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Welcome to the Getting Started guide, This is what you will achieve by following the next steps:
- Getting Saga
- Setting up the environment
- Deploying Saga
- Running Saga
- Checking that it's working!
Prerequisites
- ElasticSearch 7+/Opensearch v. 1.1
- Java 11 or above
Step 1: Getting Saga
You'll be able to get it from here (SCA Artifactory repository).
You can also find documentation here (Saga MS Teams site):
- Saga introductory presentation
- Saga user manual
Step 2: Set up the environment
- Check that Java 11 is installed on your machine by running on terminal (or system console):
$> java -version
- Unpackage Saga in your preferred location.
This is our recommended setup but you can pretty much handle the paths as you wish.
This guide will refer to Saga's working directory as {SAGA_HOME}
. - Saga uses ElasticSearch (7+) or Opensearch (v.1.1).
- Deploy ElasticSearch (ES) or Opensearch
- Run ES by executing the binary on {ELASTIC_HOME}/
bin
. - See this link on how to setup Opensearch on your machine.
Step 3: Deploy Saga
Once you have Saga in {SAGA_HOME}
validate the following:
There is a {SAGA_HOME}/lib
folder containing the following JARs:
saga-classification-trainer-stage-1.3.1
saga-faq-stage-1.3.1.jar
saga-lang-detector-stage-1.3.1.jar
saga-name-trainer-stage-1.3.1.jar
saga-parts-of-speech-stage-1.3.1.jar
saga-sentence-breaker-stage-1.3.1.jar
saga-spellchecking-stage-1.3.1.jar
Check the basic configuration on {SAGA_HOME}/config/config.json
:
- "apiPort": 8080 → The port used by the server.
- "host": "0.0.0.0" → This IP/mask is used to restrict inbound connections, open to all connections by default.
- "security" → Security access to the Saga Server and Management UI (recommended only when ssl is also enabled)
- "enable": true → Indicates the use of security
- "encryptionKeyFile": → file containing the encryption key. A file is provided by default but it is recommended to change it.
- "users.username" → Specify the username to use
- "users.password" → Specify the password for the username. Can be either plain or encrypted
- "ssl" → Enables SSL for the communication with the Saga Server
- enable": true → Indicates the use of ssl
- keyStore → Path to the keyStore
- keyStorePassword → Password of the keyStore. Can be either plain or encrypted
- "libraryJars": ["./lib"] → Folder where library jars are located
- If you are running elasticseach in localhost then you don't need to change anything. But if your elasticsearch runs somewhere else then you'll need to adjust the "nodeUrls" property in both "elasticSearch" solution and "Elastic" provider. In case you have a cluster, you can specify them separated by comma, for example: " nodeUrls": ["elastic1:9200", "elastic2:9200", "elastic3:9200"],
If you have some valid "models" you'd like to include them on the server:
- Create a
{SAGA-HOME}/nt-models
folder for "name trainers" and copy the model there. - Create a
{SAGA-HOME}/ct-models
folder for "classification trainers" and copy the model there. - Create a
{SAGA-HOME}/tf-models
folder for "FAQ" (uses TensorFlow) and copy the model there.
To add datasets:
- Create a
{SAGA-HOME}/datasets
folder. - Each dataset must be placed in its own folder. This folder name will be the one displayed for "test runs".
- Each data document in the dataset must be compliant with Saga's data file JSON format.
- Each folder must contain a ".metadata" file with information about the dataset and how to read it.
You can check out the dataset format here.
Step 4: Run Saga
To run Saga:
Check that ElasticSearch is running.
Use the bundled startup script on {SAGA_HOME}/bin (either startup.bat
for Windows or startup.sh
for Linux and Mac).
If you didn't change the default port on the configuration, you should be able to access Saga UI at http://localhost:8080/.
If not, then check your configuration for the right port.
Step 5: Run Python Bridge Server
Saga has a python recognizer and python stage that can be used to process text using machine learning python models like Bert.
In case you need this, follow instruction on how to setup and run the python bridge here.