diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md index 9579226a94..8cff2cda5f 100644 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -25,5 +25,5 @@ - [ ] I've read the [`CONTRIBUTING.md`](https://github.com/Giskard-AI/ai-inspector/blob/master/CONTRIBUTING.md) guide. - [ ] I've written tests for all new methods and classes that I created. - [ ] I've written the docstring in Google format for all the methods and classes that I used. -- [ ] I've updated the `pdm.lock` running `pdm update-lock` (only applicable when `pyproject.toml` has been +- [ ] I've updated the `uv.lock` running `uv lock` (only applicable when `pyproject.toml` has been modified) diff --git a/.github/workflows/build-python.yml b/.github/workflows/build-python.yml index 2e364d2a6b..c6847ccb79 100644 --- a/.github/workflows/build-python.yml +++ b/.github/workflows/build-python.yml @@ -43,6 +43,7 @@ concurrency: cancel-in-progress: true env: GSK_DISABLE_ANALYTICS: true + GISKARD_DEV_MODE: true GSK_DISABLE_SENTRY: true defaults: run: @@ -116,12 +117,10 @@ jobs: with: fetch-depth: 0 - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: ${{ matrix.python-version }} - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Cache Giskard test resources uses: actions/cache@v4 @@ -138,14 +137,14 @@ jobs: - name: Install dependencies (Windows) if: ${{ matrix.os == 'windows-2022' }} run: | - pdm install -G :all --without tensorflow - pdm list + uv sync --all-groups --extra llm --extra talk + uv pip list - name: Install dependencies if: ${{ matrix.os != 'windows-2022' }} run: | - pdm install -G :all - pdm list + uv sync --all-groups --extra llm --extra talk --extra tensorflow + uv pip list - name: Check yet again new disk space run: | @@ -154,49 +153,49 @@ jobs: - name: Re-install lightgbm from sources for MacOS if: ${{ matrix.os == 'macos-latest' }} run: | - pdm run pip uninstall lightgbm -y - pdm run pip install --no-binary lightgbm lightgbm --config-settings=cmake.define.USE_OPENMP=OFF + uv run pip uninstall lightgbm -y + uv run pip install --no-binary lightgbm lightgbm --config-settings=cmake.define.USE_OPENMP=OFF brew install libomp - name: Install pydantic v1 if: ${{ matrix.pydantic_v1 }} run: | - pdm run pip uninstall pydantic pydantic_core -y - pdm run pip install "pydantic>=1,<2" + uv pip uninstall pydantic pydantic_core -y + uv pip install "pydantic>=1,<2" - name: Check Pydantic installed version run: | - pdm run pip freeze | grep '^pydantic' - pdm run pip freeze | grep -q '^pydantic==${{ matrix.pydantic_v1 && '1' || '2' }}\.' + uv pip list | grep -i pydantic + uv run python -c "import pydantic; assert pydantic.__version__.startswith('${{ matrix.pydantic_v1 && '1' || '2' }}.'), f'Wrong pydantic version: {pydantic.__version__}'" - name: Install langchain minimal version if: ${{ matrix.langchain_minimal }} run: | - pdm run pip uninstall langchain -y - pdm run pip install "langchain==0.0.275" + uv pip uninstall langchain -y + uv pip install "langchain==0.0.275" - name: Check langchain installed version if: ${{ matrix.langchain_minimal }} run: | - pdm run pip freeze | grep '^langchain' - pdm run pip freeze | grep -q '^langchain==0.0.275' + uv pip list | grep -i langchain + uv run python -c "import langchain; assert langchain.__version__ == '0.0.275'" - name: Install pandas v1 if: ${{ matrix.pandas_v1 }} run: | - pdm run pip uninstall pandas -y - pdm run pip install "pandas<2" + uv pip uninstall pandas -y + uv pip install "pandas>=1.0,<2.0" - name: Check Pandas installed version run: | - pdm run pip freeze | grep '^pandas' - pdm run pip freeze | grep -q '^pandas==${{ matrix.pandas_v1 && '1' || '2' }}\.' + uv pip list | grep -i pandas + uv run python -c "import pandas; version = pandas.