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Merge pull request #22 from CityofEdmonton/add-gif-readme
short demo gif
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<img src="www/text_depot_icon/TextDepotIcon_TextImage_S.jpg" width="25%"> | ||
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Text Depot is a tool to search and analyze topics of interest within a large database of text data. The Text Depot dashboard (this repo) provides a front-end to a set of indexes in ElasticSearch. To use this repository, you must provide one or more [Elastic Search](http://www.elastic.co) indexes in a particular format. | ||
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## Local Machine Setup | ||
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1. Clone this repo. | ||
2. Run `cp .configs_sample .configs` and fill in the relevant values. | ||
![Text Depot in action](www/TD_demo_short.gif) | ||
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### Running Locally | ||
<hr/> | ||
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1. Install any missing libraries with `install.packages("DT")` (for example). A list of required libraries can be found in the included `Dockerfile` | ||
2. Run `Rscript run_text_depot_dashboard.R` | ||
<img src="www/text_depot_icon/TextDepotIcon_TextBeside_M.jpg" width="60%"> | ||
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### Running via Docker | ||
Text Depot is a tool to search and analyze topics of interest within a large database of text data. The Text Depot dashboard (this repo) provides a front-end to a set of indexes in ElasticSearch. To use this repository, you must provide one or more [Elastic Search](http://www.elastic.co) indexes in a particular format. | ||
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1. Optionally, create a `.dockerignore` file to exclude any local files. | ||
2. Use the provided `Dockerfile` to build and run the app: | ||
## Setup | ||
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1. Setup Elastic Search Server | ||
2. Create one or more index using Text Depot mappings. | ||
3. Clone this repo. | ||
4. Run `cp .configs_sample .configs` and fill in the relevant values. | ||
5. Build and run docker container: | ||
``` | ||
$ DOCKER_BUILDKIT=1 docker build -t text_depot_dashboard . | ||
$ docker run -it -p 8080:3838 text_depot_dashboard | ||
DOCKER_BUILDKIT=1 docker build -t text_depot_dashboard . && docker run -it -p 8080:3838 text_depot_dashboard | ||
``` | ||
6. Open the dashboard on your browser: [http://localhost:8080](http://localhost:8080) | ||
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3. Open the dashboard on your browser: [http://localhost:8080](http://localhost:8080) | ||
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## ElasticSearch | ||
## Elastic Search | ||
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Each data source should be stored in its own Elastic Search index. For more information, see [elasticsearch/](elasticsearch/) | ||
Each data source should be stored in its own Elastic Search index. For more information on how to configure your Elastic Search server, see [elasticsearch/](elasticsearch/) | ||
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## Notes | ||
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Our workflow contained the following components: | ||
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![Overall Workflow](workflow.png) | ||
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This repository contains the dashboard code (Blue above) for Text Depot. The green components were scheduled with cron jobs, and keep the indexes up-to-date in the ElasticSearch Database. We wrote a custom Parser for each data source, and a single Annotator class that adds the fields below to each document before insertion. The orange components were added for authentication and embeddings-based search, and are optional components. | ||
This repository contains the dashboard code (Blue above) for Text Depot. The green components were scheduled with cron jobs, and keep the indexes up-to-date in the ElasticSearch Database. We wrote a custom Parser for each data source, and a single Annotator class that adds the `[nieghbourhoods, sentiment, embeddings]` fields to each document and inserts them. The orange components were added for authentication and embeddings-based search, and are optional components. | ||
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