Add ONNX testing workflow

[seonglae]

Summary

• add GitHub Actions workflow running pytest
• switch torch dependency to CPU-friendly version
• allow encode_onnx to handle token_type_ids
• add regression test for onnx embedding

Testing

• python3 -m py_compile $(git ls-files '*.py')
• pytest -q tests/test_onnx.py -vv

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https://chatgpt.com/codex/tasks/task_e_68460bd4684c83279d35c7ec44aa7377

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[Copilot]

Pull Request Overview

This pull request enhances the project's testing and deployment configuration by adding an ONNX testing workflow, updating dependency versions with a focus on CPU-based inference, and extending the embedding functionality to support token_type_ids.

• Add a regression test for the ONNX embedding workflow.
• Update torch dependency and include onnxruntime.
• Modify the embedding processing and inference flow for local ONNX support.

Reviewed Changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
tests/test_onnx.py	Added a regression test for verifying ONNX embedding output shape.
pyproject.toml	Updated torch dependency and added onnxruntime dependency.
index_to.py	Introduced local inference option with inline embed function definitions.
curiosity/embedding.py	Added functions for loading and using an ONNX model for inference.
README.md	Updated usage examples to reflect new local ONNX inference functionality.
.github/workflows/test.yml	Added GitHub Actions workflow for running tests.

Comments suppressed due to low confidence (1)

curiosity/embedding.py:48

• Consider adding a comment explaining the rationale for initializing 'token_type_ids' with zeros when missing, to help future maintainers understand this adjustment for ONNX model requirements.

if 'token_type_ids' not in ort_inputs: