Sxnan opened a new pull request, #158:
URL: https://github.com/apache/flink-agents/pull/158
### Purpose of change
This PR introduces a comprehensive quickstart workflow for Flink Agents with
practical examples demonstrating how to integrate LLM-powered agents with Flink
streaming pipelines. The changes include:
1. **Two complete example workflows:**
- `product_review_analysis.py`: A simple streaming pipeline that analyzes
product reviews using an LLM agent to extract review scores and unsatisfied
reasons
- `product_improve_suggestion.py`: A more complex multi-stage pipeline
that aggregates review analysis results and generates product improvement
suggestions
2. **Agent implementations:**
- `ReviewAnalysisAgent`: Analyzes individual product reviews
- `ProductSuggestionAgent`: Generates improvement suggestions based on
aggregated review data
3. **Sample data:** Product review data in JSON format for testing the
examples
These examples serve as a practical entry point for users to understand how
to build streaming applications that leverage LLM agents for real-time data
processing and analysis.
### Tests
### API
This change does not modify any public APIs. It only adds example code that
demonstrates usage of existing Flink Agents APIs
### Documentation
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