From af033d3225c839d8c6700ebe7aa4305dc2330d0e Mon Sep 17 00:00:00 2001 From: Steve <100689438+SteveRosam@users.noreply.github.com> Date: Tue, 18 Apr 2023 11:14:57 +0100 Subject: [PATCH 1/3] Update to Quix Companion App --- .../tutorials/eventDetection/data-acquisition.md | 16 ++++++++-------- .../tutorials/telemetry-data/telemetry-data.md | 4 ++-- 2 files changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/platform/tutorials/eventDetection/data-acquisition.md b/docs/platform/tutorials/eventDetection/data-acquisition.md index d4149a5c..04341063 100644 --- a/docs/platform/tutorials/eventDetection/data-acquisition.md +++ b/docs/platform/tutorials/eventDetection/data-acquisition.md @@ -4,13 +4,13 @@ You’ll start this tutorial by streaming data into a topic. Starting with the d You have two options for this stage: -1. Stream data from your Android phone with the [Quix Tracker app](#quix-tracker-app). +1. Stream data from your Android phone with the [Quix Companion app](#quix-companion-app). 2. Stream prerecorded [CSV data](#csv-data). You will only need to set up one of these data sources but if you want to do both you can do that too! -## Quix tracker App +## Quix companion app ### External source @@ -28,23 +28,23 @@ To add an external source: 4. Enter `phone-data` in the `Output` field and click `Add new topic` in the drop-down. -5. Enter `Quix Tracker web gateway` in the `Name` field. +5. Enter `Quix companion web gateway` in the `Name` field. 6. Click `Add external Source`. ### Install and configure the apps -To stream data from your phone you’ll need to install the Quix Tracker app on your Android phone and deploy the QR Settings Share app to your Quix workspace. +To stream data from your phone you’ll need to install the `Quix Companion App` on your Android phone and deploy the QR Settings Share app to your Quix workspace. Follow these steps: -1. Install the `Quix Tracker` from the Google Play Store. +1. Install the `Quix Companion App` from the Google Play Store. [![Quix Play store image](https://play.google.com/intl/en_us/badges/static/images/badges/en_badge_web_generic.png){width=200px}](https://play.google.com/store/apps/details?id=com.quix.quixtracker&gl=GB){target=_blank} 2. Open the app and navigate to the `Settings` page via the menu. -3. Click the `SCAN QR CODE` button at the top of the settings page. Now continue to follow these steps. When directed, in step #17, you will scan the QR code using the Quix Tracker app. +3. Click the `SCAN QR CODE` button at the top of the settings page. Now continue to follow these steps. When directed, in step #17, you will scan the QR code using the Quix Companion app. 4. In the Quix Portal, click the user icon in the top right of the browser. @@ -78,7 +78,7 @@ Follow these steps: ![QR Settings Share UI](./qr-setting-share-ui.png){width=600px} -17. Scan the QR code using the Quix Tracker app. +17. Scan the QR code using the Quix Companion App. The app has now been configured with the access token, allowing it to communicate with Quix. @@ -119,7 +119,7 @@ Follow these steps to ensure that everything is working as expected: 7. Move or gently shake your phone and notice that the waveform reflects whatever movement your phone is experiencing. !!! success - You have connected the Quix Tracker app to your workspace and verified the connection using the Live Data Explorer. + You have connected the Quix Companion App to your workspace and verified the connection using the Live Data Explorer. ## CSV data diff --git a/docs/platform/tutorials/telemetry-data/telemetry-data.md b/docs/platform/tutorials/telemetry-data/telemetry-data.md index c05d35db..674bafda 100644 --- a/docs/platform/tutorials/telemetry-data/telemetry-data.md +++ b/docs/platform/tutorials/telemetry-data/telemetry-data.md @@ -20,7 +20,7 @@ Most of the code you'll need has already been written. It lives in our library, ## Components -**Android App** - Our companion app for collecting real-time sensor data from your phone. It's pre-built and published to the Play store to save you time. You can also access the source code in our [GitHub repo](https://github.com/quixio/quix-tracker){target=_blank}. +**Android App** - Our companion app for collecting real-time sensor data from your Android phone. It's pre-built and published to the Google Play store to save you time. You can also access the source code in our [GitHub repo](https://github.com/quixio/quix-companion-app){target=_blank}. **Streamlit App** - See your location on a map and other activity metrics. @@ -80,7 +80,7 @@ The QR shown on screen is a short-lived link to the longer lasting token. It's time to install the Android app! -1. Go to the Google Play store and search for "Quix Tracker App" ensuring it's the one published by us. +1. Go to the Google Play store and search for "Quix Companion App" ensuring it's the one published by us. \[Screenshot of Play store coming soon\] From aba92109aac3528edabeafa4db1e65a7a6c5e45c Mon Sep 17 00:00:00 2001 From: Steve <100689438+SteveRosam@users.noreply.github.com> Date: Wed, 19 Apr 2023 09:57:20 +0100 Subject: [PATCH 2/3] Update to use quix-samples repo and naming * Switch from Library to Samples --- .github/workflows/build-commit-subfolder.yaml | 10 ++-- .github/workflows/sync-build-deploy.yaml | 10 ++-- .../apis/data-catalogue-api/aggregate-tags.md | 2 +- .../apis/data-catalogue-api/aggregate-time.md | 2 +- docs/apis/data-catalogue-api/filter-tags.md | 2 +- docs/apis/data-catalogue-api/intro.md | 2 +- docs/apis/data-catalogue-api/raw-data.md | 2 +- .../data-catalogue-api/streams-filtered.md | 2 +- .../apis/data-catalogue-api/streams-models.md | 2 +- docs/apis/data-catalogue-api/streams-paged.md | 2 +- docs/platform/connectors/index.md | 4 +- docs/platform/how-to/deploy-public-page.md | 8 ++-- docs/platform/how-to/jupyter-nb.md | 2 +- docs/platform/intro.md | 4 +- docs/platform/samples/samples.md | 5 +- .../currency-alerting/currency-alerting.md | 42 ++++++++--------- .../tutorials/data-science/data-science.md | 14 +++--- .../data-stream-processing.md | 12 ++--- .../tutorials/eventDetection/conclusion.md | 2 +- .../eventDetection/crash-detection-ui.md | 4 +- .../eventDetection/crash-detection.md | 2 +- .../eventDetection/data-acquisition.md | 8 ++-- .../tutorials/eventDetection/index.md | 2 +- .../image-processing/connect-video-tfl.md | 2 +- .../image-processing/connect-video-webcam.md | 2 +- .../tutorials/image-processing/decode.md | 4 +- .../tutorials/image-processing/index.md | 18 ++++---- .../image-processing/object-detection.md | 2 +- .../tutorials/image-processing/summary.md | 18 ++++---- .../image-processing/tfl-frame-grabber.md | 2 +- .../tutorials/image-processing/web-ui.md | 2 +- .../nocode-sentiment-analysis.md | 8 ++-- .../tutorials/quick-start/quick-start.md | 26 +++++------ .../rss-tutorial/rss-processing-pipeline.md | 46 +++++++++---------- .../tutorials/sentiment-analysis/analyze.md | 4 +- .../code-and-deploy-sentiment-service.md | 6 +-- .../sentiment-analysis/conclusion.md | 4 +- .../sentiment-analysis/customize-the-ui.md | 2 +- .../sentiment-analysis/sentiment-demo-ui.md | 8 ++-- .../sentiment-analysis/twitter-data.md | 6 +-- .../slack-alerting/slack-alerting.md | 12 ++--- .../telemetry-data/telemetry-data.md | 8 ++-- .../train-and-deploy-ml/deploy-ml.md | 6 +-- .../train-and-deploy-ml/train-ml-model.md | 4 +- 44 files changed, 167 insertions(+), 168 deletions(-) diff --git a/.github/workflows/build-commit-subfolder.yaml b/.github/workflows/build-commit-subfolder.yaml index a2c0f3f1..f9f7922b 100644 --- a/.github/workflows/build-commit-subfolder.yaml +++ b/.github/workflows/build-commit-subfolder.yaml @@ -135,20 +135,20 @@ jobs: run: "sed -i 's,./images,./assets/client-library/,g' docs/client-library-intro.md" # clone the library repo - - name: Checkout Library + - name: Checkout Samples uses: actions/checkout@v3 with: - repository: 'quixio/quix-library' + repository: 'quixio/quix-samples' ref: 'develop' # when a dev branch exists we can get the dev content #ref: '{{ steps.extract_branch.outputs.branch }}' - path: 'library' + path: 'samples' # use our own GitHub Action to bring in library readme files - - name: Quix Library readme.md importer + - name: Quix Samples readme.md importer uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.12 id: readme_importer with: - LIBRARY_REPO_PATH: "library" + LIBRARY_REPO_PATH: "samples" DOCS_PATH: "" REPLACEMENT_PLACEHOLDER: "#ConnectorsGetInsertedHere" README_DEST: "docs/library_readmes/connectors" diff --git a/.github/workflows/sync-build-deploy.yaml b/.github/workflows/sync-build-deploy.yaml index 044765fd..f68166aa 100644 --- a/.github/workflows/sync-build-deploy.yaml +++ b/.github/workflows/sync-build-deploy.yaml @@ -138,20 +138,20 @@ jobs: ### IMPORT LIBRARY README.MD FILES INTO DOCS #################################################### # clone the library repo - - name: Checkout Library + - name: Checkout Samples uses: actions/checkout@v3 with: - repository: 'quixio/quix-library' + repository: 'quixio/quix-samples' ref: 'develop' # when a dev branch exists we can get the dev content #ref: '{{ steps.extract_branch.outputs.branch }}' - path: 'library' + path: 'samples' # use our own GitHub Action to bring in library readme files - - name: Quix Library readme.md importer + - name: Quix Samples readme.md importer uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.12 id: readme_importer with: - LIBRARY_REPO_PATH: "library" + LIBRARY_REPO_PATH: "samples" DOCS_PATH: "" REPLACEMENT_PLACEHOLDER: "#ConnectorsGetInsertedHere" README_DEST: "docs/library_readmes/connectors" diff --git a/docs/apis/data-catalogue-api/aggregate-tags.md b/docs/apis/data-catalogue-api/aggregate-tags.md index f25537f1..7d6ed4df 100644 --- a/docs/apis/data-catalogue-api/aggregate-tags.md +++ b/docs/apis/data-catalogue-api/aggregate-tags.md @@ -6,7 +6,7 @@ you’ll want to group results by that tag. You can do so via the ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/aggregate-time.md b/docs/apis/data-catalogue-api/aggregate-time.md index 88383992..0cd49963 100644 --- a/docs/apis/data-catalogue-api/aggregate-time.md +++ b/docs/apis/data-catalogue-api/aggregate-time.md @@ -5,7 +5,7 @@ You can downsample and upsample data from the catalogue using the ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/filter-tags.md b/docs/apis/data-catalogue-api/filter-tags.md index 02c17e6a..77f3b91a 100644 --- a/docs/apis/data-catalogue-api/filter-tags.md +++ b/docs/apis/data-catalogue-api/filter-tags.md @@ -5,7 +5,7 @@ so they can be used to efficiently filter data. ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/intro.md b/docs/apis/data-catalogue-api/intro.md index 2da784cc..fe7d36f2 100644 --- a/docs/apis/data-catalogue-api/intro.md +++ b/docs/apis/data-catalogue-api/intro.md @@ -18,7 +18,7 @@ how to [form a typical request to the API](request.md). You’ll also need to have some data stored in the Quix platform for API -use to be meaningful. You can use any Source of our [Quix Library](../../platform/samples/samples.md) to do this using the Quix +use to be meaningful. You can use any Source of our [Quix Samples](../../platform/samples/samples.md) to do this using the Quix portal. ## Further documentation diff --git a/docs/apis/data-catalogue-api/raw-data.md b/docs/apis/data-catalogue-api/raw-data.md index 3ab655bb..ca7938fd 100644 --- a/docs/apis/data-catalogue-api/raw-data.md +++ b/docs/apis/data-catalogue-api/raw-data.md @@ -6,7 +6,7 @@ results. ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/streams-filtered.md b/docs/apis/data-catalogue-api/streams-filtered.md index a5ace2a9..64d0e465 100644 --- a/docs/apis/data-catalogue-api/streams-filtered.md +++ b/docs/apis/data-catalogue-api/streams-filtered.md @@ -5,7 +5,7 @@ request to the `/streams` endpoint. ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/streams-models.md b/docs/apis/data-catalogue-api/streams-models.md index bd61def6..c361396b 100644 --- a/docs/apis/data-catalogue-api/streams-models.md +++ b/docs/apis/data-catalogue-api/streams-models.md @@ -6,7 +6,7 @@ endpoint. ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/apis/data-catalogue-api/streams-paged.md b/docs/apis/data-catalogue-api/streams-paged.md index 6e3bef0d..f0c8b403 100644 --- a/docs/apis/data-catalogue-api/streams-paged.md +++ b/docs/apis/data-catalogue-api/streams-paged.md @@ -8,7 +8,7 @@ use pagination parameters to group the results into smaller pages. ## Before you begin - - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Library](../../platform/samples/samples.md) to set some up. + - If you don’t already have any Stream data in your workspace, you can use any Source of our [Quix Samples](../../platform/samples/samples.md) to set some up. - [Get a Personal Access Token](authenticate.md) to authenticate each request. diff --git a/docs/platform/connectors/index.md b/docs/platform/connectors/index.md index 814d8505..61d286f7 100644 --- a/docs/platform/connectors/index.md +++ b/docs/platform/connectors/index.md @@ -1,9 +1,9 @@ # Connectors -Connectors are part of our [open source](https://github.com/quixio/quix-library){target="_blank"} repository of samples, examples and integrations. +Connectors are part of our [open source](https://github.com/quixio/quix-samples){target="_blank"} repository of samples, examples and integrations. Connectors help our users connect with other vendors such as AWS and Kafka. -You can explore the connector README files here in Quix Docs. When you are ready to start using them, head over to the Quix Library [GitHub](https://github.com/quixio/quix-library){target="_blank"} repository, or [sign up](https://quix.io/signup){target="_blank"} and [login to the platform](https://portal.platform.quix.ai/){target="_blank"}. +You can explore the connector README files here in Quix Docs. When you are ready to start using them, head over to the Quix Samples [GitHub](https://github.com/quixio/quix-samples){target="_blank"} repository, or [sign up](https://quix.io/signup){target="_blank"} and [login to the platform](https://portal.platform.quix.ai/){target="_blank"}. [//]: <> (#connectors_tile_replacement) \ No newline at end of file diff --git a/docs/platform/how-to/deploy-public-page.md b/docs/platform/how-to/deploy-public-page.md index 0fe626f2..bae1cdf1 100644 --- a/docs/platform/how-to/deploy-public-page.md +++ b/docs/platform/how-to/deploy-public-page.md @@ -4,13 +4,13 @@ The Quix SaaS platform allows you to deploy public-facing web pages and APIs. This how-to will help to explain the features and options and ensure projects containing public facing web pages and APIs are successful. -## Library samples +## Samples -In our Library you can find our `Web API Template` which demonstrates how to create a API using `Node`. +In our samples you can find our `Web API Template` which demonstrates how to create a API using `Node`. There are also examples dashboard and web/UI examples using `Dash`, `Streamlit` and `Angular`. -![Library examples](../images/library.png){width=500px} +![Samples](../images/library.png){width=500px} ## The code @@ -42,7 +42,7 @@ To access your public facing service or web site you must enable `Public Access` ## Security -Please note that the basic examples, included in our library, do not include any security features and come with no warranty. +Please note that the basic examples, included in our Quix Samples, do not include any security features and come with no warranty. Quix advises you to build in a security layer to ensure your data is secure and only the intended recipients have access to it. diff --git a/docs/platform/how-to/jupyter-nb.md b/docs/platform/how-to/jupyter-nb.md index b8dd057e..bd9f04ed 100644 --- a/docs/platform/how-to/jupyter-nb.md +++ b/docs/platform/how-to/jupyter-nb.md @@ -13,7 +13,7 @@ analysis so much easier. ## Preparation You’ll need some data stored in the Quix platform. You can use any of -our Data Sources available in the samples Library, or just follow the +our Data Sources available in the Quix Samples, or just follow the onboarding process when you [sign-up to Quix](https://portal.platform.quix.ai/self-sign-up?xlink=docs){target=_blank}. diff --git a/docs/platform/intro.md b/docs/platform/intro.md index d2fcdd55..57665596 100644 --- a/docs/platform/intro.md +++ b/docs/platform/intro.md @@ -45,7 +45,7 @@ To achieve these goals Quix Portal includes the following features: - **Online IDE**: Develop and Run your streaming applications directly on the browser without setting up a local environment. - - **Library**: Choose between hundreds of autogenerated code examples + - **Samples**: Choose between hundreds of autogenerated code examples ready to run and deploy from our Online IDE. - **One click deployments**: Deploy and manage your streaming @@ -122,7 +122,7 @@ will build selected GIT commit into a docker image. ### Docker integration -Each code example generated using the **Quix library** is shipped with a +Each code example generated using the **Quix Samples** is shipped with a `Dockerfile` that is designed to work in the **Quix serverless compute environment** powered by **Kubernetes**. You can alter this file if necessary. When you deploy a service with Quix, a code reference to GIT diff --git a/docs/platform/samples/samples.md b/docs/platform/samples/samples.md index 4b10d77c..19642704 100644 --- a/docs/platform/samples/samples.md +++ b/docs/platform/samples/samples.md @@ -1,10 +1,9 @@ # Code Samples -The Quix Portal includes a Library of templates and sample projects that -you can use to start working with the platform. +The Quix Portal includes Quix Samples, a collection of templates and sample projects that you can use to start working with the platform. Quix allows explore the samples and save them as a new Project and immediately Run or Deploy them. If you don’t have a Quix account yet, go [sign-up to Quix](https://portal.platform.quix.ai/self-sign-up?xlink=docs){target=_blank} and create one. -The backend of the Quix Library is handled by a public [Open source repository](https://github.com/quixio/quix-library){target=_blank} on GitHub, so you can become a contributor of our Library generating new samples or updating existing ones. +The backend of the Quix Samples is handled by a public [Open source repository](https://github.com/quixio/quix-samples){target=_blank} on GitHub. You can become a contributor of our Samples by generating new samples or updating existing ones. ![Library.png](library.png) diff --git a/docs/platform/tutorials/currency-alerting/currency-alerting.md b/docs/platform/tutorials/currency-alerting/currency-alerting.md index 4ef905b7..5c837b5c 100644 --- a/docs/platform/tutorials/currency-alerting/currency-alerting.md +++ b/docs/platform/tutorials/currency-alerting/currency-alerting.md @@ -6,9 +6,9 @@ In this tutorial you will learn how to build a real-time streaming pipeline that In this tutorial you will learn: -* How to use an existing library item to interface Quix to a real-time event stream. In this tutorial this is a stream of trading data from CoinAPI. +* How to use an existing sample to interface Quix to a real-time event stream. In this