diff --git a/autogen/agentchat/contrib/agent_eval/agent_eval.py b/autogen/agentchat/contrib/agent_eval/agent_eval.py
index 4ad81b72d..58abe0ed1 100644
--- a/autogen/agentchat/contrib/agent_eval/agent_eval.py
+++ b/autogen/agentchat/contrib/agent_eval/agent_eval.py
@@ -6,12 +6,12 @@
 # SPDX-License-Identifier: MIT
 from typing import Literal, Optional, Union
 
-import autogen
-from autogen.agentchat.contrib.agent_eval.criterion import Criterion
-from autogen.agentchat.contrib.agent_eval.critic_agent import CriticAgent
-from autogen.agentchat.contrib.agent_eval.quantifier_agent import QuantifierAgent
-from autogen.agentchat.contrib.agent_eval.subcritic_agent import SubCriticAgent
-from autogen.agentchat.contrib.agent_eval.task import Task
+from .... import GroupChat, GroupChatManager, UserProxyAgent
+from .criterion import Criterion
+from .critic_agent import CriticAgent
+from .quantifier_agent import QuantifierAgent
+from .subcritic_agent import SubCriticAgent
+from .task import Task
 
 
 def generate_criteria(
@@ -38,7 +38,7 @@ def generate_criteria(
         llm_config=llm_config,
     )
 
-    critic_user = autogen.UserProxyAgent(
+    critic_user = UserProxyAgent(
         name="critic_user",
         max_consecutive_auto_reply=0,  # terminate without auto-reply
         human_input_mode="NEVER",
@@ -53,10 +53,8 @@ def generate_criteria(
         )
         agents.append(subcritic)
 
-    groupchat = autogen.GroupChat(
-        agents=agents, messages=[], max_round=max_round, speaker_selection_method="round_robin"
-    )
-    critic_manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
+    groupchat = GroupChat(agents=agents, messages=[], max_round=max_round, speaker_selection_method="round_robin")
+    critic_manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
 
     critic_user.initiate_chat(critic_manager, message=task.get_sys_message())
     criteria = critic_user.last_message()
@@ -90,7 +88,7 @@ def quantify_criteria(
         llm_config=llm_config,
     )
 
-    quantifier_user = autogen.UserProxyAgent(
+    quantifier_user = UserProxyAgent(
         name="quantifier_user",
         max_consecutive_auto_reply=0,  # terminate without auto-reply
         human_input_mode="NEVER",
diff --git a/autogen/agentchat/contrib/agent_eval/critic_agent.py b/autogen/agentchat/contrib/agent_eval/critic_agent.py
index 0ac62b9bd..bf7bd8139 100644
--- a/autogen/agentchat/contrib/agent_eval/critic_agent.py
+++ b/autogen/agentchat/contrib/agent_eval/critic_agent.py
@@ -6,7 +6,7 @@
 # SPDX-License-Identifier: MIT
 from typing import Optional
 
-from autogen.agentchat.conversable_agent import ConversableAgent
+from ...conversable_agent import ConversableAgent
 
 
 class CriticAgent(ConversableAgent):
diff --git a/autogen/agentchat/contrib/agent_eval/quantifier_agent.py b/autogen/agentchat/contrib/agent_eval/quantifier_agent.py
index b933afc23..c475bc9c3 100644
--- a/autogen/agentchat/contrib/agent_eval/quantifier_agent.py
+++ b/autogen/agentchat/contrib/agent_eval/quantifier_agent.py
@@ -6,7 +6,7 @@
 # SPDX-License-Identifier: MIT
 from typing import Optional
 
-from autogen.agentchat.conversable_agent import ConversableAgent
+from ...conversable_agent import ConversableAgent
 
 
 class QuantifierAgent(ConversableAgent):
diff --git a/autogen/agentchat/contrib/agent_eval/subcritic_agent.py b/autogen/agentchat/contrib/agent_eval/subcritic_agent.py
index 7c0261107..3b163dbd3 100755
--- a/autogen/agentchat/contrib/agent_eval/subcritic_agent.py
+++ b/autogen/agentchat/contrib/agent_eval/subcritic_agent.py
@@ -6,7 +6,7 @@
 # SPDX-License-Identifier: MIT
 from typing import Optional
 
-from autogen.agentchat.conversable_agent import ConversableAgent
+from ...conversable_agent import ConversableAgent
 
 
 class SubCriticAgent(ConversableAgent):
diff --git a/autogen/agentchat/contrib/agent_optimizer.py b/autogen/agentchat/contrib/agent_optimizer.py
index efc2448b0..d297f075a 100644
--- a/autogen/agentchat/contrib/agent_optimizer.py
+++ b/autogen/agentchat/contrib/agent_optimizer.py
@@ -8,8 +8,8 @@
 import json
 from typing import Optional
 
-import autogen
-from autogen.code_utils import execute_code
+from ... import OpenAIWrapper, filter_config
+from ...code_utils import execute_code
 
 ADD_FUNC = {
     "type": "function",
@@ -209,10 +209,8 @@ def __init__(
             raise ValueError(
                 "When using OpenAI or Azure OpenAI endpoints, specify a non-empty 'model' either in 'llm_config' or in each config of 'config_list'."
             )
-        self.llm_config["config_list"] = autogen.filter_config(
-            llm_config["config_list"], {"model": [self.optimizer_model]}
-        )
-        self._client = autogen.OpenAIWrapper(**self.llm_config)
+        self.llm_config["config_list"] = filter_config(llm_config["config_list"], {"model": [self.optimizer_model]})
+        self._client = OpenAIWrapper(**self.llm_config)
 
     def record_one_conversation(self, conversation_history: list[dict], is_satisfied: bool = None):
         """Record one conversation history.
diff --git a/autogen/agentchat/contrib/capabilities/agent_capability.py b/autogen/agentchat/contrib/capabilities/agent_capability.py
index 4987119b7..e6dda25f2 100644
--- a/autogen/agentchat/contrib/capabilities/agent_capability.py
+++ b/autogen/agentchat/contrib/capabilities/agent_capability.py
@@ -4,7 +4,7 @@
 #
 # Portions derived from  https://github.com/microsoft/autogen are under the MIT License.
 # SPDX-License-Identifier: MIT
-from autogen.agentchat.assistant_agent import ConversableAgent
+from ...assistant_agent import ConversableAgent
 
 
 class AgentCapability:
diff --git a/autogen/agentchat/contrib/capabilities/teachability.py b/autogen/agentchat/contrib/capabilities/teachability.py
index 420d5a02d..acb79779d 100644
--- a/autogen/agentchat/contrib/capabilities/teachability.py
+++ b/autogen/agentchat/contrib/capabilities/teachability.py
@@ -8,14 +8,15 @@
 import pickle
 from typing import Optional, Union
 
-import chromadb
-from chromadb.config import Settings
-
-from autogen.agentchat.assistant_agent import ConversableAgent
-from autogen.agentchat.contrib.capabilities.agent_capability import AgentCapability
-from autogen.agentchat.contrib.text_analyzer_agent import TextAnalyzerAgent
-
 from ....formatting_utils import colored
+from ....import_utils import optional_import_block, require_optional_import
+from ...assistant_agent import ConversableAgent
+from ..text_analyzer_agent import TextAnalyzerAgent
+from .agent_capability import AgentCapability
+
+with optional_import_block():
+    import chromadb
+    from chromadb.config import Settings
 
 
 class Teachability(AgentCapability):
@@ -238,6 +239,7 @@ def _analyze(self, text_to_analyze: Union[dict, str], analysis_instructions: Uni
         return self.teachable_agent.last_message(self.analyzer)["content"]
 
 
+@require_optional_import("chromadb", "teachable")
 class MemoStore:
     """Provides memory storage and retrieval for a teachable agent, using a vector database.
     Each DB entry (called a memo) is a pair of strings: an input text and an output text.
diff --git a/autogen/agentchat/contrib/capabilities/tools_capability.py b/autogen/agentchat/contrib/capabilities/tools_capability.py
index b3bf13b13..068afff8b 100644
--- a/autogen/agentchat/contrib/capabilities/tools_capability.py
+++ b/autogen/agentchat/contrib/capabilities/tools_capability.py
@@ -2,8 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-from autogen.agentchat import ConversableAgent
-from autogen.tools import Tool
+from ....agentchat import ConversableAgent
+from ....tools import Tool
 
 
 class ToolsCapability:
diff --git a/autogen/agentchat/contrib/capabilities/transforms.py b/autogen/agentchat/contrib/capabilities/transforms.py
index 330bf2f3a..88ad4d701 100644
--- a/autogen/agentchat/contrib/capabilities/transforms.py
+++ b/autogen/agentchat/contrib/capabilities/transforms.py
@@ -11,10 +11,9 @@
 import tiktoken
 from termcolor import colored
 
