diff --git a/.idea/electro.iml b/.idea/electro.iml
index caf2fb7..e29f7b9 100644
--- a/.idea/electro.iml
+++ b/.idea/electro.iml
@@ -5,7 +5,7 @@
       <sourceFolder url="file://$MODULE_DIR$/electro" isTestSource="false" />
       <excludeFolder url="file://$MODULE_DIR$/logs" />
     </content>
-    <orderEntry type="jdk" jdkName="Poetry (electro)" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="uv (electro)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
   </component>
 </module>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
index 48e806c..ddf973f 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -4,5 +4,5 @@
     <option name="enabledOnReformat" value="true" />
     <option name="sdkName" value="Poetry (electro)" />
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Poetry (electro)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="uv (electro)" project-jdk-type="Python SDK" />
 </project>
\ No newline at end of file
diff --git a/.python-version b/.python-version
new file mode 100644
index 0000000..fdcfcfd
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.12
\ No newline at end of file
diff --git a/Procfile b/Procfile
new file mode 100644
index 0000000..0c5634a
--- /dev/null
+++ b/Procfile
@@ -0,0 +1 @@
+web: uvicorn --host=0.0.0.0 --port=${PORT:-8000} electro.app:app
\ No newline at end of file
diff --git a/electro/app.py b/electro/app.py
index 13d736d..ff27145 100644
--- a/electro/app.py
+++ b/electro/app.py
@@ -1,10 +1,13 @@
 """The API server that works as an endpoint for all the Electro Interfaces."""
 
 from fastapi import FastAPI
+from starlette.middleware.cors import CORSMiddleware
 from tortoise.contrib.fastapi import register_tortoise
 
 from . import types_ as types
+from .chat_router import chat__router
 from .flow_manager import global_flow_manager
+from .settings import settings
 from .toolkit.tortoise_orm import get_tortoise_config
 
 app = FastAPI(
@@ -14,6 +17,20 @@
     # docs_url="/",
     # redoc_url=None,
 )
+app.add_middleware(
+    CORSMiddleware,
+    allow_origin_regex=(
+        # Allow http or https, with or without port, with or without subdomain
+        rf"(http|https)://.*{settings.DOMAIN.split(':', maxsplit=1)[0]}(:\d+)*"
+        if settings.DEBUG
+        # Allow all subdomains of the main domain, but only https
+        # pylint: disable=anomalous-backslash-in-string
+        else rf"https:\/\/.*\.?{'\.'.join(settings.DOMAIN.split('.')[-2:])}"
+    ),
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
 
 
 @app.post("/message")
@@ -23,6 +40,8 @@ async def process_message(message: types.Message) -> list[types.MessageToSend] |
     return await global_flow_manager.on_message(message)
 