__version__; print(f'pandas version: {version}'); assert version.startswith('${{ matrix.pandas_v1 && '1' || '2' }}.'), f'Expected pandas v${{ matrix.pandas_v1 && '1' || '2' }}.x, got {version}'" - name: Lint code - run: pdm run lint + run: uv run ruff check giskard tests - name: Test code - run: pdm test-fast + run: uv run pytest -c pyproject.toml --cov=giskard --cov-report=xml --cov-append --disable-warnings --no-header -vv --durations=0 -n auto -m 'not slow' --use-subprocess tests env: PYTEST_XDIST_AUTO_NUM_WORKERS: 2 @@ -208,7 +207,7 @@ jobs: SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }} - name: Build - run: pdm build + run: uv build - name: "Python client: archive built artifacts" # Upload needs to be done only once by workflo run, so we need to select one only in the matrix @@ -221,7 +220,7 @@ jobs: if: ${{ inputs.run-integration-tests }} env: PYTEST_XDIST_AUTO_NUM_WORKERS: 2 - run: pdm test-slow tests/ + run: uv run pytest -c pyproject.toml --cov=giskard --cov-report=xml --cov-append --disable-warnings --no-header -vv --durations=0 -m 'slow' --use-subprocess tests/ - name: "Memory csv" if: ${{ always() && matrix.os == 'ubuntu-latest' && matrix.python-version == '3.10' && !matrix.langchain_minimal && !matrix.pandas_v1 && !matrix.pydantic_v1 }} @@ -247,14 +246,12 @@ jobs: steps: - name: Checkout code uses: actions/checkout@v4 - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Build wheel - run: pdm build + run: uv build - name: Install Poetry uses: snok/install-poetry@v1 - name: Create new project, install wheel and import (Poetry) @@ -271,42 +268,43 @@ jobs: steps: - name: Checkout code uses: actions/checkout@v4 - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Build wheel - run: pdm build + run: uv build - name: Create new project, install wheel and import (Pip) run: | python -m venv .venv-test-pip source .venv-test-pip/bin/activate python -m pip install "$(ls ./dist/*.whl)" python -c "import giskard" - install-pdm: - name: "Check if wheel can be installed with PDM" + install-uv: + name: "Check if wheel can be installed with UV" runs-on: ubuntu-latest steps: - name: Checkout code uses: actions/checkout@v4 - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Build wheel - run: pdm build - - name: Create new project, install wheel and import (PDM) + run: uv build + - name: Create new project, install wheel and import (UV) run: | - mkdir ./install-run - cd ./install-run - pdm init --python 3.10 -n - sed -i 's/^\(requires-python *= *\).*$/\1">=3.10,<3.12"/' pyproject.toml - pdm add "$(ls ../dist/*.whl)" - pdm run python -c "import giskard" + mkdir -p /tmp/install-run + cd /tmp/install-run + cat > pyproject.toml << 'EOF' + [project] + name = "install-run" + version = "0.1.0" + requires-python = ">=3.10,<3.13" + dependencies = [] + EOF + uv add "$(ls ${{ github.workspace }}/dist/*.whl)" + uv run python -c "import giskard" check-doc: name: "Build and check doc" runs-on: ubuntu-latest @@ -346,12 +344,10 @@ jobs: with: fetch-depth: 0 - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Set up Pandoc (needed for doc) uses: r-lib/actions/setup-pandoc@v2 @@ -359,14 +355,14 @@ jobs: pandoc-version: "3.1.7" # https://github.com/jgm/pandoc/releases - name: Install dependencies - run: pdm install -G :all + run: uv sync --all-groups --extra llm --extra talk --extra tensorflow - name: Check new disk space run: | df -h - name: Build doc - run: pdm doc + run: uv run sphinx-build docs docs/_build/html - name: Check doc - run: pdm check-doc + run: uv run python ./docs/scrapper.py diff --git a/.github/workflows/create-release.yml b/.github/workflows/create-release.yml index daa4165df2..af5e124d6a 100644 --- a/.github/workflows/create-release.yml +++ b/.github/workflows/create-release.yml @@ -43,18 +43,18 @@ jobs: ref: main token: ${{ secrets.RELEASE_PAT_TOKEN }} # Needed to trigger other actions - - name: Edit pyproject.toml - run: sed -i 's/^\(version *= *\).