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[python][examples] Add quickstart workflow examples - #158
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| aggregated_analysis_res_stream = ( | ||
| review_analysis_res_stream.key_by(lambda x: x.id) | ||
| .window(TumblingProcessingTimeWindows.of(Time.minutes(1))) | ||
| .process(AggregateScoreDistributionAndDislikeReasons()) | ||
| ) |
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I wonder if we can convert the output of ReviewAnalysisAgent into a table, and apply some event-time windowing. The purpose is to show how to integrate the agent with not only datastream but also table api, and event-time is more frequently used by flink users.
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@xintongsong Thanks for the review! All the comments are addressed. Please take another look. |
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LGTM. Please merge after resolving the conflicts.
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Conflict resolved, merging... |
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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:
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 reasonsproduct_improve_suggestion.py: A more complex multi-stage pipeline that aggregates review analysis results and generates product improvement suggestionsAgent implementations:
ReviewAnalysisAgent: Analyzes individual product reviewsProductSuggestionAgent: Generates improvement suggestions based on aggregated review dataSample 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