-from autogen import token_count_utils
-from autogen.cache import AbstractCache, Cache
-from autogen.types import MessageContentType
-
+from .... import token_count_utils
+from ....cache import AbstractCache, Cache
+from ....types import MessageContentType
 from . import transforms_util
 from .text_compressors import LLMLingua, TextCompressor
 
diff --git a/autogen/agentchat/contrib/capabilities/transforms_util.py b/autogen/agentchat/contrib/capabilities/transforms_util.py
index a3c2524cd..ab323b8d4 100644
--- a/autogen/agentchat/contrib/capabilities/transforms_util.py
+++ b/autogen/agentchat/contrib/capabilities/transforms_util.py
@@ -7,10 +7,10 @@
 from collections.abc import Hashable
 from typing import Any, Optional
 
-from autogen import token_count_utils
-from autogen.cache.abstract_cache_base import AbstractCache
-from autogen.oai.openai_utils import filter_config
-from autogen.types import MessageContentType
+from .... import token_count_utils
+from ....cache.abstract_cache_base import AbstractCache
+from ....oai.openai_utils import filter_config
+from ....types import MessageContentType
 
 
 def cache_key(content: MessageContentType, *args: Hashable) -> str:
diff --git a/autogen/agentchat/contrib/capabilities/vision_capability.py b/autogen/agentchat/contrib/capabilities/vision_capability.py
index bad988f33..8c69ccab2 100644
--- a/autogen/agentchat/contrib/capabilities/vision_capability.py
+++ b/autogen/agentchat/contrib/capabilities/vision_capability.py
@@ -7,16 +7,16 @@
 import copy
 from typing import Callable, Optional, Union
 
-from autogen.agentchat.assistant_agent import ConversableAgent
-from autogen.agentchat.contrib.capabilities.agent_capability import AgentCapability
-from autogen.agentchat.contrib.img_utils import (
+from ....code_utils import content_str
+from ....oai.client import OpenAIWrapper
+from ...assistant_agent import ConversableAgent
+from ..img_utils import (
     convert_base64_to_data_uri,
     get_image_data,
     get_pil_image,
     gpt4v_formatter,
 )
-from autogen.code_utils import content_str
-from autogen.oai.client import OpenAIWrapper
+from .agent_capability import AgentCapability
 
 DEFAULT_DESCRIPTION_PROMPT = (
     "Write a detailed caption for this image. "
diff --git a/autogen/agentchat/contrib/captainagent/agent_builder.py b/autogen/agentchat/contrib/captainagent/agent_builder.py
index 56c50f6e2..26ac24746 100644
--- a/autogen/agentchat/contrib/captainagent/agent_builder.py
+++ b/autogen/agentchat/contrib/captainagent/agent_builder.py
@@ -15,7 +15,8 @@
 
 from termcolor import colored
 
-import autogen
+from .... import AssistantAgent, ConversableAgent, OpenAIWrapper, UserProxyAgent, config_list_from_json
+from ....code_utils import CODE_BLOCK_PATTERN
 
 __all__ = ["AgentBuilder"]
 
@@ -37,7 +38,7 @@ def _config_check(config: dict):
 
 
 def _retrieve_json(text):
-    match = re.findall(autogen.code_utils.CODE_BLOCK_PATTERN, text, flags=re.DOTALL)
+    match = re.findall(CODE_BLOCK_PATTERN, text, flags=re.DOTALL)
     if not match:
         return text
     code_blocks = []
@@ -203,7 +204,7 @@ def __init__(
             builder_filter_dict.update({"model": builder_model})
         if len(builder_model_tags) != 0:
             builder_filter_dict.update({"tags": builder_model_tags})
-        builder_config_list = autogen.config_list_from_json(
+        builder_config_list = config_list_from_json(
             config_file_or_env, file_location=config_file_location, filter_dict=builder_filter_dict
         )
         if len(builder_config_list) == 0:
@@ -211,7 +212,7 @@ def __init__(
                 f"Fail to initialize build manager: {builder_model}{builder_model_tags} does not exist in {config_file_or_env}. "
                 f'If you want to change this model, please specify the "builder_model" in the constructor.'
             )
-        self.builder_model = autogen.OpenAIWrapper(config_list=builder_config_list)
+        self.builder_model = OpenAIWrapper(config_list=builder_config_list)
 
         self.agent_model = agent_model if isinstance(agent_model, list) else [agent_model]
         self.agent_model_tags = agent_model_tags
@@ -222,7 +223,7 @@ def __init__(
         self.agent_configs: list[dict] = []
         self.open_ports: list[str] = []
         self.agent_procs: dict[str, tuple[sp.Popen, str]] = {}
-        self.agent_procs_assign: dict[str, tuple[autogen.ConversableAgent, str]] = {}
+        self.agent_procs_assign: dict[str, tuple[ConversableAgent, str]] = {}
         self.cached_configs: dict = {}
 
         self.max_agents = max_agents
@@ -239,7 +240,7 @@ def _create_agent(
         member_name: list[str],
         llm_config: dict,
         use_oai_assistant: Optional[bool] = False,
-    ) -> autogen.AssistantAgent:
+    ) -> AssistantAgent:
         """Create a group chat participant agent.
 
         If the agent rely on an open-source model, this function will automatically set up an endpoint for that agent.
@@ -274,7 +275,7 @@ def _create_agent(
             filter_dict.update({"model": model_name_or_hf_repo})
         if len(model_tags) > 0:
             filter_dict.update({"tags": model_tags})
-        config_list = autogen.config_list_from_json(
+        config_list = config_list_from_json(
             self.config_file_or_env, file_location=self.config_file_location, filter_dict=filter_dict
         )
         if len(config_list) == 0:
@@ -287,7 +288,7 @@ def _create_agent(
         current_config = llm_config.copy()
         current_config.update({"config_list": config_list})
         if use_oai_assistant:
-            from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent
+            from ..gpt_assistant_agent import GPTAssistantAgent
 
             agent = GPTAssistantAgent(
                 name=agent_name,
@@ -302,14 +303,14 @@ def _create_agent(
                     "\nThe group also include a Computer_terminal to help you run the python and shell code."
                 )
 
-            model_class = autogen.AssistantAgent
+            model_class = AssistantAgent
             if agent_path:
                 module_path, model_class_name = agent_path.replace("/", ".").rsplit(".", 1)
                 module = importlib.import_module(module_path)
                 model_class = getattr(module, model_class_name)
-                if not issubclass(model_class, autogen.ConversableAgent):
+                if not issubclass(model_class, ConversableAgent):
                     logger.error(f"{model_class} is not a ConversableAgent. Use AssistantAgent as default")
-                    model_class = autogen.AssistantAgent
+                    model_class = AssistantAgent
 
             additional_config = {
                 k: v
@@ -365,10 +366,10 @@ def build(
         coding: Optional[bool] = None,
         code_execution_config: Optional[dict] = None,
         use_oai_assistant: Optional[bool] = False,
-        user_proxy: Optional[autogen.ConversableAgent] = None,
+        user_proxy: Optional[ConversableAgent] = None,
         max_agents: Optional[int] = None,
         **kwargs,
-    ) -> tuple[list[autogen.ConversableAgent], dict]:
+    ) -> tuple[list[ConversableAgent], dict]:
         """Auto build agents based on the building task.
 
         Args:
@@ -496,9 +497,9 @@ def build_from_library(
         code_execution_config: Optional[dict] = None,
         use_oai_assistant: Optional[bool] = False,
         embedding_model: Optional[str] = "all-mpnet-base-v2",
-        user_proxy: Optional[autogen.ConversableAgent] = None,
+        user_proxy: Optional[ConversableAgent] = None,
         **kwargs,
-    ) -> tuple[list[autogen.ConversableAgent], dict]:
+    ) -> tuple[list[ConversableAgent], dict]:
         """Build agents from a library.
         The library is a list of agent configs, which contains the name and system_message for each agent.
         We use a build manager to decide what agent in that library should be involved to the task.
@@ -655,8 +656,8 @@ def build_from_library(
         return self._build_agents(use_oai_assistant, user_proxy=user_proxy, **kwargs)
 
     def _build_agents(
-        self, use_oai_assistant: Optional[bool] = False, user_proxy: Optional[autogen.ConversableAgent] = None, **kwargs
-    ) -> tuple[list[autogen.ConversableAgent], dict]:
+        self, use_oai_assistant: Optional[bool] = False, user_proxy: Optional[ConversableAgent] = None, **kwargs
+    ) -> tuple[list[ConversableAgent], dict]:
         """Build agents with generated configs.
 
         Args:
@@ -687,7 +688,7 @@ def _build_agents(
         if coding is True:
             print("Adding user console proxy...", flush=True)
             if user_proxy is None:
-                user_proxy = autogen.UserProxyAgent(
+                user_proxy = UserProxyAgent(
                     name="Computer_terminal",
                     is_termination_msg=lambda x: x == "TERMINATE" or x == "TERMINATE.",
                     code_execution_config=code_execution_config,
@@ -722,7 +723,7 @@ def load(
         config_json: Optional[str] = None,
         use_oai_assistant: Optional[bool] = False,
         **kwargs,
-    ) -> tuple[list[autogen.ConversableAgent], dict]:
+    ) -> tuple[list[ConversableAgent], dict]:
         """Load building configs and call the build function to complete building without calling online LLMs' api.
 
