Initial commit

Author: juandspy

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
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+# Sphinx documentation
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+# PyBuilder
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+target/
+
+# Jupyter Notebook
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+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
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+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   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
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
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+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
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+ENV/
+env.bak/
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+/site
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+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

README.md

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+# Assert LLM
+
+A tool for lazy people that doesn't want to spend time on writing tests.
+
+(Just a project that I wrote for fun)
+
+## How to run
+
+Install the required packages with `pip install .`
+
+Load any model on [LM Studio](https://lmstudio.ai) and start the "Local Inference Server".
+Assuming it's configured to expose the port `1234` on localhost, you can use this tool
+on your unit tests like this:
+
+```
+>>> from src.main import llm_assert
+>>> from src.engines.lmstudio import LMStudioEngine
+>>> engine = LMStudioEngine("http://localhost:1234/v1")
+>>> llm_assert(engine, "5", "this is a number")
+>>> llm_assert(engine, "5", "this is not a number")
+Traceback (most recent call last):
+  File "<stdin>", line 1, in <module>
+  File "/Users/jdiazsua/Documents/Projects/PoCs/assert-llm/src/main.py", line 49, in llm_assert
+    assert answer == "True", f"'{sut}' doesn't match the prompt '{prompt}'"
+           ^^^^^^^^^^^^^^^^
+AssertionError: '5' doesn't match the prompt 'this is not a number'
+```
+
+This looks like an overkill, but it can be useful for lazy checks like:
+
+```
+>>> input_text = """
+Lorem ipsum dolor sit amet, consectetur adipiscing elit.
+123 Elm Street, Springfield, IL 62704.
+Vivamus aliquet, augue id semper varius, ex tellus luctus justo, nec viverra metus lectus nec magna.
+"""
+>>> llm_assert(engine, input_text, "it contains an address")
+>>> llm_assert(engine, input_text, "it contains a telephone number")
+Traceback (most recent call last):
+  File "<stdin>", line 1, in <module>
+  File "/Users/jdiazsua/Documents/Projects/PoCs/assert-llm/src/main.py", line 49, in llm_assert
+    assert answer == "True", f"'{sut}' doesn't match the prompt '{prompt}'"
+           ^^^^^^^^^^^^^^^^
+AssertionError: '
+Lorem ipsum dolor sit amet, consectetur adipiscing elit.
+123 Elm Street, Springfield, IL 62704.
+Vivamus aliquet, augue id semper varius, ex tellus luctus justo, nec viverra metus lectus nec magna.
+' doesn't match the prompt 'it contains a telephone number'
+```
+
+## Contributing
+
+Feel free to add new engines to the [engines](src/engines/) package. The only requirement is that
+they must implement the `Engine` interface, as it will be used by the `llm_assert` function.
+
+You can also contribute by adding new functions with different `system_message` and `prompt`
+or calling different APIs.

pyproject.toml

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+[build-system]
+requires = ["setuptools>=61.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "llm-assert"
+version = "0.1.3"
+description = "Assertify using LLMs"
+authors = [{name = "Juan D.", email = "[email protected]"}]
+readme = "README.md"
+requires-python = ">=3.7.1"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: Apache Software License",
+    "Operating System :: OS Independent",
+]
+dependencies = [
+    "openai",
+    "pytest"
+]
+
+[project.urls]
+Homepage = "https://github.com/juandspy/llm-assert"
+Issues = "https://github.com/juandspy/llm-assert/issues"

src/engines/__init__.py

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+from abc import ABC, abstractmethod
+
+class Engine(ABC):
+    """Engine is an interface that must be implemented by any LLM engine."""
+    @abstractmethod
+    def ask_chat(self, system_message: str, user_message: str, temperature=0.7) -> str:
+        """Use an LLM to get a response."""

