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Obsei
Low-code AI automation for social data collection and analysis
Obsei streamlines gathering, AI-driven analysis, and routing of unstructured social and review data, enabling automated insights, alerts, and ticket creation with minimal code.
Overview
Overview
Obsei is a low‑code framework that lets data engineers and product teams build end‑to‑end pipelines for unstructured social and review content. By configuring an Observer you can pull data from Twitter, Reddit, Facebook, app‑store reviews, news sites, and more without writing custom scrapers.
AI‑enhanced processing
Collected items flow into the Analyzer, where plug‑in AI tasks such as sentiment classification, language translation, PII detection, or custom models can be applied. The results are then handed to an Informer, which can create tickets in Jira, push records to Elasticsearch, store dataframes, or trigger Slack alerts. Observers optionally persist their cursor state in SQLite, PostgreSQL or MySQL, making the workflow suitable for cron jobs, Airflow DAGs, or serverless functions.
Getting started and considerations
Install with pip install obsei[all] or select only the needed extras (e.g., twitter-api, analyzer). The modular design enables rapid prototyping, but the project is currently in alpha, so users should prefer released versions for production. Documentation and community channels are available for support.
Highlights
Modular observers for dozens of public and private data sources
Pluggable AI analyzers supporting sentiment, classification, translation, PII detection, etc.
Flexible informers to route results to ticketing systems, databases, or messaging platforms
State persistence in SQLite, PostgreSQL, MySQL for scheduled or serverless execution
Pros
- Extensible architecture lets you mix and match sources, analyzers, and sinks
- Broad coverage of social, review, and news platforms out of the box
- Low‑code configuration reduces development effort
- Python ecosystem integration with optional extras for lean installations
Considerations
- Project is in alpha; breaking changes may occur between releases
- Requires Python environment and appropriate AI libraries (e.g., PyTorch) for some analyzers
- No built‑in visual UI; interactions are code‑first
- Full installation with all extras can be heavyweight
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Fit guide
Great for
- Teams building automated social listening and sentiment pipelines
- Developers needing quick AI‑enhanced data flows without writing scrapers
- Organizations creating labeled datasets from public reviews for machine‑learning projects
- Small operations automating ticket creation and alerting from customer feedback
Not ideal when
- Enterprises that need guaranteed enterprise‑grade stability and SLA
- Users without Python programming experience
- High‑throughput real‑time streaming at massive scale
- Projects that require an out‑of‑the‑box dashboard or visual analytics
How teams use it
Social listening dashboard
Continuously collect brand mentions from Twitter and Reddit, analyze sentiment, and push daily summaries to a Slack channel.
Automated ticket creation
Detect negative customer complaints in app‑store reviews, classify issue type, and automatically open tickets in Jira with relevant tags.
Market research dataset
Scrape product reviews from Amazon and Google Play, run classification and translation, and store the enriched dataset in a CSV for model training.
Compliance monitoring
Scan public comments for PII, flag matches, and send alerts to a secure Elasticsearch index for audit.
Tech snapshot
Python60%
Jupyter Notebook39%
Dockerfile1%
HTML1%
Frequently asked questions
What programming language does Obsei require?
Obsei runs on Python 3.7 or newer.
Can I use Obsei without installing all optional dependencies?
Yes, you can install only the extras you need, such as `twitter-api` or `analyzer`, via pip.
How does Obsei store the state of observers?
Observers can persist their cursor or last‑fetched timestamp in SQLite, PostgreSQL, MySQL, or other supported databases.
Is there a graphical user interface?
Obsei is primarily a code‑first library; a UI is not provided out of the box.
Is Obsei suitable for production use?
The project is currently in alpha; it is recommended to use released versions and evaluate stability before critical production deployments.
Project at a glance
Active- Stars
- 1,371
- Watchers
- 1,371
- Forks
- 175
LicenseApache-2.0
Repo age5 years old
Last commit2 months ago
Primary languagePython
Last synced 2 hours ago