         Args:
diff --git a/autogen/agentchat/contrib/captainagent/captainagent.py b/autogen/agentchat/contrib/captainagent/captainagent.py
index f71f6de03..f496333f6 100644
--- a/autogen/agentchat/contrib/captainagent/captainagent.py
+++ b/autogen/agentchat/contrib/captainagent/captainagent.py
@@ -8,10 +8,8 @@
 
 from termcolor import colored
 
-import autogen
-from autogen import UserProxyAgent
-from autogen.agentchat.conversable_agent import ConversableAgent
-
+from .... import GroupChat, GroupChatManager, UserProxyAgent
+from ...conversable_agent import ConversableAgent
 from .agent_builder import AgentBuilder
 from .tool_retriever import ToolBuilder, format_ag2_tool, get_full_tool_description
 
@@ -465,13 +463,13 @@ def _run_autobuild(self, group_name: str, execution_task: str, building_task: st
 
         self.build_times += 1
         # start nested chat
-        nested_group_chat = autogen.GroupChat(
+        nested_group_chat = GroupChat(
             agents=agent_list,
             messages=[],
             allow_repeat_speaker=agent_list[:-1] if agent_configs["coding"] is True else agent_list,
             **self._nested_config["group_chat_config"],
         )
-        manager = autogen.GroupChatManager(
+        manager = GroupChatManager(
             groupchat=nested_group_chat,
             llm_config=self._nested_config["group_chat_llm_config"],
         )
diff --git a/autogen/agentchat/contrib/captainagent/tool_retriever.py b/autogen/agentchat/contrib/captainagent/tool_retriever.py
index a37b171b4..87612c2bc 100644
--- a/autogen/agentchat/contrib/captainagent/tool_retriever.py
+++ b/autogen/agentchat/contrib/captainagent/tool_retriever.py
@@ -16,15 +16,18 @@
 from textwrap import dedent, indent
 from typing import Optional, Union
 
-import pandas as pd
-from sentence_transformers import SentenceTransformer, util
-
 from .... import AssistantAgent, UserProxyAgent
 from ....coding import CodeExecutor, CodeExtractor, LocalCommandLineCodeExecutor, MarkdownCodeExtractor
 from ....coding.base import CodeBlock, CodeResult
+from ....import_utils import optional_import_block, require_optional_import
 from ....tools import Tool, get_function_schema, load_basemodels_if_needed
 
+with optional_import_block():
+    import pandas as pd
+    from sentence_transformers import SentenceTransformer, util
+
 
+@require_optional_import(["pandas", "sentence_transformers"], "retrievechat")
 class ToolBuilder:
     TOOL_PROMPT_DEFAULT = """\n## Functions
 You have access to the following functions. They can be accessed from the module called 'functions' by their function names.
diff --git a/autogen/agentchat/contrib/captainagent/tools/data_analysis/shapiro_wilk_test.py b/autogen/agentchat/contrib/captainagent/tools/data_analysis/shapiro_wilk_test.py
index 18f77c47a..feced5c47 100644
--- a/autogen/agentchat/contrib/captainagent/tools/data_analysis/shapiro_wilk_test.py
+++ b/autogen/agentchat/contrib/captainagent/tools/data_analysis/shapiro_wilk_test.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["pandas", "scipy"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_download.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_download.py
index 53e9e45c1..d7a2fed0b 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_download.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_download.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 import arxiv
 
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["arxiv"], ["arxiv"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_search.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_search.py
index 9cbc68b91..41df6fd92 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_search.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/arxiv_search.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 import arxiv
 
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["arxiv"], ["arxiv"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_image.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_image.py
index ce2a7d111..e609d5f68 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_image.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_image.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 import os
 
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["PyMuPDF"], ["os"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_text.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_text.py
index 689b3f419..dc2642d9f 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_text.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/extract_pdf_text.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["PyMuPDF"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/image_qa.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/image_qa.py
index 4d68b4090..5b9eb9fd0 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/image_qa.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/image_qa.py
@@ -5,7 +5,7 @@
 
 from PIL import Image
 
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["transformers", "torch"], ["transformers", "torch", "PIL", "os"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/optical_character_recognition.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/optical_character_recognition.py
index e7d78cb96..7efba600c 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/optical_character_recognition.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/optical_character_recognition.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 import os
 
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["easyocr"], ["os"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/transcribe_audio_file.py b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/transcribe_audio_file.py
index c96257d69..2e1dd81eb 100644
--- a/autogen/agentchat/contrib/captainagent/tools/information_retrieval/transcribe_audio_file.py
+++ b/autogen/agentchat/contrib/captainagent/tools/information_retrieval/transcribe_audio_file.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["openai-whisper"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/math/calculate_circle_area_from_diameter.py b/autogen/agentchat/contrib/captainagent/tools/math/calculate_circle_area_from_diameter.py
index 161a9fb42..b7d4e5809 100644
--- a/autogen/agentchat/contrib/captainagent/tools/math/calculate_circle_area_from_diameter.py
+++ b/autogen/agentchat/contrib/captainagent/tools/math/calculate_circle_area_from_diameter.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["sympy"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/math/calculate_matrix_power.py b/autogen/agentchat/contrib/captainagent/tools/math/calculate_matrix_power.py
index b13cc42d9..697dfed2a 100644
--- a/autogen/agentchat/contrib/captainagent/tools/math/calculate_matrix_power.py
+++ b/autogen/agentchat/contrib/captainagent/tools/math/calculate_matrix_power.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["sympy"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/math/complex_numbers_product.py b/autogen/agentchat/contrib/captainagent/tools/math/complex_numbers_product.py
index 5c79a8b91..c826da557 100644
--- a/autogen/agentchat/contrib/captainagent/tools/math/complex_numbers_product.py
+++ b/autogen/agentchat/contrib/captainagent/tools/math/complex_numbers_product.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["sympy"])
diff --git a/autogen/agentchat/contrib/captainagent/tools/math/compute_currency_conversion.py b/autogen/agentchat/contrib/captainagent/tools/math/compute_currency_conversion.py
index b88e48b73..45f99b81a 100644
--- a/autogen/agentchat/contrib/captainagent/tools/math/compute_currency_conversion.py
+++ b/autogen/agentchat/contrib/captainagent/tools/math/compute_currency_conversion.py
@@ -1,7 +1,7 @@
 # Copyright (c) 2023 - 2024, Owners of https://github.com/ag2ai
 #
 # SPDX-License-Identifier: Apache-2.0
-from autogen.coding.func_with_reqs import with_requirements
+from ......coding.func_with_reqs import with_requirements
 
 
 @with_requirements(["sympy"])
diff --git a/autogen/agentchat/contrib/gpt_assistant_agent.py b/autogen/agentchat/contrib/gpt_assistant_agent.py
index d0a2f6f82..fcd6e55e1 100644
--- a/autogen/agentchat/contrib/gpt_assistant_agent.py
+++ b/autogen/agentchat/contrib/gpt_assistant_agent.py
@@ -11,11 +11,11 @@
 from collections import defaultdict
 from typing import Any, Optional, Union
 
-from autogen import OpenAIWrapper
-from autogen.agentchat.agent import Agent
-from autogen.agentchat.assistant_agent import AssistantAgent, ConversableAgent
-from autogen.oai.openai_utils import create_gpt_assistant, retrieve_assistants_by_name, update_gpt_assistant
-from autogen.runtime_logging import log_new_agent, logging_enabled
+from ... import OpenAIWrapper
+from ...oai.openai_utils import create_gpt_assistant, retrieve_assistants_by_name, update_gpt_assistant
+from ...runtime_logging import log_new_agent, logging_enabled
+from ..agent import Agent
+from ..assistant_agent import AssistantAgent, ConversableAgent
 
 logger = logging.getLogger(__name__)
 
diff --git a/autogen/agentchat/contrib/graph_rag/falkor_graph_query_engine.py b/autogen/agentchat/contrib/graph_rag/falkor_graph_query_engine.py
index 37eca45c0..d9ecb9330 100644
--- a/autogen/agentchat/contrib/graph_rag/falkor_graph_query_engine.py
+++ b/autogen/agentchat/contrib/graph_rag/falkor_graph_query_engine.py
@@ -4,18 +4,22 @@
 
 import os
 import warnings
+from typing import Optional
 
-from falkordb import FalkorDB, Graph
-from graphrag_sdk import KnowledgeGraph, Source
-from graphrag_sdk.model_config import KnowledgeGraphModelConfig
-from graphrag_sdk.models import GenerativeModel
-from graphrag_sdk.models.openai import OpenAiGenerativeModel
-from graphrag_sdk.ontology import Ontology
-
+from ....import_utils import optional_import_block, require_optional_import
 from .document import Document
 from .graph_query_engine import GraphStoreQueryResult
 
+with optional_import_block():
+    from falkordb import FalkorDB, Graph
+    from graphrag_sdk import KnowledgeGraph, Source
+    from graphrag_sdk.model_config import KnowledgeGraphModelConfig
+    from graphrag_sdk.models import GenerativeModel
+    from graphrag_sdk.models.openai import OpenAiGenerativeModel
+    from graphrag_sdk.ontology import Ontology
+
 
+@require_optional_import(["falkordb", "graphrag_sdk"], "graph-rag-falkor-db")
 class FalkorGraphQueryEngine:
     """This is a wrapper for FalkorDB KnowledgeGraph."""
 