 
+app.include_router(chat__router, prefix="/chat")
+
 # region Register Tortoise
 register_tortoise(
     app,
diff --git a/electro/assistant_functions.py b/electro/assistant_functions.py
new file mode 100644
index 0000000..ffdd74d
--- /dev/null
+++ b/electro/assistant_functions.py
@@ -0,0 +1,92 @@
+"""Functions for OpenAI Assistant."""
+
+import json
+from contextvars import ContextVar
+
+from .enums import FrontendAction
+from .toolkit.loguru_logging import logger
+
+# Create a ContextVar to store frontend actions
+action_context: ContextVar[list[str]] = ContextVar("actions", default=[])
+
+
+async def get_frontend_actions(*_, **__) -> str:
+    """
+    Asynchronously fetches the list of frontend actions from the database.
+    This function is designed to work directly with OpenAI Assistant's tool calling pattern.
+
+    Returns:
+        str: JSON string containing the list of frontend actions or error information
+
+    Schema:
+    {
+        "name": "get_frontend_actions",
+        "description": "Fetch the list of the actions that can be performed by the frontend",
+        "parameters": {
+            "type": "object",
+            "required": [],
+            "properties": {}
+        }
+    }
+    """
+    try:
+        # Fetch the list of frontend actions
+        frontend_actions = [action.value for action in FrontendAction]
+
+        # Return the list of frontend actions
+        return json.dumps(frontend_actions, ensure_ascii=False, indent=2)
+
+    except Exception as e:
+        logger.error(f"Unexpected error while fetching frontend actions: {str(e)}")
+        error_response = {"error": str(e), "status": "failed"}
+        return json.dumps(error_response, ensure_ascii=False, indent=2)
+
+
+async def submit_frontend_action(action: str, *_, **__) -> str:
+    """
+    Asynchronously submits a frontend action to the database.
+    This function is designed to work directly with OpenAI Assistant's tool calling pattern.
+
+    Args:
+        action (str): The frontend action to submit
+
+    Returns:
+        str: JSON string containing the result or error information
+
+    Schema:
+    {
+        "name": "submit_frontend_action",
+        "description": "Submit an action to be performed by the frontend",
+        "parameters": {
+            "type": "object",
+            "required": ["action"],
+            "properties": {
+                "action": {
+                    "type": "string",
+                    "description": "The frontend action to submit"
+                }
+            }
+        }
+    }
+    """
+    try:
+        # Input validation
+        if not action or not isinstance(action, str):
+            error_response = {"error": "action must be a non-empty string", "status": "failed"}
+            return json.dumps(error_response, ensure_ascii=False, indent=2)
+
+        # Check if the action is valid
+        if action not in [frontend_action.value for frontend_action in FrontendAction]:
+            error_response = {"error": "Invalid frontend action", "status": "failed"}
+            return json.dumps(error_response, ensure_ascii=False, indent=2)
+
+        # Save the frontend action
+        # TODO: [2025-01-31 by Mykola] Check if we can `.append()` it in-place, or we need to `.get()` and `.set()` it
+        action_context.get().append(action)
+
+        return json.dumps({"status": "success"}, ensure_ascii=False, indent=2)
+
+    except Exception as exception:
+        logger.error(f"Error submitting frontend action: {exception}")
+        error_response = {"error": str(exception), "status": "failed"}
+        return json.dumps(error_response, ensure_ascii=False, indent=2)
diff --git a/electro/auth_dependencies.py b/electro/auth_dependencies.py
new file mode 100644
index 0000000..2cb04fd
--- /dev/null
+++ b/electro/auth_dependencies.py
@@ -0,0 +1,13 @@
+"""Authentication dependencies, using JWT."""
+
+# TODO: [2025-07-14 by Mykola] Actually use JWT (or some other authentication method) for User authentication.
+
+from fastapi.requests import Request
+
+from .models import User
+
+
+async def get_current_user(_request: Request) -> User:
+    """Get the current user from the request."""
+
+    return await User.get(id=1)
diff --git a/electro/chat_router.py b/electro/chat_router.py
new file mode 100644
index 0000000..600a4a4
--- /dev/null
+++ b/electro/chat_router.py
@@ -0,0 +1,363 @@
+"""The Chat Router."""
+
+from typing import AsyncIterator
+
+from fastapi import APIRouter, Depends, HTTPException, status
+from starlette.responses import StreamingResponse
+
+from .assistant_functions import action_context, get_frontend_actions, submit_frontend_action
+from .auth_dependencies import get_current_user
+from .enums import AssistantType, FrontendAction
+from .helpers import (
+    create_new_chat_thread,
+    current_message_id,
+    get_assistant_response,
+    get_assistant_response__async,
+    save_assistant_user_message,
+)
+from .models import Assistant, AssistantChatMessage, AssistantChatThread, User
+from .schemas import (
+    AssistantChatMessageCreateSchema,
+    AssistantChatMessageDeltaSchema,
+    AssistantChatMessageSchema,
+    AssistantChatThreadCreateSchema,
+    AssistantChatThreadSchema,
+)
+from .toolkit.loguru_logging import logger
+
+chat__router = APIRouter(tags=["Chat"], dependencies=[Depends(get_current_user)])
+
+
+ENABLED_FUNCTIONS = {
+    "get_frontend_actions": get_frontend_actions,
+    "submit_frontend_action": submit_frontend_action,
+}
+
+
+async def _get_thread(thread_id: str, user: User) -> AssistantChatThread:
+    """
+    Ensure that the user has ownership of the chat thread.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread
+        user (User): The current user
+
+    Returns:
+        AssistantChatThread: The chat thread object if the user has ownership
+    """
+    if not (thread := await AssistantChatThread.get_or_none(thread_id=thread_id).prefetch_related("user", "assistant")):
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"No chat thread found with ID {thread_id}",
+        )
+
+    if not thread.user == user and not user.is_admin:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="You are not allowed to access this chat thread",
+        )
+
+    return thread
+
+
+async def _validate_message(message: AssistantChatMessageCreateSchema) -> AssistantChatMessageCreateSchema:
+    """
+    Validate the message before saving it.
+
+    Args:
+        message (AssistantChatMessageCreateSchema): The message to validate
+
+    Raises:
+        HTTPException: If the message is invalid
+    """
+    if not message.role or message.role != "user":
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="The message role must be 'user'",
+        )
+
+    if not message.content:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="The message content cannot be empty",
+        )
+
+    return message
+
+
+# region Chat Endpoints
+@chat__router.get("/threads")
+async def get_chat_threads(
+    assistant_type: AssistantType | None = None, user: User = Depends(get_current_user)
+) -> list[AssistantChatThreadSchema]:
+    """
+    Get the list of chat threads.
+
+    Args:
+        assistant_type (AssistantType | None): The type of the chat thread (optional)
+        user (User): The current user
+
+    Returns:
+        Dict containing the list of chat threads
+    """
+    assistant_chats__query = AssistantChatThread.filter(user=user).prefetch_related("assistant")
+
+    if assistant_type:
+        assistant_chats__query = assistant_chats__query.filter(assistant__assistant_type=assistant_type)
+
+    assistant_chat_threads = [
+        AssistantChatThreadSchema.model_validate(thread) for thread in await assistant_chats__query
+    ]
+
+    return assistant_chat_threads
+
+
+@chat__router.post("/threads")
+async def create_chat_thread(
+    thread: AssistantChatThreadCreateSchema,
+    user: User = Depends(get_current_user),
+) -> AssistantChatThreadSchema:
+    """
+    Create a chat thread.
+
+    Args:
+        thread (AssistantChatThreadCreateSchema): The chat thread to create
+        user (User): The current user
+
+    Returns:
+        Dict containing the created chat thread
+    """
+    if not (
+        assistant := await Assistant.filter(assistant_type=thread.assistant_type, is_active=True, is_deleted=False)
+        .order_by("-date_added")
+        .first()
+    ):
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"No active assistant found with type {thread.assistant_type}",
+        )
+
+    try:
+        created_thread = await create_new_chat_thread()
+    except Exception as exception:
+        logger.error(f"Error creating chat thread: {exception}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="Error creating chat thread",
+        )
+
+    thread__obj = await AssistantChatThread.create(
+        user=user,
+        assistant=assistant,
+        thread_id=created_thread.id,
+        **thread.model_dump(exclude_unset=True, exclude={"assistant_type"}),
+    )
+
+    return AssistantChatThreadSchema.model_validate(thread__obj)
+
+
+@chat__router.get("/{thread_id}/messages")
+async def get_chat_thread_messages(
+    thread_id: str, approved_user: User = Depends(get_current_user)
+) -> list[AssistantChatMessageSchema]:
+    """
+    Get the messages of the chat thread with the given ID.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread
+        approved_user (User): The current approved user
+
+    Returns:
+        Dict containing the messages of the chat thread
+    """
+    thread = await _get_thread(thread_id, approved_user)
+
+    return [
+        AssistantChatMessageSchema.model_validate(message)
+        for message in await AssistantChatMessage.filter(thread=thread)
+    ]
+
+
+@chat__router.post("/{thread_id}/messages")
+async def create_chat_thread_message(
+    thread_id: str, message: AssistantChatMessageCreateSchema, approved_user: User = Depends(get_current_user)
+) -> list[AssistantChatMessageSchema]:
+    """
+    Create a message in the chat thread with the given ID.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread
+        message (AssistantChatMessageCreateSchema): The message to create
+        approved_user (User): The current user
+
+    Returns:
+        Dict containing the created message
+    """
+    thread = await _get_thread(thread_id, approved_user)
+
+    message = await _validate_message(message)
+
+    # Save the user message as a message
+    user_message = await AssistantChatMessage.create(thread=thread, **message.model_dump(exclude_unset=True))
+    logger.info(f"User message saved: {user_message}")
+
+    # Reset the frontend actions context for this request
+    action_context.set([])
+
+    # TODO: [2025-07-10 by Mykola] Allow getting multiple messages from the Assistant
+    assistant_response = await get_assistant_response(
+        assistant_id=thread.assistant.id,
+        prompt=message.content,
+        thread_id=thread_id,
+        functions=ENABLED_FUNCTIONS,
+        approved_user=approved_user,
+    )
+    logger.info(f"Assistant response: {assistant_response}")
+
+    # Save the assistant response as a message