*$/\1"${{ env.VERSION_NUMBER }}"/' pyproject.toml - name: Remove dark theme logo from README run: sed -i 's/.*#gh-dark-mode-only.*//' README.md - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false + - name: Change version + run: | + set -euo pipefail + uv version "${INPUT_VERSION}" - name: "@slack Release process started" id: slack @@ -87,7 +87,7 @@ jobs: # build .tar.gz sdist tarball - name: Build source distribution tarball - run: pdm build + run: uv build - name: Create Github Release id: github-release @@ -101,7 +101,7 @@ jobs: dist/giskard-*.whl - name: Push to Pipy - run: pdm publish --no-build --username "${{ secrets.PIPY_USERNAME }}" --password "${{ secrets.PIPY_PASSWORD }}" + run: uv publish --username "${{ secrets.PIPY_USERNAME }}" --password "${{ secrets.PIPY_PASSWORD }}" - name: Set job success env var run: | diff --git a/.github/workflows/lock-deps.yml b/.github/workflows/lock-deps.yml index b19e6af8f1..65bcc9aaae 100644 --- a/.github/workflows/lock-deps.yml +++ b/.github/workflows/lock-deps.yml @@ -21,7 +21,7 @@ permissions: jobs: lock-deps: if: ${{ !github.event.pull_request || contains( github.event.pull_request.labels.*.name, 'Lockfile') }} - name: "Lock dependencies using PDM" + name: "Lock dependencies using UV" runs-on: ubuntu-latest continue-on-error: false # https://ncorti.com/blog/howto-github-actions-build-matrix steps: @@ -51,15 +51,13 @@ jobs: token: ${{ secrets.RELEASE_PAT_TOKEN }} # Needed to trigger other actions ref: ${{ steps.extract_branch.outputs.branch }} - - name: Setup PDM - uses: pdm-project/setup-pdm@v4 + - name: Setup UV + uses: astral-sh/setup-uv@61cb8a9741eeb8a550a1b8544337180c0fc8476b # v7.2.0 with: python-version: "3.10" - version: head # Issue with PDM 2.20.1: https://github.com/pdm-project/pdm/issues/3271 - cache: false - name: Install dependencies - run: rm -rf pdm.lock && pdm lock -G :all + run: rm -rf uv.lock && uv lock - name: Configure git run: | @@ -68,8 +66,8 @@ jobs: - name: Adding file run: | - git add pdm.lock - git commit -m "Regenerating pdm.lock" --allow-empty + git add uv.lock + git commit -m "Regenerating uv.lock" --allow-empty - name: Remove label if: ${{ github.event.pull_request}} diff --git a/.gitignore b/.gitignore index d133ea1b12..10ee0add35 100755 --- a/.gitignore +++ b/.gitignore @@ -109,16 +109,8 @@ ipython_config.py # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control #poetry.lock -# pdm -# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. -#pdm.lock -# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it -# in version control. -# https://pdm.fming.dev/#use-with-ide -.pdm.toml -.pdm-python - -# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and similar tools __pypackages__/ # Celery stuff diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 76a5327f13..882611fe76 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -6,8 +6,8 @@ build: python: "3.10" jobs: post_create_environment: - - pip install pdm - - pdm export --without-hashes -G doc,llm -o requirements-sphinx.txt + - pip install uv + - uv export --no-hashes --group doc --extra llm -o requirements-sphinx.txt sphinx: configuration: docs/conf.py diff --git a/docs/community/contribution_guidelines/dev-environment.md b/docs/community/contribution_guidelines/dev-environment.md index 2ad5723201..db548cc5ad 100644 --- a/docs/community/contribution_guidelines/dev-environment.md +++ b/docs/community/contribution_guidelines/dev-environment.md @@ -4,16 +4,16 @@ After cloning the repository here are the useful commands to set up the local en ## Install dependencies -We work with [PDM](https://pdm-project.org/en/latest/) as our package manager. You can find the installation instructions [here](https://pdm-project.org/en/latest/#installation). +We work with [uv](https://docs.astral.sh/uv/) as our Python package and project manager. You can find the installation instructions [here](https://docs.astral.sh/uv/getting-started/installation/). -After installing PDM, we can install the dependencies by running: +After installing uv, we can install the dependencies by running: ```shell -pdm install +uv sync --all-extras --all-groups ``` ## Pre-commit hooks installation -Pre-commit hooks ensure that the basic code quality checks are performed before the code is committed. Pre-commit has already been installed as a dev dependency using `pdm`. +Pre-commit hooks ensure that the basic code quality checks are performed before the code is committed. Pre-commit has already been installed as a dev dependency using `uv`. The current pre-commit hook configuration is defined in `.pre-commit-config.yaml`. diff --git a/docs/open_source/scan/scan_llm/index.md b/docs/open_source/scan/scan_llm/index.md index 75d778e246..c5d2fdbedf 100644 --- a/docs/open_source/scan/scan_llm/index.md +++ b/docs/open_source/scan/scan_llm/index.md @@ -176,18 +176,39 @@ class MyCustomLLM(litellm.CustomLLM): ) return litellm.ModelResponse(**response.json()) + + # Custom embeddings + def embedding( + self, + model: str, + input: list, + api_key: Optional[str] = None, + **kwargs, + ) -> litellm.EmbeddingResponse: + api_key = api_key or os.environ.get("MY_SECRET_KEY") + if api_key is None: + raise litellm.AuthenticationError("`api_key` was not provided") + + response = requests.post( + "https://www.my-custom-llm.ai/embeddings", + json={"model": model, "input": input}, + headers={"Authorization": api_key}, + ) + + return litellm.EmbeddingResponse(**response.json()) -os.eviron["MY_SECRET_KEY"] = "" # "my-secret-key" +os.environ["MY_SECRET_KEY"] = "" # "my-secret-key" my_custom_llm = MyCustomLLM() litellm.custom_provider_map = [ # 👈 KEY STEP - REGISTER HANDLER - {"provider": "my-custom-llm-endpoint", "custom_handler": my_custom_llm} + {"provider": "my-custom-provider", "custom_handler": my_custom_llm} ] api_key = os.environ["MY_SECRET_KEY"] -giskard.llm.set_llm_model("my-custom-llm-endpoint/my-custom-model", api_key=api_key) +giskard.llm.set_llm_model("my-custom-provider/my-custom-model", api_key=api_key) +giskard.llm.set_embedding_model("my-custom-provider/my-custom-model", api_key=api_key) ``` :::::: diff --git a/docs/open_source/setting_up/index.md b/docs/open_source/setting_up/index.md index 923b706a15..e07a675d82 100644 --- a/docs/open_source/setting_up/index.md +++ b/docs/open_source/setting_up/index.md @@ -203,18 +203,39 @@ class MyCustomLLM(litellm.CustomLLM): ) return litellm.ModelResponse(**response.json()) + + # Custom embeddings + def embedding( + self, + model: str, + input: list, + api_key: Optional[str] = None, + **kwargs, + ) -> litellm.EmbeddingResponse: + api_key = api_key or os.environ.get("MY_SECRET_KEY") + if api_key is None: + raise litellm.AuthenticationError("`api_key` was not provided") + + response = requests.post( + "https://www.my-custom-llm.ai/embeddings", + json={"model": model, "input": input}, + headers={"Authorization": api_key}, + ) + + return litellm.EmbeddingResponse(**response.json()) -os.eviron["MY_SECRET_KEY"] = "" # "my-secret-key" +os.environ["MY_SECRET_KEY"] = "" # "my-secret-key" my_custom_llm = MyCustomLLM() litellm.custom_provider_map = [ # 👈 KEY STEP - REGISTER HANDLER - {"provider": "my-custom-llm-endpoint", "custom_handler": my_custom_llm} + {"provider": "my-custom-provider", "custom_handler": my_custom_llm} ] api_key = os.environ["MY_SECRET_KEY"] -giskard.llm.set_llm_model("my-custom-llm-endpoint/my-custom-model", api_key=api_key) +giskard.llm.set_llm_model("my-custom-provider/my-custom-model", api_key=api_key) +giskard.llm.set_embedding_model("my-custom-provider/my-custom-model", api_key=api_key) ``` If you run into any issues configuring the LLM client, don't hesitate to [ask us on Discord](https://discord.com/invite/ABvfpbu69R) or open a new issue on [our GitHub