chore: Update dependencies and configurations

.github/workflows/pytest.yml

@@ -0,0 +1,29 @@
+name: Python Tests
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.10', '3.11', '3.12']
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pytest
+        pip install -r requirements.txt
+    - name: Run tests
+      run: |
+        pytest

.vscode/settings.json

@@ -2,5 +2,6 @@
     "python.autoComplete.extraPaths": ["./ava_mosaic_ai"],
     "python.analysis.extraPaths": ["./ava_mosaic_ai"],
     "python.defaultInterpreterPath": "./ava_mosaic_ai/venv/bin/python",
-    "python.envFile": "${workspaceFolder}/ava_mosaic_ai/.env"
+    "python.envFile": "${workspaceFolder}/ava_mosaic_ai/.env",
+    "search.useIgnoreFiles": false
 }

ava_mosaic_ai/config/settings.py

@@ -1,7 +1,6 @@
 from typing import Optional, Dict, Any
 from enum import Enum
 from pydantic import BaseModel, Field
-from pydantic_settings import BaseSettings, SettingsConfigDict
 from functools import lru_cache
 from dotenv import load_dotenv
 import os
@@ -17,9 +16,9 @@ class LLMProvider(str, Enum):
 
 
 class LLMProviderSettings(BaseModel):
-    temperature: float = Field(default=0.0)
+    temperature: float = 0.0
     max_tokens: Optional[int] = None
-    max_retries: int = Field(default=3)
+    max_retries: int = 3
 
 
 class OpenAISettings(LLMProviderSettings):
@@ -46,12 +45,10 @@ class AzureOpenAISettings(LLMProviderSettings):
     azure_endpoint: str
 
 
-class Settings(BaseSettings):
+class Settings(BaseModel):
     app_name: str = Field(default="GenAI Project Template")
     _providers: Dict[LLMProvider, Any] = {}
 
-    model_config = SettingsConfigDict(env_file=".env", extra="ignore")
-
     def get_provider_settings(self, provider: LLMProvider) -> Any:
         if provider not in self._providers:
             if provider == LLMProvider.OPENAI:

ava_mosaic_ai/llm_factory.py

@@ -1,6 +1,5 @@
 
 from typing import Any, Dict, List, Type, Union
-
 import instructor
 from anthropic import Anthropic
 from openai import OpenAI, AzureOpenAI
@@ -16,7 +15,6 @@ def __init__(self, provider: Union[LLMProvider, str]) -> None:
             provider = get_llm_provider(provider)
 
         self.provider = provider
-        print(f"Provider: {self.provider}")
         self.settings = get_settings().get_provider_settings(provider)
         self.client = self._initialize_client()
 

playground.py

@@ -1,6 +1,9 @@
 from pydantic import Field, BaseModel
 import ava_mosaic_ai
 
+import warnings
+warnings.filterwarnings('error', category=UserWarning)
+
 class CompletionModel(BaseModel):
     response: str = Field(description="Your response to the user.")
     reasoning: str = Field(description="Explain your reasoning for the response.")

pyproject.toml

@@ -14,7 +14,6 @@ instructor = "^1.3.7"
 pydantic = "^2.8.2"
 anthropic = "^0.34.0"
 openai = "^1.41.0"
-pydantic-settings = "^2.4.0"
 python-dotenv = "^1.0.1"
 
 

tests/conftest.py

@@ -0,0 +1,9 @@
+import sys
+import os
+from pathlib import Path
+
+# Get the parent directory of the directory containing this file
+parent_dir = Path(__file__).resolve().parent.parent
+
+# Add the parent directory to sys.path
+sys.path.insert(0, str(parent_dir))

