In the realm of AI-driven automation, Obsei (pronounced Ob see əb-sē) emerges as a groundbreaking open-source tool designed to seamlessly collect, analyze, and disseminate unstructured data. With its low-code structure, Obsei empowers users to automate complex workflows effortlessly. Whether you’re dealing with social media feedback or customer complaints, Obsei has got you covered. Let’s dive into how to install and use this potent tool!

Understanding Obsei’s Components

To better grasp Obsei’s functionality, let’s liken its three main components to a well-organized library:

• Observer: Think of this as your librarian, collecting books (or data) from a variety of sources, including tweets, reviews, and articles. The Observer gathers all this unstructured information for future use.
• Analyzer: Once the books are collected, the Analyzer acts like a book reviewer who evaluates the contents. It reviews the collected data using various AI techniques such as classification, sentiment analysis, and more, interpreting the information at a more profound level.
• Informer: Finally, the Informer serves as the delivery system, sending all the critical insights and analyses to designated recipients (like sending librarian notes to authors or departments) for further action and contemplation.

Installation of Obsei

Before you can begin utilizing Obsei, ensure you have the prerequisites installed:

• Python 3.7+
• PIP

Once the prerequisites are handled, you can install Obsei in two different ways:

1. Install Via PIP

pip install obsei[all]

2. Install From Master Branch

git clone https://github.com/obsei/obsei.git
cd obsei
pip install --editable .[all]

Note: If you wish to install just the components you need, you can specify by using options like:

pip install obsei[source]  # For Observers
pip install obsei[sink]    # For Informers
pip install obsei[analyzer]  # For Analyzers

How to Use Obsei

Using Obsei is straightforward. Here’s a simple step-by-step process to create your first workflow:

Step 1: Configure Your Source (Observer)

Suppose you want to gather tweets.

from obsei.source.twitter_source import TwitterCredentials, TwitterSource, TwitterSourceConfig

source_config = TwitterSourceConfig(
    keywords=[issue],
    lookup_period='1h',
    cred_info=TwitterCredentials(
        consumer_key=twitter_consumer_key,
        consumer_secret=twitter_consumer_secret,
        bearer_token=ENTER_BEARET_TOKEN,
    )
)

source = TwitterSource()

Step 2: Configure Your Analyzer

Now that we have our data, let’s define how we will analyze it.

from obsei.analyzer.classification_analyzer import ClassificationAnalyzerConfig, ZeroShotClassificationAnalyzer

analyzer_config = ClassificationAnalyzerConfig(
    labels=[service, delay, performance],
)
text_analyzer = ZeroShotClassificationAnalyzer(
    model_name_or_path='typeform/mobilebert-uncased-mnli',
    device='auto'
)

Step 3: Set Up Your Sink (Informer)

Lastly, choose where to send the analyzed results. For instance, let’s configure a Slack sink to receive updates.

from obsei.sink.slack_sink import SlackSink, SlackSinkConfig

sink_config = SlackSinkConfig(
    slack_token=Slack_app_token,
    channel_id=C01LRS6CT9Q
)
sink = SlackSink()

Step 4: Execute Your Workflow

Finally, combine these steps in a Python script and run it to fetch, analyze, and send your data!

source_response_list = source.lookup(source_config)
analyzer_response_list = text_analyzer.analyze_input(source_response_list, analyzer_config)
sink.send_data(analyzer_response_list, sink_config)

Troubleshooting Tips

If you encounter any issues during installation or usage, here are a few tips to help you troubleshoot:

• Ensure that all prerequisites are installed and updated to their latest versions.
• Check your connection to the APIs you are trying to access, such as Twitter or Slack.
• If you face errors related to configuration, double-check the credentials and settings you are using.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Conclusion

Congratulations! You’re now equipped to harness the power of Obsei for your automation needs. Embrace the foundation of AI technologies and redefine how you collect and analyze data!