@@ -26,8 +30,8 @@ def __init__(
         port: int = 6379,
         username: str | None = None,
         password: str | None = None,
-        model: GenerativeModel = OpenAiGenerativeModel("gpt-4o"),
-        ontology: Ontology | None = None,
+        model: Optional["GenerativeModel"] = None,
+        ontology: Optional["Ontology"] = None,
     ):
         """Initialize a FalkorDB knowledge graph.
         Please also refer to https://github.com/FalkorDB/GraphRAG-SDK/blob/main/graphrag_sdk/kg.py
@@ -50,7 +54,7 @@ def __init__(
         self.port = port
         self.username = username
         self.password = password
-        self.model = model
+        self.model = model or OpenAiGenerativeModel("gpt-4o")
         self.model_config = KnowledgeGraphModelConfig.with_model(model)
         self.ontology = ontology
         self.knowledge_graph = None
@@ -149,17 +153,17 @@ def delete(self) -> bool:
             self.falkordb.select_graph(self.ontology_table_name).delete()
         return True
 
-    def __get_ontology_storage_graph(self) -> Graph:
+    def __get_ontology_storage_graph(self) -> "Graph":
         return self.falkordb.select_graph(self.ontology_table_name)
 
-    def _save_ontology_to_db(self, ontology: Ontology):
+    def _save_ontology_to_db(self, ontology: "Ontology"):
         """Save graph ontology to a separate table with {graph_name}_ontology"""
         if self.ontology_table_name in self.falkordb.list_graphs():
             raise ValueError(f"Knowledge graph {self.name} is already created.")
         graph = self.__get_ontology_storage_graph()
         ontology.save_to_graph(graph)
 
-    def _load_ontology_from_db(self) -> Ontology:
+    def _load_ontology_from_db(self) -> "Ontology":
         if self.ontology_table_name not in self.falkordb.list_graphs():
             raise ValueError(f"Knowledge graph {self.name} has not been created.")
         graph = self.__get_ontology_storage_graph()
diff --git a/autogen/agentchat/contrib/graph_rag/falkor_graph_rag_capability.py b/autogen/agentchat/contrib/graph_rag/falkor_graph_rag_capability.py
index 4b09a2a58..2c7cb3b79 100644
--- a/autogen/agentchat/contrib/graph_rag/falkor_graph_rag_capability.py
+++ b/autogen/agentchat/contrib/graph_rag/falkor_graph_rag_capability.py
@@ -4,8 +4,7 @@
 
 from typing import Any, Optional, Union
 
-from autogen import Agent, ConversableAgent, UserProxyAgent
-
+from .... import Agent, ConversableAgent, UserProxyAgent
 from .falkor_graph_query_engine import FalkorGraphQueryEngine
 from .graph_query_engine import GraphStoreQueryResult
 from .graph_rag_capability import GraphRagCapability
diff --git a/autogen/agentchat/contrib/graph_rag/graph_rag_capability.py b/autogen/agentchat/contrib/graph_rag/graph_rag_capability.py
index 70823b78b..129a0417a 100644
--- a/autogen/agentchat/contrib/graph_rag/graph_rag_capability.py
+++ b/autogen/agentchat/contrib/graph_rag/graph_rag_capability.py
@@ -4,9 +4,8 @@
 #
 # Portions derived from https://github.com/microsoft/autogen are under the MIT License.
 # SPDX-License-Identifier: MIT
-from autogen.agentchat.contrib.capabilities.agent_capability import AgentCapability
-from autogen.agentchat.conversable_agent import ConversableAgent
-
+from ...conversable_agent import ConversableAgent
+from ..capabilities.agent_capability import AgentCapability
 from .graph_query_engine import GraphQueryEngine
 
 
diff --git a/autogen/agentchat/contrib/graph_rag/neo4j_graph_query_engine.py b/autogen/agentchat/contrib/graph_rag/neo4j_graph_query_engine.py
index afba87847..b86dbf287 100644
--- a/autogen/agentchat/contrib/graph_rag/neo4j_graph_query_engine.py
+++ b/autogen/agentchat/contrib/graph_rag/neo4j_graph_query_engine.py
@@ -2,26 +2,35 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 import os
-from typing import Optional, TypeAlias, Union
-
-from llama_index.core import PropertyGraphIndex, SimpleDirectoryReader
-from llama_index.core.base.embeddings.base import BaseEmbedding
-from llama_index.core.indices.property_graph import (
-    DynamicLLMPathExtractor,
-    SchemaLLMPathExtractor,
-)
-from llama_index.core.indices.property_graph.transformations.schema_llm import Triple
-from llama_index.core.llms import LLM
-from llama_index.core.readers.json import JSONReader
-from llama_index.core.schema import Document as LlamaDocument
-from llama_index.embeddings.openai import OpenAIEmbedding
-from llama_index.graph_stores.neo4j import Neo4jPropertyGraphStore
-from llama_index.llms.openai import OpenAI
+import sys
+from typing import Optional, Union
 
+if sys.version_info >= (3, 10):
+    from typing import TypeAlias
+else:
+    from typing_extensions import TypeAlias
+
+from ....import_utils import optional_import_block, require_optional_import
 from .document import Document, DocumentType
 from .graph_query_engine import GraphQueryEngine, GraphStoreQueryResult
 
-
+with optional_import_block():
+    from llama_index.core import PropertyGraphIndex, SimpleDirectoryReader
+    from llama_index.core.base.embeddings.base import BaseEmbedding
+    from llama_index.core.indices.property_graph import (
+        DynamicLLMPathExtractor,
+        SchemaLLMPathExtractor,
+    )
+    from llama_index.core.indices.property_graph.transformations.schema_llm import Triple
+    from llama_index.core.llms import LLM
+    from llama_index.core.readers.json import JSONReader
+    from llama_index.core.schema import Document as LlamaDocument
+    from llama_index.embeddings.openai import OpenAIEmbedding
+    from llama_index.graph_stores.neo4j import Neo4jPropertyGraphStore
+    from llama_index.llms.openai import OpenAI
+
+
+@require_optional_import("llama_index", "neo4j")
 class Neo4jGraphQueryEngine(GraphQueryEngine):
     """This class serves as a wrapper for a property graph query engine backed by LlamaIndex and Neo4j,
     facilitating the creating, connecting, updating, and querying of LlamaIndex property graphs.
@@ -49,11 +58,11 @@ def __init__(
         database: str = "neo4j",
         username: str = "neo4j",
         password: str = "neo4j",
-        llm: LLM = OpenAI(model="gpt-4o", temperature=0.0),
-        embedding: BaseEmbedding = OpenAIEmbedding(model_name="text-embedding-3-small"),
-        entities: Optional[TypeAlias] = None,
-        relations: Optional[TypeAlias] = None,
-        schema: Optional[Union[dict[str, str], list[Triple]]] = None,
+        llm: Optional["LLM"] = None,
+        embedding: Optional["BaseEmbedding"] = None,
+        entities: Optional["TypeAlias"] = None,
+        relations: Optional["TypeAlias"] = None,
+        schema: Optional[Union[dict[str, str], list["Triple"]]] = None,
         strict: Optional[bool] = False,
     ):
         """Initialize a Neo4j Property graph.
@@ -78,8 +87,8 @@ def __init__(
         self.database = database
         self.username = username
         self.password = password
-        self.llm = llm
-        self.embedding = embedding
+        self.llm = llm or OpenAI(model="gpt-4o", temperature=0.0)
+        self.embedding = embedding or OpenAIEmbedding(model_name="text-embedding-3-small")
         self.entities = entities
         self.relations = relations
         self.schema = schema
@@ -188,7 +197,7 @@ def _clear(self) -> None:
         with self.graph_store._driver.session() as session:
             session.run("MATCH (n) DETACH DELETE n;")
 
-    def _load_doc(self, input_doc: list[Document]) -> list[LlamaDocument]:
+    def _load_doc(self, input_doc: list[Document]) -> list["LlamaDocument"]:
         """Load documents from the input files. Currently support the following file types:
         .csv - comma-separated values
         .docx - Microsoft Word
diff --git a/autogen/agentchat/contrib/graph_rag/neo4j_graph_rag_capability.py b/autogen/agentchat/contrib/graph_rag/neo4j_graph_rag_capability.py
index 9362cb8fe..50a379b17 100644
--- a/autogen/agentchat/contrib/graph_rag/neo4j_graph_rag_capability.py
+++ b/autogen/agentchat/contrib/graph_rag/neo4j_graph_rag_capability.py
@@ -4,8 +4,7 @@
 
 from typing import Any, Optional, Union
 
-from autogen import Agent, ConversableAgent, UserProxyAgent
-
+from .... import Agent, ConversableAgent, UserProxyAgent
 from .graph_query_engine import GraphStoreQueryResult
 from .graph_rag_capability import GraphRagCapability
 from .neo4j_graph_query_engine import Neo4jGraphQueryEngine
diff --git a/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_query_engine.py b/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_query_engine.py
index 7b85b0c2d..8f5a6921c 100644
--- a/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_query_engine.py
+++ b/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_query_engine.py
@@ -6,23 +6,26 @@
 import logging
 from typing import List, Optional, Union
 