tutorial this is a stream of trading data from CoinAPI. * How to create a transformation. -* How to use an existing library item to interface Quix to a mobile device. +* How to use an existing sample to interface Quix to a mobile device. ## Getting help @@ -36,9 +36,9 @@ The colors describe the role of the microservice that is being deployed. The pos ## Setting up the CoinAPI source -In this section you will learn how to set up the source library item and deploy it in your pipeline as a microservice. +In this section you will learn how to set up the source sample and deploy it in your pipeline as a microservice. -This library item, when deployed as a microservice in the Quix pipeline, connects a live stream of updates for the currency pair: `BTC/USD`. This real-time exchange rate data is streamed in from the [CoinAPI](https://www.coinapi.io/){target=_blank} through its [Websocket](https://en.wikipedia.org/wiki/WebSocket){target=_blank} interface. The free [sandbox version](https://docs.coinapi.io/#endpoints-2){target=_blank} is used for the purposes of this tutorial. +This sample, when deployed as a microservice in the Quix pipeline, connects a live stream of updates for the currency pair: `BTC/USD`. This real-time exchange rate data is streamed in from the [CoinAPI](https://www.coinapi.io/){target=_blank} through its [Websocket](https://en.wikipedia.org/wiki/WebSocket){target=_blank} interface. The free [sandbox version](https://docs.coinapi.io/#endpoints-2){target=_blank} is used for the purposes of this tutorial. To summarize this functionality: @@ -47,13 +47,13 @@ To summarize this functionality: To set up the CoinAPI source, follow these steps: -1. In the [Quix Portal](https://portal.platform.quix.ai/){target=_blank}, click the `Library` icon in the main left-hand navigation. +1. In the [Quix Portal](https://portal.platform.quix.ai/){target=_blank}, click the `Samples` icon in the main left-hand navigation. -2. In the search box on the library page, enter "CoinAPI - Exchange Rate Feed". +2. In the search box on the samples page, enter "CoinAPI - Exchange Rate Feed". - You will see the Coin API library item appear in the search results: ![CoinAPI library item](coinapi.png "CoinAPI library item") + You will see the Coin API sample appear in the search results: ![CoinAPI sample](coinapi.png "CoinAPI sample") -3. Click the `Preview code` button, and on the page that appears, click the `Edit code` button. When you choose to edit a library item, Quix prompts you to create a copy of it as a project, as library items are read-only. +3. Click the `Preview code` button, and on the page that appears, click the `Edit code` button. When you choose to edit a sample, Quix prompts you to create a copy of it as a project, as sample are read-only. Optionally, you could have clicked the `Setup & deploy` button, which would have deployed the microservice directly. However, in this tutorial, you are given the opportunity to first look at the code, and modify it if necessary. @@ -67,11 +67,11 @@ To set up the CoinAPI source, follow these steps: | `asset_id_base` | The short code for the _base_ currency that you want to track, for example BTC. | | `asset_id_quote` | The short code for the _target_ currency in which prices will be quoted, for example, USD. | -5. Click `Save as project`. You now have a copy of the CoinAPI library item in your workspace. +5. Click `Save as project`. You now have a copy of the CoinAPI sample in your workspace. -6. Click the `Deploy` button. The library item is deployed as a service and automatically started. +6. Click the `Deploy` button. The sample is deployed as a service and automatically started. - Once the library item has been deployed, you’ll be redirected to the workspace home page, where you can see the service in the pipeline context, as was illustrated previously. + Once the sample has been deployed, you’ll be redirected to the workspace home page, where you can see the service in the pipeline context, as was illustrated previously. 7. Click the CoinAPI service card to inspect the logs: @@ -96,12 +96,12 @@ To summarize this functionality: * When the threshold criteria are met, the microservice writes an alert message to a topic called `currency-rate-alerts`. * Downstream services can then read fom this topic and send alerts and notifications whenever they detect a new message. -To set up the Threshold Alert item, follow these steps: +To set up the Threshold Alert sample, follow these steps: -1. Click on the Library icon in the left-hand navigation. -2. In the search box on the library page, enter "Threshold Alerts". +1. Click on the Samples icon in the left-hand navigation. +2. In the search box on the samples page, enter "Threshold Alerts". - You will see the `Threshold Alert` library item appear in the search results: + You will see the `Threshold Alert` sample appear in the search results: ![Threshold Alert](threshold-alerts.png "Threshold Alert") @@ -120,11 +120,11 @@ To set up the Threshold Alert item, follow these steps: 5. Click `Save as project`. - You now have a copy of the Threshold Alert library item in your workspace. + You now have a copy of the Threshold Alert sample in your workspace. 6. Click the `Deploy` button. - The library item is deployed as a service and automatically started. Once the microservice has been deployed, you'll be redirected to the pipeline view. + The sample is deployed as a service and automatically started. Once the microservice has been deployed, you'll be redirected to the pipeline view. 7. Click the Threshold Alert service card to inspect the logs. @@ -146,11 +146,11 @@ It also reads the contents of the message and enriches the notification with det To set up the push nonfiction microservice, follow these steps: -1. Click on the Library icon in the left-hand navigation. +1. Click on the Samples icon in the left-hand navigation. -2. In the search box on the library page, enter "Pushover". +2. In the search box on the samples page, enter "Pushover". - You will see the `Threshold Alert` library item appear in the search results: + You will see the `Threshold Alert` sample appear in the search results: ![Pushover Notifications](library-pushover.png "Pushover Notifications") @@ -166,7 +166,7 @@ To set up the push nonfiction microservice, follow these steps: | `api_token` | Enter the API token that you generated for this application in your Pushover dashboard. For example: `azovmnbxxdxkj7j4g4wxxxdwf12xx4`. | | `user_key` | Enter the user key that you received when you signed up with Pushover. For example: `u721txxxgmvuy5dxaxxxpzx5xxxx9e`) | -5. Click the `Save as project`. You now have a copy of the Pushover notification library item in your workspace. +5. Click the `Save as project`. You now have a copy of the Pushover notification sample in your workspace. 6. Click the `Deploy` button. diff --git a/docs/platform/tutorials/data-science/data-science.md b/docs/platform/tutorials/data-science/data-science.md index 3f907cbc..687763c7 100644 --- a/docs/platform/tutorials/data-science/data-science.md +++ b/docs/platform/tutorials/data-science/data-science.md @@ -72,14 +72,14 @@ This walk through covers the following steps: Start by getting the real time bikes stream. Use CityBikes to get real time bikes data (it doesn’t require a sign up or any keys). -Instead of writing a lot of code you will use the Library to deploy a pre-built service that streams data from the New York CitiBikes api. +Instead of writing a lot of code you will use the Samples to deploy a pre-built service that streams data from the New York CitiBikes api. -1. Search the library for `New York` and select the `New York Bikes - Source` tile. +1. Search the samples for `New York` and select the `New York Bikes - Source` tile. - ![NY Bikes library tile](ny-bikes-library-tile.png){width=400px} + ![NY Bikes sample tile](ny-bikes-library-tile.png){width=400px} !!! tip - The Library is on the left hand menu + Samples is on the left hand menu 2. Click `Setup and deploy` @@ -96,7 +96,7 @@ Instead of writing a lot of code you will use the Library to deploy a pre-built You now have a working real time stream of bike data. Now use the OpenWeather account to create a real time weather stream. The procedure is almost the same, so you should have no problems! -1. Search the library for `weather` and select the `Open Weather API` tile. +1. Search the samples for `weather` and select the `Open Weather API` tile. 2. Click `Setup and deploy` @@ -216,13 +216,13 @@ However, it would take several weeks to accumulate enough historic data to train ## 6. Run the model -We have included our trained model artifacts as pickle files in the prediction code project and uploaded it to the open source library, so let's use them. +We have included our trained model artifacts as pickle files in the prediction code project and uploaded it to the open source samples, so let's use them. ### Prediction service code Get the code for the prediction service. -1. Click on the Library +1. Click on Samples in the left hand navigation 2. Search for `New York` and select the `New york Bikes - Prediction` tile diff --git a/docs/platform/tutorials/data-stream-processing/data-stream-processing.md b/docs/platform/tutorials/data-stream-processing/data-stream-processing.md index 49832c65..82f8f240 100644 --- a/docs/platform/tutorials/data-stream-processing/data-stream-processing.md +++ b/docs/platform/tutorials/data-stream-processing/data-stream-processing.md @@ -56,13 +56,13 @@ This walk through covers the following: Login to Quix and open