https://github.com/mslinn/ibm-personality-insights-fun
Fun With IBM Personality Insights
https://github.com/mslinn/ibm-personality-insights-fun
artificial-intelligence personality-insights
Last synced: about 2 months ago
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Fun With IBM Personality Insights
- Host: GitHub
- URL: https://github.com/mslinn/ibm-personality-insights-fun
- Owner: mslinn
- License: apache-2.0
- Created: 2018-09-05T19:09:30.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-09-06T22:48:21.000Z (over 6 years ago)
- Last Synced: 2025-01-09T01:12:32.323Z (4 months ago)
- Topics: artificial-intelligence, personality-insights
- Language: Python
- Homepage: https://console.bluemix.net/docs/services/personality-insights/getting-started.html#gettingStarted
- Size: 152 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Fun With IBM Personality Insights
In this project I use `curl` and Python 3 to play around with [IBM Personality Insights](https://console.bluemix.net/docs/services/personality-insights).
I used [IBM's free Lite service](https://console.bluemix.net/catalog/services/personality-insights),
which provides 1,000 API calls per month at no cost, and deploy to the US South region.
I enabled a Lite
[Personality Insights service instance](https://console.bluemix.net/catalog/services/personality-insights),
which only lasts 30 days.
I followed the [Getting started](9https://console.bluemix.net/docs/services/personality-insights/getting-started.html#getting-started-tutorial)
instructions and referred to the
[API reference](https://www.ibm.com/watson/developercloud/personality-insights/api/).
The service name was automatically created: `Personality Insights-ca`
The Getting Started examples use `curl` to call methods of the HTTP interface.
Ubuntu's version of `curl` installed by default is the correct version.
I used jq to pretty-print the returned JSON.
Here is how to install it in Ubuntu:
```
$ sudo apt install jq
```
[Step 1](https://console.bluemix.net/docs/services/personality-insights/getting-started.html#gettingStarted)
of the Getting Started instructions has a serious error: instead of providing the `apiKey`,
your `username:password` must be provided.
Because I did not want to hard-code credentials into a program, I defined environment variables to hold this sensitive data.
```
export PI_USERNAME="999999-8888-7777-6666-12345678" # replace with your Personality Insights username
export PI_PASSWORD="zYxWv" # replace with your Personality Insights password
```
## Curl
The IBM Personality Insights Getting Started instructions show a `curl` example, which I modified as shown.
I then wrote a simple Python equivalent, shown in the next section.
```
export PATH_OF_TEXT_TO_ANALYSE=./profile.txt
curl -sSX POST --user "$PI_USERNAME:$PI_PASSWORD" \
--header "Content-Type: text/plain;charset=utf-8" \
--header "Accept: application/json" \
--data-binary @"$PATH_OF_TEXT_TO_ANALYSE" \
"https://gateway.watsonplatform.net/personality-insights/api/v3/profile?version=2017-10-13" | \
jq .
```
Notice the leading `@` character before `$PATH_OF_TEXT_TO_ANALYSE`.
If you don't put that character there, the path is interpreted as the text analyze, instead of the filename of containing the text to analyze.
[Here is the JSON output.](example1a.json)
## Python
I found the
[Python docstring for the PersonalityInsightsV3 constructor](https://github.com/watson-developer-cloud/python-sdk/blob/master/watson_developer_cloud/personality_insights_v3.py#L63-L102)
to be helpful.
The Python version is more ambitious than the `curl` version;
the Python version reads two blog postings, combines them, and
submits them for analysis. [Here is the resulting JSON](example1b.json).