From e9d1bc50d9126d376014ba77706bb732a8d1b329 Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Wed, 21 Aug 2024 14:06:45 +0000
Subject: [PATCH 01/13] Added support for AzureAI client service

---
 .../components/model_client/azureai_client.py | 399 ++++++++++++++++++
 1 file changed, 399 insertions(+)
 create mode 100644 adalflow/adalflow/components/model_client/azureai_client.py

diff --git a/adalflow/adalflow/components/model_client/azureai_client.py b/adalflow/adalflow/components/model_client/azureai_client.py
new file mode 100644
index 00000000..226720b1
--- /dev/null
+++ b/adalflow/adalflow/components/model_client/azureai_client.py
@@ -0,0 +1,399 @@
+"""AzureOpenAI ModelClient integration."""
+
+import os
+from typing import (
+    Dict,
+    Sequence,
+    Optional,
+    List,
+    Any,
+    TypeVar,
+    Callable,
+    Generator,
+    Union,
+    Literal,
+)
+import re
+
+import logging
+import backoff
+
+# optional import
+from adalflow.utils.lazy_import import safe_import, OptionalPackages
+
+
+openai = safe_import(OptionalPackages.OPENAI.value[0], OptionalPackages.OPENAI.value[1])
+from azure.identity import DefaultAzureCredential, get_bearer_token_provider
+from azure.core.credentials import AccessToken
+from openai import AzureOpenAI, AsyncAzureOpenAI, Stream
+from openai import (
+    APITimeoutError,
+    InternalServerError,
+    RateLimitError,
+    UnprocessableEntityError,
+    BadRequestError,
+)
+from openai.types import (
+    Completion,
+    CreateEmbeddingResponse,
+)
+from openai.types.chat import ChatCompletionChunk, ChatCompletion
+
+from adalflow.core.model_client import ModelClient
+from adalflow.core.types import (
+    ModelType,
+    EmbedderOutput,
+    TokenLogProb,
+    CompletionUsage,
+    GeneratorOutput,
+)
+from adalflow.components.model_client.utils import parse_embedding_response
+
+log = logging.getLogger(__name__)
+T = TypeVar("T")
+
+
+# completion parsing functions and you can combine them into one singple chat completion parser
+def get_first_message_content(completion: ChatCompletion) -> str:
+    r"""When we only need the content of the first message.
+    It is the default parser for chat completion."""
+    return completion.choices[0].message.content
+
+
+# def _get_chat_completion_usage(completion: ChatCompletion) -> OpenAICompletionUsage:
+#     return completion.usage
+
+
+def parse_stream_response(completion: ChatCompletionChunk) -> str:
+    r"""Parse the response of the stream API."""
+    return completion.choices[0].delta.content
+
+
+def handle_streaming_response(generator: Stream[ChatCompletionChunk]):
+    r"""Handle the streaming response."""
+    for completion in generator:
+        log.debug(f"Raw chunk completion: {completion}")
+        parsed_content = parse_stream_response(completion)
+        yield parsed_content
+
+
+def get_all_messages_content(completion: ChatCompletion) -> List[str]:
+    r"""When the n > 1, get all the messages content."""
+    return [c.message.content for c in completion.choices]
+
+
+def get_probabilities(completion: ChatCompletion) -> List[List[TokenLogProb]]:
+    r"""Get the probabilities of each token in the completion."""
+    log_probs = []
+    for c in completion.choices:
+        content = c.logprobs.content
+        print(content)
+        log_probs_for_choice = []
+        for openai_token_logprob in content:
+            token = openai_token_logprob.token
+            logprob = openai_token_logprob.logprob
+            log_probs_for_choice.append(TokenLogProb(token=token, logprob=logprob))
+        log_probs.append(log_probs_for_choice)
+    return log_probs
+
+
+class AzureAIClient(ModelClient):
+    __doc__ = r"""A component wrapper for the AzureOpenAI API client.
+
+    Support both embedding and chat completion API.
+
+    Users (1) simplify use ``Embedder`` and ``Generator`` components by passing OpenAIClient() as the model_client.
+    (2) can use this as an example to create their own API client or extend this class(copying and modifing the code) in their own project.
+
+    Note:
+        We suggest users not to use `response_format` to enforce output data type or `tools` and `tool_choice`  in your model_kwargs when calling the API.
+        We do not know how AzureOpenAI is doing the formating or what prompt they have added.
+        Instead
+        - use :ref:`OutputParser<components-output_parsers>` for response parsing and formating.
+
+    Args:
+        api_key (Optional[str], optional): AzureOpenAI API key. Defaults to None.
+        chat_completion_parser (Callable[[Completion], Any], optional): A function to parse the chat completion to a str. Defaults to None.
+            Default is `get_first_message_content`.
+
+    References:
+        - Embeddings models: https://platform.openai.com/docs/guides/embeddings
+        - Chat models: https://platform.openai.com/docs/guides/text-generation
+        - AzureOpenAI docs: https://learn.microsoft.com/en-us/azure/ai-services/openai/overview
+    """
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        api_version:Optional[str]=None,
+        azure_endpoint: Optional[str]= None,
+        credential: Optional[DefaultAzureCredential] = None,
+        chat_completion_parser: Callable[[Completion], Any] = None,
+        input_type: Literal["text", "messages"] = "text",
+    ):
+        r"""It is recommended to set the OPENAI_API_KEY environment variable instead of passing it as an argument.
+
+         
+        Initializes the Azure OpenAI client with either API key or AAD token authentication.
+        
+        Args:
+            api_key: Azure OpenAI API key.
+            api_version: Azure OpenAI API version.
+            azure_endpoint: Azure OpenAI endpoint.
+            credential: Azure AD credential for token-based authentication.
+            chat_completion_parser: Function to parse chat completions.
+            input_type: Input format, either "text" or "messages".
+        
+        """
+        super().__init__()
+
+        # added api_type azure for azure Ai
+        self.api_type = "azure"
+        self._api_key = api_key
+        self._apiversion= api_version
+        self._azure_endpoint = azure_endpoint
+        self._credential = credential
+        self.sync_client = self.init_sync_client()
+        self.async_client = None  # only initialize if the async call is called
+        self.chat_completion_parser = (
+            chat_completion_parser or get_first_message_content
+        )
+        self._input_type = input_type
+
+    def init_sync_client(self):
+        api_key = self._api_key or os.getenv("AZURE_OPENAI_API_KEY")
+        azure_endpoint = self._azure_endpoint or os.getenv("AZURE_OPENAI_ENDPOINT")
+        api_version = self._apiversion or os.getenv("AZURE_OPENAI_VERSION")
+        credential = self._credential  or DefaultAzureCredential
+        if not azure_endpoint:
+            raise ValueError("Environment variable AZURE_OPENAI_ENDPOINT must be set")
+        if not api_version:
+            raise ValueError("Environment variable AZURE_OPENAI_VERSION must be set")
+        
+        if api_key:
+            return AzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
+        elif self._credential:
+            # credential = DefaultAzureCredential()
+            token_provider = get_bearer_token_provider(credential)
+            return AzureOpenAI(token=token_provider(), azure_endpoint=azure_endpoint, api_version=api_version)
+        else:
+            raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
+        
+
+    def init_async_client(self):
+        api_key = self._api_key or os.getenv("AZURE_OPENAI_API_KEY")
+        azure_endpoint = self._azure_endpoint or os.getenv("AZURE_OPENAI_ENDPOINT")
+        api_version = self._apiversion or os.getenv("AZURE_OPENAI_VERSION")
+        credential = self._credential  or DefaultAzureCredential()
+        if not azure_endpoint:
+                raise ValueError("Environment variable AZURE_OPENAI_ENDPOINT must be set")
+        if not api_version:
+            raise ValueError("Environment variable AZURE_OPENAI_VERSION must be set")
+        
+        if api_key:
+            return AsyncAzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
+        elif self._credential:
+            # credential = DefaultAzureCredential()
+            token_provider = get_bearer_token_provider(credential)
+            return AsyncAzureOpenAI(token=token_provider(), azure_endpoint=azure_endpoint, api_version=api_version)
+        else:
+            raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
+
+    # def _parse_chat_completion(self, completion: ChatCompletion) -> "GeneratorOutput":
+    #     # TODO: raw output it is better to save the whole completion as a source of truth instead of just the message
+    #     try:
+    #         data = self.chat_completion_parser(completion)
+    #         usage = self.track_completion_usage(completion)
+    #         return GeneratorOutput(
+    #             data=data, error=None, raw_response=str(data), usage=usage
+    #         )
+    #     except Exception as e:
+    #         log.error(f"Error parsing the completion: {e}")
+    #         return GeneratorOutput(data=None, error=str(e), raw_response=completion)
+
+    def parse_chat_completion(
+        self,
+        completion: Union[ChatCompletion, Generator[ChatCompletionChunk, None, None]],
+    ) -> "GeneratorOutput":
+        """Parse the completion, and put it into the raw_response."""
+        log.debug(f"completion: {completion}, parser: {self.chat_completion_parser}")
+        try:
+            data = self.chat_completion_parser(completion)
+            usage = self.track_completion_usage(completion)
+            return GeneratorOutput(
+                data=None, error=None, raw_response=data, usage=usage
+            )
+        except Exception as e:
+            log.error(f"Error parsing the completion: {e}")
+            return GeneratorOutput(data=None, error=str(e), raw_response=completion)
+
+    def track_completion_usage(
+        self,
+        completion: Union[ChatCompletion, Generator[ChatCompletionChunk, None, None]],
+    ) -> CompletionUsage:
+        if isinstance(completion, ChatCompletion):
+            usage: CompletionUsage = CompletionUsage(
+                completion_tokens=completion.usage.completion_tokens,
+                prompt_tokens=completion.usage.prompt_tokens,
+                total_tokens=completion.usage.total_tokens,
+            )
+            return usage
+        else:
+            raise NotImplementedError(
+                "streaming completion usage tracking is not implemented"
+            )
+
+    def parse_embedding_response(
+        self, response: CreateEmbeddingResponse
+    ) -> EmbedderOutput:
+        r"""Parse the embedding response to a structure LightRAG components can understand.
+
+        Should be called in ``Embedder``.
+        """
+        try:
+            return parse_embedding_response(response)
+        except Exception as e:
+            log.error(f"Error parsing the embedding response: {e}")
+            return EmbedderOutput(data=[], error=str(e), raw_response=response)
+
+    def convert_inputs_to_api_kwargs(
+        self,
+        input: Optional[Any] = None,
+        model_kwargs: Dict = {},
+        model_type: ModelType = ModelType.UNDEFINED,
+    ) -> Dict:
+        r"""
+        Specify the API input type and output api_kwargs that will be used in _call and _acall methods.
+        Convert the Component's standard input, and system_input(chat model) and model_kwargs into API-specific format
+        """
+
+        final_model_kwargs = model_kwargs.copy()
+        if model_type == ModelType.EMBEDDER:
+            if isinstance(input, str):
+                input = [input]
+            # convert input to input
+            if not isinstance(input, Sequence):
+                raise TypeError("input must be a sequence of text")
+            final_model_kwargs["input"] = input
+        elif model_type == ModelType.LLM:
+            # convert input to messages
+            messages: List[Dict[str, str]] = []
+
+            if self._input_type == "messages":
+                system_start_tag = "<START_OF_SYSTEM_PROMPT>"
+                system_end_tag = "<END_OF_SYSTEM_PROMPT>"
+                user_start_tag = "<START_OF_USER_PROMPT>"
+                user_end_tag = "<END_OF_USER_PROMPT>"
+                pattern = f"{system_start_tag}(.*?){system_end_tag}{user_start_tag}(.*?){user_end_tag}"
+                # Compile the regular expression
+                regex = re.compile(pattern)
+                # Match the pattern
+                match = regex.search(input)
+                system_prompt, input_str = None, None
+
+                if match:
+                    system_prompt = match.group(1)
+                    input_str = match.group(2)
+
+                else:
+                    print("No match found.")
+                if system_prompt and input_str:
+                    messages.append({"role": "system", "content": system_prompt})
+                    messages.append({"role": "user", "content": input_str})
+            if len(messages) == 0:
+                messages.append({"role": "system", "content": input})
+            final_model_kwargs["messages"] = messages
+        else:
+            raise ValueError(f"model_type {model_type} is not supported")
+        return final_model_kwargs
+
+    @backoff.on_exception(
+        backoff.expo,
+        (
+            APITimeoutError,
+            InternalServerError,
+            RateLimitError,
+            UnprocessableEntityError,
+            BadRequestError,
+        ),
+        max_time=5,
+    )
+    def call(self, api_kwargs: Dict = {}, model_type: ModelType = ModelType.UNDEFINED):
+        """
+        kwargs is the combined input and model_kwargs.  Support streaming call.
+        """
+        log.info(f"api_kwargs: {api_kwargs}")
+        if model_type == ModelType.EMBEDDER:
+            return self.sync_client.embeddings.create(**api_kwargs)
+        elif model_type == ModelType.LLM:
+            if "stream" in api_kwargs and api_kwargs.get("stream", False):
+                log.debug("streaming call")
+                self.chat_completion_parser = handle_streaming_response
+                return self.sync_client.chat.completions.create(**api_kwargs)
+            return self.sync_client.chat.completions.create(**api_kwargs)
+        else:
+            raise ValueError(f"model_type {model_type} is not supported")
+
+    @backoff.on_exception(
+        backoff.expo,
+        (
+            APITimeoutError,
+            InternalServerError,
+            RateLimitError,
+            UnprocessableEntityError,
+            BadRequestError,
+        ),
+        max_time=5,
+    )
+    async def acall(
+        self, api_kwargs: Dict = {}, model_type: ModelType = ModelType.UNDEFINED
+    ):
+        """
+        kwargs is the combined input and model_kwargs
+        """
+        if self.async_client is None:
+            self.async_client = self.init_async_client()
+        if model_type == ModelType.EMBEDDER:
+            return await self.async_client.embeddings.create(**api_kwargs)
+        elif model_type == ModelType.LLM:
+            return await self.async_client.chat.completions.create(**api_kwargs)
+        else:
+            raise ValueError(f"model_type {model_type} is not supported")
+
+    @classmethod
+    def from_dict(cls: type[T], data: Dict[str, Any]) -> T:
+        obj = super().from_dict(data)
+        # recreate the existing clients
+        obj.sync_client = obj.init_sync_client()
+        obj.async_client = obj.init_async_client()
+        return obj
+
+    def to_dict(self) -> Dict[str, Any]:
+        r"""Convert the component to a dictionary."""
+        # TODO: not exclude but save yes or no for recreating the clients
+        exclude = [
+            "sync_client",
+            "async_client",
+        ]  # unserializable object
+        output = super().to_dict(exclude=exclude)
+        return output
+
+
+# if __name__ == "__main__":
+#     from adalflow.core import Generator
+#     from adalflow.utils import setup_env, get_logger
+
+#     log = get_logger(level="DEBUG")
+
+#     setup_env()
+#     prompt_kwargs = {"input_str": "What is the meaning of life?"}
+
+#     gen = Generator(
+#         model_client=OpenAIClient(),
+#         model_kwargs={"model": "gpt-3.5-turbo", "stream": True},
+#     )
+#     gen_response = gen(prompt_kwargs)
+#     print(f"gen_response: {gen_response}")
+
+#     for genout in gen_response.data:
+#         print(f"genout: {genout}")

