Pattern preview · 12 of 4,089 sample rules shown · site-specific intelligence stays private
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dependency_resolution
infrastructure-dependency-resolutio-installing-vllm-on-macos-fails-with-error-could-no-dda96e16
IFInstalling vLLM on macOS fails with error 'Could not find a version that satisfies the requirement torch==2.4.0' because PyTorch stopped providing macOS x86_64 binaries after version 2.2.2.
THENOverride the torch dependency to a compatible version (2.2.2) on macOS. One method is to use PDM with resolution overrides as shown in the code example, or use pip with --force-reinstall specifying torch==2.2.2 and torchvision==0.17.2.
Tier 170%
dependency_resolution
infrastructure-dependency-resolutio-error-no-solution-found-when-resolving-dependencie-3cc9dcc8
IFError 'No solution found when resolving dependencies' because required PyTorch nightly build (torch==2.9.0.dev20250804+cu128) is no longer available.
THENInstall the specific PyTorch wheel directly from the official PyTorch website using uv pip install with the exact URL. Then install vLLM from gpt-oss wheels using an extra index with unsafe-best-match strategy. This bypasses the missing nightly version.
Tier 170%
dependency_resolution
infrastructure-dependency-resolutio-importerror-cannot-import-name-basecache-from-lang-85892767
IFImportError: cannot import name 'BaseCache' from 'langchain' when using older versions of llama-index with LangChain.
THENUse the correct import path 'from langchain.schema.cache import BaseCache' instead of the deprecated path. Alternatively, downgrade langchain to version 0.0.340 or upgrade llama-index to the latest version to align dependencies.
Tier 170%
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