+    assistant_message = await AssistantChatMessage.create(thread=thread, content=assistant_response, role="assistant")
+    logger.info(f"Assistant message saved: {assistant_message}")
+
+    # TODO: [2025-07-14 by Mykola] Make it non-ugly
+    assistant_message.frontend_actions = action_context.get()
+
+    return [
+        # TODO: [2025-07-14 by Mykola] Allow getting multiple messages from the Assistant
+        AssistantChatMessageSchema.model_validate(assistant_message)
+    ]
+
+
+async def create_chat_thread_message__streaming(
+    thread_id: str, message: AssistantChatMessageCreateSchema, approved_user: User = Depends(get_current_user)
+) -> AsyncIterator[AssistantChatMessageDeltaSchema]:
+    """
+    Create a message in the chat thread with the given ID.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread
+        message (AssistantChatMessageCreateSchema): The message to create
+        approved_user (User): The current user
+
+    Returns:
+        StreamingResponse: The created message as a stream
+    """
+    thread = await _get_thread(thread_id, approved_user)
+
+    message = await _validate_message(message)
+
+    # Save the user message as a message
+    user_message = await AssistantChatMessage.create(thread=thread, **message.model_dump(exclude_unset=True))
+    logger.info(f"User message saved: {user_message}")
+
+    # Reset the frontend actions context for this request
+    action_context.set([])
+    # Set the current message ID to the user message ID
+    current_message_id.set(None)
+
+    user_thread_message = await save_assistant_user_message(
+        thread_id=thread.thread_id,
+        content=message.content,
+    )
+
+    # Save the message_id from the `user_thread_message`
+    user_message.message_id = user_thread_message.id
+    await user_message.save()
+
+    all_content_blocks = []
+    async for message_block, assistant_message_delta_type in get_assistant_response__async(
+        assistant_id=thread.assistant.id,
+        thread_message=user_thread_message,
+        thread_id=thread_id,
+        functions=ENABLED_FUNCTIONS,
+        approved_user=approved_user,
+    ):
+        logger.info(f"Assistant response: {message_block}")
+        all_content_blocks.append(message_block)
+
+        # frontend_actions: list[str] = action_context.get()
+        # if frontend_actions:
+        #     yield AssistantChatMessageDeltaSchema(
+        #         role="assistant",
+        #         content=message_block,
+        #         type=AssistantMessageDeltaType.CONTENT_BLOCK,
+        #     )
+
+        frontend_actions: list[str] = action_context.get()
+
+        yield AssistantChatMessageDeltaSchema(
+            message_id=current_message_id.get(),
+            role="assistant",
+            content=message_block,
+            type=assistant_message_delta_type,
+            frontend_actions=[FrontendAction(action) for action in frontend_actions],
+        )
+
+        # Reset the frontend actions context for the next message
+        if frontend_actions:
+            action_context.set([])
+
+    # Save the assistant response as a message
+    assistant_message = await AssistantChatMessage.create(
+        thread=thread, content="".join(all_content_blocks), role="assistant", message_id=current_message_id.get()
+    )
+    logger.info(f"Assistant message saved: {assistant_message}")
+
+    # Reset the current message ID
+    current_message_id.set(None)
+
+
+async def assistant_delta_messages_to_sse(
+    assistant_delta_messages: AsyncIterator[AssistantChatMessageDeltaSchema],
+) -> AsyncIterator[str]:
+    """
+    Convert the assistant delta messages to Server-Sent Events.
+
+    Args:
+        assistant_delta_messages (AsyncIterator[AssistantChatMessageDeltaSchema]): The assistant delta messages
+
+    Returns:
+        AsyncIterator[str]: The Server-Sent Events
+    """
+    async for assistant_delta_message in assistant_delta_messages:
+        yield f"data: {assistant_delta_message.model_dump_json()}\n\n"
+
+
+@chat__router.post("/{thread_id}/messages/stream")
+async def create_chat_thread_message_streaming(
+    thread_id: str, message: AssistantChatMessageCreateSchema, approved_user: User = Depends(get_current_user)
+) -> StreamingResponse:
+    """
+    Create a message in the chat thread with the given ID.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread
+        message (AssistantChatMessageCreateSchema): The message to create
+        approved_user (User): The current user
+
+    Returns:
+        StreamingResponse: The created message as a stream
+    """
+    return StreamingResponse(
+        assistant_delta_messages_to_sse(create_chat_thread_message__streaming(thread_id, message, approved_user)),
+        media_type="text/event-stream",
+    )
+
+
+@chat__router.delete("/{thread_id}")
+async def delete_chat_thread(thread_id: str, superuser_user: User = Depends(get_current_user)) -> dict:
+    """
+    Delete a chat thread by its thread_id.
+
+    Args:
+        thread_id (str): The `.thread_id` of the chat thread to delete
+        superuser_user (User): The current superuser user
+
+    Returns:
+        dict: Confirmation message
+    """
+    thread = await _get_thread(thread_id, superuser_user)
+
+    await AssistantChatMessage.filter(thread=thread).delete()
+    await thread.delete()
+
+    return {"message": "Chat thread deleted successfully"}
diff --git a/electro/enums.py b/electro/enums.py
index 13a5cad..58bcf95 100644
--- a/electro/enums.py
+++ b/electro/enums.py
@@ -30,3 +30,33 @@ class ChannelType(Enum):
 