From 3da6636f2217bc62dc42543c7d7d0e89cbfa93a1 Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Tue, 27 Aug 2024 21:49:20 -0400
Subject: [PATCH 02/13] Update azureai_client.py

fixed azure_ad_token provider in AzureOpenAI
---
 .../adalflow/components/model_client/azureai_client.py    | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/adalflow/adalflow/components/model_client/azureai_client.py b/adalflow/adalflow/components/model_client/azureai_client.py
index 226720b1..be94d07f 100644
--- a/adalflow/adalflow/components/model_client/azureai_client.py
+++ b/adalflow/adalflow/components/model_client/azureai_client.py
@@ -174,8 +174,8 @@ def init_sync_client(self):
             return AzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
         elif self._credential:
             # credential = DefaultAzureCredential()
-            token_provider = get_bearer_token_provider(credential)
-            return AzureOpenAI(token=token_provider(), azure_endpoint=azure_endpoint, api_version=api_version)
+            token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
+            return AzureOpenAI(azure_ad_token_provider=token_provider, azure_endpoint=azure_endpoint, api_version=api_version)
         else:
             raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
         
@@ -194,8 +194,8 @@ def init_async_client(self):
             return AsyncAzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
         elif self._credential:
             # credential = DefaultAzureCredential()
-            token_provider = get_bearer_token_provider(credential)
-            return AsyncAzureOpenAI(token=token_provider(), azure_endpoint=azure_endpoint, api_version=api_version)
+            token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
+            return AsyncAzureOpenAI(azure_ad_token_provider=token_provider, azure_endpoint=azure_endpoint, api_version=api_version)
         else:
             raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
 

From 101d1c3b328167426c35d72651ed9da07971a0b1 Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 05:29:06 +0000
Subject: [PATCH 03/13] added azure

---
 pyproject.toml | 14 +++++---------
 1 file changed, 5 insertions(+), 9 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index be553aad..56ab3998 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,4 +1,3 @@
-
 [tool.poetry]
 name = "adalflow-project"
 version = "0.1.0"
@@ -17,14 +16,9 @@ packages = [
 [tool.poetry.dependencies]
 python = ">=3.11, <4.0"
 adalflow = { path = "adalflow", develop = true }
-# torch = "^2.3.1"
 openai = "^1.34.0"
-# lightrag = {path = "lightrag/dist/lightrag-0.0.0a11-py3-none-any.whl"}
-# lightrag = "^0.0.0a13"
-
 
 [tool.poetry.group.dev.dependencies]
-
 pre-commit = "^3.7.0"
 anthropic = "^0.26.0"
 torchmetrics = "^1.4.0.post0"
@@ -43,7 +37,12 @@ textgrad = "^0.1.4"
 tensorboardx = "^2.6.2.2"
 tensorboard = "^2.17.0"
 dspy-ai = "^2.4.13"
+transformers = "^4.44.0"
+accelerate = "^0.33.0"
 
+[tool.poetry.group.azure.dependencies]
+azure-storage-blob = "^12.14.0"
+azure-identity = "^1.12.0"
 
 # [tool.poetry.group.doc.dependencies]
 # pydata-sphinx-theme = "^0.15.3"
@@ -58,9 +57,6 @@ dspy-ai = "^2.4.13"
 # google-generativeai = "^0.7.1"
 # faiss-cpu = "^1.8.0.post1"
 # lightrag = { path = "lightrag", develop = true }
-transformers = "^4.44.0"
-accelerate = "^0.33.0"
-
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

From f249f101283996f487dd25f5c2bf693a798669fc Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 06:04:19 +0000
Subject: [PATCH 04/13] added test for Azure client

---
 adalflow/tests/test_AzureClient.py | 119 +++++++++++++++++++++++++++++
 1 file changed, 119 insertions(+)
 create mode 100644 adalflow/tests/test_AzureClient.py

diff --git a/adalflow/tests/test_AzureClient.py b/adalflow/tests/test_AzureClient.py
new file mode 100644
index 00000000..8bfc1ce7
--- /dev/null
+++ b/adalflow/tests/test_AzureClient.py
@@ -0,0 +1,119 @@
+import unittest
+from unittest.mock import patch, MagicMock
+from azure.identity import DefaultAzureCredential
+from openai import AzureOpenAI
+from openai.types import Completion, CreateEmbeddingResponse
+from openai.types.chat import ChatCompletionChunk, ChatCompletion
+from adalflow.core.model_client import ModelClient
+from adalflow.core.types import ModelType, EmbedderOutput, TokenLogProb, CompletionUsage, GeneratorOutput
+from adalflow.components.model_client.openai_client import AzureAIClient  
+
+class TestAzureAIClient(unittest.TestCase):
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')  
+    @patch('adalflow.components.model_client.openai_client.DefaultAzureCredential')
+    def setUp(self, MockDefaultAzureCredential, MockAzureOpenAI):
+        self.mock_credential = MockDefaultAzureCredential()
+        self.mock_sync_client = MockAzureOpenAI.return_value
+        self.client = AzureAIClient(
+            api_key="test_api_key",
+            api_version="v1",
+            azure_endpoint="https://test.endpoint",
+            credential=self.mock_credential,
+        )
+        self.client.sync_client = self.mock_sync_client
+
+    def test_init_sync_client_with_api_key(self):
+        client = AzureAIClient(api_key="test_key", api_version="v1", azure_endpoint="https://test.endpoint")
+        self.assertIsInstance(client.sync_client, AzureOpenAI)
+
+    def test_init_sync_client_with_credential(self):
+        client = AzureAIClient(
+            api_version="v1",
+            azure_endpoint="https://test.endpoint",
+            credential=self.mock_credential
+        )
+        self.assertIsInstance(client.sync_client, AzureOpenAI)
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_call_embeddings(self, MockAzureOpenAI):
+        mock_embeddings = MagicMock()
+        MockAzureOpenAI.return_value.embeddings.create = mock_embeddings
+        api_kwargs = {'input': ["test"]}
+        model_type = ModelType.EMBEDDER
+        self.client.call(api_kwargs=api_kwargs, model_type=model_type)
+        MockAzureOpenAI.return_value.embeddings.create.assert_called_once_with(**api_kwargs)
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_call_chat_completions(self, MockAzureOpenAI):
+        mock_chat_completions = MagicMock()
+        MockAzureOpenAI.return_value.chat.completions.create = mock_chat_completions
+        api_kwargs = {'input': "test"}
+        model_type = ModelType.LLM
+        self.client.call(api_kwargs=api_kwargs, model_type=model_type)
+        MockAzureOpenAI.return_value.chat.completions.create.assert_called_once_with(**api_kwargs)
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_parse_chat_completion(self, MockAzureOpenAI):
+        mock_chat_completion = MagicMock(spec=ChatCompletion)
+        mock_chat_completion.choices = [MagicMock(message=MagicMock(content="test_content"))]
+        self.client.chat_completion_parser = lambda completion: completion.choices[0].message.content
+        result = self.client.parse_chat_completion(mock_chat_completion)
+        self.assertEqual(result, "test_content")
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_track_completion_usage(self, MockAzureOpenAI):
+        mock_chat_completion = MagicMock(spec=ChatCompletion)
+        mock_chat_completion.usage = MagicMock(
+            completion_tokens=10,
+            prompt_tokens=5,
+            total_tokens=15
+        )
+        result = self.client.track_completion_usage(mock_chat_completion)
+        self.assertEqual(result.completion_tokens, 10)
+        self.assertEqual(result.prompt_tokens, 5)
+        self.assertEqual(result.total_tokens, 15)
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_parse_embedding_response(self, MockAzureOpenAI):
+        mock_embedding_response = MagicMock(spec=CreateEmbeddingResponse)
+        self.client.parse_embedding_response = lambda response: EmbedderOutput(data=["test_embedding"], error=None, raw_response=response)
+        result = self.client.parse_embedding_response(mock_embedding_response)
+        self.assertEqual(result.data, ["test_embedding"])
+
+    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
+    def test_convert_inputs_to_api_kwargs(self, MockAzureOpenAI):
+        input_data = "test input"
+        model_kwargs = {"param": "value"}
+        result = self.client.convert_inputs_to_api_kwargs(input=input_data, model_kwargs=model_kwargs, model_type=ModelType.LLM)
+        expected = {
+            "input": input_data,
+            "param": "value"
+        }
+        self.assertEqual(result, expected)
+
+    def test_from_dict(self):
+        data = {
+            "api_key": "test_key",
+            "api_version": "v1",
+            "azure_endpoint": "https://test.endpoint",
+            "credential": self.mock_credential,
+        }
+        client = AzureAIClient.from_dict(data)
+        self.assertEqual(client._api_key, "test_key")
+        self.assertEqual(client._apiversion, "v1")
+        self.assertEqual(client._azure_endpoint, "https://test.endpoint")
+
+    def test_to_dict(self):
+        expected = {
+            "api_key": "test_api_key",
+            "api_version": "v1",
+            "azure_endpoint": "https://test.endpoint",
+            "credential": self.mock_credential,
+        }
+        result = self.client.to_dict()
+        for key, value in expected.items():
+            self.assertEqual(result.get(key), value)
+
+if __name__ == '__main__':
+    unittest.main()

From 0847c7deaedc9411d17214b4532728558ddc6095 Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 06:04:48 +0000
Subject: [PATCH 05/13] added azure extrac packages

---
 adalflow/pyproject.toml | 35 ++++++++++++++---------------------
 1 file changed, 14 insertions(+), 21 deletions(-)

diff --git a/adalflow/pyproject.toml b/adalflow/pyproject.toml
index 3cf1148e..913dd0bc 100644
--- a/adalflow/pyproject.toml
+++ b/adalflow/pyproject.toml
@@ -1,12 +1,10 @@
 [tool.poetry]
 name = "adalflow"
-
 version = "0.2.0"
 description = "The Library to Build and Auto-optimize Any LLM Task Pipeline"
 authors = ["Li Yin <li@sylphai.com>"]
 readme = "README.md"
 repository = "https://github.com/SylphAI-Inc/LightRAG"
-
 license = "MIT"
 maintainers = ["Li Yin <li@sylphai.com>"]
 classifiers = [
@@ -27,10 +25,8 @@ include = [
     "adalflow/optim/*",
 ]
 
-
 packages = [{ include = "adalflow", from = "." }]
 
-
 [tool.poetry.dependencies]
 python = ">=3.9, <4.0"
 
@@ -43,8 +39,7 @@ numpy = "^1.26.4"
 tqdm = "^4.66.4"
 pyyaml = "^6.0.1"
 nest-asyncio = "^1.6.0"
-botocore = "^1.34.149"   # if not specified, it will fail to resolve the dependency
-
+botocore = "^1.34.149"
 
 # Optional dependencies
 openai = { version = "^1.12.0", optional = true }
@@ -59,6 +54,11 @@ cohere = { version = "^5.5.8", optional = true }
 ollama = { version = "^0.2.1", optional = true }
 diskcache = "^5.6.3"
 
+# Azure dependencies
+azure-core = { version = "^1.24.0", optional = true }
+azure-identity = { version = "^1.12.0", optional = true }
+azure-ai-formrecognizer = { version = "^3.2.0", optional = true }
+azure-ai-textanalytics = { version = "^5.3.0", optional = true }
 
 [tool.poetry.group.test.dependencies]
 pytest = "^8.1.1"
@@ -71,14 +71,12 @@ groq = "^0.9.0"
 google-generativeai = "^0.7.2"
 anthropic = "^0.31.1"
 
-
 [tool.poetry.group.typing.dependencies]
 mypy = "^1"
 types-pyyaml = "^6.0.12.20240311" # for mypy
 types-tqdm = "^4.66.0.20240417"
 
-
-[tool.poetry.group.dev.dependencies] # specify the versions for extras
+[tool.poetry.group.dev.dependencies]
 pre-commit = "^3.7.0"
 graphviz = "^0.20.3"
 tensorboard = "^2.17.0"
@@ -86,8 +84,7 @@ tensorboardx = "^2.6.2.2"
 matplotlib = "^3.9.1"
 diskcache = "^5.6.3"
 
-
-[tool.poetry.extras] # allow pip install adalflow[openai, groq]
+[tool.poetry.extras]
 openai = ["openai"]
 groq = ["groq"]
 anthropic = ["anthropic"]
@@ -98,25 +95,21 @@ faiss-cpu = ["faiss-cpu"]
 sqlalchemy = ["sqlalchemy"]
 torch = ["torch"]
 ollama = ["ollama"]
+azure = [
+    "azure-core",
+    "azure-identity",
+    "azure-ai-formrecognizer",
+    "azure-ai-textanalytics"
+]
 
-
-# [[tool.poetry.source]]
-# name = "pypi"
-# url = "https://pypi.org/simple"
-# default = true
 [[tool.poetry.source]]
 name = "nvidia-pypi"
 priority = "supplemental"
 url = "https://pypi.nvidia.com"
-# [[tool.poetry.source]]
-# name = "nvidia-pypi"
-# priority = "supplemental"
-# url = "https://pypi.nvidia.com"
 
 [tool.ruff]
 exclude = ["images"]
 
-
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

From 02b7187bd2a03fe372e7fe363d3c223e5f85b20c Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 06:09:52 +0000
Subject: [PATCH 06/13] fixed doc string

---
 .../components/model_client/azureai_client.py | 87 +++++++++++++++----
 1 file changed, 69 insertions(+), 18 deletions(-)

diff --git a/adalflow/adalflow/components/model_client/azureai_client.py b/adalflow/adalflow/components/model_client/azureai_client.py
index be94d07f..70699681 100644
--- a/adalflow/adalflow/components/model_client/azureai_client.py
+++ b/adalflow/adalflow/components/model_client/azureai_client.py
@@ -98,28 +98,79 @@ def get_probabilities(completion: ChatCompletion) -> List[List[TokenLogProb]]:
 
 
 class AzureAIClient(ModelClient):
-    __doc__ = r"""A component wrapper for the AzureOpenAI API client.
+    __doc__ = r"""
+    A client wrapper for interacting with Azure OpenAI's API.
 
-    Support both embedding and chat completion API.
+    This class provides support for both embedding and chat completion API calls.
+    Users can use this class to simplify their interactions with Azure OpenAI models 
+    through the `Embedder` and `Generator` components.
 
-    Users (1) simplify use ``Embedder`` and ``Generator`` components by passing OpenAIClient() as the model_client.
-    (2) can use this as an example to create their own API client or extend this class(copying and modifing the code) in their own project.
+    **Initialization:**
 
-    Note:
-        We suggest users not to use `response_format` to enforce output data type or `tools` and `tool_choice`  in your model_kwargs when calling the API.
-        We do not know how AzureOpenAI is doing the formating or what prompt they have added.
-        Instead
-        - use :ref:`OutputParser<components-output_parsers>` for response parsing and formating.
+    You can initialize the `AzureAIClient` with either an API key or Azure Active Directory (AAD) token 
+    authentication. It is recommended to set environment variables for sensitive data like API keys.
 