tests/test_llm_factory.py

@@ -0,0 +1,154 @@
+import pytest
+from unittest.mock import Mock, patch
+from typing import Any, Dict, List
+from pydantic import BaseModel, ConfigDict, Field
+
+from ava_mosaic_ai.config.settings import LLMProvider, Settings
+from ava_mosaic_ai import (
+    LLMFactory
+) 
+
+class CompletionModel(BaseModel):
+    response: str = Field(description="Your response to the user.")
+    reasoning: str = Field(description="Explain your reasoning for the response.")
+
+    model_config = ConfigDict(populate_by_name=True)
+
+
+@pytest.fixture
+def mock_settings():
+    settings = Mock(spec=Settings)
+    settings.get_provider_settings.return_value = Mock(
+        api_key="test_key",
+        default_model="test_model",
+        temperature=0.7,
+        max_retries=3,
+        max_tokens=100,
+    )
+    return settings
+
+@pytest.fixture
+def mock_get_settings(mock_settings):
+    with patch(
+        "ava_mosaic_ai.llm_factory.get_settings", return_value=mock_settings
+    ) as mock:
+        yield mock
+
+
+
+@pytest.fixture
+def mock_instructor():
+    with patch(
+        "ava_mosaic_ai.llm_factory.instructor"
+    ) as mock: 
+        yield mock
+
+
+@pytest.fixture
+def llm_factory(mock_get_settings, mock_instructor):
+    return LLMFactory(LLMProvider.OPENAI)
+
+def test_initialization(llm_factory, mock_get_settings):
+    assert llm_factory.provider == LLMProvider.OPENAI
+    assert llm_factory.settings is not None
+    assert llm_factory.client is not None
+    mock_get_settings.assert_called_once()
+
+
+def test_initialize_client_openai(mock_instructor, mock_get_settings):
+    factory = LLMFactory(LLMProvider.OPENAI)
+    mock_instructor.from_openai.assert_called_once()
+
+
+def test_initialize_client_anthropic(mock_instructor, mock_get_settings):
+    factory = LLMFactory(LLMProvider.ANTHROPIC)
+    mock_instructor.from_anthropic.assert_called_once()
+
+
+def test_initialize_client_llama(mock_instructor):
+    settings = Mock(spec=Settings)
+    settings.get_provider_settings.return_value = Mock(
+        api_key="test_key",
+        default_model="test_model",
+        base_url="http://localhost:11434/v1",
+        temperature=0.7,
+        max_retries=3,
+        max_tokens=100,
+    )
+    with patch("ava_mosaic_ai.llm_factory.get_settings", return_value=settings) as mock:
+        factory = LLMFactory(LLMProvider.LLAMA)
+    mock_instructor.from_openai.assert_called_once()
+
+
+def test_initialize_client_azure_openai(mock_instructor, mock_get_settings):
+    factory = LLMFactory(LLMProvider.AZURE_OPENAI)
+    mock_instructor.from_openai.assert_called_once()
+
+
+def test_initialize_client_unsupported():
+    with pytest.raises(AttributeError, match="'UNSUPPORTED_PROVIDER' is not supported"):
+        LLMFactory("UNSUPPORTED_PROVIDER")
+
+def test_create_completion(llm_factory):
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Hello, how are you?"},
+    ]
+
+    mock_completion = Mock(spec=CompletionModel)
+    mock_completion.response = "I'm doing well, thank you!"
+    mock_completion.reasoning = "As an AI assistant, I'm functioning properly."
+
+    llm_factory.client.chat.completions.create.return_value = mock_completion
+
+    result = llm_factory.create_completion(
+        response_model=CompletionModel,
+        messages=messages,
+    )
+
+    assert isinstance(result, CompletionModel)
+    assert result.response == "I'm doing well, thank you!"
+    assert result.reasoning == "As an AI assistant, I'm functioning properly."
+
+    llm_factory.client.chat.completions.create.assert_called_once_with(
+        model=llm_factory.settings.default_model,
+        temperature=llm_factory.settings.temperature,
+        max_retries=llm_factory.settings.max_retries,
+        max_tokens=llm_factory.settings.max_tokens,
+        response_model=CompletionModel,
+        messages=messages,
+    )
+
+
+def test_create_completion_with_custom_params(llm_factory):
+    messages = [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Hello, how are you?"},
+    ]
+
+    mock_completion = Mock(spec=CompletionModel)
+    llm_factory.client.chat.completions.create.return_value = mock_completion
+
+    custom_model = "gpt-4"
+    custom_temperature = 0.9
+    custom_max_retries = 5
+    custom_max_tokens = 200
+
+    llm_factory.create_completion(
+        response_model=CompletionModel,
+        messages=messages,
+        model=custom_model,
+        temperature=custom_temperature,
+        max_retries=custom_max_retries,
+        max_tokens=custom_max_tokens,
+    )
+
+    llm_factory.client.chat.completions.create.assert_called_once_with(
+        model=custom_model,
+        temperature=custom_temperature,
+        max_retries=custom_max_retries,
+        max_tokens=custom_max_tokens,
+        response_model=CompletionModel,
+        messages=messages,
+    )
+