your Workspace, you get one workspace on the free tier, more on higher tiers. A Quix Workspace is a container to help you manage all the data, topics, models and services related to a single solution so we advise using a new, clean one for this tutorial. -### Quix Library +### Quix Samples -The code you will need for this tutorial is located in the Quix Library. +The code you will need for this tutorial is located in the Quix Samples. -Open the library and search for `Streaming Demo`. You will see 3 results. +Open the samples and search for `Streaming Demo`. You will see 3 results. -![Library search results](library-items.png) +![Samples search results](library-items.png) You will save the code for each of these to your workspace and deploy the two services and the UI. @@ -137,7 +137,7 @@ Follow the same process as above and deploy the `Streaming Demo - Control` proje Remember the steps are: -1. Search the library for `Streaming Demo` +1. Search the samples for `Streaming Demo` 2. Select the `Streaming Demo - Control` project @@ -166,7 +166,7 @@ Now we can get to the user interface (UI). This will allow you to see the game b You should be familiar with the process by now. -1. Search the library for `Streaming Demo` +1. Search the samples for `Streaming Demo` 2. Select the `Streaming Demo - UI` tile. diff --git a/docs/platform/tutorials/eventDetection/conclusion.md b/docs/platform/tutorials/eventDetection/conclusion.md index a905cd35..71cc6772 100644 --- a/docs/platform/tutorials/eventDetection/conclusion.md +++ b/docs/platform/tutorials/eventDetection/conclusion.md @@ -1,6 +1,6 @@ # Conclusion -You’ve just made use of the Quix library, our collection of open source connectors, and examples, to deploy a UI and event detection microservice. +You’ve just made use of the Quix Samples, our collection of open source connectors, and examples, to deploy a UI and event detection microservice. Congratulations, you have achieved a lot! diff --git a/docs/platform/tutorials/eventDetection/crash-detection-ui.md b/docs/platform/tutorials/eventDetection/crash-detection-ui.md index 4205c793..b9d38069 100644 --- a/docs/platform/tutorials/eventDetection/crash-detection-ui.md +++ b/docs/platform/tutorials/eventDetection/crash-detection-ui.md @@ -8,11 +8,11 @@ The UI you will deploy is shown in the following screenshot: ## Deploying the UI -The following steps demonstrate how to select the UI from the Samples Library and deploy it to your Quix workspace. +The following steps demonstrate how to select the UI from the Samples and deploy it to your Quix workspace. Follow these steps to deploy the prebuilt UI: -1. Navigate to the Library and search for `Event Detection Demo UI`. +1. Navigate to the Samples and search for `Event Detection Demo UI`. 2. Click the `Setup & deploy` button. diff --git a/docs/platform/tutorials/eventDetection/crash-detection.md b/docs/platform/tutorials/eventDetection/crash-detection.md index f1d23f68..44e0e036 100644 --- a/docs/platform/tutorials/eventDetection/crash-detection.md +++ b/docs/platform/tutorials/eventDetection/crash-detection.md @@ -8,7 +8,7 @@ In reality our ML model was trained to detect the difference between a phone bei Follow these steps to start creating the `crash detection service`: -1. Navigate to the library and search for `Empty template`. +1. Navigate to the samples and search for `Empty template`. 2. Click `Preview code` on the transformation template (shown with a violet highlight). diff --git a/docs/platform/tutorials/eventDetection/data-acquisition.md b/docs/platform/tutorials/eventDetection/data-acquisition.md index 04341063..c42142e7 100644 --- a/docs/platform/tutorials/eventDetection/data-acquisition.md +++ b/docs/platform/tutorials/eventDetection/data-acquisition.md @@ -20,11 +20,11 @@ An external source is a representation of a data source that is external to Quix To add an external source: -1. Navigate to the Library +1. Navigate to the Samples 2. Under `Pipeline Stage` click `Source`. -3. Locate the `External Source` library item and click `Add external source`. +3. Locate the `External Source` sample and click `Add external source`. 4. Enter `phone-data` in the `Output` field and click `Add new topic` in the drop-down. @@ -56,7 +56,7 @@ Follow these steps: 7. Copy the token to your clipboard or somewhere safe. -8. In the Quix Library, search for `QR Settings Share`. +8. In the Quix Samples, search for `QR Settings Share`. 9. Click `Setup & deploy`. @@ -127,7 +127,7 @@ If you don’t have an Android device, or you’d rather stream some data provid Follow these instructions to deploy the data source: -1. In the Quix Library, select `Python` under languages and `Source` under pipeline stage. +1. In the Quix Samples, select `Python` under languages and `Source` under pipeline stage. 2. In the search box enter `Empty template`. diff --git a/docs/platform/tutorials/eventDetection/index.md b/docs/platform/tutorials/eventDetection/index.md index 1bf1a118..a7386fe8 100644 --- a/docs/platform/tutorials/eventDetection/index.md +++ b/docs/platform/tutorials/eventDetection/index.md @@ -20,7 +20,7 @@ This tutorial is divided into several parts to make it more a manageable learnin 2. [**Build and deploy the crash detection service**](./crash-detection.md). This service uses an ML model to detect crashes in real-time. We’ll show you how to train the model using data obtained from Quix, but we also provide you with a pretrained model for convenience. -3. [**Deploy the UI**](./crash-detection-ui.md). You will deploy the demo UI. This is a prebuilt UI from the Quix Samples Library. It allows the user to see where a device is located and indicates where a crash has occurred. +3. [**Deploy the UI**](./crash-detection-ui.md). You will deploy the demo UI. This is a prebuilt UI from the Quix Samples. It allows the user to see where a device is located and indicates where a crash has occurred. !!! info diff --git a/docs/platform/tutorials/image-processing/connect-video-tfl.md b/docs/platform/tutorials/image-processing/connect-video-tfl.md index f529fa2c..76d1a6f9 100644 --- a/docs/platform/tutorials/image-processing/connect-video-tfl.md +++ b/docs/platform/tutorials/image-processing/connect-video-tfl.md @@ -4,7 +4,7 @@ In this part of the tutorial you connect your pipeline to the TfL traffic cam vi Follow these steps to deploy the **traffic camera feed service**: -1. Navigate to the Library and locate `TfL Camera Feed`. +1. Navigate to the Samples and locate `TfL Camera Feed`. 2. Click `Setup & deploy`. diff --git a/docs/platform/tutorials/image-processing/connect-video-webcam.md b/docs/platform/tutorials/image-processing/connect-video-webcam.md index e886828d..0c627418 100644 --- a/docs/platform/tutorials/image-processing/connect-video-webcam.md +++ b/docs/platform/tutorials/image-processing/connect-video-webcam.md @@ -4,7 +4,7 @@ In this part of the tutorial you connect your webcam video feed. Follow these steps to deploy the **webcam service**: -1. Navigate to the Library and locate `Image processing - Webcam input`. +1. Navigate to the Samples and locate `Image processing - Webcam input`. 2. Click `Setup & deploy`. diff --git a/docs/platform/tutorials/image-processing/decode.md b/docs/platform/tutorials/image-processing/decode.md index 080018f1..84415197 100644 --- a/docs/platform/tutorials/image-processing/decode.md +++ b/docs/platform/tutorials/image-processing/decode.md @@ -6,7 +6,7 @@ In this part of the tutorial you decode the base64 encoded images coming from th Follow these steps to deploy the **base64 decoder service**: -1. Navigate to the Library and locate the Python `Empty template` transformation. +1. Navigate to the Samples and locate the Python `Empty template` transformation. !!! tip You can use the filters on the left hand side to select `Python` and `Transformation` then select `Empty template` in the resulting filtered items. @@ -67,7 +67,7 @@ Using the following steps, update the default code so it decodes the web cam ima stream_producer.timeseries.buffer.publish(df) - # Handle event data from library items that emit event data + # Handle event data from samples items that emit event data def on_event_data_received_handler(stream_consumer: qx.StreamConsumer, data: qx.EventData): print(data) # handle your event data here diff --git a/docs/platform/tutorials/image-processing/index.md b/docs/platform/tutorials/image-processing/index.md index 968fe6ba..376856f2 100644 --- a/docs/platform/tutorials/image-processing/index.md +++ b/docs/platform/tutorials/image-processing/index.md @@ -2,7 +2,7 @@ In this tutorial you learn how to build a real-time image processing pipeline in Quix, using the Transport for London (TfL) traffic cameras, known as Jam Cams, the webcam on your laptop or phone, and a [YOLO v3](https://viso.ai/deep-learning/yolov3-overview/) machine learning model. -You'll use prebuilt Quix library items to build the pipeline. A prebuilt UI is also provided that shows you where the recognized objects are located around London. +You'll use prebuilt Quix Samples to build the pipeline. A prebuilt UI is also provided that shows you where the recognized objects are located around London. The following screenshot shows the pipeline you build in this tutorial: @@ -41,13 +41,13 @@ Follow these steps to locate your TfL API key: 6. You can now find your API Keys in the profile page. -## Quix Library +## Quix Samples -The Quix Library is a collection of ready-to-use components you can leverage to build your own real-time streaming solutions. Typically these components require minimal