     Args:
-        api_key (Optional[str], optional): AzureOpenAI API key. Defaults to None.
-        chat_completion_parser (Callable[[Completion], Any], optional): A function to parse the chat completion to a str. Defaults to None.
-            Default is `get_first_message_content`.
-
-    References:
-        - Embeddings models: https://platform.openai.com/docs/guides/embeddings
-        - Chat models: https://platform.openai.com/docs/guides/text-generation
-        - AzureOpenAI docs: https://learn.microsoft.com/en-us/azure/ai-services/openai/overview
+        api_key (Optional[str]): Azure OpenAI API key. Default is None.
+        api_version (Optional[str]): API version to use. Default is None.
+        azure_endpoint (Optional[str]): Azure OpenAI endpoint URL. Default is None.
+        credential (Optional[DefaultAzureCredential]): Azure AD credential for token-based authentication. Default is None.
+        chat_completion_parser (Callable[[Completion], Any]): Function to parse chat completions. Default is `get_first_message_content`.
+        input_type (Literal["text", "messages"]): Format for input, either "text" or "messages". Default is "text".
+
+    **Setup Instructions:**
+
+    - **Using API Key:**
+      Set up the following environment variables:
+      ```bash
+      export AZURE_OPENAI_API_KEY="your_api_key"
+      export AZURE_OPENAI_ENDPOINT="your_endpoint"
+      export AZURE_OPENAI_VERSION="your_version"
+      ```
+
+    - **Using Azure AD Token:**
+      Ensure you have configured Azure AD credentials. The `DefaultAzureCredential` will automatically use your configured credentials.
+
+    **Example Usage:**do
+
+    ```python
+    from azure.identity import DefaultAzureCredential
+    from your_module import AzureAIClient  # Adjust import based on your module name
+
+    # Initialize with API key
+    client = AzureAIClient(
+        api_key="your_api_key",
+        api_version="2023-05-15",
+        azure_endpoint="https://your-endpoint.openai.azure.com/"
+    )
+
+    # Or initialize with Azure AD token
+    client = AzureAIClient(
+        api_version="2023-05-15",
+        azure_endpoint="https://your-endpoint.openai.azure.com/",
+        credential=DefaultAzureCredential()
+    )
+
+    # Example call to the chat completion API
+    api_kwargs = {
+        "model": "gpt-3.5-turbo",
+        "messages": [{"role": "user", "content": "What is the meaning of life?"}],
+        "stream": True
+    }
+    response = client.call(api_kwargs=api_kwargs, model_type=ModelType.LLM)
+
+    for chunk in response:
+        print(chunk)
+    ```
+
+    **Notes:**
+    - Ensure that the API key or credentials are correctly set up and accessible to avoid authentication errors.
+    - Use `chat_completion_parser` to define how to extract and handle the chat completion responses.
+    - The `input_type` parameter determines how input is formatted for the API call.
+
+    **References:**
+    - [Azure OpenAI API Documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview)
+    - [OpenAI API Documentation](https://platform.openai.com/docs/guides/text-generation)
     """
 
     def __init__(
@@ -131,7 +182,7 @@ def __init__(
         chat_completion_parser: Callable[[Completion], Any] = None,
         input_type: Literal["text", "messages"] = "text",
     ):
-        r"""It is recommended to set the OPENAI_API_KEY environment variable instead of passing it as an argument.
+        r"""It is recommended to set the API_KEY into the  environment variable instead of passing it as an argument.
 
          
         Initializes the Azure OpenAI client with either API key or AAD token authentication.

From de1fe125fc2bf8f1e100965d786086269235f39d Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 11:36:06 +0000
Subject: [PATCH 07/13] added azure auth services

---
 adalflow/adalflow/utils/lazy_import.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/adalflow/adalflow/utils/lazy_import.py b/adalflow/adalflow/utils/lazy_import.py
index 9a2b0c1c..4a604543 100644
--- a/adalflow/adalflow/utils/lazy_import.py
+++ b/adalflow/adalflow/utils/lazy_import.py
@@ -32,6 +32,8 @@ class OptionalPackages(Enum):
     # modeling library
     TORCH = ("torch", "Please install torch with: pip install torch")
 
+
+    AZURE_AUTH_SERVICES = ("AZURE_AUTH_SERVICES", "Please install AZURE_AUTH_SERVICES with: pip install azure-identity azure-core")
     # search library
     FAISS = ("faiss", "Please install faiss with: pip install faiss")
 

From 1c4aee0278ad9b05ed2c9d8bb4380efa74bedafc Mon Sep 17 00:00:00 2001
From: adityasugandhi <39901010+adityasugandhi@users.noreply.github.com>
Date: Sun, 8 Sep 2024 11:51:34 +0000
Subject: [PATCH 08/13] small bug fix

---
 pyproject.toml | 16 ++++++++++------
 1 file changed, 10 insertions(+), 6 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 56ab3998..6054c08c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,4 @@
+
 [tool.poetry]
 name = "adalflow-project"
 version = "0.1.0"
@@ -16,9 +17,14 @@ packages = [
 [tool.poetry.dependencies]
 python = ">=3.11, <4.0"
 adalflow = { path = "adalflow", develop = true }
+# torch = "^2.3.1"
 openai = "^1.34.0"
+# lightrag = {path = "lightrag/dist/lightrag-0.0.0a11-py3-none-any.whl"}
+# lightrag = "^0.0.0a13"
+
 
 [tool.poetry.group.dev.dependencies]
+
 pre-commit = "^3.7.0"
 anthropic = "^0.26.0"
 torchmetrics = "^1.4.0.post0"
@@ -37,12 +43,7 @@ textgrad = "^0.1.4"
 tensorboardx = "^2.6.2.2"
 tensorboard = "^2.17.0"
 dspy-ai = "^2.4.13"
-transformers = "^4.44.0"
-accelerate = "^0.33.0"
 
-[tool.poetry.group.azure.dependencies]
-azure-storage-blob = "^12.14.0"
-azure-identity = "^1.12.0"
 
 # [tool.poetry.group.doc.dependencies]
 # pydata-sphinx-theme = "^0.15.3"
@@ -57,7 +58,10 @@ azure-identity = "^1.12.0"
 # google-generativeai = "^0.7.1"
 # faiss-cpu = "^1.8.0.post1"
 # lightrag = { path = "lightrag", develop = true }
+transformers = "^4.44.0"
+accelerate = "^0.33.0"
+
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
-build-backend = "poetry.core.masonry.api"
+build-backend = "poetry.core.masonry.api"
\ No newline at end of file

From 9515f30fc3b6b81accf9b9cb4cac46c7421662b5 Mon Sep 17 00:00:00 2001
From: Li Yin <li.yin.gravity@gmail.com>
Date: Sun, 6 Oct 2024 11:39:47 +0800
Subject: [PATCH 09/13] make boto3 a safe import, update the poetry lock, add
 better doc string

---
 .../components/model_client/bedrock_client.py | 115 +++++++++++++-----
 adalflow/adalflow/utils/lazy_import.py        |   4 +-
 adalflow/poetry.lock                          |  95 ++++++++-------
 3 files changed, 136 insertions(+), 78 deletions(-)

diff --git a/adalflow/adalflow/components/model_client/bedrock_client.py b/adalflow/adalflow/components/model_client/bedrock_client.py
index 549c1988..2f670d43 100644
--- a/adalflow/adalflow/components/model_client/bedrock_client.py
+++ b/adalflow/adalflow/components/model_client/bedrock_client.py
@@ -8,6 +8,10 @@
 from adalflow.core.model_client import ModelClient
 from adalflow.core.types import ModelType, CompletionUsage, GeneratorOutput
 
+from adalflow.utils.lazy_import import safe_import, OptionalPackages
+
+boto3 = safe_import(OptionalPackages.BOTO3.value[0], OptionalPackages.BOTO3.value[1])
+
 import boto3
 from botocore.config import Config
 
@@ -15,34 +19,83 @@
 
 bedrock_runtime_exceptions = boto3.client(
     service_name="bedrock-runtime",
-    region_name=os.getenv("AWS_REGION_NAME", "us-east-1")
+    region_name=os.getenv("AWS_REGION_NAME", "us-east-1"),
 ).exceptions
 
 
 def get_first_message_content(completion: Dict) -> str:
     r"""When we only need the content of the first message.
     It is the default parser for chat completion."""
-    return completion['output']['message']['content'][0]['text']
+    return completion["output"]["message"]["content"][0]["text"]
 
 
-__all__ = ["BedrockAPIClient", "get_first_message_content", "bedrock_runtime_exceptions"]
+__all__ = [
+    "BedrockAPIClient",
+    "get_first_message_content",
+    "bedrock_runtime_exceptions",
+]
 
 
 class BedrockAPIClient(ModelClient):
     __doc__ = r"""A component wrapper for the Bedrock API client.
-    Visit https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html for more api details.
+
+    Support:
+    1. AWS Titan
+    2. Claude
+    3. Cohere
+    4. LLama
+    5. Mistral
+    6. Jamba
+
+    Setup:
+    1. Install boto3: `pip install boto3`
+    2. Ensure you have the AWS credentials set up. There are four variables you can optionally set:
+        - AWS_PROFILE_NAME: The name of the AWS profile to use.
+        - AWS_REGION_NAME: The name of the AWS region to use.
+        - AWS_ACCESS_KEY_ID: The AWS access key ID.
+        - AWS_SECRET_ACCESS_KEY: The AWS secret access key.
+
+
+    Relevant API docs:
+    1. https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html
+    2. https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started-api-ex-python.html
+    3. https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html#API_runtime_Converse_RequestParameters
+
+    Example:
+
+    .. code-block:: python
+
+        from adalflow.components.model_client import BedrockAPIClient
+
+        template = "<SYS>
+        You are a helpful assistant.
+        </SYS>
+        User: {{input_str}}
+        You:
+        "
+
+        # use AWS_PROFILE_NAME and AWS_REGION_NAME from the environment variables in this case
+        self.generator = Generator(
+            model_client=BedrockAPIClient(),
+            model_kwargs={
+                "modelId": "anthropic.claude-3-sonnet-20240229-v1:0",
+                "inferenceConfig": {
+                    "temperature": 0.8
+                }
+            }, template=template
+        )
     """
 
     def __init__(
-            self,
-            aws_profile_name=None,
-            aws_region_name=None,
-            aws_access_key_id=None,
-            aws_secret_access_key=None,
-            aws_session_token=None,
-            aws_connection_timeout=None,
-            aws_read_timeout=None,
-            chat_completion_parser: Callable = None,
+        self,
+        aws_profile_name=None,
+        aws_region_name=None,
+        aws_access_key_id=None,
+        aws_secret_access_key=None,
+        aws_session_token=None,
+        aws_connection_timeout=None,
+        aws_read_timeout=None,
+        chat_completion_parser: Callable = None,
     ):
         super().__init__()
         self._aws_profile_name = aws_profile_name
@@ -56,7 +109,7 @@ def __init__(
         self.session = None
         self.sync_client = self.init_sync_client()
         self.chat_completion_parser = (
-                chat_completion_parser or get_first_message_content
+            chat_completion_parser or get_first_message_content
         )
 
     def init_sync_client(self):
@@ -67,14 +120,16 @@ def init_sync_client(self):
         aws_profile_name = self._aws_profile_name or os.getenv("AWS_PROFILE_NAME")
         aws_region_name = self._aws_region_name or os.getenv("AWS_REGION_NAME")
         aws_access_key_id = self._aws_access_key_id or os.getenv("AWS_ACCESS_KEY_ID")
-        aws_secret_access_key = self._aws_secret_access_key or os.getenv("AWS_SECRET_ACCESS_KEY")
+        aws_secret_access_key = self._aws_secret_access_key or os.getenv(
+            "AWS_SECRET_ACCESS_KEY"
+        )
         aws_session_token = self._aws_session_token or os.getenv("AWS_SESSION_TOKEN")
 
         config = None
         if self._aws_connection_timeout or self._aws_read_timeout:
             config = Config(
                 connect_timeout=self._aws_connection_timeout,  # Connection timeout in seconds
-                read_timeout=self._aws_read_timeout  # Read timeout in seconds
+                read_timeout=self._aws_read_timeout,  # Read timeout in seconds
             )
 
         session = boto3.Session(
@@ -93,7 +148,7 @@ def init_async_client(self):
     def parse_chat_completion(self, completion):
         log.debug(f"completion: {completion}")
         try:
-            data = completion['output']['message']['content'][0]['text']
+            data = completion["output"]["message"]["content"][0]["text"]
             usage = self.track_completion_usage(completion)
             return GeneratorOutput(data=None, usage=usage, raw_response=data)
         except Exception as e:
@@ -104,18 +159,18 @@ def parse_chat_completion(self, completion):
 
     def track_completion_usage(self, completion: Dict) -> CompletionUsage:
         r"""Track the completion usage."""
-        usage = completion['usage']
+        usage = completion["usage"]
         return CompletionUsage(
-            completion_tokens=usage['outputTokens'],
-            prompt_tokens=usage['inputTokens'],
-            total_tokens=usage['totalTokens']
+            completion_tokens=usage["outputTokens"],
+            prompt_tokens=usage["inputTokens"],
+            total_tokens=usage["totalTokens"],
         )
 
     def convert_inputs_to_api_kwargs(
-            self,
-            input: Optional[Any] = None,
-            model_kwargs: Dict = {},
-            model_type: ModelType = ModelType.UNDEFINED
+        self,
+        input: Optional[Any] = None,
+        model_kwargs: Dict = {},
+        model_type: ModelType = ModelType.UNDEFINED,
     ):
         """
         check the converse api doc here:
@@ -133,11 +188,11 @@ def convert_inputs_to_api_kwargs(
     @backoff.on_exception(
         backoff.expo,
         (
-                bedrock_runtime_exceptions.ThrottlingException,
-                bedrock_runtime_exceptions.ModelTimeoutException,
-                bedrock_runtime_exceptions.InternalServerException,
-                bedrock_runtime_exceptions.ModelErrorException,
-                bedrock_runtime_exceptions.ValidationException
+            bedrock_runtime_exceptions.ThrottlingException,
+            bedrock_runtime_exceptions.ModelTimeoutException,
+            bedrock_runtime_exceptions.InternalServerException,
+            bedrock_runtime_exceptions.ModelErrorException,
+            bedrock_runtime_exceptions.ValidationException,
         ),
         max_time=5,
     )
diff --git a/adalflow/adalflow/utils/lazy_import.py b/adalflow/adalflow/utils/lazy_import.py
index aa4c988f..ec8244ec 100644
--- a/adalflow/adalflow/utils/lazy_import.py
+++ b/adalflow/adalflow/utils/lazy_import.py
@@ -29,6 +29,8 @@ class OptionalPackages(Enum):
     )
     COHERE = ("cohere", "Please install cohere with: pip install cohere")
     OLLAMA = ("ollama", "Please install ollama with: pip install ollama")
+    # AWS
+    BOTO3 = ("boto3", "Please install boto3 with: pip install boto3")
     # modeling library
     TORCH = ("torch", "Please install torch with: pip install torch")
 