     def __str__(self):
         return self.name
+
+
+# region Real-time Assistant Messages (using SSE)
+class AssistantMessageDeltaType(str, Enum):
+    """The types of deltas for an assistant's chat message."""
+
+    MESSAGE_START = "message_start"
+    MESSAGE_END = "message_end"
+
+    METADATA = "metadata"
+
+    CONTENT_BLOCK = "content_block"
+
+    ERROR = "error"
+
+
+class AssistantType(str, Enum):
+    """The Assistant types."""
+
+    CONVERSATIONAL = "conversational"
+
+
+class FrontendAction(str, Enum):
+    """The Front-end actions."""
+
+    ADD_SPARKLES = "add_sparkles"
+    ADD_BALLOONS = "add_balloons"
+
+
+# endregion
diff --git a/electro/helpers.py b/electro/helpers.py
new file mode 100644
index 0000000..bbc29a5
--- /dev/null
+++ b/electro/helpers.py
@@ -0,0 +1,382 @@
+"""Chat helpers."""
+
+import asyncio
+import json
+from contextvars import ContextVar
+from typing import Any, AsyncGenerator, Callable, Tuple
+
+from httpx import ReadTimeout
+from openai.types.beta import Thread
+from openai.types.beta.assistant_stream_event import (
+    AssistantStreamEvent,
+    ThreadMessageCreated,
+    ThreadMessageDelta,
+    ThreadRunCancelled,
+    ThreadRunCancelling,
+    ThreadRunCompleted,
+    ThreadRunCreated,
+    ThreadRunExpired,
+    ThreadRunFailed,
+    ThreadRunInProgress,
+    ThreadRunQueued,
+    ThreadRunRequiresAction,
+    ThreadRunStepCancelled,
+    ThreadRunStepFailed,
+)
+from openai.types.beta.threads import RequiredActionFunctionToolCall
+from openai.types.beta.threads.message import Message
+from openai.types.beta.threads.run_submit_tool_outputs_params import ToolOutput
+
+from .schemas import AssistantMessageDeltaType
+from .settings import settings
+from .toolkit.loguru_logging import logger
+from .toolkit.openai_client import async_openai_client
+
+
+async def create_new_chat_thread() -> Thread:
+    """
+    Create an Assistant chat thread.
+
+    Returns:
+        str: The `.thread_id` of the created chat thread
+    """
+
+    return await async_openai_client.beta.threads.create()
+
+
+async def get_assistant_response(
+    assistant_id: str,
+    prompt: str,
+    thread_id: str,
+    functions: dict[str, Callable],
+    **kwargs: dict[str, Any],
+) -> str:
+    """
+    Get the assistant response.
+
+    Args:
+        assistant_id (str): The ID of the assistant to use
+        prompt (str): The prompt to send to the assistant
+        thread_id (str): The ID of the chat thread
+        functions (dict[str, callable]): The functions to execute
+        **kwargs (dict[str, Any]): The keyword arguments to pass to the functions
+
+    Returns:
+        str: The response from the assistant
+    """
+
+    logger.info(f"Getting the Assistant response for {prompt=}...")
+
+    # TODO: [2025-07-10 by Mykola] Allow different assistants to be chosen by the user and/or depending on the use-case
+    assistant = await async_openai_client.beta.assistants.retrieve(assistant_id)
+
+    thread = await async_openai_client.beta.threads.retrieve(thread_id)
+
+    # TODO: [2025-07-11 by Mykola] Stop all the active runs for the thread before creating a new one
+
+    thread_message = await async_openai_client.beta.threads.messages.create(
+        thread_id=thread.id, role="user", content=prompt
+    )
+    logger.info(f"Created a message in Assistants API: {thread_message=}, {thread_id=}.")
+
+    run = await async_openai_client.beta.threads.runs.create(
+        thread_id=thread.id,
+        assistant_id=assistant.id,
+        # max_prompt_tokens=settings.OPENAI_MAX_PROMPT_TOKENS,
+        # max_completion_tokens=settings.OPENAI_MAX_COMPLETION_TOKENS,
+    )
+    logger.info(f"Run the thread with: {thread_message=}, {thread_id=}. Got {run=}")
+
+    # Initial sleep, just to give the API some time to process the request
+    await asyncio.sleep(3)
+
+    re_run_count = 0
+    run_retry_count = 0
+    while True:
+        for retry_n in range(1, settings.OPENAI_API_RUN_FETCH_RETRIES + 1):
+            logger.info(f"Trying to retrieve a run. Try #{retry_n}: {run.id=}")
+            try:
+                run = await async_openai_client.beta.threads.runs.retrieve(
+                    thread_id=thread.id, run_id=run.id, timeout=10
+                )
+                logger.info(f"Retrieved a run: {run=} for {thread_id=}")
+                break
+            except ReadTimeout as exception:
+                logger.exception(
+                    f"Hit a ReadTimeout while retrieving a run: {thread_id=}, {run.id=}", exc_info=exception
+                )
+
+                logger.info("Sleeping for 1 second")
+                await asyncio.sleep(1)
+
+        if run.status == "completed":
+            break
+
+        elif run.status == "requires_action":
+            if not functions:
+                raise ValueError(f"The functions are not set: {functions=}")
+
+            tool_outputs: list[ToolOutput] = []
+            # Get the action to perform
+            for tool_call in run.required_action.submit_tool_outputs.tool_calls:
+                # Get the function to execute
+                function_to_execute = functions.get(tool_call.function.name)
+
+                if not function_to_execute:
+                    raise ValueError(f"The function to execute is not found: {tool_call.function.name}")
+
+                # Execute the function
+                action_output = await function_to_execute(**(kwargs | json.loads(tool_call.function.arguments)))
+
+                # Add the output to the tool outputs
+                tool_outputs.append(
+                    ToolOutput(
+                        tool_call_id=tool_call.id,
+                        output=action_output,
+                    )
+                )
+
+            # Submit tool outputs
+            await async_openai_client.beta.threads.runs.submit_tool_outputs(
+                thread_id=thread.id,
+                run_id=run.id,
+                tool_outputs=tool_outputs,
+            )
+
+        elif run.status == "in_progress":
+            logger.debug(f"Run {run.id} is in progress. Sleeping for 1 second...")
+            await asyncio.sleep(1)
+
+        elif run.status == "queued":
+            logger.debug(f"Run {run.id} is queued. Sleeping for 1 second...")
+            await asyncio.sleep(1)
+
+        elif run.status == "failed":
+            logger.error(f"Run {run.id} failed: {run.last_error=}")
+
+            if run.last_error and run.last_error.code == "rate_limit_exceeded":
+                if re_run_count >= settings.OPENAI_API_RUN_FAILED_RETRIES:
+                    raise ValueError(f"Reached the maximum number of RUN_FAILED retries: {re_run_count=} for {run.id=}")
+
+                logger.warning(f"Rate limit exceeded for {run.id=}. Sleeping for 5 second...")
+                await asyncio.sleep(5)
+
+                continue
+
+            if run_retry_count >= settings.OPENAI_API_RUN_RETRIED_RETRIES:
+                raise ValueError(f"Reached the maximum number of RUN_RETRIED retries: {run_retry_count=} for {run.id=}")
+
+            # Retry the run
+            run = await async_openai_client.beta.threads.runs.create(
+                thread_id=thread.id,
+                assistant_id=assistant.id,
+            )
+            logger.info(f"Re-run the thread with: {thread_message=}, {thread_id=}. Got {run=}")
+
+            re_run_count += 1
+            await asyncio.sleep(1)
+
+        else:
+            raise ValueError(f"The Run status is unexpected: {run.status}")
+
+    thread_messages = await async_openai_client.beta.threads.messages.list(thread_id=thread.id)
+    response_message_text: str = thread_messages.data[0].content[0].text.value
+
+    return response_message_text
+
+
+async def _process_assistant_tool_calls(
+    tool_calls: list[RequiredActionFunctionToolCall],
+    tools: dict[str, Callable],
+    **kwargs: dict[str, Any],
+) -> list[ToolOutput]:
+    """
+    Process the assistant tool calls.
+
+    Args:
+        tool_calls (list[ToolOutput]): The tool calls to process
+        functions (dict[str, callable]): The functions to execute
+        **kwargs (dict[str, Any]): The keyword arguments to pass to the functions
+
+    Returns:
+        list[ToolOutput]: The processed tool outputs
+    """
+
+    tool_outputs = []
+    for tool_call in tool_calls:
+        function_name = tool_call.function.name
+        function_to_execute = tools.get(function_name)
+
+        if not function_to_execute:
+            raise ValueError(f"The function to execute is not found: {function_name}")
+
+        # Execute the function with combined kwargs
+        function_args = json.loads(tool_call.function.arguments)
+        action_output = await function_to_execute(**(kwargs | function_args))
+
+        # Add the output to the tool outputs
+        tool_outputs.append(
+            ToolOutput(
+                tool_call_id=tool_call.id,
+                output=action_output,
+            )
+        )
+
+    return tool_outputs
+
+
+current_message_id: ContextVar[str | None] = ContextVar("current_message_id", default=None)
+
+
+async def _process_assistant_event(
+    event: AssistantStreamEvent,
+    thread: Thread,
+    tools: dict[str, Callable],
+    **kwargs: dict[str, Any],
+) -> AsyncGenerator[Tuple[str, AssistantMessageDeltaType], None]:
+    """
+    Process the assistant event.
+
+    Args:
+        event (AssistantStreamEvent): The event to process
+        thread (Thread): The thread to process the event for
+
+    Returns:
+        Any: The processed event
+    """
+    logger.info(f"Processing event: {event}")
+
+    if isinstance(event, ThreadRunCreated):
+        logger.info("Assistant is thinking...")
+        yield "", AssistantMessageDeltaType.MESSAGE_START
+
+    elif isinstance(event, ThreadMessageCreated):
+        # Set the current message ID
+        logger.info(f"New message created: {event.data.id=}")
+        current_message_id.set(event.data.id)
+
+    elif isinstance(event, ThreadRunInProgress):
+        logger.info("Processing your request...")
+        yield "", AssistantMessageDeltaType.METADATA
+
+    elif isinstance(event, ThreadMessageDelta):
+        data = event.data.delta.content
+        for d in data:
+            yield d.text.value, AssistantMessageDeltaType.CONTENT_BLOCK
+
+    elif isinstance(event, ThreadRunQueued):
+        logger.info("Request queued...")
+
+    elif isinstance(event, ThreadRunRequiresAction):
+        run = event.data
+        tool_outputs = await _process_assistant_tool_calls(
+            tool_calls=run.required_action.submit_tool_outputs.tool_calls, tools=tools, **kwargs
+        )
+        tool_output_events = await async_openai_client.beta.threads.runs.submit_tool_outputs(
+            thread_id=thread.id, run_id=run.id, tool_outputs=tool_outputs, stream=True
+        )
+        async for tool_event in tool_output_events:
+            async for token in _process_assistant_event(tool_event, thread=thread, tools=tools, **kwargs):
+                yield token
+
+    elif isinstance(event, ThreadRunCompleted):
+        logger.info("Assistant finished processing your request.")
+        yield "", AssistantMessageDeltaType.MESSAGE_END
+
+    elif any(
+        isinstance(event, cls)
+        for cls in [
+            ThreadRunFailed,
+            ThreadRunCancelling,
+            ThreadRunCancelled,
+            ThreadRunExpired,
+            ThreadRunStepFailed,
+            ThreadRunStepCancelled,
+        ]
+    ):
+        raise Exception("Run failed")  # pylint: disable=broad-exception-raised
+
+    else:
+        logger.warning(f"Unhandled Assistant event: {event}")
+
+
+async def save_assistant_user_message(
+    thread_id: str,
+    content: str,
+) -> Message:
+    """
+    Save the assistant user message.
+
+    Args:
+        thread_id (str): The ID of the chat thread
+        content (str): The content of the message
+
+    Returns:
+        None
+    """
+
+    thread_message: Message = await async_openai_client.beta.threads.messages.create(
+        thread_id=thread_id, role="user", content=content
+    )
+    logger.info(f"Created a message in Assistants API: {thread_message=}, {thread_id=}.")
+
+    return thread_message
+
+
+async def get_assistant_response__async(
+    assistant_id: str,
+    thread_message: Message,
+    thread_id: str,
+    functions: dict[str, Callable],
+    **kwargs: dict[str, Any],
+) -> AsyncGenerator[Tuple[str, AssistantMessageDeltaType], None]:
+    """
+    Get the assistant response.
+
+    Args:
+        assistant_id (str): The ID of the assistant to use
+        thread_message (Message): The prompt to send to the assistant
+        thread_id (str): The ID of the chat thread
+        functions (dict[str, callable]): The functions to execute
+        **kwargs (dict[str, Any]): The keyword arguments to pass to the functions
+
+    Yields:
+        str: Status updates and the final response from the assistant
+    """
+
+    logger.info(f"Getting the Assistant response for {thread_message.content=}...")
+
+    # TODO: [2025-01-29 by Mykola] Allow different assistants to be chosen by the user and/or depending on the use-case
+    assistant = await async_openai_client.beta.assistants.retrieve(assistant_id)
+
+    thread = await async_openai_client.beta.threads.retrieve(thread_id)
+
+    # TODO: [2025-01-31 by Mykola] Stop all the active runs for the thread before creating a new one
+    try:
+        async with async_openai_client.beta.threads.runs.stream(
+            thread_id=thread.id,
+            assistant_id=assistant.id,
+            # max_prompt_tokens=settings.OPENAI_MAX_PROMPT_TOKENS,
+            # max_completion_tokens=settings.OPENAI_MAX_COMPLETION_TOKENS,
+        ) as stream:
+            logger.info(f"Stream the thread with: {thread_message=}, {thread_id=}. Got {stream=}")
+
+            async for event in stream:
+                logger.info(f"Got an Assistant event: {event.event}")
+
+                async for yielded_event in _process_assistant_event(event, thread=thread, tools=functions, **kwargs):
+                    yield yielded_event
+
+    except Exception as e:
+        error_message = f"Error processing assistant response: {str(e)}"
+        logger.error(error_message)
+        yield f"\nError: {error_message}", AssistantMessageDeltaType.ERROR
+
+        # Attempt to cancel the run if an exception occurs
+        try:
+            await async_openai_client.beta.threads.runs.cancel(
+                thread_id=thread.id,
+                run_id=stream.current_run.id,
+            )
+        except Exception as cancel_error:
+            logger.error(f"Failed to cancel run after error: {str(cancel_error)}")
diff --git a/electro/models.py b/electro/models.py
index f516e0e..e4c68a9 100644
--- a/electro/models.py
+++ b/electro/models.py
@@ -5,6 +5,7 @@
 from tortoise import fields
 from tortoise.fields import ForeignKeyRelation
 