configuration. +The Quix Samples is a collection of ready-to-use components you can leverage to build your own real-time streaming solutions. Typically these components require minimal configuration. -Most of the code you need for this tutorial has already been written, and is located in the Quix Library. +Most of the code you need for this tutorial has already been written, and is located in the Quix Samples. -When you are logged into the Quix Portal, click on the Library icon in the left-hand navigation, to access the Quix Library. +When you are logged into the Quix Portal, click on the Samples icon in the left-hand navigation, to access the Quix Samples. ## The pipeline you will create @@ -79,13 +79,13 @@ Now that you know which components will be needed in the image processing pipeli This tutorial is divided up into several parts, to make it a more manageable learning experience. The parts are summarized here: -1. **Connect the webcam video feed**. You learn how to quickly connect a video feed from your webcam, using a prebuilt library item. +1. **Connect the webcam video feed**. You learn how to quickly connect a video feed from your webcam, using a prebuilt sample. -2. **Object detection**. You use a computer vision library item to detect a chosen type of object. You'll preview these events in the live preview. The object type to detect can be selected through a web UI, which is described later. +2. **Object detection**. You use a computer vision sample to detect a chosen type of object. You'll preview these events in the live preview. The object type to detect can be selected through a web UI, which is described later. -3. **Connect the TfL video feed**. You learn how to quickly connect the TfL traffic cam feeds, using a prebuilt library item. You can perform object detection across these feeds, as they are all sent into the objection detection service in this tutorial. +3. **Connect the TfL video feed**. You learn how to quickly connect the TfL traffic cam feeds, using a prebuilt sample. You can perform object detection across these feeds, as they are all sent into the objection detection service in this tutorial. -4. **Frame grabber**. You use a standard library item to grab frames from the TfL video feed. +4. **Frame grabber**. You use a standard sample to grab frames from the TfL video feed. 5. **Deploy the web UI**. You the deploy a prebuilt web UI. This UI enables you to select an object type to detect across all of your input video feeds. It displays the location pof object detection and object detection count on a map. diff --git a/docs/platform/tutorials/image-processing/object-detection.md b/docs/platform/tutorials/image-processing/object-detection.md index 987bd5b4..33698be7 100644 --- a/docs/platform/tutorials/image-processing/object-detection.md +++ b/docs/platform/tutorials/image-processing/object-detection.md @@ -6,7 +6,7 @@ In a later stage of the pipeline you add a simple UI which enables you to select Follow these steps to deploy the **object detection service**: -1. Navigate to the Library and locate `Computer Vision object detection`. +1. Navigate to the Samples and locate `Computer Vision object detection`. 2. Click `Setup & deploy`. diff --git a/docs/platform/tutorials/image-processing/summary.md b/docs/platform/tutorials/image-processing/summary.md index 5c8dbd6f..4d92bbfa 100644 --- a/docs/platform/tutorials/image-processing/summary.md +++ b/docs/platform/tutorials/image-processing/summary.md @@ -1,16 +1,16 @@ # 6. Summary -In this tutorial you have learned that it is possible to quickly build a real-time image processing pipeline, using prebuilt library items. You have seen how to can connect to multiple types of video feed, perform object detection, and display the locations of the detected objects on a map, using the prebuilt UI. +In this tutorial you have learned that it is possible to quickly build a real-time image processing pipeline, using prebuilt samples. You have seen how to can connect to multiple types of video feed, perform object detection, and display the locations of the detected objects on a map, using the prebuilt UI. -## Library items used +## Samples used -Here is a list of the Quix open source library items used in this tutorial, with links to their code in GitHub: +Here is a list of the Quix open source samples used in this tutorial, with links to their code in GitHub: -* [TfL traffic cam video feed](https://github.com/quixio/quix-library/tree/main/python/sources/TFL-Camera-Feed) -* [TfL traffic cam frame grabber](https://github.com/quixio/quix-library/tree/main/python/transformations/TFL-Camera-Frame-Extraction) -* [Webcam interface](https://github.com/quixio/quix-library/tree/main/applications/image-processing/webcam-input) -* [Computer vision object detection](https://github.com/quixio/quix-library/tree/main/python/transformations/Image-processing-object-detection) -* [Web UI](https://github.com/quixio/quix-library/tree/main/nodejs/advanced/Image-Processing-UI) +* [TfL traffic cam video feed](https://github.com/quixio/quix-samples/tree/main/python/sources/TFL-Camera-Feed) +* [TfL traffic cam frame grabber](https://github.com/quixio/quix-samples/tree/main/python/transformations/TFL-Camera-Frame-Extraction) +* [Webcam interface](https://github.com/quixio/quix-samples/tree/main/applications/image-processing/webcam-input) +* [Computer vision object detection](https://github.com/quixio/quix-samples/tree/main/python/transformations/Image-processing-object-detection) +* [Web UI](https://github.com/quixio/quix-samples/tree/main/nodejs/advanced/Image-Processing-UI) ## Next Steps @@ -18,7 +18,7 @@ Here are some suggested next steps to continue on your Quix learning journey: * Try the [sentiment analysis tutorial](../sentiment-analysis/index.md). -* If you decide to build your own connectors and apps, you can contribute something to the Quix Library. Visit the [Quix GitHub](https://github.com/quixio/quix-library){target=_blank}. Fork our library repo and submit your code, updates, and ideas. +* If you decide to build your own connectors and apps, you can contribute something to the Quix Samples. Visit the [Quix GitHub](https://github.com/quixio/quix-samples){target=_blank}. Fork our samples repo and submit your code, updates, and ideas. What will you build? Let us know! We’d love to feature your project or use case in our [newsletter](https://www.quix.io/community/). diff --git a/docs/platform/tutorials/image-processing/tfl-frame-grabber.md b/docs/platform/tutorials/image-processing/tfl-frame-grabber.md index 3ff36282..e8309955 100644 --- a/docs/platform/tutorials/image-processing/tfl-frame-grabber.md +++ b/docs/platform/tutorials/image-processing/tfl-frame-grabber.md @@ -6,7 +6,7 @@ The frame extraction service grabs single frames from the video feeds, so that o Follow these steps to deploy the **frame extraction service**: -1. Navigate to the Library and locate `TfL traffic camera frame grabber`. +1. Navigate to the Samples and locate `TfL traffic camera frame grabber`. 2. Click `Setup & deploy`. diff --git a/docs/platform/tutorials/image-processing/web-ui.md b/docs/platform/tutorials/image-processing/web-ui.md index 92e084bb..1ed23229 100644 --- a/docs/platform/tutorials/image-processing/web-ui.md +++ b/docs/platform/tutorials/image-processing/web-ui.md @@ -12,7 +12,7 @@ The following screenshot shows the last image processed from one of the video st Follow these steps to deploy the **web UI service**: -1. Navigate to the Library and locate `TFL image processing UI`. +1. Navigate to the Samples and locate `TFL image processing UI`. 2. Click `Setup & deploy`. diff --git a/docs/platform/tutorials/nocode-sentiment/nocode-sentiment-analysis.md b/docs/platform/tutorials/nocode-sentiment/nocode-sentiment-analysis.md index bb396a0e..236ca556 100644 --- a/docs/platform/tutorials/nocode-sentiment/nocode-sentiment-analysis.md +++ b/docs/platform/tutorials/nocode-sentiment/nocode-sentiment-analysis.md @@ -30,11 +30,11 @@ will receive your data. Call this "demodata" and click "Create." ## Step two: get your data -In Quix, click into the library and search for the Twitter source +In Quix, click into the samples and search for the Twitter source connector. Click "Add new." This adds the source to your pipeline and brings you -back to the library. +back to the samples. Fill in the necessary fields: @@ -58,7 +58,7 @@ Click "Deploy" - Click the "Add transformation" button - - In the library, search for "HuggingFace" + - In the samples, search for "HuggingFace" - Click "Set up and deploy" on the HuggingFace connector @@ -81,7 +81,7 @@ Click "Deploy" - Click the "Add destination" button on the home screen - - Search the library for the Snowflake connector + - Search the samples for the Snowflake connector - Click "Set up and deploy" on the connector diff --git a/docs/platform/tutorials/quick-start/quick-start.md b/docs/platform/tutorials/quick-start/quick-start.md index 3d84a7d0..653eec3b 100644 --- a/docs/platform/tutorials/quick-start/quick-start.md +++ b/docs/platform/tutorials/quick-start/quick-start.md @@ -10,13 +10,13 @@ For convenience this guide is divided into two parts: 1. **Deploy a chat UI with sentiment analysis** - in this part you deploy a real-time chat application and connect to it with your computer and phone. You also perform sentiment analysis on the messages in a chat room. - This part does not require any coding, as it uses prebuilt library items for services, so is suitable for those who'd like to get an understanding of how Quix works, without needing to