-from neo4j import GraphDatabase
-from neo4j_graphrag.embeddings import Embedder, OpenAIEmbeddings
-from neo4j_graphrag.experimental.pipeline.kg_builder import SimpleKGPipeline
-from neo4j_graphrag.generation import GraphRAG
-from neo4j_graphrag.indexes import create_vector_index
-from neo4j_graphrag.llm.openai_llm import LLMInterface, OpenAILLM
-from neo4j_graphrag.retrievers import VectorRetriever
-
+from ....import_utils import optional_import_block, require_optional_import
 from .document import Document, DocumentType
 from .graph_query_engine import GraphQueryEngine, GraphStoreQueryResult
 
+with optional_import_block():
+    from neo4j import GraphDatabase
+    from neo4j_graphrag.embeddings import Embedder, OpenAIEmbeddings
+    from neo4j_graphrag.experimental.pipeline.kg_builder import SimpleKGPipeline
+    from neo4j_graphrag.generation import GraphRAG
+    from neo4j_graphrag.indexes import create_vector_index
+    from neo4j_graphrag.llm.openai_llm import LLMInterface, OpenAILLM
+    from neo4j_graphrag.retrievers import VectorRetriever
+
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 logging.getLogger("httpx").setLevel(logging.WARNING)
 logger = logging.getLogger(__name__)
 
 
+@require_optional_import(["neo4j", "neo4j_graphrag"], "neo4j")
 class Neo4jNativeGraphQueryEngine(GraphQueryEngine):
     """A graph query engine implemented using the Neo4j GraphRAG SDK.
     Provides functionality to initialize a knowledge graph,
@@ -35,13 +38,10 @@ def __init__(
         port: int = 7687,
         username: str = "neo4j",
         password: str = "password",
-        embeddings: Optional[Embedder] = OpenAIEmbeddings(model="text-embedding-3-large"),
+        embeddings: Optional["Embedder"] = None,
         embedding_dimension: Optional[int] = 3072,
-        llm: Optional[LLMInterface] = OpenAILLM(
-            model_name="gpt-4o",
-            model_params={"response_format": {"type": "json_object"}, "temperature": 0},
-        ),
-        query_llm: Optional[LLMInterface] = OpenAILLM(model_name="gpt-4o", model_params={"temperature": 0}),
+        llm: Optional["LLMInterface"] = None,
+        query_llm: Optional["LLMInterface"] = None,
         entities: Optional[List[str]] = None,
         relations: Optional[List[str]] = None,
         potential_schema: Optional[List[tuple[str, str, str]]] = None,
@@ -64,10 +64,13 @@ def __init__(
         """
         self.uri = f"{host}:{port}"
         self.driver = GraphDatabase.driver(self.uri, auth=(username, password))
-        self.embeddings = embeddings
+        self.embeddings = embeddings or OpenAIEmbeddings(model="text-embedding-3-large")
         self.embedding_dimension = embedding_dimension
-        self.llm = llm
-        self.query_llm = query_llm
+        self.llm = llm or OpenAILLM(
+            model_name="gpt-4o",
+            model_params={"response_format": {"type": "json_object"}, "temperature": 0},
+        )
+        self.query_llm = query_llm or OpenAILLM(model_name="gpt-4o", model_params={"temperature": 0})
         self.entities = entities
         self.relations = relations
         self.potential_schema = potential_schema
diff --git a/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_rag_capability.py b/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_rag_capability.py
index 31175f0a6..a91f14f69 100644
--- a/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_rag_capability.py
+++ b/autogen/agentchat/contrib/graph_rag/neo4j_native_graph_rag_capability.py
@@ -4,8 +4,7 @@
 
 from typing import Any, Optional, Union
 
-from autogen import Agent, ConversableAgent
-
+from .... import Agent, ConversableAgent
 from .graph_query_engine import GraphStoreQueryResult
 from .graph_rag_capability import GraphRagCapability
 from .neo4j_native_graph_query_engine import Neo4jNativeGraphQueryEngine
diff --git a/autogen/agentchat/contrib/img_utils.py b/autogen/agentchat/contrib/img_utils.py
index e1ca180b8..5f2fd1f47 100644
--- a/autogen/agentchat/contrib/img_utils.py
+++ b/autogen/agentchat/contrib/img_utils.py
@@ -15,11 +15,11 @@
 import requests
 
 from ...import_utils import optional_import_block, require_optional_import
+from .. import utils
 
 with optional_import_block():
     from PIL import Image
 
-from autogen.agentchat import utils
 
 # Parameters for token counting for images for different models
 MODEL_PARAMS = {
diff --git a/autogen/agentchat/contrib/llamaindex_conversable_agent.py b/autogen/agentchat/contrib/llamaindex_conversable_agent.py
index 8e90e51c3..b6751e07a 100644
--- a/autogen/agentchat/contrib/llamaindex_conversable_agent.py
+++ b/autogen/agentchat/contrib/llamaindex_conversable_agent.py
@@ -6,11 +6,10 @@
 # SPDX-License-Identifier: MIT
 from typing import Optional, Union
 
-from autogen import OpenAIWrapper
-from autogen.agentchat import Agent, ConversableAgent
-from autogen.agentchat.contrib.vectordb.utils import get_logger
-
+from ... import OpenAIWrapper
 from ...import_utils import optional_import_block, require_optional_import
+from .. import Agent, ConversableAgent
+from .vectordb.utils import get_logger
 
 logger = get_logger(__name__)
 
@@ -44,7 +43,7 @@ class LLamaIndexConversableAgent(ConversableAgent):
     def __init__(
         self,
         name: str,
-        llama_index_agent: AgentRunner,
+        llama_index_agent: "AgentRunner",
         description: Optional[str] = None,
         **kwargs,
     ):
@@ -85,7 +84,7 @@ def _generate_oai_reply(
         """Generate a reply using autogen.oai."""
         user_message, history = self._extract_message_and_history(messages=messages, sender=sender)
 
-        chat_response: AgentChatResponse = self._llama_index_agent.chat(message=user_message, chat_history=history)
+        chat_response: "AgentChatResponse" = self._llama_index_agent.chat(message=user_message, chat_history=history)
 
         extracted_response = chat_response.response
 
@@ -100,7 +99,7 @@ async def _a_generate_oai_reply(
         """Generate a reply using autogen.oai."""
         user_message, history = self._extract_message_and_history(messages=messages, sender=sender)
 
-        chat_response: AgentChatResponse = await self._llama_index_agent.achat(
+        chat_response: "AgentChatResponse" = await self._llama_index_agent.achat(
             message=user_message, chat_history=history
         )
 
@@ -110,7 +109,7 @@ async def _a_generate_oai_reply(
 
     def _extract_message_and_history(
         self, messages: Optional[list[dict]] = None, sender: Optional[Agent] = None
-    ) -> tuple[str, list[ChatMessage]]:
+    ) -> tuple[str, list["ChatMessage"]]:
         """Extract the message and history from the messages."""
         if not messages:
             messages = self._oai_messages[sender]
@@ -121,7 +120,7 @@ def _extract_message_and_history(
         message = messages[-1].get("content", "")
 
         history = messages[:-1]
-        history_messages: list[ChatMessage] = []
+        history_messages: list["ChatMessage"] = []
         for history_message in history:
             content = history_message.get("content", "")
             role = history_message.get("role", "user")
diff --git a/autogen/agentchat/contrib/llava_agent.py b/autogen/agentchat/contrib/llava_agent.py
index 5f1dec12e..35cf38194 100644
--- a/autogen/agentchat/contrib/llava_agent.py
+++ b/autogen/agentchat/contrib/llava_agent.py
@@ -8,15 +8,17 @@
 import logging
 from typing import Optional
 
-import replicate
 import requests
 
-from autogen.agentchat.agent import Agent
-from autogen.agentchat.contrib.img_utils import get_image_data, llava_formatter
-from autogen.agentchat.contrib.multimodal_conversable_agent import MultimodalConversableAgent
-from autogen.code_utils import content_str
-
+from ...code_utils import content_str
 from ...formatting_utils import colored
+from ...import_utils import optional_import_block, require_optional_import
+from ..agent import Agent
+from .img_utils import get_image_data, llava_formatter
+from .multimodal_conversable_agent import MultimodalConversableAgent
+
+with optional_import_block():
+    import replicate
 
 logger = logging.getLogger(__name__)
 
@@ -95,6 +97,7 @@ def _image_reply(self, messages=None, sender=None, config=None):
         return True, out
 
 
+@require_optional_import("replicate", "lmm")
 def _llava_call_binary_with_config(
     prompt: str, images: list, config: dict, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1
 ):
@@ -140,6 +143,7 @@ def _llava_call_binary_with_config(
     return output
 
