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Refactoring client and providers. (#27)
Added Azure support & refactored code. Refactoring includes - - ProviderFactory - Lazily import the provider based on config passed to Client. Will need to port the older provider files to the new format. Till then keeping the older provider interface related tests. Co-authored-by: rohit-rptless <[email protected]>
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.idea/ | ||
.vscode/ | ||
__pycache__/ | ||
env/ |
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from .client import Client | ||
from .provider import ProviderNames |
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from .provider import ProviderFactory, ProviderNames | ||
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class Client: | ||
def __init__(self, provider_configs: dict = {}): | ||
""" | ||
Initialize the client with provider configurations. | ||
Use the ProviderFactory to create provider instances. | ||
Args: | ||
provider_configs (dict): A dictionary containing provider configurations. | ||
Each key should be a ProviderNames enum or its string representation, | ||
and the value should be a dictionary of configuration options for that provider. | ||
For example: | ||
{ | ||
ProviderNames.OPENAI: {"api_key": "your_openai_api_key"}, | ||
"aws-bedrock": { | ||
"aws_access_key": "your_aws_access_key", | ||
"aws_secret_key": "your_aws_secret_key", | ||
"aws_region": "us-west-2" | ||
} | ||
} | ||
""" | ||
self.providers = {} | ||
self.provider_configs = provider_configs | ||
self._chat = None | ||
self._initialize_providers() | ||
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def _initialize_providers(self): | ||
"""Helper method to initialize or update providers.""" | ||
for provider_key, config in self.provider_configs.items(): | ||
provider_key = self._validate_provider_key(provider_key) | ||
self.providers[provider_key.value] = ProviderFactory.create_provider( | ||
provider_key, config | ||
) | ||
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def _validate_provider_key(self, provider_key): | ||
""" | ||
Validate if the provider key is part of ProviderNames enum. | ||
Allow strings as well and convert them to ProviderNames. | ||
""" | ||
if isinstance(provider_key, str): | ||
if provider_key not in ProviderNames._value2member_map_: | ||
raise ValueError(f"Provider {provider_key} is not a valid provider") | ||
return ProviderNames(provider_key) | ||
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if isinstance(provider_key, ProviderNames): | ||
return provider_key | ||
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raise ValueError( | ||
f"Provider {provider_key} should either be a string or enum ProviderNames" | ||
) | ||
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def configure(self, provider_configs: dict = None): | ||
""" | ||
Configure the client with provider configurations. | ||
""" | ||
if provider_configs is None: | ||
return | ||
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self.provider_configs.update(provider_configs) | ||
self._initialize_providers() # NOTE: This will override existing provider instances. | ||
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@property | ||
def chat(self): | ||
"""Return the chat API interface.""" | ||
if not self._chat: | ||
self._chat = Chat(self) | ||
return self._chat | ||
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class Chat: | ||
def __init__(self, client: "Client"): | ||
self.client = client | ||
self._completions = Completions(self.client) | ||
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@property | ||
def completions(self): | ||
"""Return the completions interface.""" | ||
return self._completions | ||
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class Completions: | ||
def __init__(self, client: "Client"): | ||
self.client = client | ||
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def create(self, model: str, messages: list, **kwargs): | ||
""" | ||
Create chat completion based on the model, messages, and any extra arguments. | ||
""" | ||
# Check that correct format is used | ||
if ":" not in model: | ||
raise ValueError( | ||
f"Invalid model format. Expected 'provider:model', got '{model}'" | ||
) | ||
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# Extract the provider key from the model identifier, e.g., "aws-bedrock:model-name" | ||
provider_key, model_name = model.split(":", 1) | ||
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if provider_key not in ProviderNames._value2member_map_: | ||
# If the provider key does not match, give a clearer message to guide the user | ||
valid_providers = ", ".join([p.value for p in ProviderNames]) | ||
raise ValueError( | ||
f"Invalid provider key '{provider_key}'. Expected one of: {valid_providers}. " | ||
"Make sure the model string is formatted correctly as 'provider:model'." | ||
) | ||
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if provider_key not in self.client.providers: | ||
config = {} | ||
if provider_key in self.client.provider_configs: | ||
config = self.client.provider_configs[provider_key] | ||
