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@hejny hejny commented Aug 28, 2025

Integrate Effect.js via via Cline. This is more about demonstrating the capabilities of LLMs on complex codebases than about the feature itself. We discussed it in episode #17 of the AI at Krajta podcast with @BleedingDev, @JorgeSquared and Matyas.

The prompt to Cline:

Use efect.js, find some meaningful usecases in Promptbook project and add it here
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vercel bot commented Aug 28, 2025

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book-components Ready Ready Preview Comment Aug 28, 2025 8:41pm

@hejny hejny changed the title Integrate [Effect.js](https://effect.website/) [via Cline](https://cline.bot/) Integrate Effect.js via Cline Aug 28, 2025
@hejny hejny changed the title Integrate Effect.js via Cline Integrate Effect.js <- Cline Aug 28, 2025
@hejny hejny changed the title Integrate Effect.js <- Cline Integrate Effect.js <- via Cline Aug 28, 2025
@hejny hejny changed the title Integrate Effect.js <- via Cline ✨ Integrate Effect.js <- Cline Aug 28, 2025
…or handling and resource management

- Added EffectPipelineExecutor class for executing pipelines with validation, tool acquisition, and error handling.
- Introduced custom error types for better error reporting.
- Implemented concurrent execution of multiple pipelines with controlled concurrency.
- Added retry policies with exponential backoff for pipeline execution.

feat: Enhance LLM Provider with circuit breaker, rate limiting, and robust error handling

- Created EffectLlmProvider class to manage LLM calls with circuit breaker and rate limiting.
- Implemented error handling for various failure modes including rate limits and model unavailability.
- Added batch processing capabilities for multiple LLM calls with concurrency control.

feat: Develop Effect.js-enhanced Remote Server with health monitoring and graceful shutdown

- Introduced EffectRemoteServer class for managing remote server operations with structured concurrency.
- Implemented connection pooling, request metrics, and health checks.
- Added graceful shutdown handling for active requests and fibers.
- Included rate limiting per client to manage request load effectively.
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4 participants