 
+@require_optional_import("replicate", "lmm")
 def llava_call_binary(
     prompt: str, images: list, config_list: list, max_new_tokens: int = 1000, temperature: float = 0.5, seed: int = 1
 ):
diff --git a/autogen/agentchat/contrib/math_user_proxy_agent.py b/autogen/agentchat/contrib/math_user_proxy_agent.py
index 089053040..193827477 100644
--- a/autogen/agentchat/contrib/math_user_proxy_agent.py
+++ b/autogen/agentchat/contrib/math_user_proxy_agent.py
@@ -11,12 +11,11 @@
 
 from pydantic import BaseModel, Extra, root_validator
 
-from autogen._pydantic import PYDANTIC_V1
-from autogen.agentchat import Agent, UserProxyAgent
-from autogen.code_utils import UNKNOWN, execute_code, extract_code, infer_lang
-from autogen.math_utils import get_answer
-
+from ..._pydantic import PYDANTIC_V1
+from ...code_utils import UNKNOWN, execute_code, extract_code, infer_lang
 from ...import_utils import optional_import_block, require_optional_import
+from ...math_utils import get_answer
+from .. import Agent, UserProxyAgent
 
 with optional_import_block() as result:
     import wolframalpha
diff --git a/autogen/agentchat/contrib/multimodal_conversable_agent.py b/autogen/agentchat/contrib/multimodal_conversable_agent.py
index c41019f8e..9af171e39 100644
--- a/autogen/agentchat/contrib/multimodal_conversable_agent.py
+++ b/autogen/agentchat/contrib/multimodal_conversable_agent.py
@@ -7,15 +7,14 @@
 import copy
 from typing import Optional, Union
 
-from autogen import OpenAIWrapper
-from autogen.agentchat import Agent, ConversableAgent
-from autogen.agentchat.contrib.img_utils import (
+from ... import OpenAIWrapper
+from ..._pydantic import model_dump
+from ...code_utils import content_str
+from .. import Agent, ConversableAgent
+from ..contrib.img_utils import (
     gpt4v_formatter,
     message_formatter_pil_to_b64,
 )
-from autogen.code_utils import content_str
-
-from ..._pydantic import model_dump
 
 DEFAULT_LMM_SYS_MSG = """You are a helpful AI assistant."""
 DEFAULT_MODEL = "gpt-4-vision-preview"
diff --git a/autogen/agentchat/contrib/qdrant_retrieve_user_proxy_agent.py b/autogen/agentchat/contrib/qdrant_retrieve_user_proxy_agent.py
index cf04c4a17..9ec3979b4 100644
--- a/autogen/agentchat/contrib/qdrant_retrieve_user_proxy_agent.py
+++ b/autogen/agentchat/contrib/qdrant_retrieve_user_proxy_agent.py
@@ -7,15 +7,14 @@
 import warnings
 from typing import Callable, Literal, Optional
 
-from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent
-from autogen.agentchat.contrib.vectordb.utils import (
+from ...import_utils import optional_import_block, require_optional_import
+from ...retrieve_utils import TEXT_FORMATS, get_files_from_dir, split_files_to_chunks
+from ..contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent
+from ..contrib.vectordb.utils import (
     chroma_results_to_query_results,
     filter_results_by_distance,
     get_logger,
 )
-from autogen.retrieve_utils import TEXT_FORMATS, get_files_from_dir, split_files_to_chunks
-
-from ...import_utils import optional_import_block, require_optional_import
 
 logger = get_logger(__name__)
 
@@ -162,7 +161,7 @@ def retrieve_docs(self, problem: str, n_results: int = 20, search_string: str =
 def create_qdrant_from_dir(
     dir_path: str,
     max_tokens: int = 4000,
-    client: QdrantClient = None,
+    client: "QdrantClient" = None,
     collection_name: str = "all-my-documents",
     chunk_mode: str = "multi_lines",
     must_break_at_empty_line: bool = True,
@@ -173,8 +172,8 @@ def create_qdrant_from_dir(
     extra_docs: bool = False,
     parallel: int = 0,
     on_disk: bool = False,
-    quantization_config: Optional[models.QuantizationConfig] = None,
-    hnsw_config: Optional[models.HnswConfigDiff] = None,
+    quantization_config: Optional["models.QuantizationConfig"] = None,
+    hnsw_config: Optional["models.HnswConfigDiff"] = None,
     payload_indexing: bool = False,
     qdrant_client_options: Optional[dict] = {},
 ):
@@ -268,12 +267,12 @@ def create_qdrant_from_dir(
 def query_qdrant(
     query_texts: list[str],
     n_results: int = 10,
-    client: QdrantClient = None,
+    client: "QdrantClient" = None,
     collection_name: str = "all-my-documents",
     search_string: str = "",
     embedding_model: str = "BAAI/bge-small-en-v1.5",
     qdrant_client_options: Optional[dict] = {},
-) -> list[list[QueryResponse]]:
+) -> list[list["QueryResponse"]]:
     """Perform a similarity search with filters on a Qdrant collection
 
     Args:
diff --git a/autogen/agentchat/contrib/retrieve_assistant_agent.py b/autogen/agentchat/contrib/retrieve_assistant_agent.py
index 75a5c9dff..cc7966762 100644
--- a/autogen/agentchat/contrib/retrieve_assistant_agent.py
+++ b/autogen/agentchat/contrib/retrieve_assistant_agent.py
@@ -7,8 +7,8 @@
 import warnings
 from typing import Any, Optional, Union
 
-from autogen.agentchat.agent import Agent
-from autogen.agentchat.assistant_agent import AssistantAgent
+from ..agent import Agent
+from ..assistant_agent import AssistantAgent
 
 
 class RetrieveAssistantAgent(AssistantAgent):
diff --git a/autogen/agentchat/contrib/retrieve_user_proxy_agent.py b/autogen/agentchat/contrib/retrieve_user_proxy_agent.py
index 35aad52c4..73eb88562 100644
--- a/autogen/agentchat/contrib/retrieve_user_proxy_agent.py
+++ b/autogen/agentchat/contrib/retrieve_user_proxy_agent.py
@@ -10,31 +10,29 @@
 import uuid
 from typing import Any, Callable, Literal, Optional, Union
 
-from IPython import get_ipython
-
-from autogen.agentchat import UserProxyAgent
-from autogen.agentchat.agent import Agent
-from autogen.agentchat.contrib.vectordb.base import Document, QueryResults, VectorDB, VectorDBFactory
-from autogen.agentchat.contrib.vectordb.utils import (
-    chroma_results_to_query_results,
-    filter_results_by_distance,
-    get_logger,
-)
-from autogen.code_utils import extract_code
-from autogen.retrieve_utils import (
+from ...code_utils import extract_code
+from ...formatting_utils import colored
+from ...import_utils import optional_import_block, require_optional_import
+from ...retrieve_utils import (
     TEXT_FORMATS,
     create_vector_db_from_dir,
     get_files_from_dir,
     query_vector_db,
     split_files_to_chunks,
 )
-from autogen.token_count_utils import count_token
-
-from ...formatting_utils import colored
-from ...import_utils import optional_import_block, require_optional_import
+from ...token_count_utils import count_token
+from .. import UserProxyAgent
+from ..agent import Agent
+from ..contrib.vectordb.base import Document, QueryResults, VectorDB, VectorDBFactory
+from ..contrib.vectordb.utils import (
+    chroma_results_to_query_results,
+    filter_results_by_distance,
+    get_logger,
+)
 
 with optional_import_block():
     import chromadb
+    from IPython import get_ipython
 
 logger = get_logger(__name__)
 
@@ -91,7 +89,7 @@
 UPDATE_CONTEXT_IN_PROMPT = "you should reply exactly `UPDATE CONTEXT`"
 
 
-@require_optional_import("chromadb", "retrievechat")
+@require_optional_import(["chromadb", "IPython"], "retrievechat")
 class RetrieveUserProxyAgent(UserProxyAgent):
     """(In preview) The Retrieval-Augmented User Proxy retrieves document chunks based on the embedding
     similarity, and sends them along with the question to the Retrieval-Augmented Assistant
diff --git a/autogen/agentchat/contrib/society_of_mind_agent.py b/autogen/agentchat/contrib/society_of_mind_agent.py
index 6533974ce..0f409ceff 100644
--- a/autogen/agentchat/contrib/society_of_mind_agent.py
+++ b/autogen/agentchat/contrib/society_of_mind_agent.py
@@ -9,7 +9,7 @@
 import traceback
 from typing import Callable, Literal, Optional, Union
 
-from autogen import Agent, ConversableAgent, GroupChat, GroupChatManager, OpenAIWrapper
+from ... import Agent, ConversableAgent, GroupChat, GroupChatManager, OpenAIWrapper
 
 
 class SocietyOfMindAgent(ConversableAgent):
diff --git a/autogen/agentchat/contrib/swarm_agent.py b/autogen/agentchat/contrib/swarm_agent.py
index 416a99ab8..7139367bc 100644
--- a/autogen/agentchat/contrib/swarm_agent.py
+++ b/autogen/agentchat/contrib/swarm_agent.py
@@ -12,9 +12,8 @@
 
 from pydantic import BaseModel
 
-from autogen.oai import OpenAIWrapper
-from autogen.tools import get_function_schema
-
+from ...oai import OpenAIWrapper
+from ...tools import get_function_schema
 from ..agent import Agent
 from ..chat import ChatResult
 from ..conversable_agent import ConversableAgent
diff --git a/autogen/agentchat/contrib/text_analyzer_agent.py b/autogen/agentchat/contrib/text_analyzer_agent.py
index 289d5eb2e..708740d1b 100644
--- a/autogen/agentchat/contrib/text_analyzer_agent.py
+++ b/autogen/agentchat/contrib/text_analyzer_agent.py
@@ -6,8 +6,8 @@
 # SPDX-License-Identifier: MIT
 from typing import Any, Literal, Optional, Union
 
-from autogen.agentchat.agent import Agent
-from autogen.agentchat.assistant_agent import ConversableAgent
+from ..agent import Agent
+from ..assistant_agent import ConversableAgent
 
 system_message = """You are an expert in text analysis.
 The user will give you TEXT to analyze.
diff --git a/autogen/agentchat/contrib/vectordb/chromadb.py b/autogen/agentchat/contrib/vectordb/chromadb.py
index 29feab636..03e32764d 100644
--- a/autogen/agentchat/contrib/vectordb/chromadb.py
+++ b/autogen/agentchat/contrib/vectordb/chromadb.py
@@ -69,7 +69,7 @@ def __init__(
 
     def create_collection(
         self, collection_name: str, overwrite: bool = False, get_or_create: bool = True
-    ) -> Collection:
+    ) -> "Collection":
         """Create a collection in the vector database.
         Case 1. if the collection does not exist, create the collection.
         Case 2. the collection exists, if overwrite is True, it will overwrite the collection.
@@ -111,7 +111,7 @@ def create_collection(
         else:
             raise ValueError(f"Collection {collection_name} already exists.")
 
-    def get_collection(self, collection_name: str = None) -> Collection:
+    def get_collection(self, collection_name: str = None) -> "Collection":
         """Get the collection from the vector database.
 
         Args:
@@ -149,7 +149,7 @@ def delete_collection(self, collection_name: str) -> None:
             self.active_collection = None
 
     def _batch_insert(
-        self, collection: Collection, embeddings=None, ids=None, metadatas=None, documents=None, upsert=False
+        self, collection: "Collection", embeddings=None, ids=None, metadatas=None, documents=None, upsert=False
     ) -> None:
         batch_size = int(CHROMADB_MAX_BATCH_SIZE)
         for i in range(0, len(documents), min(batch_size, len(documents))):
diff --git a/autogen/agentchat/contrib/vectordb/mongodb.py b/autogen/agentchat/contrib/vectordb/mongodb.py
index 0065273cb..9e1d1ec3f 100644
--- a/autogen/agentchat/contrib/vectordb/mongodb.py
+++ b/autogen/agentchat/contrib/vectordb/mongodb.py
@@ -7,18 +7,21 @@
 from collections.abc import Iterable, Mapping
 from copy import deepcopy
 from time import monotonic, sleep
-from typing import Any, Callable, Literal, Union
+from typing import Any, Callable, Literal, Optional, Union
 
 import numpy as np
-from pymongo import MongoClient, UpdateOne, errors
-from pymongo.collection import Collection
-from pymongo.driver_info import DriverInfo
-from pymongo.operations import SearchIndexModel
-from sentence_transformers import SentenceTransformer
 
+from ....import_utils import optional_import_block, require_optional_import
 from .base import Document, ItemID, QueryResults, VectorDB
 from .utils import get_logger
 
+with optional_import_block():
+    from pymongo import MongoClient, UpdateOne, errors
+    from pymongo.collection import Collection
+    from pymongo.driver_info import DriverInfo
+    from pymongo.operations import SearchIndexModel
+    from sentence_transformers import SentenceTransformer
+
 logger = get_logger(__name__)
 
 DEFAULT_INSERT_BATCH_SIZE = 100_000
@@ -31,6 +34,7 @@ def with_id_rename(docs: Iterable) -> list[dict[str, Any]]:
     return [{**{k: v for k, v in d.items() if k != "_id"}, "id": d["_id"]} for d in docs]
 
 
+@require_optional_import(["pymongo", "sentence_transformers"], "retrievechat-mongodb")
 class MongoDBAtlasVectorDB(VectorDB):
     """A Collection object for MongoDB."""
 
@@ -38,7 +42,7 @@ def __init__(
         self,
         connection_string: str = "",
         database_name: str = "vector_db",
-        embedding_function: Callable = SentenceTransformer("all-MiniLM-L6-v2").encode,
+        embedding_function: Optional[Callable] = None,
         collection_name: str = None,
         index_name: str = "vector_index",
         overwrite: bool = False,
@@ -60,7 +64,7 @@ def __init__(
             wait_until_document_ready: float | None | Blocking call to wait until the
                 database indexes are ready. None, the default, means no wait.
         """
-        self.embedding_function = embedding_function
+        self.embedding_function = embedding_function or SentenceTransformer("all-MiniLM-L6-v2").encode
         self.index_name = index_name
         self._wait_until_index_ready = wait_until_index_ready
         self._wait_until_document_ready = wait_until_document_ready
@@ -82,7 +86,7 @@ def __init__(
         else:
             self.active_collection = None
 
-    def _is_index_ready(self, collection: Collection, index_name: str):
+    def _is_index_ready(self, collection: "Collection", index_name: str):
         """Check for the index name in the list of available search indexes to see if the
         specified index is of status READY
 
@@ -98,7 +102,7 @@ def _is_index_ready(self, collection: Collection, index_name: str):
                 return True
         return False
 
-    def _wait_for_index(self, collection: Collection, index_name: str, action: str = "create"):
+    def _wait_for_index(self, collection: "Collection", index_name: str, action: str = "create"):
         """Waits for the index action to be completed. Otherwise throws a TimeoutError.
 
         Timeout set on instantiation.
@@ -115,7 +119,7 @@ def _wait_for_index(self, collection: Collection, index_name: str, action: str =
 
         raise TimeoutError(f"Index {self.index_name} is not ready!")
 
-    def _wait_for_document(self, collection: Collection, index_name: str, doc: Document):
+    def _wait_for_document(self, collection: "Collection", index_name: str, doc: Document):
         start = monotonic()
         while monotonic() - start < self._wait_until_document_ready:
             query_result = _vector_search(
@@ -146,7 +150,7 @@ def create_collection(
         collection_name: str,
         overwrite: bool = False,
         get_or_create: bool = True,
-    ) -> Collection:
+    ) -> "Collection":
         """Create a collection in the vector database and create a vector search index in the collection.
 
         Args:
@@ -172,7 +176,7 @@ def create_collection(
             # get_or_create is False and the collection already exists, raise an error.
             raise ValueError(f"Collection {collection_name} already exists.")
 
-    def create_index_if_not_exists(self, index_name: str = "vector_index", collection: Collection = None) -> None:
+    def create_index_if_not_exists(self, index_name: str = "vector_index", collection: "Collection" = None) -> None:
         """Creates a vector search index on the specified collection in MongoDB.
 
         Args:
@@ -182,7 +186,7 @@ def create_index_if_not_exists(self, index_name: str = "vector_index", collectio
         if not self._is_index_ready(collection, index_name):
             self.create_vector_search_index(collection, index_name)
 
-    def get_collection(self, collection_name: str = None) -> Collection:
+    def get_collection(self, collection_name: str = None) -> "Collection":
         """Get the collection from the vector database.
 
         Args:
@@ -218,7 +222,7 @@ def delete_collection(self, collection_name: str) -> None:
 
     def create_vector_search_index(
         self,
-        collection: Collection,
+        collection: "Collection",
         index_name: Union[str, None] = "vector_index",
         similarity: Literal["euclidean", "cosine", "dotProduct"] = "cosine",
     ) -> None:
@@ -334,7 +338,7 @@ def insert_docs(
                 self._wait_for_document(collection, self.index_name, docs[-1])
 
     def _insert_batch(
-        self, collection: Collection, texts: list[str], metadatas: list[Mapping[str, Any]], ids: list[ItemID]
+        self, collection: "Collection", texts: list[str], metadatas: list[Mapping[str, Any]], ids: list[ItemID]
     ) -> set[ItemID]:
         """Compute embeddings for and insert a batch of Documents into the Collection.
 