+from .enums import AssistantType
 from .toolkit.images_storage.storages_enums import StoragesIDs
 from .toolkit.tortoise_orm import Model
 
@@ -54,6 +55,8 @@ class User(BaseModel):
 
     files: fields.ReverseRelation[File]
 
+    assistant_chat_threads: fields.ReverseRelation[AssistantChatThread]
+
     def __str__(self) -> str:
         """Return the string representation of the model."""
         return f"{self.username}#{self.discriminator}"
@@ -262,3 +265,50 @@ class Meta:  # pylint: disable=too-few-public-methods
 
 
 # endregion
+
+
+# region Assistant Chat models
+class Assistant(BaseModel):
+    """The model for an assistant."""
+
+    id = fields.CharField(primary_key=True, max_length=255)
+    assistant_type = fields.CharEnumField(AssistantType, max_length=255)
+
+    chat_threads: fields.ReverseRelation[AssistantChatThread]
+
+
+class AssistantChatThread(BaseModel):
+    """The model for an assistant's chat thread."""
+
+    user: fields.ForeignKeyRelation[User] | User = fields.ForeignKeyField(
+        "electro.User", related_name="assistant_chat_threads", on_delete=fields.SET_NULL, null=True
+    )
+
+    assistant: fields.ForeignKeyRelation[Assistant] | Assistant = fields.ForeignKeyField(
+        "electro.Assistant", related_name="chat_threads", on_delete=fields.SET_NULL, null=True
+    )
+
+    thread_id = fields.TextField()
+
+    name = fields.TextField(null=True)
+    description = fields.TextField(null=True)
+
+    is_completed = fields.BooleanField(default=False)
+
+    messages: fields.ReverseRelation[AssistantChatMessage]
+
+
+class AssistantChatMessage(BaseModel):
+    """The model for an assistant's chat message."""
+
+    thread: fields.ForeignKeyRelation[AssistantChatThread] = fields.ForeignKeyField(
+        "electro.AssistantChatThread", related_name="messages", on_delete=fields.CASCADE
+    )
+
+    message_id = fields.TextField(null=True)
+
+    role = fields.TextField()
+    content = fields.TextField()
+
+
+# endregion
diff --git a/electro/schemas.py b/electro/schemas.py
new file mode 100644
index 0000000..ce89c36
--- /dev/null
+++ b/electro/schemas.py
@@ -0,0 +1,87 @@
+from abc import ABC
+from datetime import datetime
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from .enums import AssistantMessageDeltaType, AssistantType, FrontendAction
+
+
+class AssistantSchema(BaseModel):
+    """The schema for an assistant."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+    id: str = Field(..., title="The ID of the assistant")
+
+    assistant_type: AssistantType = Field(..., title="The type of the assistant")
+
+    date_added: datetime = Field(..., title="The date the assistant was added")
+    date_updated: datetime = Field(..., title="The date the assistant was updated")
+
+
+class AssistantChatThreadBaseSchema(BaseModel, ABC):
+    """The base schema for an assistant's chat thread."""
+
+    name: str | None = Field(None, title="The name of the chat thread")
+    description: str | None = Field(None, title="The description of the chat thread")
+
+
+class AssistantChatThreadCreateSchema(AssistantChatThreadBaseSchema):
+    """The schema for creating an assistant's chat thread."""
+
+    assistant_type: AssistantType = Field(..., title="The type of the Assistant to be used in the chat thread")
+
+
+class AssistantChatThreadSchema(AssistantChatThreadBaseSchema):
+    """The schema for an assistant's chat thread."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+    assistant: AssistantSchema = Field(..., title="The assistant used in the chat thread")
+
+    thread_id: str = Field(..., title="The ID of the chat thread")
+
+    is_completed: bool = Field(..., title="Whether the chat thread is finished")
+
+    date_added: datetime = Field(..., title="The date the chat thread was added")
+    date_updated: datetime = Field(..., title="The date the chat thread was updated")
+
+
+class AssistantChatMessageBaseSchema(BaseModel, ABC):
+    """The base schema for an assistant's chat message."""
+
+    role: str = Field(..., title="The role of the chat message")
+    content: str = Field(..., title="The content of the chat message")
+
+
+class AssistantChatMessageCreateSchema(AssistantChatMessageBaseSchema):
+    """The schema for creating an assistant's chat message."""
+
+    # The maximum length of the message _to create_ is set in the settings
+    content: str = Field(
+        ...,
+        title="The content of the chat message to create",
+    )
+
+
+class AssistantChatMessageSchema(AssistantChatMessageBaseSchema):
+    """The schema for an assistant's chat message."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+    frontend_actions: list[FrontendAction] = Field([], title="The actions to be performed by the frontend")
+
+    date_added: datetime = Field(..., title="The date the chat message was added")
+    date_updated: datetime = Field(..., title="The date the chat message was updated")
+
+
+class AssistantChatMessageDeltaSchema(AssistantChatMessageBaseSchema):
+    """The schema for a delta of an assistant's chat message."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+    message_id: str | None = Field(None, title="The ID of the chat message")
+
+    type: AssistantMessageDeltaType = Field(..., title="The type of the delta")
+
+    frontend_actions: list[FrontendAction] = Field([], title="The actions to be performed by the frontend")
diff --git a/electro/settings.py b/electro/settings.py
index 39eac1e..bc5a7df 100644
--- a/electro/settings.py
+++ b/electro/settings.py
@@ -19,6 +19,8 @@ class Settings(BaseSettings):
     DEBUG: bool = False
     LOG_LEVEL: str = "INFO"
 
+    DOMAIN: str = "localhost"  # The domain of the bot API
+
     LOCALES_PATH: str = "locales"  # Relative to the current working directory
     DEFAULT_LOCALE: str = "en"  # Should mirror the `BOT_LANGUAGE` setting. User in the `make upload-locales` target
 
@@ -78,6 +80,10 @@ class Settings(BaseSettings):
     OPENAI_CHAT_COMPLETION_MODEL: str = "gpt-4o"
     OPENAI_DALLE_MODEL: str = "dall-e-3"
 
+    OPENAI_API_RUN_FETCH_RETRIES: int = 5
+    OPENAI_API_RUN_FAILED_RETRIES: int = 3
+    OPENAI_API_RUN_RETRIED_RETRIES: int = 3
+
     DEFAULT_SLEEP_TIME: int = 3  # seconds
     SLEEP_TIME_PER_CHARACTER: float = 0.05
 
@@ -104,4 +110,5 @@ class Settings(BaseSettings):
         )
 
