Sentiment analysis (Spanish)

Service activation and resource plan purchase

Before you use this service, you must activate it. After activation, you can purchase a resource plan.

• Activate service: Activation page

• Purchase resource plan: Purchase page

Service invocation and debugging

For more information about model invocation, see Model invocation.

For more information about software development kit (SDK) examples, see SDK examples.

Debug

Configure access credentials (AKSK) using environment variables

1. Notes:

   1. An Alibaba Cloud account AccessKey has full access to all APIs. This poses a high security risk. For improved security, create and use a Resource Access Management (RAM) user to make API calls or perform routine O&M. To create a RAM user, log on to the RAM console.

   2. To prevent security risks from leaked keys, do not hard-code your AccessKey ID and AccessKey secret into your code. Instead, configure them as environment variables.

2. Configure on Linux and macOS

   export NLP_AK_ENV=<your_access_key_id>
   export NLP_SK_ENV=<your_access_key_secret>

   Replace <your_access_key_id> with your AccessKey ID and <your_access_key_secret> with your AccessKey secret. For more information about how to obtain an AccessKey ID and an AccessKey secret, see Step 2: Obtain an AccessKey pair.

3. Configure on Windows

   1. Create a file for environment variables. Add the NLP_AK_ENV and NLP_SK_ENV environment variables and set their values to your AccessKey ID and AccessKey secret.

   2. Restart Windows.

Java code example

/**
 * An Alibaba Cloud account AccessKey has full access to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user to make API calls or perform routine O&M. To create a RAM user, log on to the RAM console.
 * This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
 * To prevent security threats from key leaks, do not hard-code your AccessKey ID and AccessKey secret into your code.
 */
String accessKeyId = System.getenv("NLP_AK_ENV");
String accessKeySecret = System.getenv("NLP_SK_ENV");
DefaultProfile defaultProfile = DefaultProfile.getProfile("cn-hangzhou",accessKeyId,accessKeySecret);
IAcsClient client = new DefaultAcsClient(defaultProfile);
Map<String, Object> map = new HashMap<>();
List<String> messages = new ArrayList<>();
messages.add("Luego te envían un pendrive de 8gb");
map.put("messages", messages);
RunPreTrainServiceRequest request = new RunPreTrainServiceRequest();
request.setServiceName("NLP-Es-Sentiment-Analysis");
request.setPredictContent(JSON.toJSONString(map));
RunPreTrainServiceResponse response = client.getAcsResponse(request);
System.out.println(response.getPredictResult());

Python code example

# Install dependencies
pip install aliyun-python-sdk-core
pip install aliyun-python-sdk-nlp-automl

# -*- coding: utf8 -*-
import json
import os

from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.acs_exception.exceptions import ClientException
from aliyunsdkcore.acs_exception.exceptions import ServerException
from aliyunsdknlp_automl.request.v20191111 import RunPreTrainServiceRequest

# An Alibaba Cloud account AccessKey has full access to all APIs. This poses a high security threat. We strongly recommend that you create and use a RAM user to make API calls or perform routine O&M. To create a RAM user, log on to the RAM console.
# This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
# To prevent security threats from key leaks, do not hard-code your AccessKey ID and AccessKey secret into your code.
access_key_id = os.environ['NLP_AK_ENV']
access_key_secret = os.environ['NLP_SK_ENV']

# Initialize AcsClient instance
client = AcsClient(
  access_key_id,
  access_key_secret,
  "cn-hangzhou"
);
messages=["Luego te envían un pendrive de 8gb"]
content ={"messages": messages}
# Initialize a request and set parameters
request = RunPreTrainServiceRequest.RunPreTrainServiceRequest()
request.set_ServiceName('NLP-Es-Sentiment-Analysis')
request.set_PredictContent(json.dumps(content))
# Print response
response = client.do_action_with_exception(request)
resp_obj = json.loads(response)
predict_result = json.loads(resp_obj['PredictResult'])
print(predict_result['predictions'])

PredictContent example

{
  "messages": ["Luego te envían un pendrive de 8gb"],
}

PredictResult example

{
  "predictions":["neutral"]
}

Request parameters

Response parameters