src/engines/lmstudio.py

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+"""Logic to make use of LM Studio models."""
+from openai import OpenAI
+
+
+class BaseEngine:
+    def __init__(self, base_url: str, api_key: str="not-needed"):
+        self.client = OpenAI(base_url=base_url, api_key=api_key)
+        self.model = "local-model"
+
+    def ask_chat(self, system_message: str, user_message: str, temperature=0.7) -> str:
+        completion = self.client.chat.completions.create(
+            model=self.model,
+            messages=[
+                {"role": "system", "content": system_message},
+                {"role": "user", "content": user_message}
+            ],
+            temperature=temperature,
+        )
+        return completion.choices[0].message.content
+
+class LMStudioEngine(BaseEngine):
+    pass
+
+class OpenAIEngine(BaseEngine):
+    def __init__(self, base_url: str, api_key: str):
+        if not api_key:
+            raise ValueError("API key cannot be empty")
+        super().__init__(base_url, api_key)
+
+
+if __name__ == "__main__":
+    engine = LMStudioEngine(base_url="http://localhost:1234/v1")
+    answer = engine.ask_chat(
+        system_message="Always answer in rhymes.",
+        user_message="Introduce yourself.")
+    print(answer)

src/main.py

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+"""Main functions of the package."""
+from typing import Any
+from src.engines import Engine
+
+
+class UnexpectedEngineResponseError(Exception):
+    """Raised when the LLM Engine provides an unexpected response."""
+
+# Characters we want to include on the answer
+whitelist = set('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ')
+
+def llm_assert(engine: Engine, sut: Any, prompt: str):
+    """
+    Assert, using an LLM Engine, whether an input matches a prompt.
+    
+    This function queries an LLM engine using the prompt parameter,
+    informing it that it can only respond with 'True' or 'False'.
+    It filters the engine's response, removing any characters that are not letters.
+    If the filtered response is not 'True' or 'False', it raises a ValueError.
+    Otherwise, it returns a boolean value based on the response.
+
+    Example:
+        >>> engine = LMStudioEngine("http://localhost:1234/v1")
+        >>> assert llm_assert(engine, "5", "this is a number")
+        >>> assert llm_assert(engine, "apple", "this is a number")
+        Traceback (most recent call last):
+        File "<stdin>", line 1, in <module>
+        AssertionError
+
+    Args:
+        engine (Engine): The LLM Engine to ask the question.
+        sut (Any): The item under test.
+        prompt (str): The question to ask the engine.
+        
+    Raises:
+        UnexpectedEngineResponseError: If the engine's response is not 'True' or 'False'.
+        AssertionError: If the engine's response is 'False'
+    """
+    answer = engine.ask_chat(
+        system_message="""
+        You can only answer 'True' or 'False', no matter what the input is.
+        Don't provide any explanation.
+        """,
+        user_message=f"{sut}: {prompt}")
+    answer = ''.join(filter(whitelist.__contains__, answer))
+    if answer not in ["True", "False"]:
+        raise UnexpectedEngineResponseError(
+            f"Got unexpected answer from the LLM Engine: '{answer}'.")
+    assert answer == "True", f"'{sut}' doesn't match the prompt '{prompt}'"

tests/__init__.py

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+"""Test the main functions of the package."""
+import pytest
+
+from src.main import llm_assert
+from src.engines.lmstudio import LMStudioEngine
+
+
+INPUTS= [
+    ("5", "this is a number", True),
+    ("twenty", "this is a number", True),
+    ("apple", "this is a number", False),
+    ("5", "this is not a number", False),
+    ("twenty", "this is not a number", False),
+    ("apple", "this is not a number", True)
+]
+
+class MockEngine:
+    def __init__(self, mocked_answer: str):
+        self.mocked_answer = mocked_answer
+    def ask_chat(self, system_message: str, user_message: str, temperature=0.7) -> str:
+        return self.mocked_answer
+
+@pytest.mark.parametrize("sut,prompt,expected_exception", INPUTS)
+def test_llm_assert__mock(sut, prompt, expected_exception):
+    """Test the assert function"""
+    engine = MockEngine(str(expected_exception))
+    if not expected_exception:
+        with pytest.raises(AssertionError):
+            llm_assert(engine, sut, prompt)
+    else:
+        llm_assert(engine, sut, prompt)
+
+
+@pytest.mark.parametrize("sut,prompt,expected_exception", INPUTS)
+def test_llm_assert__lmstudio(sut, prompt, expected_exception):
+    """Test the assert function"""
+    engine = LMStudioEngine("http://localhost:1234/v1")
+    if not expected_exception:
+        with pytest.raises(AssertionError):
+            llm_assert(engine, sut, prompt)
+    else:
+        llm_assert(engine, sut, prompt)