repo](https://github.com/Giskard-AI/giskard). diff --git a/docs/open_source/testset_generation/testset_generation/index.md b/docs/open_source/testset_generation/testset_generation/index.md index 8efa053f64..ed6f8c9f19 100644 --- a/docs/open_source/testset_generation/testset_generation/index.md +++ b/docs/open_source/testset_generation/testset_generation/index.md @@ -214,18 +214,39 @@ class MyCustomLLM(litellm.CustomLLM): ) return litellm.ModelResponse(**response.json()) + + # Custom embeddings + def embedding( + self, + model: str, + input: list, + api_key: Optional[str] = None, + **kwargs, + ) -> litellm.EmbeddingResponse: + api_key = api_key or os.environ.get("MY_SECRET_KEY") + if api_key is None: + raise litellm.AuthenticationError("`api_key` was not provided") + + response = requests.post( + "https://www.my-custom-llm.ai/embeddings", + json={"model": model, "input": input}, + headers={"Authorization": api_key}, + ) + + return litellm.EmbeddingResponse(**response.json()) -os.eviron["MY_SECRET_KEY"] = "" # "my-secret-key" +os.environ["MY_SECRET_KEY"] = "" # "my-secret-key" my_custom_llm = MyCustomLLM() litellm.custom_provider_map = [ # 👈 KEY STEP - REGISTER HANDLER - {"provider": "my-custom-llm-endpoint", "custom_handler": my_custom_llm} + {"provider": "my-custom-provider", "custom_handler": my_custom_llm} ] api_key = os.environ["MY_SECRET_KEY"] -giskard.llm.set_llm_model("my-custom-llm-endpoint/my-custom-model", api_key=api_key) +giskard.llm.set_llm_model("my-custom-provider/my-custom-model", api_key=api_key) +giskard.llm.set_embedding_model("my-custom-provider/my-custom-model", api_key=api_key) ``` :::::: diff --git a/pdm.lock b/pdm.lock deleted file mode 100644 index 256693aa02..0000000000 --- a/pdm.lock +++ /dev/null @@ -1,8671 +0,0 @@ -# This file is @generated by PDM. -# It is not intended for manual editing. - -[metadata] -groups = ["default", "dev", "doc", "llm", "ml-runtime", "talk", "tensorflow", "test"] -strategy = ["inherit_metadata"] -lock_version = "4.5.0" -content_hash = "sha256:ecf506f7488c98a088ba47f54c1c97c2c1117d0bfa4be2993907c5346452ba08" - -[[metadata.targets]] -requires_python = ">=3.9,<3.13" - -[[package]] -name = "absl-py" -version = "2.3.0" -requires_python = ">=3.8" -summary = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py." -groups = ["tensorflow"] -files = [ - 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&& /root/.local/bin/pdm lock -G :all -v\"" - -[tool.pdm.dev-dependencies] +[dependency-groups] dev = [ "typing-extensions", "jupyter>=1.0.0", @@ -167,7 +149,7 @@ dependencies = [ "chardet", # text metadata "jinja2>=3", # scan template "requests-toolbelt>=0.9.1", - "setuptools", # used for pkg_resources + "setuptools<70", # used for pkg_resources, <70 to ensure pkg_resources is available "typing_extensions", # used in registry/decorators, for python <3.10 "pyyaml", "packaging", # used in settings @@ -188,7 +170,7 @@ llm = [ "bokeh>=3.3.4, <3.5", # Bokeh >= 3.6 cause issue with rendering plots when saving to html file "umap-learn>=0.5.5", "scikit-learn>=1.3.2", - "litellm<1.66.0", + "litellm>=1.71.1,<2", "groq>=0.10.0", ] diff --git a/tests/llm/test_llm_client.py b/tests/llm/test_llm_client.py index 04f2521e3f..9e99cda840 100644 --- a/tests/llm/test_llm_client.py +++ b/tests/llm/test_llm_client.py @@ -127,6 +127,74 @@ def completion(self, model: str, messages: list, api_key: str, **kwargs) -> lite assert f"Mock response - {message}" == response.content +@pytest.mark.skipif(not PYDANTIC_V2, reason="LiteLLM raise an error with pydantic < 2") +def test_litellm_client_custom_model_with_embeddings(): + import litellm + + from giskard.llm import get_default_client, set_llm_model + from giskard.llm.client import ChatMessage + from giskard.llm.embeddings import get_default_embedding, set_embedding_model + + class MockLLMWithEmbeddings(litellm.CustomLLM): + def