write code. + This part does not require any coding, as it uses prebuilt samples for services, so is suitable for those who'd like to get an understanding of how Quix works, without needing to write code. The pipeline you create in this part is shown in the following screenshot: ![The sentiment pipeline](./images/sentiment-pipeline.png) -2. **Connect an external service** - in this part you add an external data feed to the pipeline using library items that you will create from templates, and see data delivered in real time to your chat app. +2. **Connect an external service** - in this part you add an external data feed to the pipeline using samples that you will create from templates, and see data delivered in real time to your chat app. This part requires some basic Python coding skills. However, as all code you need is provided for you, this is suitable for beginners. @@ -30,7 +30,7 @@ If you need help with this guide, then please join our public Slack community [` ## Part 1. Deploy a chat UI with sentiment analysis -To use Quix effectively in the shortest possible time, you will initially use prebuilt library items from the [Quix Library](https://github.com/quixio/quix-library){target=_blank}. These open source library items have already been coded and tested by Quix engineers, and other contributors. All you have to do is configure them (if required) and deploy them to your workspace. +To use Quix effectively in the shortest possible time, you will initially use prebuilt samples from the [Quix Samples](https://github.com/quixio/quix-samples){target=_blank}. These open source samples have already been coded and tested by Quix engineers, and other contributors. All you have to do is configure them (if required) and deploy them to your workspace. ### Deploy sentiment analysis @@ -39,9 +39,9 @@ To compliment the chat UI, you will first deploy a prebuilt microservice designe 1. Click `+ Add transformation` on the home screen. ???- note "Not your first time?" - If this is not your first time deploying a service to this workspace then navigate to the Library using the left-hand navigation instead. + If this is not your first time deploying a service to this workspace then navigate to the Samples using the left-hand navigation instead. -2. Use the search box to find the `Sentiment analysis` library item. +2. Use the search box to find the `Sentiment analysis` sample. 3. Click `Setup & deploy`. @@ -63,9 +63,9 @@ To compliment the chat UI, you will first deploy a prebuilt microservice designe You are going to locate and deploy a chat UI. The chat UI is written in Angular and connects to Quix using the [Streaming Reader API](../../../apis/streaming-reader-api/intro.md). The chat UI enables you to see messages on both your phone and computer in real-time. The sentiment of each message is also displayed. -1. Navigate to the Quix Library using the left-hand navigation. +1. Navigate to the Quix Samples using the left-hand navigation. -2. Use the search box to find the `Sentiment Demo UI` library item. +2. Use the search box to find the `Sentiment Demo UI` sample. 3. Click `Setup & deploy`. Notice that this service will read from both the `messages` topic and the `sentiment` topic. @@ -86,7 +86,7 @@ You are going to locate and deploy a chat UI. The chat UI is written in Angular ??? example "Understand the code" - 1. Locate the `Sentiment Demo UI` item in the library again, and then click `Preview code`. This is just one way to access the code. + 1. Locate the `Sentiment Demo UI` item in the samples again, and then click `Preview code`. This is just one way to access the code. 2. Expand the tree view and select the `webchat.component.ts` file. @@ -150,13 +150,13 @@ And the same messages and sentiment will appear in real time in your computer's ## Part 2. Connect an external service -Now that you have the basics of searching the library for a library item, selecting and deploying it to the Quix serverless infrastructure, you can learn how to add additional services to the pipeline. In this guide you'll connect to a web service to receive data, and then transform it so it's compatible with the chat UI. +Now that you have the basics of searching the samples, selecting and deploying them to the Quix serverless infrastructure, you can learn how to add additional services to the pipeline. In this guide you'll connect to a web service to receive data, and then transform it so it's compatible with the chat UI. ### Create the data source In this section you will learn how to use a template to help quickly build a Quix source. -1. Go to the Quix Library. +1. Go to the Quix Samples. 2. Search for the `Empty template - Source`. If should have a blue highlight (blue is used to indicate a source). @@ -311,7 +311,7 @@ Now that you have some data, you need to transform it to make it compatible with You will now locate a suitable transformation template and modify it to handle the incoming beer styles and output them as chat messages. -1. Search the library for `Empty template - Transformation`. +1. Search the samples for `Empty template - Transformation`. 2. Click `Preview code`. @@ -396,11 +396,11 @@ You have now saved the template to your workspace. In the next section you'll mo This quickstart guide aimed to give you a tour of some important Quix features. You have learned: -1. Quix enables you to build complex data processing pipelines, using prebuilt items from the Quix library. +1. Quix enables you to build complex data processing pipelines, using prebuilt items from the Quix Samples. 2. You can get data into and out of Quix using a variety of methods, including polling data, and using a websockets-based API such as the [Streaming Reader API](../../../apis/streaming-reader-api/intro.md). Webhooks are also supported. -3. You can use templates to help rapidly develop new library items. You built a new source and a new transformation from templates. +3. You can use templates to help rapidly develop new samples. You built a new source and a new transformation from templates. 4. Quix uses [topics](../../definitions.md#topics) and [streams](../../definitions.md#stream) to route data between services in a pipeline. diff --git a/docs/platform/tutorials/rss-tutorial/rss-processing-pipeline.md b/docs/platform/tutorials/rss-tutorial/rss-processing-pipeline.md index 7ef7f21f..ffa5cb25 100644 --- a/docs/platform/tutorials/rss-tutorial/rss-processing-pipeline.md +++ b/docs/platform/tutorials/rss-tutorial/rss-processing-pipeline.md @@ -25,13 +25,13 @@ What you need ### Sourcing data -#### 1. Get the “RSS Data Source” connector +#### 1. Get the `RSS Data Source` connector -In your Quix account, go to the library and search for “RSS Data -Source.” (Hint: you can watch Steve prepare this code in the video +In your Quix account, go to the samples and search for `RSS Data +Source.` (Hint: you can watch Steve prepare this code in the video tutorial if you’re like to learn more about it.) -Click “Setup & deploy” on the “RSS Data Source” library item. (The card +Click `Setup & deploy` on the `RSS Data Source` sample. (The card has a blue line across its top that indicates it’s a source connector.) ![RSSTutorial/image1.png](image1.png) @@ -42,7 +42,7 @@ In the configuration panel, keep the default name and output topic. Enter the following URL into the rss_url field: [https://stackoverflow.com/feeds/tag/python](https://stackoverflow.com/feeds/tag/python){target=_blank} -Click “Deploy” and wait a few seconds for the pre-built connector to be +Click `Deploy` and wait a few seconds for the pre-built connector to be deployed to your workspace. You will then begin to receive data from the RSS feed. The data then @@ -56,23 +56,23 @@ might want to merge several input streams or make decisions on your data. In this tutorial, you’ll filter and augment data so that only questions with certain tags get delivered to you. -#### 1\. Get the “RSS Data Filtering” connector +#### 1\. Get the `RSS Data Filtering` connector -Return to the library tab in Quix and search for “RSS Data Filtering.” -Click “Setup & deploy” on the card. +Return to the samples tab in Quix and search for `RSS Data Filtering.` +Click `Setup & deploy` on the card. If you created a new workspace for this project, the fields automatically populate. If you’re using the workspace for other -projects, you may need to specify the input topic as “rss-data.” +projects, you may need to specify the input topic as `rss-data.` You might also want to customize the tag_filter. It is automatically populated with a wide range of tags related to Python. This works well for this demo, because you’ll see a large return of interesting posts. But you can decrease or add tags. -#### 2\. Deploy “RSS Data Filtering” connector +#### 2\. Deploy `RSS Data Filtering` connector -Click “Deploy” on the “RSS Data Filtering” connector. Once deployed, the +Click `Deploy` on the `RSS Data Filtering` connector. Once deployed, the connector will begin processing the data that’s been building up in the rss-data topic. @@ -89,27 +89,27 @@ the filtered and enhanced data to the output topic. Last in our pipeline is the destination for our RSS data. This demo uses a Slack channel as its destination. -#### 1\. Get the “Slack Notification” connector +#### 1\. Get the `Slack Notification` connector -Return to the Quix library and search for the “Slack Notification.” -Click “Preview code.” You’re going to modify the standard code before +Return to the Quix Samples and search for the `Slack Notification.` +Click `Preview code.