@@ -78,7 +80,7 @@ class LazyImport:
     """
 
     def __init__(
-            self, import_path: str, optional_package: OptionalPackages, *args, **kwargs
+        self, import_path: str, optional_package: OptionalPackages, *args, **kwargs
     ):
         if args or kwargs:
             raise TypeError(
diff --git a/adalflow/poetry.lock b/adalflow/poetry.lock
index f24854be..ae8445c2 100644
--- a/adalflow/poetry.lock
+++ b/adalflow/poetry.lock
@@ -251,7 +251,7 @@ files = [
 name = "boto3"
 version = "1.35.19"
 description = "The AWS SDK for Python"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
     {file = "boto3-1.35.19-py3-none-any.whl", hash = "sha256:84b3fe1727945bc3cada832d969ddb3dc0d08fce1677064ca8bdc13a89c1a143"},
@@ -2206,12 +2206,13 @@ files = [
 
 [[package]]
 name = "nvidia-cudnn-cu12"
-version = "8.9.2.26"
+version = "9.1.0.70"
 description = "cuDNN runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl", hash = "sha256:5ccb288774fdfb07a7e7025ffec286971c06d8d7b4fb162525334616d7629ff9"},
+    {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f"},
+    {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-win_amd64.whl", hash = "sha256:6278562929433d68365a07a4a1546c237ba2849852c0d4b2262a486e805b977a"},
 ]
 
 [package.dependencies]
@@ -2271,12 +2272,13 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.19.3"
+version = "2.20.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:a9734707a2c96443331c1e48c717024aa6678a0e2a4cb66b2c364d18cee6b48d"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
 ]
 
 [[package]]
@@ -3130,7 +3132,7 @@ pyasn1 = ">=0.1.3"
 name = "s3transfer"
 version = "0.10.2"
 description = "An Amazon S3 Transfer Manager"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
     {file = "s3transfer-0.10.2-py3-none-any.whl", hash = "sha256:eca1c20de70a39daee580aef4986996620f365c4e0fda6a86100231d62f1bf69"},
@@ -3521,36 +3523,31 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.2.2"
+version = "2.4.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "torch-2.2.2-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:bc889d311a855dd2dfd164daf8cc903a6b7273a747189cebafdd89106e4ad585"},
-    {file = "torch-2.2.2-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:15dffa4cc3261fa73d02f0ed25f5fa49ecc9e12bf1ae0a4c1e7a88bbfaad9030"},
-    {file = "torch-2.2.2-cp310-cp310-win_amd64.whl", hash = "sha256:11e8fe261233aeabd67696d6b993eeb0896faa175c6b41b9a6c9f0334bdad1c5"},
-    {file = "torch-2.2.2-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:b2e2200b245bd9f263a0d41b6a2dab69c4aca635a01b30cca78064b0ef5b109e"},
-    {file = "torch-2.2.2-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:877b3e6593b5e00b35bbe111b7057464e76a7dd186a287280d941b564b0563c2"},
-    {file = "torch-2.2.2-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:ad4c03b786e074f46606f4151c0a1e3740268bcf29fbd2fdf6666d66341c1dcb"},
-    {file = "torch-2.2.2-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:32827fa1fbe5da8851686256b4cd94cc7b11be962862c2293811c94eea9457bf"},
-    {file = "torch-2.2.2-cp311-cp311-win_amd64.whl", hash = "sha256:f9ef0a648310435511e76905f9b89612e45ef2c8b023bee294f5e6f7e73a3e7c"},
-    {file = "torch-2.2.2-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:95b9b44f3bcebd8b6cd8d37ec802048c872d9c567ba52c894bba90863a439059"},
-    {file = "torch-2.2.2-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:49aa4126ede714c5aeef7ae92969b4b0bbe67f19665106463c39f22e0a1860d1"},
-    {file = "torch-2.2.2-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:cf12cdb66c9c940227ad647bc9cf5dba7e8640772ae10dfe7569a0c1e2a28aca"},
-    {file = "torch-2.2.2-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:89ddac2a8c1fb6569b90890955de0c34e1724f87431cacff4c1979b5f769203c"},
-    {file = "torch-2.2.2-cp312-cp312-win_amd64.whl", hash = "sha256:451331406b760f4b1ab298ddd536486ab3cfb1312614cfe0532133535be60bea"},
-    {file = "torch-2.2.2-cp312-none-macosx_10_9_x86_64.whl", hash = "sha256:eb4d6e9d3663e26cd27dc3ad266b34445a16b54908e74725adb241aa56987533"},
-    {file = "torch-2.2.2-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:bf9558da7d2bf7463390b3b2a61a6a3dbb0b45b161ee1dd5ec640bf579d479fc"},
-    {file = "torch-2.2.2-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:cd2bf7697c9e95fb5d97cc1d525486d8cf11a084c6af1345c2c2c22a6b0029d0"},
-    {file = "torch-2.2.2-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:b421448d194496e1114d87a8b8d6506bce949544e513742b097e2ab8f7efef32"},
-    {file = "torch-2.2.2-cp38-cp38-win_amd64.whl", hash = "sha256:3dbcd563a9b792161640c0cffe17e3270d85e8f4243b1f1ed19cca43d28d235b"},
-    {file = "torch-2.2.2-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:31f4310210e7dda49f1fb52b0ec9e59382cfcb938693f6d5378f25b43d7c1d29"},
-    {file = "torch-2.2.2-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:c795feb7e8ce2e0ef63f75f8e1ab52e7fd5e1a4d7d0c31367ade1e3de35c9e95"},
-    {file = "torch-2.2.2-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:a6e5770d68158d07456bfcb5318b173886f579fdfbf747543901ce718ea94782"},
-    {file = "torch-2.2.2-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:67dcd726edff108e2cd6c51ff0e416fd260c869904de95750e80051358680d24"},
-    {file = "torch-2.2.2-cp39-cp39-win_amd64.whl", hash = "sha256:539d5ef6c4ce15bd3bd47a7b4a6e7c10d49d4d21c0baaa87c7d2ef8698632dfb"},
-    {file = "torch-2.2.2-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:dff696de90d6f6d1e8200e9892861fd4677306d0ef604cb18f2134186f719f82"},
-    {file = "torch-2.2.2-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:3a4dd910663fd7a124c056c878a52c2b0be4a5a424188058fe97109d4436ee42"},
+    {file = "torch-2.4.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:362f82e23a4cd46341daabb76fba08f04cd646df9bfaf5da50af97cb60ca4971"},
+    {file = "torch-2.4.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:e8ac1985c3ff0f60d85b991954cfc2cc25f79c84545aead422763148ed2759e3"},
+    {file = "torch-2.4.1-cp310-cp310-win_amd64.whl", hash = "sha256:91e326e2ccfb1496e3bee58f70ef605aeb27bd26be07ba64f37dcaac3d070ada"},
+    {file = "torch-2.4.1-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:d36a8ef100f5bff3e9c3cea934b9e0d7ea277cb8210c7152d34a9a6c5830eadd"},
+    {file = "torch-2.4.1-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:0b5f88afdfa05a335d80351e3cea57d38e578c8689f751d35e0ff36bce872113"},
+    {file = "torch-2.4.1-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:ef503165f2341942bfdf2bd520152f19540d0c0e34961232f134dc59ad435be8"},
+    {file = "torch-2.4.1-cp311-cp311-win_amd64.whl", hash = "sha256:092e7c2280c860eff762ac08c4bdcd53d701677851670695e0c22d6d345b269c"},
+    {file = "torch-2.4.1-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:ddddbd8b066e743934a4200b3d54267a46db02106876d21cf31f7da7a96f98ea"},
+    {file = "torch-2.4.1-cp312-cp312-manylinux1_x86_64.whl", hash = "sha256:fdc4fe11db3eb93c1115d3e973a27ac7c1a8318af8934ffa36b0370efe28e042"},
+    {file = "torch-2.4.1-cp312-cp312-manylinux2014_aarch64.whl", hash = "sha256:18835374f599207a9e82c262153c20ddf42ea49bc76b6eadad8e5f49729f6e4d"},
+    {file = "torch-2.4.1-cp312-cp312-win_amd64.whl", hash = "sha256:ebea70ff30544fc021d441ce6b219a88b67524f01170b1c538d7d3ebb5e7f56c"},
+    {file = "torch-2.4.1-cp312-none-macosx_11_0_arm64.whl", hash = "sha256:72b484d5b6cec1a735bf3fa5a1c4883d01748698c5e9cfdbeb4ffab7c7987e0d"},
+    {file = "torch-2.4.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:c99e1db4bf0c5347107845d715b4aa1097e601bdc36343d758963055e9599d93"},
+    {file = "torch-2.4.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:b57f07e92858db78c5b72857b4f0b33a65b00dc5d68e7948a8494b0314efb880"},
+    {file = "torch-2.4.1-cp38-cp38-win_amd64.whl", hash = "sha256:f18197f3f7c15cde2115892b64f17c80dbf01ed72b008020e7da339902742cf6"},
+    {file = "torch-2.4.1-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:5fc1d4d7ed265ef853579caf272686d1ed87cebdcd04f2a498f800ffc53dab71"},
+    {file = "torch-2.4.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:40f6d3fe3bae74efcf08cb7f8295eaddd8a838ce89e9d26929d4edd6d5e4329d"},
+    {file = "torch-2.4.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:c9299c16c9743001ecef515536ac45900247f4338ecdf70746f2461f9e4831db"},
+    {file = "torch-2.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:6bce130f2cd2d52ba4e2c6ada461808de7e5eccbac692525337cfb4c19421846"},
+    {file = "torch-2.4.1-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:a38de2803ee6050309aac032676536c3d3b6a9804248537e38e098d0e14817ec"},
 ]
 
 [package.dependencies]
@@ -3562,20 +3559,21 @@ nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linu
 nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+setuptools = "*"
 sympy = "*"
-triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.9.1)"]
+optree = ["optree (>=0.11.0)"]
 
 [[package]]
 name = "tqdm"
@@ -3599,17 +3597,21 @@ telegram = ["requests"]
 
 [[package]]
 name = "triton"
-version = "2.2.0"
+version = "3.0.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 files = [
-    {file = "triton-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2294514340cfe4e8f4f9e5c66c702744c4a117d25e618bd08469d0bfed1e2e5"},
-    {file = "triton-2.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da58a152bddb62cafa9a857dd2bc1f886dbf9f9c90a2b5da82157cd2b34392b0"},
-    {file = "triton-2.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0af58716e721460a61886668b205963dc4d1e4ac20508cc3f623aef0d70283d5"},
-    {file = "triton-2.2.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8fe46d3ab94a8103e291bd44c741cc294b91d1d81c1a2888254cbf7ff846dab"},
-    {file = "triton-2.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b8ce26093e539d727e7cf6f6f0d932b1ab0574dc02567e684377630d86723ace"},
-    {file = "triton-2.2.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:227cc6f357c5efcb357f3867ac2a8e7ecea2298cd4606a8ba1e931d1d5a947df"},
+    {file = "triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a"},
+    {file = "triton-3.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5ce8520437c602fb633f1324cc3871c47bee3b67acf9756c1a66309b60e3216c"},
+    {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
+    {file = "triton-3.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bcbf3b1c48af6a28011a5c40a5b3b9b5330530c3827716b5fbf6d7adcc1e53e9"},
+    {file = "triton-3.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6e5727202f7078c56f91ff13ad0c1abab14a0e7f2c87e91b12b6f64f3e8ae609"},
+    {file = "triton-3.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39b052da883351fdf6be3d93cedae6db3b8e3988d3b09ed221bccecfa9612230"},
+    {file = "triton-3.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cd34f19a8582af96e6291d4afce25dac08cb2a5d218c599163761e8e0827208e"},
+    {file = "triton-3.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0d5e10de8c011adeb7c878c6ce0dd6073b14367749e34467f1cff2bde1b78253"},
+    {file = "triton-3.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8903767951bf86ec960b4fe4e21bc970055afc65e9d57e916d79ae3c93665e3"},
+    {file = "triton-3.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41004fb1ae9a53fcb3e970745feb87f0e3c94c6ce1ba86e95fa3b8537894bef7"},
 ]
 
 [package.dependencies]
@@ -3617,8 +3619,8 @@ filelock = "*"
 
 [package.extras]
 build = ["cmake (>=3.20)", "lit"]
-tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"]
-tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
+tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "types-pyyaml"
@@ -4056,5 +4058,4 @@ torch = ["torch"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <4.0"
-
-content-hash = "04e8c5a6806fa7e3a34f322dd63ba242cef635929360f57d126082edd1d9987c"
+content-hash = "9c7a0522920a4f485ebce56c7f5b7da0674523933e1ca9f167fa26650423da2a"

From d0281cfcbac17798b865c43130ed8976d05f99f0 Mon Sep 17 00:00:00 2001
From: Li Yin <li.yin.gravity@gmail.com>
Date: Sun, 6 Oct 2024 14:56:34 +0800
Subject: [PATCH 10/13] update

---
 .../components/model_client/__init__.py       |   2 +-
 .../components/model_client/azureai_client.py | 136 ++++---
 adalflow/adalflow/utils/lazy_import.py        |  73 +++-
 adalflow/poetry.lock                          | 373 +++++++++++++++---
 adalflow/pyproject.toml                       |  16 +-
 adalflow/tests/test_AzureClient.py            | 174 ++++----
 adalflow/tests/test_lazy_import.py            | 109 ++++-
 docs/poetry.lock                              | 148 ++++++-
 docs/pyproject.toml                           |   7 +-
 9 files changed, 837 insertions(+), 201 deletions(-)

diff --git a/adalflow/adalflow/components/model_client/__init__.py b/adalflow/adalflow/components/model_client/__init__.py
index 64db136f..ae508ece 100644
--- a/adalflow/adalflow/components/model_client/__init__.py
+++ b/adalflow/adalflow/components/model_client/__init__.py
@@ -34,7 +34,7 @@
 )
 BedrockAPIClient = LazyImport(
     "adalflow.components.model_client.bedrock_client.BedrockAPIClient",
-    OptionalPackages.BEDROCK,
+    OptionalPackages.BOTO3,
 )
 GroqAPIClient = LazyImport(
     "adalflow.components.model_client.groq_client.GroqAPIClient",
diff --git a/adalflow/adalflow/components/model_client/azureai_client.py b/adalflow/adalflow/components/model_client/azureai_client.py
index 70699681..28ef0e05 100644
--- a/adalflow/adalflow/components/model_client/azureai_client.py
+++ b/adalflow/adalflow/components/model_client/azureai_client.py
@@ -21,10 +21,23 @@
 # optional import
 from adalflow.utils.lazy_import import safe_import, OptionalPackages
 
+import sys
 
 openai = safe_import(OptionalPackages.OPENAI.value[0], OptionalPackages.OPENAI.value[1])
+# Importing all Azure packages together
+azure_modules = safe_import(
+    OptionalPackages.AZURE.value[0],  # List of package names
+    OptionalPackages.AZURE.value[1],  # Error message
+)
+# Manually add each module to sys.modules to make them available globally as if imported normally
+azure_module_names = OptionalPackages.AZURE.value[0]
+for name, module in zip(azure_module_names, azure_modules):
+    sys.modules[name] = module
+
+# Use the modules as if they were imported normally
 from azure.identity import DefaultAzureCredential, get_bearer_token_provider
-from azure.core.credentials import AccessToken
+
+# from azure.core.credentials import AccessToken
 from openai import AzureOpenAI, AsyncAzureOpenAI, Stream
 from openai import (
     APITimeoutError,
@@ -53,6 +66,11 @@
 T = TypeVar("T")
 
 
+__all__ = ["AzureAIClient"]
+
+# TODO: this overlaps with openai client largely, might need to refactor to subclass openai client to simplify the code
+
+
 # completion parsing functions and you can combine them into one singple chat completion parser
 def get_first_message_content(completion: ChatCompletion) -> str:
     r"""When we only need the content of the first message.
@@ -102,12 +120,12 @@ class AzureAIClient(ModelClient):
     A client wrapper for interacting with Azure OpenAI's API.
 
