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This pull request introduces configurable concurrency control for LLM (Large Language Model) API requests, allowing users to limit the number of simultaneous LLM requests to prevent system overload. The main change is the addition of a throttling mechanism using an asyncio semaphore, which can be configured via a new CLI option. This improves robustness and flexibility for users running evaluations and interacting with LLM services.
LLM Throttling and Concurrency Control:
llm_throttle.pythat providesget_llm_semaphoreandset_llm_concurrencyfunctions to manage and configure the concurrency limit for LLM API requests using an asyncio semaphore. The default limit is 20 concurrent requests, and the semaphore is managed per event loop to avoid cross-loop issues.UiPathLlmChatServiceand related LLM gateway service methods to use the semaphore, ensuring all LLM API calls are throttled according to the configured concurrency limit. [1] [2] [3] [4]get_llm_semaphoreandset_llm_concurrencyin theplatform.chatpackage’s public API for external configurability. [1] [2]CLI Improvements:
--max-llm-concurrency(default: 20) to theevalcommand, allowing users to set the maximum number of concurrent LLM requests when running evaluations. The value is passed toset_llm_concurrencybefore any LLM calls are made. [1] [2] [3]Versioning:
2.4.3to2.4.4to reflect the new functionality.