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"Aleph Alpha - Qdrant"
] | /documentation/embeddings/aleph-alpha/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(3) | [
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] | p | If we wanted to create text embeddings with the same model, we wouldn’t use ImagePrompt.from_file, but simply provide the input | [
"documentation",
"documentation/embeddings",
"documentation/embeddings/aleph-alpha"
] | 8,600 |
[
"Aleph Alpha - Qdrant"
] | /documentation/embeddings/aleph-alpha/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(3) | [
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] | p | The advent of quantum computing has revolutionized many areas of science and technology, and one of the most intriguing developments has been its potential application to artificial neural networks (ANNs). | [
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] | p | The primary advantage of using quantum quantization for ANN vector search is the ability to search through an arbitrary-sized database in constant time. | [
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[
"Vector Search in constant time - Qdrant",
"Vector Search in Constant Time"
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] | p | This trick is called transposition and it allows to reduce the number of Grover’s iterations from O(√N) to O(√D), where D - is a dimension of the vector space. | [
"articles",
"articles/quantum-quantization"
] | 8,624 |
[
"Vector Search in constant time - Qdrant",
"Vector Search in Constant Time"
] | /articles/quantum-quantization/ | html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8) | [
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"documentation",
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"documentation/frameworks/airbyte"
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[
"Airbyte - Qdrant",
"Airbyte"
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[
"Airbyte - Qdrant",
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] | p | You can read more about these modes in the Airbyte documentation. | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,640 |
[
"Airbyte - Qdrant"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > h2:nth-of-type(1) | [
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[
"Airbyte - Qdrant",
"Prerequisites"
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] | li | Running instance of Qdrant. | [
"documentation",
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"documentation/frameworks/airbyte"
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[
"Airbyte - Qdrant",
"Prerequisites"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(2) | [
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] | li | It has to be accessible by URL from the machine where Airbyte is running. | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,646 |
[
"Airbyte - Qdrant",
"Prerequisites"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > ol > li:nth-of-type(2) | [
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"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,647 |
[
"Airbyte - Qdrant"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > h2:nth-of-type(2) | [
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] | h2 | Setting up Qdrant as a destination | [
"documentation",
"documentation/frameworks",
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[
"Airbyte - Qdrant",
"Setting up Qdrant as a destination"
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] | p | You can choose how you want to | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,653 |
[
"Airbyte - Qdrant",
"Text processing"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(7) | [
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[
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[
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] | p | In this case, you can pass the field | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,661 |
[
"Airbyte - Qdrant",
"Embeddings"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(11) | [
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[
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[
"Airbyte - Qdrant",
"Qdrant connection details"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(13) | [
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] | p | mechanism, here is where you can pass the token. | [
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"documentation/frameworks",
"documentation/frameworks/airbyte"
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[
"Airbyte - Qdrant",
"Qdrant connection details"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(15) | [
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"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
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[
"Airbyte - Qdrant",
"Setting up connection"
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] | p | long as Airbyte supports it. | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,674 |
[
"Airbyte - Qdrant",
"Setting up connection"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(16) | [
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"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,675 |
[
"Airbyte - Qdrant",
"Setting up connection"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | More information about creating connections can be found in the | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/airbyte"
] | 8,676 |
[
"Airbyte - Qdrant",
"Setting up connection"
] | /documentation/frameworks/airbyte/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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[
"AWS Bedrock - Qdrant"
] | /documentation/embeddings/bedrock/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > h1 | [
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"documentation",
"documentation/embeddings",
"documentation/embeddings/bedrock"
] | 8,680 |
[
"AWS Bedrock - Qdrant",
"Bedrock Embeddings"
] | /documentation/embeddings/bedrock/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(2) | [
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] | p | You’ll need the following information from your AWS account: | [
"documentation",
"documentation/embeddings",
"documentation/embeddings/bedrock"
] | 8,681 |
[
"AWS Bedrock - Qdrant",
"Bedrock Embeddings"
] | /documentation/embeddings/bedrock/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > ul > li:nth-of-type(1) | [
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[
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] | p | To configure your credentials, review the following AWS article: How do I create an AWS access key. | [
"documentation",
"documentation/embeddings",
"documentation/embeddings/bedrock"
] | 8,685 |
[
"AWS Bedrock - Qdrant",
"Bedrock Embeddings"
] | /documentation/embeddings/bedrock/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(4) | [
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] | p | With the following code sample, you can generate embeddings using the Titan Embeddings G1 - Text model which produces sentence embeddings of size 1536. | [
"documentation",
"documentation/embeddings",
"documentation/embeddings/bedrock"
] | 8,686 |
[
"MindsDB - Qdrant"
] | /documentation/frameworks/mindsdb/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > h1 | [
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] | h1 | MindsDB | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/mindsdb"
] | 8,687 |
[
"MindsDB - Qdrant",
"MindsDB"
] | /documentation/frameworks/mindsdb/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > p:nth-of-type(1) | [
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] | p | With the MindsDB-Qdrant integration, you can now select Qdrant as a database to load into and retrieve from with semantic search and filtering. | [
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[
"MindsDB - Qdrant",
"MindsDB"
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[
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[
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"documentation",
"documentation/frameworks",
"documentation/frameworks/mindsdb"
] | 8,697 |
[
"MindsDB - Qdrant",
"Usage"
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] | p | The available arguments for instantiating Qdrant can be found here. | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/mindsdb"
] | 8,698 |
[
"MindsDB - Qdrant"
] | /documentation/frameworks/mindsdb/ | html > body > div:nth-of-type(1) > section > div > div > div:nth-of-type(2) > article > h2:nth-of-type(2) | [
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] | h2 | Creating a new table | [
"documentation",
"documentation/frameworks",
"documentation/frameworks/mindsdb"
] | 8,699 |
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