@@ -500,7 +504,7 @@ def retrieve_docs(
 def _vector_search(
     embedding_vector: list[float],
     n_results: int,
-    collection: Collection,
+    collection: "Collection",
     index_name: str,
     distance_threshold: float = -1.0,
     oversampling_factor=10,
diff --git a/autogen/agentchat/contrib/vectordb/pgvectordb.py b/autogen/agentchat/contrib/vectordb/pgvectordb.py
index 3ca0f8235..0b87b38e6 100644
--- a/autogen/agentchat/contrib/vectordb/pgvectordb.py
+++ b/autogen/agentchat/contrib/vectordb/pgvectordb.py
@@ -546,7 +546,7 @@ class PGVectorDB(VectorDB):
     def __init__(
         self,
         *,
-        conn: Optional[psycopg.Connection] = None,
+        conn: Optional["psycopg.Connection"] = None,
         connection_string: Optional[str] = None,
         host: Optional[str] = None,
         port: Optional[Union[int, str]] = None,
@@ -603,7 +603,7 @@ def __init__(
 
     def establish_connection(
         self,
-        conn: Optional[psycopg.Connection] = None,
+        conn: Optional["psycopg.Connection"] = None,
         connection_string: Optional[str] = None,
         host: Optional[str] = None,
         port: Optional[Union[int, str]] = None,
@@ -611,7 +611,7 @@ def establish_connection(
         username: Optional[str] = None,
         password: Optional[str] = None,
         connect_timeout: Optional[int] = 10,
-    ) -> psycopg.Connection:
+    ) -> "psycopg.Connection":
         """Establishes a connection to a PostgreSQL database using psycopg.
 
         Args:
diff --git a/autogen/agentchat/contrib/vectordb/qdrant.py b/autogen/agentchat/contrib/vectordb/qdrant.py
index 46be5d7b3..d930f9209 100644
--- a/autogen/agentchat/contrib/vectordb/qdrant.py
+++ b/autogen/agentchat/contrib/vectordb/qdrant.py
@@ -271,7 +271,7 @@ def _point_to_document(self, point) -> Document:
     def _points_to_documents(self, points) -> list[Document]:
         return [self._point_to_document(point) for point in points]
 
-    def _scored_point_to_document(self, scored_point: models.ScoredPoint) -> tuple[Document, float]:
+    def _scored_point_to_document(self, scored_point: "models.ScoredPoint") -> tuple[Document, float]:
         return self._point_to_document(scored_point), scored_point.score
 
     def _documents_to_points(self, documents: list[Document]):
@@ -290,7 +290,7 @@ def _documents_to_points(self, documents: list[Document]):
         ]
         return points
 
-    def _scored_points_to_documents(self, scored_points: list[models.ScoredPoint]) -> list[tuple[Document, float]]:
+    def _scored_points_to_documents(self, scored_points: list["models.ScoredPoint"]) -> list[tuple[Document, float]]:
         return [self._scored_point_to_document(scored_point) for scored_point in scored_points]
 
     def _validate_update_ids(self, collection_name: str, ids: list[str]) -> bool:
diff --git a/autogen/logger/file_logger.py b/autogen/logger/file_logger.py
index de351d57d..f30a7a520 100644
--- a/autogen/logger/file_logger.py
+++ b/autogen/logger/file_logger.py
@@ -143,7 +143,7 @@ def log_new_agent(self, agent: ConversableAgent, init_args: dict[str, Any] = {})
 
     def log_event(self, source: str | Agent, name: str, **kwargs: dict[str, Any]) -> None:
         """Log an event from an agent or a string source."""
-        from autogen import Agent
+        from .. import Agent
 
         # This takes an object o as input and returns a string. If the object o cannot be serialized, instead of raising an error,
         # it returns a string indicating that the object is non-serializable, along with its type's qualified name obtained using __qualname__.
diff --git a/autogen/logger/sqlite_logger.py b/autogen/logger/sqlite_logger.py
index 9c250ae74..2771f2f3c 100644
--- a/autogen/logger/sqlite_logger.py
+++ b/autogen/logger/sqlite_logger.py
@@ -307,7 +307,7 @@ def log_new_agent(self, agent: ConversableAgent, init_args: dict[str, Any]) -> N
             agent (ConversableAgent): Agent to log.
             init_args (dict[str, Any]): Initialization arguments of the agent
         """
-        from autogen import Agent
+        from .. import Agent
 
         if self.con is None:
             return
diff --git a/autogen/oai/client.py b/autogen/oai/client.py
index a8b01ab9d..1e6fdd1a1 100644
--- a/autogen/oai/client.py
+++ b/autogen/oai/client.py
@@ -60,7 +60,7 @@
         RateLimitError as cerebras_RateLimitError,
     )
 
-    from autogen.oai.cerebras import CerebrasClient
+    from .cerebras import CerebrasClient
 
 if cerebras_result.is_successful:
     cerebras_import_exception: Optional[ImportError] = None
@@ -74,7 +74,7 @@
         ResourceExhausted as gemini_ResourceExhausted,
     )
 
-    from autogen.oai.gemini import GeminiClient
+    from .gemini import GeminiClient
 
 if gemini_result.is_successful:
     gemini_import_exception: Optional[ImportError] = None
@@ -88,7 +88,7 @@
         RateLimitError as anthorpic_RateLimitError,
     )
 
-    from autogen.oai.anthropic import AnthropicClient
+    from .anthropic import AnthropicClient
 
 if anthropic_result.is_successful:
     anthropic_import_exception: Optional[ImportError] = None
@@ -102,7 +102,7 @@
         SDKError as mistral_SDKError,
     )
 
-    from autogen.oai.mistral import MistralAIClient
+    from .mistral import MistralAIClient
 
 if mistral_result.is_successful:
     mistral_import_exception: Optional[ImportError] = None
@@ -113,7 +113,7 @@
 with optional_import_block() as together_result:
     from together.error import TogetherException as together_TogetherException
 
-    from autogen.oai.together import TogetherClient
+    from .together import TogetherClient
 
 if together_result.is_successful:
     together_import_exception: Optional[ImportError] = None
@@ -128,7 +128,7 @@
         RateLimitError as groq_RateLimitError,
     )
 
-    from autogen.oai.groq import GroqClient
+    from .groq import GroqClient
 
 if groq_result.is_successful:
     groq_import_exception: Optional[ImportError] = None
@@ -143,7 +143,7 @@
         TooManyRequestsError as cohere_TooManyRequestsError,
     )
 
-    from autogen.oai.cohere import CohereClient
+    from .cohere import CohereClient
 
 if cohere_result.is_successful:
     cohere_import_exception: Optional[ImportError] = None
@@ -157,7 +157,7 @@
         ResponseError as ollama_ResponseError,
     )
 
-    from autogen.oai.ollama import OllamaClient
+    from .ollama import OllamaClient
 
 if ollama_result.is_successful:
     ollama_import_exception: Optional[ImportError] = None
@@ -171,7 +171,7 @@
         ClientError as bedrock_ClientError,
     )
 
-    from autogen.oai.bedrock import BedrockClient
+    from .bedrock import BedrockClient
 
 if bedrock_result.is_successful:
     bedrock_import_exception: Optional[ImportError] = None
diff --git a/test/agentchat/contrib/graph_rag/test_falkor_graph_rag.py b/test/agentchat/contrib/graph_rag/test_falkor_graph_rag.py
index 030153164..1c7a17fc1 100644
--- a/test/agentchat/contrib/graph_rag/test_falkor_graph_rag.py
+++ b/test/agentchat/contrib/graph_rag/test_falkor_graph_rag.py
@@ -7,16 +7,17 @@
 import sys
 
 import pytest
-from graphrag_sdk import Attribute, AttributeType, Entity, Ontology, Relation
 
+from autogen.agentchat.contrib.graph_rag.document import Document, DocumentType
+from autogen.agentchat.contrib.graph_rag.falkor_graph_query_engine import (
+    FalkorGraphQueryEngine,
+    GraphStoreQueryResult,
+)
 from autogen.import_utils import optional_import_block
 
 with optional_import_block() as result:
-    from autogen.agentchat.contrib.graph_rag.document import Document, DocumentType
-    from autogen.agentchat.contrib.graph_rag.falkor_graph_query_engine import (
-        FalkorGraphQueryEngine,
-        GraphStoreQueryResult,
-    )
+    import falkordb  # noqa: F401
+    from graphrag_sdk import Attribute, AttributeType, Entity, Ontology, Relation
 
 skip = not result.is_successful
 
diff --git a/test/agentchat/contrib/retrievechat/test_retrievechat.py b/test/agentchat/contrib/retrievechat/test_retrievechat.py
index e40e97d16..e9eb32701 100755
--- a/test/agentchat/contrib/retrievechat/test_retrievechat.py
+++ b/test/agentchat/contrib/retrievechat/test_retrievechat.py
@@ -10,6 +10,10 @@
 
 import pytest
 
+from autogen import AssistantAgent
+from autogen.agentchat.contrib.retrieve_user_proxy_agent import (
+    RetrieveUserProxyAgent,
+)
 from autogen.import_utils import optional_import_block
 
 from ....conftest import Credentials, reason
@@ -17,12 +21,9 @@
 with optional_import_block() as result:
     import chromadb
     import openai  # noqa: F401
+    from IPython import get_ipython  # noqa: F401
     from chromadb.utils import embedding_functions as ef
 
-    from autogen import AssistantAgent
-    from autogen.agentchat.contrib.retrieve_user_proxy_agent import (
-        RetrieveUserProxyAgent,
-    )
 
 skip = not result.is_successful