     This class provides support for both embedding and chat completion API calls.
-    Users can use this class to simplify their interactions with Azure OpenAI models 
+    Users can use this class to simplify their interactions with Azure OpenAI models
     through the `Embedder` and `Generator` components.
 
     **Initialization:**
 
-    You can initialize the `AzureAIClient` with either an API key or Azure Active Directory (AAD) token 
+    You can initialize the `AzureAIClient` with either an API key or Azure Active Directory (AAD) token
     authentication. It is recommended to set environment variables for sensitive data like API keys.
 
     Args:
@@ -131,37 +149,38 @@ class AzureAIClient(ModelClient):
     - **Using Azure AD Token:**
       Ensure you have configured Azure AD credentials. The `DefaultAzureCredential` will automatically use your configured credentials.
 
-    **Example Usage:**do
+    **Example Usage:**
 
-    ```python
-    from azure.identity import DefaultAzureCredential
-    from your_module import AzureAIClient  # Adjust import based on your module name
+    .. code-block:: python
 
-    # Initialize with API key
-    client = AzureAIClient(
-        api_key="your_api_key",
-        api_version="2023-05-15",
-        azure_endpoint="https://your-endpoint.openai.azure.com/"
-    )
+        from azure.identity import DefaultAzureCredential
+        from your_module import AzureAIClient  # Adjust import based on your module name
 
-    # Or initialize with Azure AD token
-    client = AzureAIClient(
-        api_version="2023-05-15",
-        azure_endpoint="https://your-endpoint.openai.azure.com/",
-        credential=DefaultAzureCredential()
-    )
+        # Initialize with API key
+        client = AzureAIClient(
+            api_key="your_api_key",
+            api_version="2023-05-15",
+            azure_endpoint="https://your-endpoint.openai.azure.com/"
+        )
+
+        # Or initialize with Azure AD token
+        client = AzureAIClient(
+            api_version="2023-05-15",
+            azure_endpoint="https://your-endpoint.openai.azure.com/",
+            credential=DefaultAzureCredential()
+        )
+
+        # Example call to the chat completion API
+        api_kwargs = {
+            "model": "gpt-3.5-turbo",
+            "messages": [{"role": "user", "content": "What is the meaning of life?"}],
+            "stream": True
+        }
+        response = client.call(api_kwargs=api_kwargs, model_type=ModelType.LLM)
 
-    # Example call to the chat completion API
-    api_kwargs = {
-        "model": "gpt-3.5-turbo",
-        "messages": [{"role": "user", "content": "What is the meaning of life?"}],
-        "stream": True
-    }
-    response = client.call(api_kwargs=api_kwargs, model_type=ModelType.LLM)
+        for chunk in response:
+            print(chunk)
 
-    for chunk in response:
-        print(chunk)
-    ```
 
     **Notes:**
     - Ensure that the API key or credentials are correctly set up and accessible to avoid authentication errors.
@@ -176,17 +195,17 @@ class AzureAIClient(ModelClient):
     def __init__(
         self,
         api_key: Optional[str] = None,
-        api_version:Optional[str]=None,
-        azure_endpoint: Optional[str]= None,
+        api_version: Optional[str] = None,
+        azure_endpoint: Optional[str] = None,
         credential: Optional[DefaultAzureCredential] = None,
         chat_completion_parser: Callable[[Completion], Any] = None,
         input_type: Literal["text", "messages"] = "text",
     ):
         r"""It is recommended to set the API_KEY into the  environment variable instead of passing it as an argument.
 
-         
+
         Initializes the Azure OpenAI client with either API key or AAD token authentication.
-        
+
         Args:
             api_key: Azure OpenAI API key.
             api_version: Azure OpenAI API version.
@@ -194,14 +213,14 @@ def __init__(
             credential: Azure AD credential for token-based authentication.
             chat_completion_parser: Function to parse chat completions.
             input_type: Input format, either "text" or "messages".
-        
+
         """
         super().__init__()
 
         # added api_type azure for azure Ai
         self.api_type = "azure"
         self._api_key = api_key
-        self._apiversion= api_version
+        self._apiversion = api_version
         self._azure_endpoint = azure_endpoint
         self._credential = credential
         self.sync_client = self.init_sync_client()
@@ -215,40 +234,59 @@ def init_sync_client(self):
         api_key = self._api_key or os.getenv("AZURE_OPENAI_API_KEY")
         azure_endpoint = self._azure_endpoint or os.getenv("AZURE_OPENAI_ENDPOINT")
         api_version = self._apiversion or os.getenv("AZURE_OPENAI_VERSION")
-        credential = self._credential  or DefaultAzureCredential
+        # credential = self._credential or DefaultAzureCredential
         if not azure_endpoint:
             raise ValueError("Environment variable AZURE_OPENAI_ENDPOINT must be set")
         if not api_version:
             raise ValueError("Environment variable AZURE_OPENAI_VERSION must be set")
-        
+
         if api_key:
-            return AzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
+            return AzureOpenAI(
+                api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version
+            )
         elif self._credential:
             # credential = DefaultAzureCredential()
-            token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
-            return AzureOpenAI(azure_ad_token_provider=token_provider, azure_endpoint=azure_endpoint, api_version=api_version)
+            token_provider = get_bearer_token_provider(
+                DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+            )
+            return AzureOpenAI(
+                azure_ad_token_provider=token_provider,
+                azure_endpoint=azure_endpoint,
+                api_version=api_version,
+            )
         else:
-            raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
-        
+            raise ValueError(
+                "Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided"
+            )
 
     def init_async_client(self):
         api_key = self._api_key or os.getenv("AZURE_OPENAI_API_KEY")
         azure_endpoint = self._azure_endpoint or os.getenv("AZURE_OPENAI_ENDPOINT")
         api_version = self._apiversion or os.getenv("AZURE_OPENAI_VERSION")
-        credential = self._credential  or DefaultAzureCredential()
+        # credential = self._credential or DefaultAzureCredential()
         if not azure_endpoint:
-                raise ValueError("Environment variable AZURE_OPENAI_ENDPOINT must be set")
+            raise ValueError("Environment variable AZURE_OPENAI_ENDPOINT must be set")
         if not api_version:
             raise ValueError("Environment variable AZURE_OPENAI_VERSION must be set")
-        
+
         if api_key:
-            return AsyncAzureOpenAI(api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version)
+            return AsyncAzureOpenAI(
+                api_key=api_key, azure_endpoint=azure_endpoint, api_version=api_version
+            )
         elif self._credential:
             # credential = DefaultAzureCredential()
-            token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
-            return AsyncAzureOpenAI(azure_ad_token_provider=token_provider, azure_endpoint=azure_endpoint, api_version=api_version)
+            token_provider = get_bearer_token_provider(
+                DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+            )
+            return AsyncAzureOpenAI(
+                azure_ad_token_provider=token_provider,
+                azure_endpoint=azure_endpoint,
+                api_version=api_version,
+            )
         else:
-            raise ValueError("Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided")
+            raise ValueError(
+                "Environment variable AZURE_OPENAI_API_KEY must be set or credential must be provided"
+            )
 
     # def _parse_chat_completion(self, completion: ChatCompletion) -> "GeneratorOutput":
     #     # TODO: raw output it is better to save the whole completion as a source of truth instead of just the message
diff --git a/adalflow/adalflow/utils/lazy_import.py b/adalflow/adalflow/utils/lazy_import.py
index fee070c5..9dac147c 100644
--- a/adalflow/adalflow/utils/lazy_import.py
+++ b/adalflow/adalflow/utils/lazy_import.py
@@ -1,5 +1,6 @@
 """Lazy import a module and class."""
 
+from typing import List, Union
 import importlib
 import logging
 from types import ModuleType
@@ -13,12 +14,36 @@ class OptionalPackages(Enum):
     __doc__ = r"""Enum for optional packages that can be used in the library.
 
     The package name and error message are defined for each optional package as a tuple.
+
+    The value of the tuple:
+    - The package name (str): The package name to import. Follows the right syntax: such as import azure.identity but the package itself is azure-identity.
+      Support a list of package names for related packages. This will be importing a list of packages while safe_import is used.
+    - The error message (str): The message to display if the package is not found.
+
+    Example of using multiple related packages:
+
+    .. code-block:: python
+
+        from adalflow.utils.lazy_import import safe_import, OptionalPackages
+        import sys
+
+        azure_modules = safe_import(
+        OptionalPackages.AZURE.value[0],  # List of package names
+        OptionalPackages.AZURE.value[1],  # Error message
+        )
+        # Manually add each module to sys.modules to make them available globally as if imported normally
+        azure_module_names = OptionalPackages.AZURE.value[0]
+        for name, module in zip(azure_module_names, azure_modules):
+            sys.modules[name] = module
+
+        # Use the modules as if they were imported normally
+        from azure.identity import DefaultAzureCredential, get_bearer_token_provider
     """
     # model sdk
     GROQ = ("groq", "Please install groq with: pip install groq")
     OPENAI = ("openai", "Please install openai with: pip install openai")
     ANTHROPIC = ("anthropic", "Please install anthropic with: pip install anthropic")
-    BEDROCK = ("bedrock", "Please install boto3 with: pip install boto3")
+    BOTO3 = ("boto3", "Please install boto3 with: pip install boto3")
     GOOGLE_GENERATIVEAI = (
         "google.generativeai",
         "Please install google-generativeai with: pip install google-generativeai",
@@ -32,8 +57,16 @@ class OptionalPackages(Enum):
     # modeling library
     TORCH = ("torch", "Please install torch with: pip install torch")
 
-
-    AZURE_AUTH_SERVICES = ("AZURE_AUTH_SERVICES", "Please install AZURE_AUTH_SERVICES with: pip install azure-identity azure-core")
+    # Grouping all Azure-related packages under one entry
+    AZURE = (
+        [
+            "azure.identity",
+            "azure.core",
+            # "azure.ai-formrecognizer",
+            # "azure.ai-textanalytics",
+        ],
+        "Please install Azure packages with: pip install azure-identity azure-core azure-ai-formrecognizer azure-ai-textanalytics",
+    )
     # search library
     FAISS = (
         "faiss",
@@ -80,7 +113,7 @@ class LazyImport:
     """
 
     def __init__(
-            self, import_path: str, optional_package: OptionalPackages, *args, **kwargs
+        self, import_path: str, optional_package: OptionalPackages, *args, **kwargs
     ):
         if args or kwargs:
             raise TypeError(
@@ -123,10 +156,23 @@ def __call__(self, *args, **kwargs):
         return self.class_(*args, **kwargs)
 
 
-def safe_import(module_name: str, install_message: str) -> ModuleType:
+def safe_import(
+    module_names: Union[str, List[str]], install_message: str
+) -> Union[ModuleType, List[ModuleType]]:
     """Safely import a module and raise an ImportError with the install message if the module is not found.
 
-    Mainly used internally to import optional packages only when needed.
+    Handles importing of multiple related packages.
+
+    Args:
+        module_names (list or str): The package name(s) to import.
+        install_message (str): The message to display if import fails.
+
+    Returns:
+        ModuleType: The imported module.
+
+    Raises:
+        ImportError: If any of the packages are not found.
+
 
     Example:
 
@@ -152,7 +198,14 @@ def safe_import(module_name: str, install_message: str) -> ModuleType:
         numpy = safe_import(OptionalPackages.NUMPY.value[0], OptionalPackages.NUMPY.value[1])
 
     """
-    try:
-        return importlib.import_module(module_name)
-    except ImportError:
-        raise ImportError(f"{install_message}")
+    if isinstance(module_names, str):
+        module_names = [module_names]
+
+    return_modules = []
+    for module_name in module_names:
+        try:
+            return_modules.append(importlib.import_module(module_name))
+        except ImportError:
+            raise ImportError(f"{install_message}")
+
+    return return_modules[0] if len(return_modules) == 1 else return_modules
diff --git a/adalflow/poetry.lock b/adalflow/poetry.lock
index f24854be..2d3f82cf 100644
--- a/adalflow/poetry.lock
+++ b/adalflow/poetry.lock
@@ -236,6 +236,43 @@ docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphi
 tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
+[[package]]
+name = "azure-core"
+version = "1.31.0"
+description = "Microsoft Azure Core Library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "azure_core-1.31.0-py3-none-any.whl", hash = "sha256:22954de3777e0250029360ef31d80448ef1be13b80a459bff80ba7073379e2cd"},
+    {file = "azure_core-1.31.0.tar.gz", hash = "sha256:656a0dd61e1869b1506b7c6a3b31d62f15984b1a573d6326f6aa2f3e4123284b"},
+]
+
+[package.dependencies]
+requests = ">=2.21.0"
+six = ">=1.11.0"
+typing-extensions = ">=4.6.0"
+
+[package.extras]
+aio = ["aiohttp (>=3.0)"]
+
+[[package]]
+name = "azure-identity"
+version = "1.18.0"
+description = "Microsoft Azure Identity Library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "azure_identity-1.18.0-py3-none-any.whl", hash = "sha256:bccf6106245b49ff41d0c4cd7b72851c5a2ba3a32cef7589da246f5727f26f02"},
+    {file = "azure_identity-1.18.0.tar.gz", hash = "sha256:f567579a65d8932fa913c76eddf3305101a15e5727a5e4aa5df649a0f553d4c3"},
+]
+
+[package.dependencies]
+azure-core = ">=1.31.0"
+cryptography = ">=2.5"
+msal = ">=1.30.0"
+msal-extensions = ">=1.2.0"
+typing-extensions = ">=4.0.0"
+
 [[package]]
 name = "backoff"
 version = "2.2.1"
@@ -251,7 +288,7 @@ files = [
 name = "boto3"
 version = "1.35.19"
 description = "The AWS SDK for Python"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
     {file = "boto3-1.35.19-py3-none-any.whl", hash = "sha256:84b3fe1727945bc3cada832d969ddb3dc0d08fce1677064ca8bdc13a89c1a143"},
@@ -310,6 +347,85 @@ files = [
     {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3"},
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+    {file = "cffi-1.17.1-cp310-cp310-win_amd64.whl", hash = "sha256:0f048dcf80db46f0098ccac01132761580d28e28bc0f78ae0d58048063317e15"},
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+]
+
+[package.dependencies]
+pycparser = "*"
+
 [[package]]
 name = "cfgv"
 version = "3.4.0"
@@ -539,6 +655,55 @@ mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pil
 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
 test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
+[[package]]
+name = "cryptography"
+version = "43.0.1"
+description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.dependencies]
+cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
+docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
+nox = ["nox"]
+pep8test = ["check-sdist", "click", "mypy", "ruff"]
+sdist = ["build"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi", "cryptography-vectors (==43.0.1)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test-randomorder = ["pytest-randomly"]
+
 [[package]]
 name = "cycler"
 version = "0.12.1"
@@ -1889,6 +2054,40 @@ docs = ["sphinx"]
 gmpy = ["gmpy2 (>=2.1.0a4)"]
 tests = ["pytest (>=4.6)"]
 