completion(self, model: str, messages: list, api_key: str, **kwargs) -> litellm.ModelResponse: + assert api_key == API_KEY, "Completion params are not passed properly" + + return litellm.ModelResponse( + choices=[ + litellm.Choices( + model=model, + message=litellm.Message( + role="assistant", content=f"Mock response - {messages[-1].get('content')}" + ), + ) + ] + ) + + def embedding(self, model: str, input: list, api_key: str, **kwargs) -> litellm.EmbeddingResponse: + assert api_key == API_KEY, "Embedding params are not passed properly" + + embeddings_data = [] + for idx, _ in enumerate(input): + embedding_vector = [float(idx + i) for i in range(10)] + embeddings_data.append({"embedding": embedding_vector, "index": idx}) + + return litellm.EmbeddingResponse( + model=model, + data=embeddings_data, + object="list", + ) + + litellm.custom_provider_map = litellm.custom_provider_map + [ + {"provider": "mock-embed", "custom_handler": MockLLMWithEmbeddings()} + ] + + set_llm_model("mock-embed/faux-bot", api_key=API_KEY) + set_embedding_model("mock-embed/faux-bot", api_key=API_KEY) + + llm_client = get_default_client() + cfg = llm_client.get_config() + assert cfg == { + "client_type": "LiteLLMClient", + "model": "mock-embed/faux-bot", + "disable_structured_output": False, + "completion_params": {"api_key": API_KEY}, + } + + message = "Mock input" + response = llm_client.complete([ChatMessage(role="user", content=message)]) + assert f"Mock response - {message}" == response.content + + embedding = get_default_embedding() + assert embedding.model == "mock-embed/faux-bot" + + test_texts = ["Hello", "World"] + embeddings = embedding.embed(test_texts) + + assert embeddings.shape == (2, 10) + assert embeddings[0][0] == 0.0 + assert embeddings[1][0] == 1.0 + + @pytest.mark.skipif(not PYDANTIC_V2, reason="Mistral raise an error with pydantic < 2") def test_mistral_client(): from mistralai.models import ChatCompletionChoice, ChatCompletionResponse, UsageInfo diff --git a/tests/models/huggingface/test_sequence_classification_pytorch.py b/tests/models/huggingface/test_sequence_classification_pytorch.py index bc1da339c2..a39cd2a2bf 100644 --- a/tests/models/huggingface/test_sequence_classification_pytorch.py +++ b/tests/models/huggingface/test_sequence_classification_pytorch.py @@ -9,14 +9,12 @@ @pytest.mark.memory_expensive def test_sequence_classification_distilbert_base_uncased_pytorch(): - tokenizer_distilbert_base_uncased = AutoTokenizer.from_pretrained("stevhliu/my_awesome_model") + model_name = "distilbert/distilbert-base-uncased-finetuned-sst-2-english" + tokenizer_distilbert_base_uncased = AutoTokenizer.from_pretrained(model_name) - id2label = {0: "NEGATIVE", 1: "POSITIVE"} label2id = {"NEGATIVE": 0, "POSITIVE": 1} - model_distilbert_base_uncased = AutoModelForSequenceClassification.from_pretrained( - "stevhliu/my_awesome_model", num_labels=2, id2label=id2label, label2id=label2id - ) + model_distilbert_base_uncased = AutoModelForSequenceClassification.from_pretrained(model_name) text = "This was a masterpiece. Not completely faithful to the books, but enthralling from beginning to end. Might be my favorite of the three." @@ -31,7 +29,7 @@ def my_preproccessing_function(df): return tokenizer_distilbert_base_uncased(list(df["text"]), return_tensors="pt") my_model = HuggingFaceModel( - name="stevhliu/my_awesome_model", + name=model_name, model=model_distilbert_base_uncased, feature_names=feature_names, model_type="classification", diff --git a/tests/models/huggingface/test_sequence_classification_pytorch_pipeline.py b/tests/models/huggingface/test_sequence_classification_pytorch_pipeline.py index 6922075cc8..17c3268ad0 100644 --- a/tests/models/huggingface/test_sequence_classification_pytorch_pipeline.py +++ b/tests/models/huggingface/test_sequence_classification_pytorch_pipeline.py @@ -9,17 +9,16 @@ @pytest.mark.memory_expensive def test_sequence_classification_distilbert_base_uncased_pytorch_pipeline(): + model_name = "distilbert/distilbert-base-uncased-finetuned-sst-2-english" text = "This was a masterpiece. Not completely faithful to the books, but enthralling from beginning to end. Might be my favorite of the three." - my_classifier = pipeline(task="sentiment-analysis", model="stevhliu/my_awesome_model") + my_classifier = pipeline(task="sentiment-analysis", model=model_name) - # The labels do not seem to correctly configured for "stevhliu/my_awesome_model" so we're using here the default - # labels provided by pipeline - label2id = {"LABEL_0": 0, "LABEL_1": 1} + label2id = {"NEGATIVE": 0, "POSITIVE": 1} raw_data = { "text": text, - "label": "LABEL_1", + "label": "POSITIVE", } test_df = pd.DataFrame(raw_data, columns=["text", "label"], index=[0]) @@ -29,7 +28,7 @@ def my_preproccessing_function(df): return df["text"].tolist() my_model = HuggingFaceModel( - name="stevhliu/my_awesome_model", + name=model_name, model=my_classifier, feature_names=feature_names, model_type="classification", @@ -42,11 +41,10 @@ def my_preproccessing_function(df): predictions = my_model.predict(my_test_dataset).prediction assert list(my_test_dataset.df["label"]) == list(predictions) - # Try with multiple samples - text2 = "Give me a label 0!" + text2 = "This movie was terrible and boring." raw_data = { "text": [text, text2, text], - "label": ["LABEL_1", "LABEL_0", "LABEL_1"], + "label": ["POSITIVE", "NEGATIVE", "POSITIVE"], } test_df = pd.DataFrame(raw_data, columns=["text", "label"]) my_test_dataset = Dataset(test_df, name="test dataset", target="label") diff --git a/tests/models/huggingface/test_sequence_classification_tensorflow.py b/tests/models/huggingface/test_sequence_classification_tensorflow.py index 7e72a67a7b..26ade10ac1 100644 --- a/tests/models/huggingface/test_sequence_classification_tensorflow.py +++ b/tests/models/huggingface/test_sequence_classification_tensorflow.py @@ -11,14 +11,12 @@ @pytest.mark.memory_expensive def test_sequence_classification_distilbert_base_uncased_tensorflow(): - tokenizer_distilbert_base_uncased = AutoTokenizer.from_pretrained("stevhliu/my_awesome_model") + model_name = "distilbert/distilbert-base-uncased-finetuned-sst-2-english" + tokenizer_distilbert_base_uncased = AutoTokenizer.from_pretrained(model_name) - id2label = {0: "NEGATIVE", 1: "POSITIVE"} label2id = {"NEGATIVE": 0, "POSITIVE": 1} - model_distilbert_base_uncased = TFAutoModelForSequenceClassification.from_pretrained( - "stevhliu/my_awesome_model", num_labels=2, id2label=id2label, label2id=label2id - ) + model_distilbert_base_uncased = TFAutoModelForSequenceClassification.from_pretrained(model_name) text = "This was a masterpiece. Not completely faithful to the books, but enthralling from beginning to end. Might be my favorite of the three." @@ -33,7 +31,7 @@ def my_preproccessing_function(df): return tokenizer_distilbert_base_uncased(list(df["text"]), return_tensors="tf") my_model = HuggingFaceModel( - name="stevhliu/my_awesome_model", + name=model_name, model=model_distilbert_base_uncased, feature_names=feature_names, model_type="classification", diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000000..5daa34c5e1 --- /dev/null +++ b/uv.lock @@ -0,0 +1,11109 @@ +version = 1 +revision = 3 +requires-python = ">=3.9, <3.13" +resolution-markers = [ + "python_full_version >= '3.12.4' and sys_platform == 'win32'", + "python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform == 'win32'", + "python_full_version >= '3.12.4' and sys_platform == 'emscripten'", + "python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform == 'emscripten'", + "python_full_version >= '3.12.4' and sys_platform == 'linux'", + "python_full_version >= '3.12' and 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