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Version v2.0.1#8

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NullPointerDepressiveDisorder merged 3 commits into
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Mar 31, 2026
Merged

Version v2.0.1#8
NullPointerDepressiveDisorder merged 3 commits into
prodfrom
main

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#7)

* fix: change default base URLs from localhost to 127.0.0.1 to prevent Windows IPv6 resolution issues, pass model_id to llama-cpp, and correct model path parsing in the sweep command.

* fix(llama_cpp): Correct model_id fallback and improve test robustness

* test: improve llama-cpp backend tests for cleanup and backend name handling
Copilot AI review requested due to automatic review settings March 31, 2026 01:43
@NullPointerDepressiveDisorder NullPointerDepressiveDisorder merged commit 18fce48 into prod Mar 31, 2026
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Pull request overview

Updates local-backend defaults and CI/testing around the v2.0.1 release, primarily to improve Windows localhost reliability and tighten llama.cpp backend behavior.

Changes:

  • Switch default local HTTP base URLs from localhost to 127.0.0.1 across resolver, backends, tests, and docs.
  • Update LlamaCppBackend to require a model_id, include it in the /completion payload, and fall back to that model_id when the server response omits model.
  • Improve CLI sweep --models parsing to handle extra = characters; add new unit tests and Codecov/coverage workflow config.

Reviewed changes

Copilot reviewed 14 out of 14 changed files in this pull request and generated 1 comment.

Show a summary per file
File Description
tests/unit/test_resolve.py Updates expected default base URLs to 127.0.0.1.
tests/unit/test_openai_compat.py Updates base URL + request URL expectations to 127.0.0.1.
tests/unit/test_llama_cpp_payload.py New async unit test asserting llama.cpp payload includes model.
tests/unit/test_llama_cpp_fallback.py New async unit test asserting response model_id fallback behavior.
tests/unit/test_cli_parsing.py New unit test covering robust --models parsing with extra =.
src/infer_check/resolve.py Updates default resolver URLs/docs to 127.0.0.1.
src/infer_check/cli.py Adjusts sweep parsing to strip leading = from paths after split.
src/infer_check/backends/vllm_mlx.py Updates default base URL and docstring to 127.0.0.1.
src/infer_check/backends/llama_cpp.py Requires model_id, includes it in request payload, improves connect error message, and adjusts result model_id fallback.
src/infer_check/backends/base.py Passes model_id into LlamaCppBackend; updates default URLs and error message example.
README.md Updates example base URLs to 127.0.0.1.
pyproject.toml Adds pytest-asyncio to dev dependencies.
codecov.yml Adds Codecov configuration.
.github/workflows/coverage.yml Updates CI workflow steps for uv + Codecov uploads (but currently has an issue with pytest coverage upload).

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Comment on lines 25 to +46
- name: Run tests with coverage
run: uv run pytest --cov=src --cov-branch --cov-report=xml
run: uv run pytest --cov --junitxml=junit.xml -o junit_family=legacy

- name: Run Mypy
run: uv run mypy src --cobertura-xml-report mypy_report

- name: Upload coverage to Codecov
- name: Upload mypy coverage
uses: codecov/codecov-action@v5
if: "!cancelled()"
with:
files: ./coverage.xml, ./mypy_report/cobertura.xml
flags: pytest,mypy
files: ./mypy_report/cobertura.xml
flags: mypy
token: ${{ secrets.CODECOV_TOKEN }}
slug: ${{ github.repository }}
fail_ci_if_error: 'true'

- name: Upload pytest cov
if: ${{ !cancelled() }}
uses: codecov/codecov-action@v5
with:
files: ./junit.xml
flags: pytest
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The workflow no longer generates or uploads pytest coverage data to Codecov: pytest --cov here doesn’t produce coverage.xml, and the “Upload pytest cov” step is uploading junit.xml as coverage (JUnit is a test-results format, not a coverage report). With fail_ci_if_error: 'true', this is likely to fail the workflow and/or result in missing coverage.

Suggested fix: generate a coverage artifact (e.g., --cov=src --cov-branch --cov-report=xml:coverage.xml or --cov-report=lcov), and upload that file in the coverage upload step; keep junit.xml only for the report_type: test_results upload (or remove files: so Codecov can auto-detect the coverage output).

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2 participants