Refactoring the codebase.

This change is a WorkInProgress.

An alternate way of writing the unified llm library.
- ProviderFactory provides a specific provider impl.
- Lazily import the provider based on config passed to Client.
- Use Enums to restrict the supported providers, but not
  restricting the model names supported by the provider.
TODO:
- Support passing extra_parameters to model in create()
- Run linter on the whole code for style conformance
- Actual implementation & test case for each provider

.gitignore

@@ -1,3 +1,4 @@
 .idea/
 .vscode/
 __pycache__/
+env/

aisuitealt/client.py

@@ -0,0 +1,56 @@
+from provider import ProviderFactory, ProviderNames
+
+
+class Client:
+    def __init__(self, provider_configs: dict):
+        """
+        Initialize the client with provider configurations. 
+        Use the ProviderFactory to create provider instances.
+        """
+        self.providers = {}
+        for provider_key, config in provider_configs.items():
+            # Check if the provider key is a valid ProviderNames enum
+            if not isinstance(provider_key, ProviderNames):
+                raise ValueError(f"Provider {provider_key} is not a valid ProviderNames enum")
+            # Store the value of the enum in the providers dictionary
+            self.providers[provider_key.value] = ProviderFactory.create_provider(provider_key, config)
+
+        self._chat = None
+
+    @property
+    def chat(self):
+        """Return the chat API interface."""
+        if not self._chat:
+            self._chat = Chat(self)
+        return self._chat
+
+
+class Chat:
+    def __init__(self, client: 'Client'):
+        self.client = client
+
+    @property
+    def completions(self):
+        """Return the completions interface."""
+        return Completions(self.client)
+
+
+class Completions:
+    def __init__(self, client: 'Client'):
+        self.client = client
+
+    def create(self, model: str, messages: list):
+        """Create chat completion based on the model."""
+        # Extract the provider key from the model identifier, e.g., "aws-bedrock:model-name"
+        provider_key, model_name = model.split(":", 1)
+
+        # Use the correct provider instance created by the factory
+        provider = self.client.providers.get(provider_key)
+        if not provider:
+            # Add the providers to the ValueError
+            raise ValueError(f"Provider {provider_key} is not present in the client. Here are the providers: {self.client.providers}")
+
+        # Delegate the chat completion to the correct provider's implementation
+        return provider.chat_completions_create(model_name, messages)
+
+

aisuitealt/provider.py

@@ -0,0 +1,57 @@
+from abc import ABC, abstractmethod
+from enum import Enum
+import importlib
+
+class LLMError(Exception):
+    """Custom exception for LLM errors."""
+    def __init__(self, message):
+        super().__init__(message)
+
+
+class Provider(ABC):
+    @abstractmethod
+    def chat_completions_create(self, model, messages):
+        """Abstract method for chat completion calls, to be implemented by each provider."""
+        pass
+
+
+class ProviderNames(Enum):
+    OPENAI = 'openai'
+    AWS_BEDROCK = 'aws-bedrock'
+
+
+class ProviderFactory:
+    """Factory to register and create provider instances based on keys."""
+
+    _provider_modules = {
+        ProviderNames.OPENAI: 'providers.openai_provider',
+        ProviderNames.AWS_BEDROCK: 'providers.aws_bedrock_provider',
+    }
+
+    @classmethod
+    def create_provider(cls, provider_key, config):
+        """Dynamically import and create an instance of a provider based on the provider key."""
+        if not isinstance(provider_key, ProviderNames):
+            raise ValueError(f"Provider {provider_key} is not a valid ProviderNames enum")
+
+        module_name = cls._provider_modules.get(provider_key)
+        if not module_name:
+            raise ValueError(f"Provider {provider_key.value} is not supported")
+
+        # Lazily load the module
+        try:
+            module = importlib.import_module(module_name)
+        except ImportError as e:
+            raise ImportError(f"Could not import module {module_name}: {str(e)}")
+
+        # Instantiate the provider class
+        provider_class = getattr(module, cls._get_provider_class_name(provider_key))
+        return provider_class(**config)
+
+    @staticmethod
+    def _get_provider_class_name(provider_key):
+        """Map provider key to the corresponding class name in the module."""
+        return {
+            ProviderNames.OPENAI: 'OpenAIProvider',
+            ProviderNames.AWS_BEDROCK: 'AWSBedrockProvider',
+        }[provider_key]

aisuitealt/providers/__init__.py

@@ -0,0 +1 @@
+# Empty __init__.py

aisuitealt/providers/aws_bedrock_provider.py

@@ -0,0 +1,22 @@
+from anthropic import AnthropicBedrock
+from provider import Provider, LLMError
+
+class AWSBedrockProvider(Provider):
+    def __init__(self, access_key, secret_key, session_token, region):
+        self.client = AnthropicBedrock(
+            aws_access_key=access_key,
+            aws_secret_key=secret_key,
+            aws_session_token=session_token,
+            aws_region=region
+        )
+
+    def chat_completions_create(self, model, messages):
+        try:
+            response = self.client.messages.create(
+                model=model,
+                max_tokens=256,
+                messages=messages
+            )
+            return response['choices'][0]['message']['content']
+        except Exception as e:
+            raise LLMError(f"AWS Bedrock API error: {str(e)}")

aisuitealt/providers/openai_provider.py

@@ -0,0 +1,16 @@
+import openai
+from provider import Provider, LLMError
+
+class OpenAIProvider(Provider):
+    def __init__(self, api_key):
+        openai.api_key = api_key
+
+    def chat_completions_create(self, model, messages):
+        try:
+            response = openai.ChatCompletion.create(
+                model=model,
+                messages=messages
+            )
+            return response['choices'][0]['message']['content']
+        except Exception as e:
+            raise LLMError(f"OpenAI API error: {str(e)}")

aisuitealt/tests/test_client.py

@@ -0,0 +1,47 @@
+import unittest
+from unittest.mock import patch
+from client import Client
+from provider import ProviderNames
+
+class TestClient(unittest.TestCase):
+
+    @patch('providers.openai_provider.OpenAIProvider.chat_completions_create')
+    @patch('providers.aws_bedrock_provider.AWSBedrockProvider.chat_completions_create')
+    def test_client_chat_completions(self, mock_bedrock, mock_openai):
+        # Mock responses from providers
+        mock_openai.return_value = "OpenAI Response"
+        mock_bedrock.return_value = "AWS Bedrock Response"
+
+        # Provider configurations
+        provider_configs = {
+            ProviderNames.OPENAI: {
+                'api_key': 'test_openai_api_key'
+            },
+            ProviderNames.AWS_BEDROCK: {
+                'access_key': 'test_aws_access_key', 
+                'secret_key': 'test_aws_secret_key',
+                'session_token': 'test_aws_session_token',
+                'region': 'us-west-2'
+            }
+        }
+
+        # Initialize the client
+        client = Client(provider_configs)
+
+        # Test OpenAI model
+        openai_response = client.chat.completions.create(ProviderNames.OPENAI.value + ":" + "gpt-4o", [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "Who won the world series in 2020?"}
+        ])
+        self.assertEqual(openai_response, "OpenAI Response")
+        mock_openai.assert_called_once()
+
+        # Test AWS Bedrock model
+        bedrock_response = client.chat.completions.create(ProviderNames.AWS_BEDROCK.value + ":" + "claude-v3", [
+            {"role": "user", "content": "Hello, world!"}
+        ])
+        self.assertEqual(bedrock_response, "AWS Bedrock Response")
+        mock_bedrock.assert_called_once()
+
+if __name__ == '__main__':
+    unittest.main()