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docs: Added Fluvio integration (#1134)
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| [Connect](./redpanda/) | Declarative data-agnostic streaming service for efficient, stateless processing. |
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| [Connect](./redpanda/) | Declarative data-agnostic streaming service for efficient, stateless processing. |
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| [Confluent](./confluent/) | Fully-managed data streaming platform with a cloud-native Apache Kafka engine. |
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| [Confluent](./confluent/) | Fully-managed data streaming platform with a cloud-native Apache Kafka engine. |
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| [DLT](./dlt/) | Python library to simplify data loading processes between several sources and destinations. |
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| [DLT](./dlt/) | Python library to simplify data loading processes between several sources and destinations. |
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| [Fluvio](./fluvio/) | Rust-based platform for high speed, real-time data processing. |
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| [Fondant](./fondant/) | Framework for developing datasets, sharing reusable operations and data processing trees. |
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| [Fondant](./fondant/) | Framework for developing datasets, sharing reusable operations and data processing trees. |
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| [MindsDB](./mindsdb/) | Platform to deploy, serve, and fine-tune models with numerous data source integrations. |
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| [MindsDB](./mindsdb/) | Platform to deploy, serve, and fine-tune models with numerous data source integrations. |
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| [NiFi](./nifi/) | Data ingestion platform to manage data transfer between different sources and destination systems. |
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| [NiFi](./nifi/) | Data ingestion platform to manage data transfer between different sources and destination systems. |
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---
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title: InfinyOn Fluvio
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---
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[InfinyOn Fluvio](https://www.fluvio.io/) is an open-source platform written in Rust for high speed, real-time data processing. It is cloud native, designed to work with any infrastructure type, from bare metal hardware to containerized platforms.
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## Usage with Qdrant
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With the [Qdrant Fluvio Connector](https://github.com/qdrant/qdrant-fluvio), you can stream records from Fluvio topics to Qdrant collections, leveraging Fluvio's delivery guarantees and high-throughput.
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### Pre-requisites
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- A Fluvio installation. You can refer to the [Fluvio Quickstart](https://www.fluvio.io/docs/fluvio/quickstart/) for instructions.
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- Qdrant server to connect to. You can set up a [local instance](/documentation/quickstart/) or a free cloud instance at [cloud.qdrant.io](https://cloud.qdrant.io/).
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### Downloading the connector
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Run the following commands after [setting up Fluvio](https://www.fluvio.io/docs/fluvio/quickstart).
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```console
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cdk hub download qdrant/qdrant-sink@0.1.0
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```
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### Example Config
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> _config.yaml_
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```yaml
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apiVersion: 0.1.0
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meta:
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version: 0.1.0
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name: my-qdrant-connector
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type: qdrant-sink
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topic: topic-name
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secrets:
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- name: QDRANT_API_KEY
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qdrant:
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url: https://xyz-example.eu-central.aws.cloud.qdrant.io:6334
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api_key: "${{ secrets.QDRANT_API_KEY }}"
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```
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> _secrets.txt_
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```text
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QDRANT_API_KEY=<SOME_API_KEY>
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```
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### Running
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```console
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cdk deploy start --ipkg qdrant-qdrant-sink-0.1.0.ipkg -c config.yaml --secrets secrets.txt
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```
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### Produce Messages
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You can now run the following to generate messages to be written into Qdrant.
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```console
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fluvio produce topic-name
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```
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### Message Formats
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This sink connector supports messages with dense/sparse/multi vectors.
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_Click each to expand._
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<details>
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<summary><b>Unnamed/Default vector</b></summary>
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Reference: [Creating a collection with a default vector](https://qdrant.tech/documentation/concepts/collections/#create-a-collection).
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```json
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{
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"collection_name": "{collection_name}",
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"id": 1,
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"vector": [
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0.1,
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0.2,
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0.7,
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0.8
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],
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"payload": {
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"name": "fluvio",
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"description": "Solution for distributed stream processing",
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"url": "https://www.fluvio.io/"
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}
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}
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```
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</details>
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<details>
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<summary><b>Named multiple vectors</b></summary>
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Reference: [Creating a collection with multiple vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-multiple-vectors).
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```json
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{
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"collection_name": "{collection_name}",
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"id": 1,
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"vector": {
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"some-dense": [
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0.1,
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0.2,
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0.8
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],
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"some-other-dense": [
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0.1,
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0.7,
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0.8
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]
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},
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"payload": {
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"name": "fluvio",
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"description": "Solution for distributed stream processing",
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"url": "https://www.fluvio.io/"
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}
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}
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```
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</details>
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<details>
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<summary><b>Sparse vectors</b></summary>
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Reference: [Creating a collection with sparse vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-sparse-vectors).
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```json
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{
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"collection_name": "{collection_name}",
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"id": 1,
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"vector": {
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"some-sparse": {
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"indices": [
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0,
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],
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"values": [
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1.0
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]
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}
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},
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"payload": {
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"name": "fluvio",
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"description": "Solution for distributed stream processing",
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"url": "https://www.fluvio.io/"
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}
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}
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```
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</details>
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<details>
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<summary><b>Multi-vector</b></summary>
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```json
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{
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"collection_name": "{collection_name}",
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"id": 1,
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"vector": {
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"some-multi": [
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[
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[
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]
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]
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},
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"payload": {
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"name": "fluvio",
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"description": "Solution for distributed stream processing",
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"url": "https://www.fluvio.io/"
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}
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}
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```
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</details>
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<details>
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<summary><b>Combination of named dense and sparse vectors</b></summary>
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Reference:
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- [Creating a collection with multiple vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-multiple-vectors).
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- [Creating a collection with sparse vectors](https://qdrant.tech/documentation/concepts/collections/#collection-with-sparse-vectors).
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```json
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{
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"collection_name": "{collection_name}",
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"id": "a10435b5-2a58-427a-a3a0-a5d845b147b7",
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"vector": {
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"some-other-dense": [
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],
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"some-sparse": {
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"indices": [
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],
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"values": [
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1.0
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]
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}
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},
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"payload": {
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"name": "fluvio",
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"description": "Solution for distributed stream processing",
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"url": "https://www.fluvio.io/"
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}
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}
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```
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</details>
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### Further Reading
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- [Fluvio Quickstart](https://www.fluvio.io/docs/fluvio/quickstart)
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- [Fluvio Tutorials](https://www.fluvio.io/docs/fluvio/tutorials/)
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- [Connector Source](https://github.com/qdrant/qdrant-fluvio)
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