first implementation

.github/workflows/linting.yml

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+name: Linting
+
+on: [push, pull_request]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: 3.12
+
+    - name: Install Poetry
+      run: pip install poetry
+
+    - name: Install dependencies
+      run: poetry install --with dev
+
+    - name: Run Ruff
+      run: poetry run ruff check magellan

.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:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# 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
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   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
+poetry.lock
+src/poetry.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# 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/
+
+# Macos
+.DS_Store
+
+.ruff_cache
+
+# Notebooks
+*.ipynb

clientai/__init__.py

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+from ._constants import OLLAMA_INSTALLED, OPENAI_INSTALLED, REPLICATE_INSTALLED
+from .client_ai import ClientAI
+
+__all__ = [
+    "ClientAI",
+    "OPENAI_INSTALLED",
+    "REPLICATE_INSTALLED",
+    "OLLAMA_INSTALLED",
+]

clientai/_common_types.py

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+from __future__ import annotations
+
+from collections.abc import Iterator
+from typing import Any, Dict, TypeVar, Union
+
+JsonDict = Dict[str, Any]
+Message = Dict[str, str]
+
+T = TypeVar("T", covariant=True)
+S = TypeVar("S", covariant=True)
+R = TypeVar("R", covariant=True)
+
+GenericResponse = Union[R, T, Iterator[Union[R, S]]]

clientai/_constants.py

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+from importlib.util import find_spec
+
+OPENAI_INSTALLED = find_spec("openai") is not None
+REPLICATE_INSTALLED = find_spec("replicate") is not None
+OLLAMA_INSTALLED = find_spec("ollama") is not None

clientai/_typing.py

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+from typing import Any, Generic, List, Protocol, TypeVar, Union
+
+from ._common_types import GenericResponse, Message, R, S, T
+from .ollama._typing import (
+    OllamaChatResponse,
+    OllamaResponse,
+    OllamaStreamResponse,
+)
+from .openai._typing import OpenAIResponse, OpenAIStreamResponse
+from .replicate._typing import ReplicateResponse, ReplicateStreamResponse
+
+ProviderResponse = Union[
+    OpenAIResponse, ReplicateResponse, OllamaResponse, OllamaChatResponse
+]
+
+ProviderStreamResponse = Union[
+    OpenAIStreamResponse, ReplicateStreamResponse, OllamaStreamResponse
+]
+
+
+class AIProviderProtocol(Protocol, Generic[R, T, S]):
+    def generate_text(
+        self,
+        prompt: str,
+        model: str,
+        return_full_response: bool = False,
+        stream: bool = False,
+        **kwargs: Any,
+    ) -> GenericResponse[R, T, S]:
+        ...
+
+    def chat(
+        self,
+        messages: List[Message],
+        model: str,
+        return_full_response: bool = False,
+        stream: bool = False,
+        **kwargs: Any,
+    ) -> GenericResponse[R, T, S]:
+        ...
+
+
+P = TypeVar("P", bound=AIProviderProtocol)
+
+AIGenericResponse = GenericResponse[
+    str, ProviderResponse, ProviderStreamResponse
+]

clientai/ai_provider.py

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+from abc import ABC, abstractmethod
+from typing import List
+
+from ._common_types import GenericResponse, Message
+
+
+class AIProvider(ABC):
+    """
+    Abstract base class for AI providers.
+    """
+
+    @abstractmethod
+    def generate_text(
+        self,
+        prompt: str,
+        model: str,
+        return_full_response: bool = False,
+        stream: bool = False,
+        **kwargs,
+    ) -> GenericResponse:
+        """
+        Generate text based on a given prompt.
+
+        Args:
+            prompt: The input prompt for text generation.
+            model: The name or identifier of the AI model to use.
+            return_full_response: If True, return the full response object
+                                  instead of just the generated text.
+            stream: If True, return an iterator for streaming responses.
+            **kwargs: Additional keyword arguments specific to
+                      the provider's API.
+
+        Returns:
+            GenericResponse:
+                The generated text response, full response object,
+                or an iterator for streaming responses.
+        """
+        pass
+
+    @abstractmethod
+    def chat(
+        self,
+        messages: List[Message],
+        model: str,
+        return_full_response: bool = False,
+        stream: bool = False,
+        **kwargs,
+    ) -> GenericResponse:
+        """
+        Engage in a chat conversation.
+
+        Args:
+            messages: A list of message dictionaries, each containing
+                      'role' and 'content'.
+            model: The name or identifier of the AI model to use.
+            return_full_response: If True, return the full response object
+                                  instead of just the chat content.
+            stream: If True, return an iterator for streaming responses.
+            **kwargs: Additional keyword arguments specific to
+                      the provider's API.
+
+        Returns:
+            GenericResponse:
+                The chat response, either as a string, a dictionary,
+                or an iterator for streaming responses.
+        """
+        pass