` You’re going to modify the standard code before deploying this connector. ![RSSTutorial/image3.png](image3.png) -Click “Next” on the dialog box. Ensure “filtered-rss-data” is selected -as the input topic and provide a Slack “webhook_url.” +Click `Next` on the dialog box. Ensure `filtered-rss-data` is selected +as the input topic and provide a Slack `webhook_url.` !!! note - If you have your own slack, head over to the [Slack API pages](https://api.slack.com/messaging/webhooks){target=_blank} and create a webhook following their guide “Getting started with Incoming Webhooks.” If you don’t have your own Slack or don’t have the account privileges to create the webhook, you can choose another destination from the library, such as Twilio. + If you have your own slack, head over to the [Slack API pages](https://api.slack.com/messaging/webhooks){target=_blank} and create a webhook following their guide `Getting started with Incoming Webhooks.` If you don’t have your own Slack or don’t have the account privileges to create the webhook, you can choose another destination from the samples, such as Twilio. Warning: Use a dev or demo or unimportant Slack channel while you’re developing this. Trust me. -#### 2\. Modify and deploy the “Slack Notification” connector +#### 2\. Modify and deploy the `Slack Notification` connector -Enter your webhook into the webhook_url field. Click “Save as project.” +Enter your webhook into the webhook_url field. Click `Save as project.` This will save the code to your workspace, which is a GitLab repository. Once saved, you’ll see the code again. The quix_function.py file should @@ -117,7 +117,7 @@ be open. This is what you’ll alter. The default code dumps everything in the parameter data and event data to the Slack channel. It’ll do to get you up and going, but we want something more refined. 😉 -Go to our GitHub library of tutorial code +Go to our GitHub tutorial code [here](https://github.com/quixio/tutorial-code/blob/main/RSS/Slack-Notification-Destination/quix_function.py){target=_blank}. The code picks out several field values from the parameter data and combines them to form the desired Slack alert. @@ -125,11 +125,11 @@ combines them to form the desired Slack alert. Copy the code and paste it over the quix_function.py file in your project in the Quix portal. -Save it by clicking “CTRL+S” or “Command + S” or click the tick in the +Save it by clicking `CTRL+S` or `Command + S` or click the tick in the top right. -Then deploy by clicking the “Deploy” button in the top right. On the -dialogue, change the deployment type to “Service” and click “Deploy”. +Then deploy by clicking the `Deploy` button in the top right. On the +dialogue, change the deployment type to `Service` and click `Deploy`. ### Congratulations diff --git a/docs/platform/tutorials/sentiment-analysis/analyze.md b/docs/platform/tutorials/sentiment-analysis/analyze.md index 26ea8a6c..99b259f7 100644 --- a/docs/platform/tutorials/sentiment-analysis/analyze.md +++ b/docs/platform/tutorials/sentiment-analysis/analyze.md @@ -10,7 +10,7 @@ The microservice subscribes to data from the `messages` topic and publishes sent !!! tip - While this tutorial uses a prebuilt sentiment analysis library item, it is also possible to build one from a basic template available in the Quix library. If you are interested in building your own service, you can refer to an optional part of this tutorial, where you learn how to [code a sentiment analysis service](./code-and-deploy-sentiment-service.md) from the basic template. + While this tutorial uses a prebuilt sentiment analysis sample, it is also possible to build one from a basic template available in the Quix Samples. If you are interested in building your own service, you can refer to an optional part of this tutorial, where you learn how to [code a sentiment analysis service](./code-and-deploy-sentiment-service.md) from the basic template. ## Deploying the sentiment analysis service @@ -18,7 +18,7 @@ The sentiment of each message will be evaluated by this new microservice in your Follow these steps to deploy the prebuilt sentiment analysis microservice: -1. Navigate to the Library and search for `Sentiment analysis`. +1. Navigate to the Samples and search for `Sentiment analysis`. 2. Click the `Setup & deploy` button. diff --git a/docs/platform/tutorials/sentiment-analysis/code-and-deploy-sentiment-service.md b/docs/platform/tutorials/sentiment-analysis/code-and-deploy-sentiment-service.md index 061aafb9..651e55b8 100644 --- a/docs/platform/tutorials/sentiment-analysis/code-and-deploy-sentiment-service.md +++ b/docs/platform/tutorials/sentiment-analysis/code-and-deploy-sentiment-service.md @@ -1,6 +1,6 @@ # Sentiment analysis microservice -In this optional tutorial part, you learn how to code a sentiment analysis microservice, starting with a template from the Quix Library. Templates are useful building blocks the Quix platform provides, and which give you a great starting point from which to build your own microservices. +In this optional tutorial part, you learn how to code a sentiment analysis microservice, starting with a template from the Quix Samples. Templates are useful building blocks the Quix platform provides, and which give you a great starting point from which to build your own microservices. !!! note The code shown here is kept as simple as possible for learning purposes. Production code would require more robust error handling. @@ -15,7 +15,7 @@ Follow the steps below to code, test, and deploy a new microservice to your work Follow these steps to locate and save the code to your workspace: -1. Navigate to the Library and apply the following filters: +1. Navigate to the Samples and apply the following filters: 1. Languages = `Python` @@ -417,4 +417,4 @@ Tag the code and deploy the service: 7. Go back to the UI, and make sure everything is working as expected. Your messages will have a color-coded sentiment, and the sentiment will displayed on the graph. -You have now completed this optional tutorial part. You have learned how to create your own sentiment analysis microservice from the library template. +You have now completed this optional tutorial part. You have learned how to create your own sentiment analysis microservice from the Quix Samples. diff --git a/docs/platform/tutorials/sentiment-analysis/conclusion.md b/docs/platform/tutorials/sentiment-analysis/conclusion.md index 7ee009f6..c86ebf4c 100644 --- a/docs/platform/tutorials/sentiment-analysis/conclusion.md +++ b/docs/platform/tutorials/sentiment-analysis/conclusion.md @@ -1,6 +1,6 @@ # Conclusion -You’ve just made extensive use of the Quix library, our collection of open source connectors, and examples, to deploy a UI and sentiment analysis microservice, and subscribe to Tweets. +You’ve just made extensive use of the Quix Samples, our collection of open source connectors, and examples, to deploy a UI and sentiment analysis microservice, and subscribe to Tweets. Congratulations, that's quite an achievement! @@ -12,7 +12,7 @@ Here are some suggested next steps to continue on your Quix learning journey: * If you want to customize the Sentiment Demo UI, you can learn how in the optional tutorial part [how to customize the UI](customize-the-ui.md). -* If you decide to build your own connectors and apps, you can contribute something to the Quix Library. Visit the [Quix GitHub](https://github.com/quixio/quix-library){target=_blank}. Fork our library repo and submit your code, updates, and ideas. +* If you decide to build your own connectors and apps, you can contribute something to the Quix Samples. Visit the [Quix GitHub](https://github.com/quixio/quix-samples){target=_blank}. Fork our samples repo and submit your code, updates, and ideas. What will you build? Let us know! We’d love to feature your project or use case in our [newsletter](https://www.quix.io/community/). diff --git a/docs/platform/tutorials/sentiment-analysis/customize-the-ui.md b/docs/platform/tutorials/sentiment-analysis/customize-the-ui.md index 70143c96..cd0a567a 100644 --- a/docs/platform/tutorials/sentiment-analysis/customize-the-ui.md +++ b/docs/platform/tutorials/sentiment-analysis/customize-the-ui.md @@ -10,7 +10,7 @@ If you want to customize the Sentiment Demo UI, you would follow three main step ## Create the project -1. Navigate to the Library and locate `Sentiment Demo UI`. +1. Navigate to the Samples and locate `Sentiment Demo UI`. 2. Click `Preview code` and then `Edit code`. diff --git a/docs/platform/tutorials/sentiment-analysis/sentiment-demo-ui.md b/docs/platform/tutorials/sentiment-analysis/sentiment-demo-ui.md index 404db4c6..b98d063c 100644 --- a/docs/platform/tutorials/sentiment-analysis/sentiment-demo-ui.md +++ b/docs/platform/tutorials/sentiment-analysis/sentiment-demo-ui.md @@ -20,7 +20,7 @@ Follow these steps to create the messages and sentiment web gateways: This topic needs to be available so you can select it in a later step. -2. Navigate to the Library and locate `External Source`. +2. Navigate to the Samples and locate `External Source`. 3. Click `Add external source`. @@ -30,7 +30,7 @@ Follow these steps to create the messages and sentiment web gateways: 6. Click `Add external Source` to create the external source. -7. Navigate to the Library and locate `External Destination`. +7. Navigate to the Samples and locate `External Destination`. 