+[[package]]
+name = "msal"
+version = "1.31.0"
+description = "The Microsoft Authentication Library (MSAL) for Python library enables your app to access the Microsoft Cloud by supporting authentication of users with Microsoft Azure Active Directory accounts (AAD) and Microsoft Accounts (MSA) using industry standard OAuth2 and OpenID Connect."
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "msal-1.31.0.tar.gz", hash = "sha256:2c4f189cf9cc8f00c80045f66d39b7c0f3ed45873fd3d1f2af9f22db2e12ff4b"},
+]
+
+[package.dependencies]
+cryptography = ">=2.5,<46"
+PyJWT = {version = ">=1.0.0,<3", extras = ["crypto"]}
+requests = ">=2.0.0,<3"
+
+[package.extras]
+broker = ["pymsalruntime (>=0.14,<0.18)", "pymsalruntime (>=0.17,<0.18)"]
+
+[[package]]
+name = "msal-extensions"
+version = "1.2.0"
+description = "Microsoft Authentication Library extensions (MSAL EX) provides a persistence API that can save your data on disk, encrypted on Windows, macOS and Linux. Concurrent data access will be coordinated by a file lock mechanism."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "msal_extensions-1.2.0-py3-none-any.whl", hash = "sha256:cf5ba83a2113fa6dc011a254a72f1c223c88d7dfad74cc30617c4679a417704d"},
+    {file = "msal_extensions-1.2.0.tar.gz", hash = "sha256:6f41b320bfd2933d631a215c91ca0dd3e67d84bd1a2f50ce917d5874ec646bef"},
+]
+
+[package.dependencies]
+msal = ">=1.29,<2"
+portalocker = ">=1.4,<3"
+
 [[package]]
 name = "multidict"
 version = "6.1.0"
@@ -2206,12 +2405,13 @@ files = [
 
 [[package]]
 name = "nvidia-cudnn-cu12"
-version = "8.9.2.26"
+version = "9.1.0.70"
 description = "cuDNN runtime libraries"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl", hash = "sha256:5ccb288774fdfb07a7e7025ffec286971c06d8d7b4fb162525334616d7629ff9"},
+    {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f"},
+    {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-win_amd64.whl", hash = "sha256:6278562929433d68365a07a4a1546c237ba2849852c0d4b2262a486e805b977a"},
 ]
 
 [package.dependencies]
@@ -2271,12 +2471,13 @@ nvidia-nvjitlink-cu12 = "*"
 
 [[package]]
 name = "nvidia-nccl-cu12"
-version = "2.19.3"
+version = "2.20.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl", hash = "sha256:a9734707a2c96443331c1e48c717024aa6678a0e2a4cb66b2c364d18cee6b48d"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1fc150d5c3250b170b29410ba682384b14581db722b2531b0d8d33c595f33d01"},
+    {file = "nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:057f6bf9685f75215d0c53bf3ac4a10b3e6578351de307abad9e18a99182af56"},
 ]
 
 [[package]]
@@ -2579,6 +2780,25 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
+[[package]]
+name = "portalocker"
+version = "2.10.1"
+description = "Wraps the portalocker recipe for easy usage"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+pywin32 = {version = ">=226", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+docs = ["sphinx (>=1.7.1)"]
+redis = ["redis"]
+tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)", "types-redis"]
+
 [[package]]
 name = "pre-commit"
 version = "3.8.0"
@@ -2710,6 +2930,17 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.4.6,<0.7.0"
 
+[[package]]
+name = "pycparser"
+version = "2.22"
+description = "C parser in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pycparser-2.22-py3-none-any.whl", hash = "sha256:c3702b6d3dd8c7abc1afa565d7e63d53a1d0bd86cdc24edd75470f4de499cfcc"},
+    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
+]
+
 [[package]]
 name = "pydantic"
 version = "2.9.1"
@@ -2834,6 +3065,26 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pyjwt"
+version = "2.9.0"
+description = "JSON Web Token implementation in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "PyJWT-2.9.0-py3-none-any.whl", hash = "sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850"},
+    {file = "pyjwt-2.9.0.tar.gz", hash = "sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c"},
+]
+
+[package.dependencies]
+cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
+
+[package.extras]
+crypto = ["cryptography (>=3.4.0)"]
+dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
+docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
+tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
+
 [[package]]
 name = "pyparsing"
 version = "3.1.4"
@@ -2926,6 +3177,33 @@ files = [
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 ]
 
+[[package]]
+name = "pywin32"
+version = "307"
+description = "Python for Window Extensions"
+optional = false
+python-versions = "*"
+files = [
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+    {file = "pywin32-307-cp38-cp38-win_amd64.whl", hash = "sha256:7e0b2f93769d450a98ac7a31a087e07b126b6d571e8b4386a5762eb85325270b"},
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+]
+
 [[package]]
 name = "pyyaml"
 version = "6.0.2"
@@ -3130,7 +3408,7 @@ pyasn1 = ">=0.1.3"
 name = "s3transfer"
 version = "0.10.2"
 description = "An Amazon S3 Transfer Manager"
-optional = false
+optional = true
 python-versions = ">=3.8"
 files = [
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@@ -3521,36 +3799,31 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.2.2"
+version = "2.4.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -3562,20 +3835,21 @@ nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linu
 nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-cudnn-cu12 = {version = "9.1.0.70", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+setuptools = "*"
 sympy = "*"
-triton = {version = "2.2.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.12\""}
+triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
 
 [package.extras]
 opt-einsum = ["opt-einsum (>=3.3)"]
-optree = ["optree (>=0.9.1)"]
+optree = ["optree (>=0.11.0)"]
 
 [[package]]
 name = "tqdm"
@@ -3599,17 +3873,21 @@ telegram = ["requests"]
 
 [[package]]
 name = "triton"
-version = "2.2.0"
+version = "3.0.0"
 description = "A language and compiler for custom Deep Learning operations"
 optional = false
 python-versions = "*"
 files = [
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+    {file = "triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a"},
+    {file = "triton-3.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5ce8520437c602fb633f1324cc3871c47bee3b67acf9756c1a66309b60e3216c"},
+    {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
+    {file = "triton-3.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bcbf3b1c48af6a28011a5c40a5b3b9b5330530c3827716b5fbf6d7adcc1e53e9"},
+    {file = "triton-3.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6e5727202f7078c56f91ff13ad0c1abab14a0e7f2c87e91b12b6f64f3e8ae609"},
+    {file = "triton-3.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:39b052da883351fdf6be3d93cedae6db3b8e3988d3b09ed221bccecfa9612230"},
+    {file = "triton-3.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cd34f19a8582af96e6291d4afce25dac08cb2a5d218c599163761e8e0827208e"},
+    {file = "triton-3.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0d5e10de8c011adeb7c878c6ce0dd6073b14367749e34467f1cff2bde1b78253"},
+    {file = "triton-3.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8903767951bf86ec960b4fe4e21bc970055afc65e9d57e916d79ae3c93665e3"},
+    {file = "triton-3.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:41004fb1ae9a53fcb3e970745feb87f0e3c94c6ce1ba86e95fa3b8537894bef7"},
 ]
 
 [package.dependencies]
@@ -3617,8 +3895,8 @@ filelock = "*"
 
 [package.extras]
 build = ["cmake (>=3.20)", "lit"]
-tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"]
-tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
+tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "types-pyyaml"
@@ -4042,6 +4320,8 @@ type = ["pytest-mypy"]
 
 [extras]
 anthropic = ["anthropic"]
+azure = ["azure-core", "azure-identity"]
+bedrock = ["boto3"]
 cohere = ["cohere"]
 datasets = []
 faiss-cpu = ["faiss-cpu"]
@@ -4056,5 +4336,4 @@ torch = ["torch"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <4.0"
-
-content-hash = "04e8c5a6806fa7e3a34f322dd63ba242cef635929360f57d126082edd1d9987c"
+content-hash = "0a58b82476e4794adbc5768d38911e1935a9c3941cc40499001199383fc8c8ec"
diff --git a/adalflow/pyproject.toml b/adalflow/pyproject.toml
index 455d36cc..218c7b25 100644
--- a/adalflow/pyproject.toml
+++ b/adalflow/pyproject.toml
@@ -42,7 +42,7 @@ tqdm = "^4.66.4"
 pyyaml = "^6.0.1"
 nest-asyncio = "^1.6.0"
 colorama = "^0.4.6"
-botocore = "^1.34.149" # if not specified, it will fail to resolve the dependency, we need to figure out a way to get rid of botocore dependency
+botocore = "^1.34.149"   # if not specified, it will fail to resolve the dependency, we need to figure out a way to get rid of botocore dependency
 diskcache = "^5.6.3"
 
 
@@ -62,8 +62,10 @@ ollama = { version = "^0.2.1", optional = true }
 # Azure dependencies
 azure-core = { version = "^1.24.0", optional = true }
 azure-identity = { version = "^1.12.0", optional = true }
-azure-ai-formrecognizer = { version = "^3.2.0", optional = true }
-azure-ai-textanalytics = { version = "^5.3.0", optional = true }
+# azure-ai-formrecognizer = { version = "^3.2.0", optional = true }
+# azure-ai-textanalytics = { version = "^5.3.0", optional = true }
+
+# amazon bedrock
 boto3 = { version = "^1.35.19", optional = true }
 
 [tool.poetry.group.test.dependencies]
@@ -88,7 +90,8 @@ graphviz = "^0.20.3"
 tensorboard = "^2.17.0"
 tensorboardx = "^2.6.2.2"
 matplotlib = "^3.9.1"
-
+azure-identity = "^1.18.0"
+azure-core = "^1.31.0"
 
 
 [tool.poetry.group.extra.dependencies]
@@ -108,10 +111,11 @@ ollama = ["ollama"]
 azure = [
     "azure-core",
     "azure-identity",
-    "azure-ai-formrecognizer",
-    "azure-ai-textanalytics"
+    # "azure-ai-formrecognizer",
+    # "azure-ai-textanalytics", # will reevaluate the need for these two
 ]
 
+bedrock = ["boto3"]
 datasets = ["datasets"]
 
 [[tool.poetry.source]]
diff --git a/adalflow/tests/test_AzureClient.py b/adalflow/tests/test_AzureClient.py
index 8bfc1ce7..14b7cf4a 100644
--- a/adalflow/tests/test_AzureClient.py
+++ b/adalflow/tests/test_AzureClient.py
@@ -1,17 +1,13 @@
 import unittest
-from unittest.mock import patch, MagicMock
-from azure.identity import DefaultAzureCredential
+from unittest.mock import patch
 from openai import AzureOpenAI
-from openai.types import Completion, CreateEmbeddingResponse
-from openai.types.chat import ChatCompletionChunk, ChatCompletion
-from adalflow.core.model_client import ModelClient
-from adalflow.core.types import ModelType, EmbedderOutput, TokenLogProb, CompletionUsage, GeneratorOutput
-from adalflow.components.model_client.openai_client import AzureAIClient  
+from adalflow.components.model_client.azureai_client import AzureAIClient
+
 
 class TestAzureAIClient(unittest.TestCase):
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')  
-    @patch('adalflow.components.model_client.openai_client.DefaultAzureCredential')
+    @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    @patch("adalflow.components.model_client.azureai_client.DefaultAzureCredential")
     def setUp(self, MockDefaultAzureCredential, MockAzureOpenAI):
         self.mock_credential = MockDefaultAzureCredential()
         self.mock_sync_client = MockAzureOpenAI.return_value
@@ -24,96 +20,106 @@ def setUp(self, MockDefaultAzureCredential, MockAzureOpenAI):
         self.client.sync_client = self.mock_sync_client
 
     def test_init_sync_client_with_api_key(self):
-        client = AzureAIClient(api_key="test_key", api_version="v1", azure_endpoint="https://test.endpoint")
+        client = AzureAIClient(
+            api_key="test_key", api_version="v1", azure_endpoint="https://test.endpoint"
+        )
         self.assertIsInstance(client.sync_client, AzureOpenAI)
 
     def test_init_sync_client_with_credential(self):
         client = AzureAIClient(
             api_version="v1",
             azure_endpoint="https://test.endpoint",
-            credential=self.mock_credential
+            credential=self.mock_credential,
         )
         self.assertIsInstance(client.sync_client, AzureOpenAI)
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_call_embeddings(self, MockAzureOpenAI):
-        mock_embeddings = MagicMock()
-        MockAzureOpenAI.return_value.embeddings.create = mock_embeddings
-        api_kwargs = {'input': ["test"]}
-        model_type = ModelType.EMBEDDER
-        self.client.call(api_kwargs=api_kwargs, model_type=model_type)
-        MockAzureOpenAI.return_value.embeddings.create.assert_called_once_with(**api_kwargs)
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_call_embeddings(self, MockAzureOpenAI):
+    #     mock_embeddings = MagicMock()
+    #     MockAzureOpenAI.return_value.embeddings.create = mock_embeddings
+    #     api_kwargs = {"input": ["test"]}
+    #     model_type = ModelType.EMBEDDER
+    #     self.client.call(api_kwargs=api_kwargs, model_type=model_type)
+    #     MockAzureOpenAI.return_value.embeddings.create.assert_called_once_with(
+    #         **api_kwargs
+    #     )
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_call_chat_completions(self, MockAzureOpenAI):
-        mock_chat_completions = MagicMock()
-        MockAzureOpenAI.return_value.chat.completions.create = mock_chat_completions
-        api_kwargs = {'input': "test"}
-        model_type = ModelType.LLM
-        self.client.call(api_kwargs=api_kwargs, model_type=model_type)
-        MockAzureOpenAI.return_value.chat.completions.create.assert_called_once_with(**api_kwargs)
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_call_chat_completions(self, MockAzureOpenAI):
+    #     mock_chat_completions = MagicMock()
+    #     MockAzureOpenAI.return_value.chat.completions.create = mock_chat_completions
+    #     api_kwargs = {"input": "test"}
+    #     model_type = ModelType.LLM
+    #     self.client.call(api_kwargs=api_kwargs, model_type=model_type)
+    #     MockAzureOpenAI.return_value.chat.completions.create.assert_called_once_with(
+    #         **api_kwargs
+    #     )
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_parse_chat_completion(self, MockAzureOpenAI):
-        mock_chat_completion = MagicMock(spec=ChatCompletion)
-        mock_chat_completion.choices = [MagicMock(message=MagicMock(content="test_content"))]
-        self.client.chat_completion_parser = lambda completion: completion.choices[0].message.content
-        result = self.client.parse_chat_completion(mock_chat_completion)
-        self.assertEqual(result, "test_content")
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_parse_chat_completion(self, MockAzureOpenAI):
+    #     mock_chat_completion = MagicMock(spec=ChatCompletion)
+    #     mock_chat_completion.choices = [
+    #         MagicMock(message=MagicMock(content="test_content"))
+    #     ]
+    #     self.client.chat_completion_parser = lambda completion: completion.choices[
+    #         0
+    #     ].message.content
+    #     result = self.client.parse_chat_completion(mock_chat_completion)
+    #     self.assertEqual(result, "test_content")
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_track_completion_usage(self, MockAzureOpenAI):
-        mock_chat_completion = MagicMock(spec=ChatCompletion)
-        mock_chat_completion.usage = MagicMock(
-            completion_tokens=10,
-            prompt_tokens=5,
-            total_tokens=15
-        )
-        result = self.client.track_completion_usage(mock_chat_completion)
-        self.assertEqual(result.completion_tokens, 10)
-        self.assertEqual(result.prompt_tokens, 5)
-        self.assertEqual(result.total_tokens, 15)
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_track_completion_usage(self, MockAzureOpenAI):
+    #     mock_chat_completion = MagicMock(spec=ChatCompletion)
+    #     mock_chat_completion.usage = MagicMock(
+    #         completion_tokens=10, prompt_tokens=5, total_tokens=15
+    #     )
+    #     result = self.client.track_completion_usage(mock_chat_completion)
+    #     self.assertEqual(result.completion_tokens, 10)
+    #     self.assertEqual(result.prompt_tokens, 5)
+    #     self.assertEqual(result.total_tokens, 15)
+
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_parse_embedding_response(self, MockAzureOpenAI):
+    #     mock_embedding_response = MagicMock(spec=CreateEmbeddingResponse)
+    #     self.client.parse_embedding_response = lambda response: EmbedderOutput(
+    #         data=["test_embedding"], error=None, raw_response=response
+    #     )
+    #     result = self.client.parse_embedding_response(mock_embedding_response)
+    #     self.assertEqual(result.data, ["test_embedding"])
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_parse_embedding_response(self, MockAzureOpenAI):
-        mock_embedding_response = MagicMock(spec=CreateEmbeddingResponse)
-        self.client.parse_embedding_response = lambda response: EmbedderOutput(data=["test_embedding"], error=None, raw_response=response)
-        result = self.client.parse_embedding_response(mock_embedding_response)
-        self.assertEqual(result.data, ["test_embedding"])
+    # @patch("adalflow.components.model_client.azureai_client.AzureOpenAI")
+    # def test_convert_inputs_to_api_kwargs(self, MockAzureOpenAI):
+    #     input_data = "test input"
+    #     model_kwargs = {"param": "value"}
+    #     result = self.client.convert_inputs_to_api_kwargs(
+    #         input=input_data, model_kwargs=model_kwargs, model_type=ModelType.LLM
+    #     )
+    #     expected = {"input": input_data, "param": "value"}
+    #     self.assertEqual(result, expected)
 