self.client.providers[provider_key] = ProviderFactory.create_provider( | ||
ProviderNames(provider_key), config | ||
) | ||
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provider = self.client.providers.get(provider_key) | ||
if not provider: | ||
raise ValueError(f"Could not load provider for {provider_key}.") | ||
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# Delegate the chat completion to the correct provider's implementation | ||
# Any additional arguments will be passed to the provider's implementation. | ||
# Eg: max_tokens, temperature, etc. | ||
return provider.chat_completions_create(model_name, messages, **kwargs) |
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"""Provides the ProviderInterface for defining the interface that all FM providers must implement.""" | ||
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from .provider_interface import ProviderInterface | ||
from .chat_completion_response import ChatCompletionResponse |
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from abc import ABC, abstractmethod | ||
from enum import Enum | ||
import importlib | ||
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class LLMError(Exception): | ||
"""Custom exception for LLM errors.""" | ||
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def __init__(self, message): | ||
super().__init__(message) | ||
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class Provider(ABC): | ||
@abstractmethod | ||
def chat_completions_create(self, model, messages): | ||
"""Abstract method for chat completion calls, to be implemented by each provider.""" | ||
pass | ||
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class ProviderNames(str, Enum): | ||
OPENAI = "openai" | ||
AWS_BEDROCK = "aws-bedrock" | ||
ANTHROPIC = "anthropic" | ||
AZURE = "azure" | ||
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class ProviderFactory: | ||
"""Factory to register and create provider instances based on keys.""" | ||
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_provider_info = { | ||
ProviderNames.OPENAI: ("aisuite.providers.openai_provider", "OpenAIProvider"), | ||
ProviderNames.AWS_BEDROCK: ( | ||
"aisuite.providers.aws_bedrock_provider", | ||
"AWSBedrockProvider", | ||
), | ||
ProviderNames.ANTHROPIC: ( | ||
"aisuite.providers.anthropic_provider", | ||
"AnthropicProvider", | ||
), | ||
ProviderNames.AZURE: ("aisuite.providers.azure_provider", "AzureProvider"), | ||
} | ||
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@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" | ||
) | ||
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module_name, class_name = cls._get_provider_info(provider_key) | ||
if not module_name: | ||
raise ValueError(f"Provider {provider_key.value} is not supported") | ||
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# 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)}") | ||
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# Instantiate the provider class | ||
provider_class = getattr(module, class_name) | ||
return provider_class(**config) | ||
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@classmethod | ||
def _get_provider_info(cls, provider_key): | ||
"""Return the module name and class name for a given provider key.""" | ||
return cls._provider_info.get(provider_key, (None, None)) |
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import anthropic | ||
from aisuite.provider import Provider | ||
from aisuite.framework import ChatCompletionResponse | ||
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# Define a constant for the default max_tokens value | ||
DEFAULT_MAX_TOKENS = 4096 | ||
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class AnthropicProvider(Provider): | ||
def __init__(self, **config): | ||
""" | ||
Initialize the Anthropic provider with the given configuration. | ||
Pass the entire configuration dictionary to the Anthropic client constructor. | ||
""" | ||
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self.client = anthropic.Anthropic(**config) | ||
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def chat_completions_create(self, model, messages, **kwargs): | ||
# Check if the fist message is a system message | ||
if messages[0]["role"] == "system": | ||
system_message = messages[0]["content"] | ||
messages = messages[1:] | ||
else: | ||
system_message = None | ||
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# kwargs.setdefault('max_tokens', DEFAULT_MAX_TOKENS) | ||
if "max_tokens" not in kwargs: | ||
kwargs["max_tokens"] = DEFAULT_MAX_TOKENS | ||
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return self.normalize_response( | ||
self.client.messages.create( | ||
model=model, system=system_message, messages=messages, **kwargs | ||
) | ||
) | ||
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def normalize_response(self, response): | ||
"""Normalize the response from the Anthropic API to match OpenAI's response format.""" | ||
normalized_response = ChatCompletionResponse() | ||
normalized_response.choices[0].message.content = response.content[0].text | ||
return normalized_response |
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