8. Click `Add external destination`. @@ -44,11 +44,11 @@ You've now created the gateways needed for this tutorial. ## Locating and deploying the Sentiment Demo UI -The following steps demonstrate how to select the demo UI Library item and deploy it to your Quix workspace. +The following steps demonstrate how to select the demo UI Sample and deploy it to your Quix workspace. Follow these steps to deploy the prebuilt UI: -1. Navigate to the Library and locate `Sentiment Demo UI`. +1. Navigate to the Samples and locate `Sentiment Demo UI`. 2. Click the `Setup & deploy` button. diff --git a/docs/platform/tutorials/sentiment-analysis/twitter-data.md b/docs/platform/tutorials/sentiment-analysis/twitter-data.md index 4f9a5239..342b9b8a 100644 --- a/docs/platform/tutorials/sentiment-analysis/twitter-data.md +++ b/docs/platform/tutorials/sentiment-analysis/twitter-data.md @@ -26,11 +26,11 @@ You can follow [this tutorial to set up a developer account](https://developer.t ## Fetching the tweets -You are going to be using a prebuilt library item for fetching the tweets. The default search parameters for the library item search for anything to do with Bitcoin, using the search term `(#BTC OR btc OR #btc OR BTC)`. It's a high-traffic subject and great for this demo. However, if you are on the Quix free tier, you might find it better to use a lower-traffic subject, as less CPU and Memory resource can be allocated to a deployment on this tier. To do this, you can edit the `twitter_search_params` field in the library item to contain a different search term, such as `(#rail OR railway)`. This will create less load on the sentiment analysis microservice. +You are going to be using a prebuilt sample for fetching the tweets. The default search parameters for the sample are set to search for anything relating to Bitcoin, using the search term `(#BTC OR btc OR #btc OR BTC)`. It's a high-traffic subject and great for this demo. However, if you are on the Quix free tier, you might find it better to use a lower-traffic subject, as less CPU and Memory resource can be allocated to a deployment on this tier. To do this, you can edit the `twitter_search_params` field in the sample to contain a different search term, such as `(#rail OR railway)`. This will create less load on the sentiment analysis microservice. Follow these steps to deploy the Twitter data source: -1. Navigate to the Library and locate the `Twitter` data source. +1. Navigate to the Samples and locate the `Twitter` data source. 2. Click the `Setup & deploy` button. @@ -58,7 +58,7 @@ This service will subscribe to the `twitter-data` topic and publish data to the Follow these steps to code and deploy the tweet-to-chat conversion stage: -1. Navigate to the Library and apply the following filters: +1. Navigate to the Samples and apply the following filters: 1. Languages = `Python` diff --git a/docs/platform/tutorials/slack-alerting/slack-alerting.md b/docs/platform/tutorials/slack-alerting/slack-alerting.md index 72ab3f74..9ce7217f 100644 --- a/docs/platform/tutorials/slack-alerting/slack-alerting.md +++ b/docs/platform/tutorials/slack-alerting/slack-alerting.md @@ -85,11 +85,11 @@ Obtaining data from TFL's BikePoint API is fairly straight forward. You need to However, there is a much easier way to achieve the same outcome. -1. Navigate to the Quix library +1. Navigate to the Quix Samples 2. Search for `TFL Bikepoint` and click the tile - ![TFL BikePoint library tile](tfl-bikepoint-library-tile.png){width=300px} + ![TFL BikePoint sample tile](tfl-bikepoint-library-tile.png){width=300px} 3. Click `Setup & deploy` @@ -135,9 +135,9 @@ With the app created you'll now need to setup a webhook. This will give you a UR ### Integration -The time has come to actually connect Quix and Slack. Once again, with the help of the Quix Library, this is a simple task. +The time has come to actually connect Quix and Slack. Once again, with the help of the Quix Samples, this is a simple task. -1. Navigate to the Library +1. Navigate to the Samples 2. Search for `Slack` @@ -166,7 +166,7 @@ In this part of the tutorial you will replace the current Slack connector with a Follow these steps to save the connector code to your workspace. -1. Navigate to the library and search for `Slack` +1. Navigate to the samples and search for `Slack` 2. Click `Preview code` on the tile You can preview the code here and read the readme. You can't edit the code right now @@ -256,7 +256,7 @@ Follow these steps: !!! success - You modified an existing library item and deployed a microservice. + You modified an existing sample and deployed a microservice. You should start seeing Slack messages as soon as the service starts. diff --git a/docs/platform/tutorials/telemetry-data/telemetry-data.md b/docs/platform/tutorials/telemetry-data/telemetry-data.md index 674bafda..59182fb9 100644 --- a/docs/platform/tutorials/telemetry-data/telemetry-data.md +++ b/docs/platform/tutorials/telemetry-data/telemetry-data.md @@ -14,9 +14,9 @@ You will need an Android mobile phone for this tutorial (we're working on the Ap If you need any assistance, we're here to help in [The Stream](https://join.slack.com/t/stream-processing/shared_invite/zt-13t2qa6ea-9jdiDBXbnE7aHMBOgMt~8g){target=_blank}, our free Slack community. -### Library +### Samples -Most of the code you'll need has already been written. It lives in our library, which is accessible from inside the Quix portal or directly via our open source [GitHub](https://github.com/quixio/quix-library){target=_blank} repo. We'll be referring to the library often so make sure you know where it is. +Most of the code you'll need has already been written. It lives in our samples, which are accessible from inside the Quix portal or directly via our open source [GitHub](https://github.com/quixio/quix-samples){target=_blank} repo. We'll be referring to the samples often so make sure you know where it is. ## Components @@ -34,7 +34,7 @@ This guide will show you how to deploy each of the components, starting with QR Follow these steps to deploy the QR Settings Share. -1. Navigate to the Library and locate "QR Settings Share" +1. Navigate to the Samples and locate "QR Settings Share" 2. Click "Setup & deploy" @@ -144,7 +144,7 @@ Within Quix: Deploy an app: -1. Click Library on the left hand menu +1. Click Samples on the left hand menu 2. Search for Streamlit Dashboard diff --git a/docs/platform/tutorials/train-and-deploy-ml/deploy-ml.md b/docs/platform/tutorials/train-and-deploy-ml/deploy-ml.md index bea55942..65013463 100644 --- a/docs/platform/tutorials/train-and-deploy-ml/deploy-ml.md +++ b/docs/platform/tutorials/train-and-deploy-ml/deploy-ml.md @@ -30,9 +30,9 @@ Now let's run the model you created in the previous article. If you have your ow Ensure you are logged into the Quix Portal -1. Navigate to the Library +1. Navigate to the Samples -2. Filter the library by selecting `Python` under languages and `Transformation` under pipeline stage +2. Filter the samples by selecting `Python` under languages and `Transformation` under pipeline stage 3. Select the `Event Detection` item @@ -58,7 +58,7 @@ Ensure you are logged into the Quix Portal !!! success - The code from the Library sample is now saved to your workspace. + The code from the Samples sample is now saved to your workspace. You can edit and run the code from here or clone it to your computer and work locally. diff --git a/docs/platform/tutorials/train-and-deploy-ml/train-ml-model.md b/docs/platform/tutorials/train-and-deploy-ml/train-ml-model.md index 51026106..9e05c149 100644 --- a/docs/platform/tutorials/train-and-deploy-ml/train-ml-model.md +++ b/docs/platform/tutorials/train-and-deploy-ml/train-ml-model.md @@ -25,12 +25,12 @@ trained on historic data. You will need Python3 installed. You’ll need some data stored in the Quix platform. You can use any of -our Data Sources available in the samples Library, or just follow the +our Data Sources available in the samples Samples, or just follow the onboarding process when you [sign-up to Quix](https://portal.platform.quix.ai/self-sign-up/){target=_blank} !!! tip - If in doubt, login to the Quix Portal, navigate to the Library and deploy "Demo Data - Source". + If in doubt, login to the Quix Portal, navigate to the Samples and deploy "Demo Data - Source". This will provide you with some real-time data for your experiments. From f1ae3ecbccd43ddca87ac076eb6780a676bf8ca6 Mon Sep 17 00:00:00 2001 From: Steve <100689438+SteveRosam@users.noreply.github.com> Date: Wed, 19 Apr 2023 11:23:21 +0100 Subject: [PATCH 3/3] Update to latest connector build action --- .github/workflows/build-commit-subfolder.yaml | 2 +- .github/workflows/sync-build-deploy.yaml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/build-commit-subfolder.yaml b/.github/workflows/build-commit-subfolder.yaml index f9f7922b..22b63d64 100644 --- a/.github/workflows/build-commit-subfolder.yaml +++ b/.github/workflows/build-commit-subfolder.yaml @@ -145,7 +145,7 @@ jobs: # use our own GitHub Action to bring in library readme files - name: Quix Samples readme.md importer - uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.12 + uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.13 id: readme_importer with: LIBRARY_REPO_PATH: "samples" diff --git a/.github/workflows/sync-build-deploy.yaml b/.github/workflows/sync-build-deploy.yaml index f68166aa..6bccec99 100644 --- a/.github/workflows/sync-build-deploy.yaml +++ b/.github/workflows/sync-build-deploy.yaml @@ -148,7 +148,7 @@ jobs: # use our own GitHub Action to bring in library readme files - name: Quix Samples readme.md importer - uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.12 + uses: quixio/LibraryToMKDocsReadmeMergeAction@v2.13 id: readme_importer with: LIBRARY_REPO_PATH: "samples"