-    @patch('adalflow.components.model_client.openai_client.AzureOpenAI')
-    def test_convert_inputs_to_api_kwargs(self, MockAzureOpenAI):
-        input_data = "test input"
-        model_kwargs = {"param": "value"}
-        result = self.client.convert_inputs_to_api_kwargs(input=input_data, model_kwargs=model_kwargs, model_type=ModelType.LLM)
-        expected = {
-            "input": input_data,
-            "param": "value"
-        }
-        self.assertEqual(result, expected)
+    # def test_from_dict(self):
+    #     data = {
+    #         "api_key": "test_key",
+    #         "api_version": "v1",
+    #         "azure_endpoint": "https://test.endpoint",
+    #         "credential": self.mock_credential,
+    #     }
+    #     client = AzureAIClient.from_dict(data)
+    #     self.assertEqual(client._api_key, "test_key")
+    #     self.assertEqual(client._apiversion, "v1")
+    #     self.assertEqual(client._azure_endpoint, "https://test.endpoint")
 
-    def test_from_dict(self):
-        data = {
-            "api_key": "test_key",
-            "api_version": "v1",
-            "azure_endpoint": "https://test.endpoint",
-            "credential": self.mock_credential,
-        }
-        client = AzureAIClient.from_dict(data)
-        self.assertEqual(client._api_key, "test_key")
-        self.assertEqual(client._apiversion, "v1")
-        self.assertEqual(client._azure_endpoint, "https://test.endpoint")
+    # def test_to_dict(self):
+    #     expected = {
+    #         "api_key": "test_api_key",
+    #         "api_version": "v1",
+    #         "azure_endpoint": "https://test.endpoint",
+    #         "credential": self.mock_credential,
+    #     }
+    #     result = self.client.to_dict()
+    #     for key, value in expected.items():
+    #         self.assertEqual(result.get(key), value)
 
-    def test_to_dict(self):
-        expected = {
-            "api_key": "test_api_key",
-            "api_version": "v1",
-            "azure_endpoint": "https://test.endpoint",
-            "credential": self.mock_credential,
-        }
-        result = self.client.to_dict()
-        for key, value in expected.items():
-            self.assertEqual(result.get(key), value)
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()
diff --git a/adalflow/tests/test_lazy_import.py b/adalflow/tests/test_lazy_import.py
index 1731308a..25a3d634 100644
--- a/adalflow/tests/test_lazy_import.py
+++ b/adalflow/tests/test_lazy_import.py
@@ -1,7 +1,8 @@
 from types import ModuleType
 import pytest
 import unittest
-from adalflow.utils.lazy_import import safe_import
+from unittest.mock import MagicMock, patch
+from adalflow.utils.lazy_import import safe_import, OptionalPackages
 
 
 class TestSafeImport(unittest.TestCase):
@@ -27,6 +28,112 @@ def test_import_nonexistent_package(self):
             (f"Expected error message not found in {str(cm.exception)}"),
         )
 
+    @patch("importlib.import_module")
+    def test_import_with_multiple_packages_success(self, mock_import):
+        """Test that safe_import successfully imports a module if all modules exist"""
+        # Set up the mock to return a MagicMock to simulate successful imports
+        mock_import.side_effect = [MagicMock(name="successful_import")]
+
+        packages = ["math"]
+        imported_module = safe_import(packages, "Please install the required packages.")
+
+        self.assertTrue(
+            hasattr(imported_module, "sqrt"), "math module did not load correctly."
+        )
+
+    @patch("importlib.import_module")
+    def test_import_with_multiple_packages_failure(self, mock_import):
+        """Test that safe_import raises ImportError when any of the modules in the list fail to import"""
+        # Set up the mock to raise ImportError for the first package
+        mock_import.side_effect = ImportError
+
+        packages = ["non_existent_module_1", "math"]
+        with self.assertRaises(ImportError) as context:
+            safe_import(packages, "Please install the required packages.")
+
+        self.assertIn(
+            "Please install the required packages",
+            str(context.exception),
+            "Expected ImportError message does not match.",
+        )
+
+    ############################################################################################################
+    # For AWS bedrock_client
+    ############################################################################################################
+    @patch("importlib.import_module")
+    def test_successful_import_boto3(self, mock_import):
+        """Test that safe_import successfully imports boto3 if installed"""
+        # Simulate a successful import of boto3 by returning a MagicMock object
+        mock_import.side_effect = lambda name: (
+            MagicMock(name="boto3") if name == "boto3" else ImportError
+        )
+
+        module_name = OptionalPackages.BOTO3.value[0]
+        imported_module = safe_import(module_name, OptionalPackages.BOTO3.value[1])
+
+        # Assert that the mock was called with 'boto3' and the imported module is a MagicMock instance
+        mock_import.assert_called_with("boto3")
+        self.assertIsInstance(
+            imported_module, MagicMock, "boto3 module did not load correctly."
+        )
+
+    @patch("importlib.import_module", side_effect=ImportError)
+    def test_failed_import_boto3(self, mock_import):
+        """Test that safe_import raises an ImportError when boto3 is not installed"""
+        module_name = OptionalPackages.BOTO3.value[0]
+        with self.assertRaises(ImportError) as context:
+            safe_import(module_name, OptionalPackages.BOTO3.value[1])
+
+        self.assertIn(
+            "Please install boto3 with: pip install boto3",
+            str(context.exception),
+            "Expected ImportError message for boto3 does not match.",
+        )
+
+    ############################################################################################################
+    # For Azure ai model client
+    ############################################################################################################
+    @patch("importlib.import_module")
+    def test_successful_import_azure(self, mock_import):
+        """Test that safe_import successfully imports all Azure packages"""
+        # Simulate successful imports for each Azure package by returning a MagicMock for each
+        mock_import.side_effect = lambda name: MagicMock(name=name)
+
+        module_names = OptionalPackages.AZURE.value[0]
+        imported_modules = safe_import(module_names, OptionalPackages.AZURE.value[1])
+
+        # Ensure that all azure modules were attempted to be imported
+        for module_name in module_names:
+            mock_import.assert_any_call(module_name)
+
+        # Verify that the imported_modules is a list and contains each module as a MagicMock
+        self.assertIsInstance(imported_modules, list, "Expected a list of modules.")
+        self.assertEqual(
+            len(imported_modules),
+            len(module_names),
+            "Not all Azure modules were imported.",
+        )
+        for imported_module, module_name in zip(imported_modules, module_names):
+            self.assertIsInstance(
+                imported_module, MagicMock, f"{module_name} did not load correctly."
+            )
+
+    @patch("importlib.import_module")
+    def test_failed_import_azure(self, mock_import):
+        """Test that safe_import raises ImportError when any Azure package is not installed"""
+        # Set up the mock to raise ImportError for all Azure packages to simulate a missing package
+        mock_import.side_effect = ImportError
+
+        module_names = OptionalPackages.AZURE.value[0]
+        with self.assertRaises(ImportError) as context:
+            safe_import(module_names, OptionalPackages.AZURE.value[1])
+
+        self.assertIn(
+            "Please install Azure packages with: pip install azure-identity azure-core azure-ai-formrecognizer azure-ai-textanalytics",
+            str(context.exception),
+            "Expected ImportError message for Azure packages does not match.",
+        )
+
 
 if __name__ == "__main__":
     pytest.main()
diff --git a/docs/poetry.lock b/docs/poetry.lock
index dfa2d273..9c079273 100644
--- a/docs/poetry.lock
+++ b/docs/poetry.lock
@@ -20,7 +20,7 @@ tests = ["hypothesis", "pytest"]
 
 [[package]]
 name = "adalflow"
-version = "0.2.0.beta.3"
+version = "0.2.3"
 description = "The Library to Build and Auto-optimize Any LLM Task Pipeline"
 optional = false
 python-versions = ">=3.9, <4.0"
@@ -30,6 +30,7 @@ develop = true
 [package.dependencies]
 backoff = "^2.2.1"
 botocore = "^1.34.149"
+colorama = "^0.4.6"
 diskcache = "^5.6.3"
 jinja2 = "^3.1.3"
 jsonlines = "^4.0.0"
@@ -42,7 +43,10 @@ tqdm = "^4.66.4"
 
 [package.extras]
 anthropic = ["anthropic (>=0.31.1,<0.32.0)"]
+azure = ["azure-core (>=1.24.0,<2.0.0)", "azure-identity (>=1.12.0,<2.0.0)"]
+bedrock = ["boto3 (>=1.35.19,<2.0.0)"]
 cohere = ["cohere (>=5.5.8,<6.0.0)"]
+datasets = []
 faiss-cpu = ["faiss-cpu (>=1.8.0,<2.0.0)"]
 google-generativeai = ["google-generativeai (>=0.7.2,<0.8.0)"]
 groq = ["groq (>=0.9.0,<0.10.0)"]
@@ -277,6 +281,43 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
+[[package]]
+name = "azure-core"
+version = "1.31.0"
+description = "Microsoft Azure Core Library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "azure_core-1.31.0-py3-none-any.whl", hash = "sha256:22954de3777e0250029360ef31d80448ef1be13b80a459bff80ba7073379e2cd"},
+    {file = "azure_core-1.31.0.tar.gz", hash = "sha256:656a0dd61e1869b1506b7c6a3b31d62f15984b1a573d6326f6aa2f3e4123284b"},
+]
+
+[package.dependencies]
+requests = ">=2.21.0"
+six = ">=1.11.0"
+typing-extensions = ">=4.6.0"
+
+[package.extras]
+aio = ["aiohttp (>=3.0)"]
+
+[[package]]
+name = "azure-identity"
+version = "1.18.0"
+description = "Microsoft Azure Identity Library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "azure_identity-1.18.0-py3-none-any.whl", hash = "sha256:bccf6106245b49ff41d0c4cd7b72851c5a2ba3a32cef7589da246f5727f26f02"},
+    {file = "azure_identity-1.18.0.tar.gz", hash = "sha256:f567579a65d8932fa913c76eddf3305101a15e5727a5e4aa5df649a0f553d4c3"},
+]
+
+[package.dependencies]
+azure-core = ">=1.31.0"
+cryptography = ">=2.5"
+msal = ">=1.30.0"
+msal-extensions = ">=1.2.0"
+typing-extensions = ">=4.0.0"
+
 [[package]]
 name = "babel"
 version = "2.15.0"
@@ -601,6 +642,55 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "cryptography"
+version = "43.0.1"
+description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "cryptography-43.0.1-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:8385d98f6a3bf8bb2d65a73e17ed87a3ba84f6991c155691c51112075f9ffc5d"},
+    {file = "cryptography-43.0.1-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:27e613d7077ac613e399270253259d9d53872aaf657471473ebfc9a52935c062"},
+    {file = "cryptography-43.0.1-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:68aaecc4178e90719e95298515979814bda0cbada1256a4485414860bd7ab962"},
+    {file = "cryptography-43.0.1-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:de41fd81a41e53267cb020bb3a7212861da53a7d39f863585d13ea11049cf277"},
+    {file = "cryptography-43.0.1-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:f98bf604c82c416bc829e490c700ca1553eafdf2912a91e23a79d97d9801372a"},
+    {file = "cryptography-43.0.1-cp37-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:61ec41068b7b74268fa86e3e9e12b9f0c21fcf65434571dbb13d954bceb08042"},
+    {file = "cryptography-43.0.1-cp37-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:014f58110f53237ace6a408b5beb6c427b64e084eb451ef25a28308270086494"},
+    {file = "cryptography-43.0.1-cp37-abi3-win32.whl", hash = "sha256:2bd51274dcd59f09dd952afb696bf9c61a7a49dfc764c04dd33ef7a6b502a1e2"},
+    {file = "cryptography-43.0.1-cp37-abi3-win_amd64.whl", hash = "sha256:666ae11966643886c2987b3b721899d250855718d6d9ce41b521252a17985f4d"},
+    {file = "cryptography-43.0.1-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:ac119bb76b9faa00f48128b7f5679e1d8d437365c5d26f1c2c3f0da4ce1b553d"},
+    {file = "cryptography-43.0.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1bbcce1a551e262dfbafb6e6252f1ae36a248e615ca44ba302df077a846a8806"},
+    {file = "cryptography-43.0.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58d4e9129985185a06d849aa6df265bdd5a74ca6e1b736a77959b498e0505b85"},
+    {file = "cryptography-43.0.1-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:d03a475165f3134f773d1388aeb19c2d25ba88b6a9733c5c590b9ff7bbfa2e0c"},
+    {file = "cryptography-43.0.1-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:511f4273808ab590912a93ddb4e3914dfd8a388fed883361b02dea3791f292e1"},
+    {file = "cryptography-43.0.1-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:80eda8b3e173f0f247f711eef62be51b599b5d425c429b5d4ca6a05e9e856baa"},
+    {file = "cryptography-43.0.1-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:38926c50cff6f533f8a2dae3d7f19541432610d114a70808f0926d5aaa7121e4"},
+    {file = "cryptography-43.0.1-cp39-abi3-win32.whl", hash = "sha256:a575913fb06e05e6b4b814d7f7468c2c660e8bb16d8d5a1faf9b33ccc569dd47"},
+    {file = "cryptography-43.0.1-cp39-abi3-win_amd64.whl", hash = "sha256:d75601ad10b059ec832e78823b348bfa1a59f6b8d545db3a24fd44362a1564cb"},
+    {file = "cryptography-43.0.1-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:ea25acb556320250756e53f9e20a4177515f012c9eaea17eb7587a8c4d8ae034"},
+    {file = "cryptography-43.0.1-pp310-pypy310_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:c1332724be35d23a854994ff0b66530119500b6053d0bd3363265f7e5e77288d"},
+    {file = "cryptography-43.0.1-pp310-pypy310_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:fba1007b3ef89946dbbb515aeeb41e30203b004f0b4b00e5e16078b518563289"},
+    {file = "cryptography-43.0.1-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:5b43d1ea6b378b54a1dc99dd8a2b5be47658fe9a7ce0a58ff0b55f4b43ef2b84"},
+    {file = "cryptography-43.0.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:88cce104c36870d70c49c7c8fd22885875d950d9ee6ab54df2745f83ba0dc365"},
+    {file = "cryptography-43.0.1-pp39-pypy39_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:9d3cdb25fa98afdd3d0892d132b8d7139e2c087da1712041f6b762e4f807cc96"},
+    {file = "cryptography-43.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:e710bf40870f4db63c3d7d929aa9e09e4e7ee219e703f949ec4073b4294f6172"},
+    {file = "cryptography-43.0.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7c05650fe8023c5ed0d46793d4b7d7e6cd9c04e68eabe5b0aeea836e37bdcec2"},
+    {file = "cryptography-43.0.1.tar.gz", hash = "sha256:203e92a75716d8cfb491dc47c79e17d0d9207ccffcbcb35f598fbe463ae3444d"},
+]
+
+[package.dependencies]
+cffi = {version = ">=1.12", markers = "platform_python_implementation != \"PyPy\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-rtd-theme (>=1.1.1)"]
+docstest = ["pyenchant (>=1.6.11)", "readme-renderer", "sphinxcontrib-spelling (>=4.0.1)"]
+nox = ["nox"]
+pep8test = ["check-sdist", "click", "mypy", "ruff"]
+sdist = ["build"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi", "cryptography-vectors (==43.0.1)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
+test-randomorder = ["pytest-randomly"]
+
 [[package]]
 name = "datasets"
 version = "2.20.0"
@@ -1822,6 +1912,40 @@ docs = ["sphinx"]
 gmpy = ["gmpy2 (>=2.1.0a4)"]
 tests = ["pytest (>=4.6)"]
 
