fix(core): lazy loading transformers, numpy, simsimd

[Won-Kyu Park (wkpark)]

fix(core): lazy loading transformers, numpy, simsimd

Summary

Optimized the initial import speed of langchain_core by converting top-level imports of transformers, numpy, and simsimd into lazy, local imports.

Details

Confirmed with python -X importtime that these dependencies are no longer loaded on initial import, and verified functionality through make format/lint and est.

Disclaimer

I used the Gemini CLI to help with the specific implementation details and to ensure compliance with linting and type checking and drafting this PR description.

before
without transformers / torch env.

$ time uv run python -c "from langchain_core.prompts import BasePromptTemplate"
real    0m0.600s
user    0m0.509s
sys     0m0.074s

with transformers / torch installed env.

$ uv pip install transformers
...
$ uv pip install numpy
...

$ time uv run python -c "from langchain_core.prompts import BasePromptTemplate"
real    0m9.664s
user    0m4.268s
sys     0m0.752s

$ time uv run python -c "from langchain_core.prompts import BasePromptTemplate" # one more time

real    0m4.030s
user    0m3.877s
sys     0m0.468s

after PR applied

$ time uv run python -c "from langchain_core.prompts import BasePromptTemplate"
real    0m0.797s
user    0m0.662s
sys     0m0.110s

$ uv pip show transformers
Name: transformers
Version: 4.55.0
Location: /home/future/repo/linkBrain-server/.venv/lib/python3.13/site-packages
Requires: filelock, huggingface-hub, numpy, packaging, pyyaml, regex, requests, safetensors, tokenizers, tqdm
Required-by: docling-ibm-models, optimum, sentence-transformers

See also #35469

[codspeed-hq]

Merging this PR will improve performance by 10.65%

⚡ 1 improved benchmark
✅ 12 untouched benchmarks
⏩ 2 skipped benchmarks¹

Performance Changes

	Mode	Benchmark	BASE	HEAD	Efficiency
⚡	WallTime	test_import_time[InMemoryVectorStore]	1.5 s	1.4 s	+10.65%

Tip

Curious why this is faster? Comment @codspeedbot explain why this is faster on this PR, or directly use the CodSpeed MCP with your agent.

---

_{Comparing wkpark:lazy_load_numpy_transformers (a34d883) with master (aef86c4)²}

Footnotes

1. 2 benchmarks were skipped, so the baseline results were used instead. If they were deleted from the codebase, click here and archive them to remove them from the performance reports. ↩

2. No successful run was found on master (06e6507) during the generation of this report, so aef86c4 was used instead as the comparison base. There might be some changes unrelated to this pull request in this report. ↩

[ajram23]

+1 running into the same problem on the Mac for transformers