
| "# Define an input topic with JSON deserializer\n", | |
| "input_topic = app.topic(inputtopicname, value_deserializer=\"json\")\n", | |
| "\n", | |
| "# Initialize a streaming dataframe based on the stream of messages from the input topic:\n", | |
| "sdf = app.dataframe(topic=input_topic)\n", | |
| "\n", | |
| "# INGESTION HAPPENS HERE\n", | |
| "### Trigger the embedding function for any new messages(rows) detected in the filtered SDF\n", | |
| "sdf = sdf.update(lambda row: ingest_vectors(row))\n", | |
| "app.run(sdf)\n", | |
| "\n", | |
| "# STOP THIS CELL MANUALLY WHEN THE BOOK ENTRIES HAVE BEEN INGESTED\n" | |
| ], | |
| "metadata": { | |
| "id": "Esc-9W2zY2IR", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "f002e767-f2db-420d-fa2e-34d83c6bdb81" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "[2024-01-30 11:46:15,198] [INFO] : Initializing processing of StreamingDataFrame\n", | |
| "INFO:quixstreams.app:Initializing processing of StreamingDataFrame\n", | |
| "[2024-01-30 11:46:15,202] [INFO] : Initializing state directory at \"/content/state/vectorizer3\"\n", | |
| "INFO:quixstreams.state.manager:Initializing state directory at \"/content/state/vectorizer3\"\n", | |
| "[2024-01-30 11:46:15,206] [INFO] : Waiting for incoming messages\n", | |
| "INFO:quixstreams.app:Waiting for incoming messages\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Ingested vector entry id: \"df35ce57-549a-4615-88a7-3541c82ac10e\"...\n", | |
| "Ingested vector entry id: \"1a54aafd-6fcc-40e9-8bca-d4a48f309297\"...\n", | |
| "Ingested vector entry id: \"eddca639-ae48-41d1-9906-8df3fe51df8a\"...\n", | |
| "Ingested vector entry id: \"612a45c1-568c-40c3-bcf8-3968dff7d235\"...\n", | |
| "Ingested vector entry id: \"8e28a5e5-1e4b-4564-a1fb-b681f3d85069\"...\n", | |
| "Ingested vector entry id: \"97dcf4bd-872d-42d5-a898-1bea38ec42b0\"...\n", | |
| "Ingested vector entry id: \"a2a86f14-1c8d-47a9-82e6-53d158eacc72\"...\n", | |
| "Ingested vector entry id: \"3e68c35f-716f-471e-a290-7ad26a21ee8b\"...\n", | |
| "Ingested vector entry id: \"a0b93e36-9dc7-4ee4-a89e-ae62c8fcdb92\"...\n", | |
| "Ingested vector entry id: \"1440acf7-fe66-40b3-80d5-2f58885173d3\"...\n", | |
| "Ingested vector entry id: \"706f79cd-66cd-4ac7-90bd-4172cf65a10d\"...\n", | |
| "Ingested vector entry id: \"cf497f84-d447-488c-ac3d-68c4681b88be\"...\n", | |
| "Ingested vector entry id: \"3a0fb63d-15b8-4ac7-8fa5-d433aec0e6ae\"...\n" | |
| ] | |
| }, | |
| { | |
| "output_type": "stream", | |
| "name": "stderr", | |
| "text": [ | |
| "[2024-01-30 11:46:28,490] [INFO] : Stop processing of StreamingDataFrame\n", | |
| "INFO:quixstreams.app:Stop processing of StreamingDataFrame\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "#### STOP THE CELL MANUALLY WHEN ALL MESSAGES HAVE BEEN READ ☝️" | |
| ], | |
| "metadata": { | |
| "id": "DOLAK4msq-Lk" | |
| } | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "source": [ | |
| "### Run a test query on the ingested vectors\n", | |
| "\n", | |
| "Use LangChain to do a basic similarity seach to make sure the vectors have been ingested properly and are matching in the expected way." | |
| ], | |
| "metadata": { | |
| "id": "BDpKDmKlluED" | |
| } | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "query = input(\"Enter your query: \") # i.e \"Aliens attack our planet\"" | |
| ], | |
| "metadata": { | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "id": "zMbJ9We7mtkh", | |
| "outputId": "200e2708-1796-4e8a-8980-1e8153c271d4" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Enter your query: Aliens attack our planet\n" | |
| ] | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "source": [ | |
| "# Let's now search for something\n", | |
| "\n", | |
| "hits = qdrant.search(\n", | |
| " collection_name=\"my_books\",\n", | |
| " query_vector=encoder.encode(query).tolist(),\n", | |
| " limit=3\n", | |
| ")\n", | |
| "\n", | |
| "print(\"Entries matching your query:\")\n", | |
| "for hit in hits:\n", | |
| " print(hit.payload, \"score:\", hit.score)" | |
| ], | |
| "metadata": { | |
| "id": "D-Sep1MUlzMj", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/" | |
| }, | |
| "outputId": "8c14116d-2068-44b0-9627-a2b17a9b596e" | |
| }, | |
| "execution_count": null, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "name": "stdout", | |
| "text": [ | |
| "Entries matching your query:\n", | |
| "{'Timestamp': 1706614923445518153, 'doc_uuid': 'a0b93e36-9dc7-4ee4-a89e-ae62c8fcdb92', 'doc_name': 'The War of the Worlds', 'doc_descr': 'A Martian invasion of Earth throws humanity into chaos.', 'doc_year': 1898, 'embeddings': [0.0011408552527427673, 0.034178461879491806, 0.05204031616449356, -0.016077376902103424, 0.03804362565279007, -0.10116572678089142, -0.04948024824261665, -0.07407407462596893, 0.031134065240621567, 0.052525173872709274, 0.018358418717980385, -0.011712891981005669, 0.029800964519381523, -0.026977602392435074, -0.058362893760204315, -0.027635620906949043, -0.05253475904464722, -0.012820189818739891, -0.03442619740962982, 0.057607319205999374, -0.07358844578266144, 0.06440331786870956, 0.005249663256108761, 0.11330675333738327, -0.09391900897026062, 0.03986871615052223, 0.019030146300792694, 0.09990473091602325, -0.049915801733732224, -0.06374746561050415, 0.03524061292409897, -0.034716494381427765, 0.05503867194056511, 0.020208658650517464, 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| "{'Timestamp': 1706614923461403838, 'doc_uuid': '706f79cd-66cd-4ac7-90bd-4172cf65a10d', 'doc_name': 'The Andromeda Strain', 'doc_descr': 'A deadly virus from outer space threatens to wipe out humanity.', 'doc_year': 1969, 'embeddings': [-0.0430397167801857, 0.04119887575507164, 0.03773803636431694, 0.010774866677820683, 0.039475660771131516, -0.0214026290923357, 0.01947275549173355, 0.00783283356577158, 0.025680115446448326, 0.09449644386768341, -0.003302122000604868, 0.047390248626470566, 0.018230438232421875, -0.028012169525027275, -0.0919637531042099, -0.038990966975688934, -0.06219663843512535, -0.032344501465559006, -0.006513610016554594, 0.06071000546216965, 0.024634677916765213, 0.10988171398639679, -0.039423488080501556, -0.00587341608479619, -0.12526513636112213, 0.05369923263788223, 0.0270853154361248, 0.03303862363100052, -0.03036661632359028, -0.010769562795758247, 0.0470658540725708, -0.04685108736157417, 0.06674157083034515, 0.006891841068863869, 0.0012519035954028368, 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| ] | |
| } | |
| ] | |
| } | |
| ] | |
| } |
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