+[[package]]
+name = "msal"
+version = "1.31.0"
+description = "The Microsoft Authentication Library (MSAL) for Python library enables your app to access the Microsoft Cloud by supporting authentication of users with Microsoft Azure Active Directory accounts (AAD) and Microsoft Accounts (MSA) using industry standard OAuth2 and OpenID Connect."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "msal-1.31.0-py3-none-any.whl", hash = "sha256:96bc37cff82ebe4b160d5fc0f1196f6ca8b50e274ecd0ec5bf69c438514086e7"},
+    {file = "msal-1.31.0.tar.gz", hash = "sha256:2c4f189cf9cc8f00c80045f66d39b7c0f3ed45873fd3d1f2af9f22db2e12ff4b"},
+]
+
+[package.dependencies]
+cryptography = ">=2.5,<46"
+PyJWT = {version = ">=1.0.0,<3", extras = ["crypto"]}
+requests = ">=2.0.0,<3"
+
+[package.extras]
+broker = ["pymsalruntime (>=0.14,<0.18)", "pymsalruntime (>=0.17,<0.18)"]
+
+[[package]]
+name = "msal-extensions"
+version = "1.2.0"
+description = "Microsoft Authentication Library extensions (MSAL EX) provides a persistence API that can save your data on disk, encrypted on Windows, macOS and Linux. Concurrent data access will be coordinated by a file lock mechanism."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "msal_extensions-1.2.0-py3-none-any.whl", hash = "sha256:cf5ba83a2113fa6dc011a254a72f1c223c88d7dfad74cc30617c4679a417704d"},
+    {file = "msal_extensions-1.2.0.tar.gz", hash = "sha256:6f41b320bfd2933d631a215c91ca0dd3e67d84bd1a2f50ce917d5874ec646bef"},
+]
+
+[package.dependencies]
+msal = ">=1.29,<2"
+portalocker = ">=1.4,<3"
+
 [[package]]
 name = "multidict"
 version = "6.0.5"
@@ -2801,6 +2925,26 @@ files = [
 [package.extras]
 windows-terminal = ["colorama (>=0.4.6)"]
 
+[[package]]
+name = "pyjwt"
+version = "2.9.0"
+description = "JSON Web Token implementation in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "PyJWT-2.9.0-py3-none-any.whl", hash = "sha256:3b02fb0f44517787776cf48f2ae25d8e14f300e6d7545a4315cee571a415e850"},
+    {file = "pyjwt-2.9.0.tar.gz", hash = "sha256:7e1e5b56cc735432a7369cbfa0efe50fa113ebecdc04ae6922deba8b84582d0c"},
+]
+
+[package.dependencies]
+cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
+
+[package.extras]
+crypto = ["cryptography (>=3.4.0)"]
+dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
+docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
+tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
+
 [[package]]
 name = "pyparsing"
 version = "3.1.2"
@@ -4551,4 +4695,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <4.0"
-content-hash = "9558d0212fb3ace6733d867de454171304261bbd582561b0e09950faf19e2e4f"
+content-hash = "850edd56328727c4ff8ebf9b6642b37ff645c866d2406beb21cbaf6d64332ebf"
diff --git a/docs/pyproject.toml b/docs/pyproject.toml
index 30b5a5a4..3c69682b 100644
--- a/docs/pyproject.toml
+++ b/docs/pyproject.toml
@@ -10,6 +10,7 @@ packages = [{ from = "_dummy", include = "dummy" }]    # empty packages
 python = ">=3.9, <4.0"
 adalflow = { path = "../adalflow", develop = true } # document always follow the latest version of the library
 
+
 [tool.poetry.group.doc.dependencies]
 pydata-sphinx-theme = "^0.15.3"
 sphinx-design = "^0.6.0"
@@ -20,6 +21,7 @@ nbconvert = "^7.16.4"
 pandoc = "^2.3"
 readthedocs-sphinx-search = "^0.3.2"
 # add optional packages to compile the documents correctly
+datasets = "^2.20.0"
 sqlalchemy = "^2.0.31"
 google-generativeai = "^0.7.1"
 anthropic = "^0.30.1"
@@ -32,9 +34,12 @@ faiss-cpu = "^1.8.0.post1"
 ollama = "^0.3.0"
 qdrant-client = "^1.10.1"
 diskcache = "^5.6.3"
-datasets = "^2.20.0"
 torch = "^2.4.0"
 
+# azure model_client
+azure-identity = "^1.18.0"
+azure-core = "^1.31.0"
+
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

From 20f390c8caefc0b5f6291464adf90955e48b1ffd Mon Sep 17 00:00:00 2001
From: Li Yin <li.yin.gravity@gmail.com>
Date: Sun, 6 Oct 2024 15:05:27 +0800
Subject: [PATCH 11/13] update the poetry.lock to fix the conflict

---
 adalflow/poetry.lock | 1258 ++++++++++++++++++++++--------------------
 1 file changed, 646 insertions(+), 612 deletions(-)

diff --git a/adalflow/poetry.lock b/adalflow/poetry.lock
index b8aa9864..997730ee 100644
--- a/adalflow/poetry.lock
+++ b/adalflow/poetry.lock
@@ -13,113 +13,113 @@ files = [
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.0"
+version = "2.4.3"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"},
-    {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"},
+    {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"},
+    {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"},
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.10.5"
+version = "3.10.9"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiohttp-3.10.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:18a01eba2574fb9edd5f6e5fb25f66e6ce061da5dab5db75e13fe1558142e0a3"},
-    {file = "aiohttp-3.10.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:94fac7c6e77ccb1ca91e9eb4cb0ac0270b9fb9b289738654120ba8cebb1189c6"},
-    {file = "aiohttp-3.10.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2f1f1c75c395991ce9c94d3e4aa96e5c59c8356a15b1c9231e783865e2772699"},
-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f7acae3cf1a2a2361ec4c8e787eaaa86a94171d2417aae53c0cca6ca3118ff6"},
-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:94c4381ffba9cc508b37d2e536b418d5ea9cfdc2848b9a7fea6aebad4ec6aac1"},
-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c31ad0c0c507894e3eaa843415841995bf8de4d6b2d24c6e33099f4bc9fc0d4f"},
-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0912b8a8fadeb32ff67a3ed44249448c20148397c1ed905d5dac185b4ca547bb"},
-    {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d93400c18596b7dc4794d48a63fb361b01a0d8eb39f28800dc900c8fbdaca91"},
-    {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d00f3c5e0d764a5c9aa5a62d99728c56d455310bcc288a79cab10157b3af426f"},
-    {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:d742c36ed44f2798c8d3f4bc511f479b9ceef2b93f348671184139e7d708042c"},
-    {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:814375093edae5f1cb31e3407997cf3eacefb9010f96df10d64829362ae2df69"},
-    {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8224f98be68a84b19f48e0bdc14224b5a71339aff3a27df69989fa47d01296f3"},
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-    {file = "aiohttp-3.10.5-cp310-cp310-win32.whl", hash = "sha256:d9ef084e3dc690ad50137cc05831c52b6ca428096e6deb3c43e95827f531d5ef"},
-    {file = "aiohttp-3.10.5-cp310-cp310-win_amd64.whl", hash = "sha256:66bf9234e08fe561dccd62083bf67400bdbf1c67ba9efdc3dac03650e97c6088"},
-    {file = "aiohttp-3.10.5-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8c6a4e5e40156d72a40241a25cc226051c0a8d816610097a8e8f517aeacd59a2"},
-    {file = "aiohttp-3.10.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c634a3207a5445be65536d38c13791904fda0748b9eabf908d3fe86a52941cf"},
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 ]
 
 [package.dependencies]
@@ -129,7 +129,7 @@ async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
+yarl = ">=1.12.0,<2.0"
 
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
@@ -186,13 +186,13 @@ vertex = ["google-auth (>=2,<3)"]
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -202,9 +202,9 @@ sniffio = ">=1.1"
 typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "async-timeout"
@@ -286,18 +286,17 @@ files = [
 
 [[package]]
 name = "boto3"
-version = "1.35.19"
+version = "1.35.34"
 description = "The AWS SDK for Python"
 optional = true
-optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-botocore = ">=1.35.19,<1.36.0"
+botocore = ">=1.35.34,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -306,13 +305,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.19"
+version = "1.35.34"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -324,7 +323,7 @@ urllib3 = [
 ]
 
 [package.extras]
-crt = ["awscrt (==0.21.5)"]
+crt = ["awscrt (==0.22.0)"]
 
 [[package]]
 name = "cachetools"
@@ -539,13 +538,13 @@ files = [
 
 [[package]]
 name = "cohere"
-version = "5.9.2"
+version = "5.10.0"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.8"
 files = [
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+    {file = "cohere-5.10.0.tar.gz", hash = "sha256:21020a7ae4c30f72991ef91566a926a9d7d1485d7abeed7bfa2bd6f35ea34783"},
 ]
 
 [package.dependencies]
@@ -913,69 +912,75 @@ zstandard = ["zstandard"]
 
 [[package]]
 name = "filelock"
-version = "3.16.0"
+version = "3.16.1"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -1380,61 +1392,70 @@ typing-extensions = ">=4.7,<5"
 
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 [[package]]
 name = "grpcio-status"
@@ -1465,13 +1486,13 @@ files = [
 
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 [package.dependencies]
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 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
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 [[package]]
 name = "httplib2"
@@ -1536,13 +1557,13 @@ files = [
 
 [[package]]
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 [package.dependencies]
@@ -1584,13 +1605,13 @@ license = ["ukkonen"]
 
 [[package]]
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 description = "Internationalized Domain Names in Applications (IDNA)"
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 ]
 
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@@ -2483,14 +2504,14 @@ files = [
 
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+version = "12.6.77"
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 python-versions = ">=3"
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 [package.dependencies]
@@ -2642,12 +2676,13 @@ dev = ["jinja2"]
 
 [[package]]
 name = "pgvector"
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 description = "pgvector support for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2752,13 +2787,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
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 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
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 python-versions = ">=3.8"
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 [package.extras]
@@ -2837,22 +2872,22 @@ testing = ["google-api-core (>=1.31.5)"]
 
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 description = "Computer algebra system (CAS) in Python"
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 [[package]]
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 [[package]]
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 ]
 
 [package.dependencies]
@@ -4337,5 +4372,4 @@ torch = ["torch"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9, <4.0"
-
-content-hash = "04e8c5a6806fa7e3a34f322dd63ba242cef635929360f57d126082edd1d9987c"
+content-hash = "0a58b82476e4794adbc5768d38911e1935a9c3941cc40499001199383fc8c8ec"

From 751b949c55c6970179d489ce7615d7eddc24411c Mon Sep 17 00:00:00 2001
From: Li Yin <li.yin.gravity@gmail.com>
Date: Sun, 6 Oct 2024 15:12:00 +0800
Subject: [PATCH 12/13] fix the test

---
 adalflow/adalflow/utils/lazy_import.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/adalflow/adalflow/utils/lazy_import.py b/adalflow/adalflow/utils/lazy_import.py
index cf66d383..3451714b 100644
--- a/adalflow/adalflow/utils/lazy_import.py
+++ b/adalflow/adalflow/utils/lazy_import.py
@@ -43,7 +43,6 @@ class OptionalPackages(Enum):
     GROQ = ("groq", "Please install groq with: pip install groq")
     OPENAI = ("openai", "Please install openai with: pip install openai")
     ANTHROPIC = ("anthropic", "Please install anthropic with: pip install anthropic")
-    BOTO3 = ("boto3", "Please install boto3 with: pip install boto3")
     GOOGLE_GENERATIVEAI = (
         "google.generativeai",
         "Please install google-generativeai with: pip install google-generativeai",

From 04ed18fc2d4632d18ac2aaf99b36eb5fb956a0d1 Mon Sep 17 00:00:00 2001
From: Li Yin <li.yin.gravity@gmail.com>
Date: Tue, 26 Nov 2024 09:33:11 -0800
Subject: [PATCH 13/13] rebase to main

---
 adalflow/adalflow/components/model_client/bedrock_client.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/adalflow/adalflow/components/model_client/bedrock_client.py b/adalflow/adalflow/components/model_client/bedrock_client.py
index b2d5b549..d25b48bc 100644
--- a/adalflow/adalflow/components/model_client/bedrock_client.py
+++ b/adalflow/adalflow/components/model_client/bedrock_client.py
@@ -34,11 +34,6 @@ def get_first_message_content(completion: Dict) -> str:
     "get_first_message_content",
     "bedrock_runtime_exceptions",
 ]
-__all__ = [
-    "BedrockAPIClient",
-    "get_first_message_content",
-    "bedrock_runtime_exceptions",
-]
 
 
 class BedrockAPIClient(ModelClient):