 
+# noinspection PyArgumentList
 settings = Settings()
diff --git a/electro/toolkit/whisper_client.py b/electro/toolkit/whisper_client.py
new file mode 100644
index 0000000..83d7a8c
--- /dev/null
+++ b/electro/toolkit/whisper_client.py
@@ -0,0 +1,131 @@
+"""Whisper client utility for audio transcription."""
+
+import logging
+import tempfile
+from pathlib import Path
+from typing import Optional
+
+from fastapi import HTTPException, UploadFile
+from openai import AsyncOpenAI
+
+from settings import settings
+
+from electro.toolkit.loguru_logging import logger
+
+
+class WhisperTranscriptionError(Exception):
+    """Custom exception for Whisper transcription errors."""
+
+    pass
+
+
+async def validate_audio_file(file: UploadFile) -> None:
+    """
+    Validate the uploaded audio file.
+    
+    Args:
+        file: The uploaded file to validate
+        
+    Raises:
+        HTTPException: If file validation fails
+    """
+    if not file.filename:
+        raise HTTPException(status_code=400, detail="No file uploaded")
+    
+    file_extension = Path(file.filename).suffix.lower().lstrip('.')
+    if file_extension not in settings.SUPPORTED_AUDIO_FORMATS:
+        raise HTTPException(
+            status_code=400, 
+            detail=f"Unsupported file format. Supported formats: {', '.join(settings.SUPPORTED_AUDIO_FORMATS)}"
+        )
+    
+    if file.size and file.size > settings.MAX_AUDIO_FILE_SIZE:
+        raise HTTPException(
+            status_code=413, 
+            detail=f"File too large. Maximum size: {settings.MAX_AUDIO_FILE_SIZE // (1024 * 1024)}MB"
+        )
+
+
+async def transcribe_audio(
+    file: UploadFile,
+    language: Optional[str] = None,
+    response_format: str = "json",
+    temperature: float = 0.0
+) -> dict:
+    """
+    Transcribe audio file using OpenAI Whisper.
+    
+    Args:
+        file: Audio file to transcribe
+        language: Optional language code (e.g., 'en', 'es', 'fr')
+        response_format: Response format ('json', 'text', 'srt', 'verbose_json', 'vtt')
+        temperature: Sampling temperature between 0 and 1
+        
+    Returns:
+        Dictionary containing transcription result
+        
+    Raises:
+        WhisperTranscriptionError: If transcription fails
+    """
+    await validate_audio_file(file)
+    
+    client = AsyncOpenAI(
+        base_url=settings.OPENAI_API_BASE_URL,
+        api_key=settings.OPENAI_API_KEY
+    )
+    
+    with tempfile.NamedTemporaryFile(delete=False, suffix=f".{Path(file.filename).suffix}") as temp_file:
+        try:
+            # Write uploaded file to temporary file
+            content = await file.read()
+            temp_file.write(content)
+            temp_file.flush()
+            
+            # Transcribe using OpenAI Whisper
+            with open(temp_file.name, 'rb') as audio_file:
+                transcription_params = {
+                    "file": audio_file,
+                    "model": settings.OPENAI_WHISPER_MODEL,
+                    "response_format": response_format,
+                    "temperature": temperature
+                }
+                
+                if language:
+                    transcription_params["language"] = language
+                
+                logger.info(f"Starting transcription for file: {file.filename}")
+                transcript = await client.audio.transcriptions.create(**transcription_params)
+                logger.info(f"Transcription completed for file: {file.filename}")
+                
+                # Handle different response formats
+                if response_format == "json":
+                    return {
+                        "text": transcript.text,
+                        "language": getattr(transcript, 'language', None),
+                        "duration": getattr(transcript, 'duration', None),
+                        "filename": file.filename
+                    }
+                elif response_format == "verbose_json":
+                    return {
+                        "text": transcript.text,
+                        "language": getattr(transcript, 'language', None),
+                        "duration": getattr(transcript, 'duration', None),
+                        "segments": getattr(transcript, 'segments', []),
+                        "filename": file.filename
+                    }
+                else:
+                    return {
+                        "text": str(transcript),
+                        "filename": file.filename
+                    }
+                    
+        except Exception as e:
+            logger.error(f"Transcription failed for file {file.filename}: {str(e)}")
+            raise WhisperTranscriptionError(f"Transcription failed: {str(e)}")
+        
+        finally:
+            # Clean up temporary file
+            try:
+                Path(temp_file.name).unlink(missing_ok=True)
+            except Exception as cleanup_error:
+                logger.warning(f"Failed to cleanup temporary file: {cleanup_error}")
\ No newline at end of file
diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index 1097170..0000000
--- a/poetry.lock
+++ /dev/null
@@ -1,3145 +0,0 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
-
-[[package]]
-name = "aerich"
-version = "0.7.2"
-description = "A database migrations tool for Tortoise ORM."
-optional = false
-python-versions = ">=3.7,<4.0"
-files = [
-    {file = "aerich-0.7.2-py3-none-any.whl", hash = "sha256:84c78c07d45436b89ca4db5411eca4e9292a591fb7d6fd4282fa4a7d0c6d2af1"},
-    {file = "aerich-0.7.2.tar.gz", hash = "sha256:31d67de7b96184636b89de99062e059e5e6204b6251d24c33eb21fc9cf982e09"},
-]
-
-[package.dependencies]
-click = "*"
-dictdiffer = "*"
-pydantic = "*"
-tomlkit = "*"
-tortoise-orm = "*"
-
-[package.extras]
-asyncmy = ["asyncmy (>=0.2.8rc1,<0.3.0)"]
-asyncpg = ["asyncpg"]
-
-[[package]]
-name = "aioboto3"
-version = "13.4.0"
-description = "Async boto3 wrapper"
-optional = false
-python-versions = "<4.0,>=3.8"
-files = [
-    {file = "aioboto3-13.4.0-py3-none-any.whl", hash = "sha256:d78f3400ef3a01b4d5515108ef244941894a0bc39c4716321a00e15898d7e002"},
-    {file = "aioboto3-13.4.0.tar.gz", hash = "sha256:3105f9e5618c686c90050e60eb5ebf9e28f7f8c4e0fa162d4481aaa402008aab"},
-]
-
-[package.dependencies]
-aiobotocore = {version = "2.18.0", extras = ["boto3"]}
-aiofiles = ">=23.2.1"
-
-[package.extras]
-chalice = ["chalice (>=1.24.0)"]
-s3cse = ["cryptography (>=2.3.1)"]
-
-[[package]]
-name = "aiobotocore"
-version = "2.18.0"
-description = "Async client for aws services using botocore and aiohttp"
-optional = false
-python-versions = ">=3.8"
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-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-propcache = ">=0.2.0"
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.12"
-content-hash = "9bb19721a52e690cd0da8adb19981586e51d3a6277068e54acec7d10ba671994"
diff --git a/pyproject.toml b/pyproject.toml
index 442a537..115060d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,42 +1,57 @@
-[tool.poetry]
+[project]
 name = "electro"
 version = "0.12.2"
 description = "A framework for building bots, made for humans."
-authors = ["Mykola Solodukha <mykola@mykolasolodukha.me>"]
+authors = [{ name = "Mykola Solodukha", email = "mykola@mykolasolodukha.me" }]
+requires-python = "~=3.12.0"
 readme = "README.md"
-packages = [
-    { include = "electro", from = "." },
+dependencies = [
+    "stringcase>=1.2.0,<2",
+    "loguru>=0.7.2,<0.8",
+    "openai>=1.36.0,<2",
+    "pydantic-settings>=2.3.4,<3",
+    "pydantic>=2.8.2,<3",
+    "dj-redis-url>=0.1.4,<0.2",
+    "redis>=5.0.7,<6",
+    "tortoise-orm[asyncpg]>=0.21.5,<0.22",
+    "aerich>=0.7.2,<0.8",
+    "tenacity>=8.5.0,<9",
+    "py-cord",
+    "aioboto3>=13.1.1,<14",
+    "azure-storage-blob>=12.23.1,<13",
+    "azure-identity>=1.18.0,<2",
+    "fastapi[standard]>=0.115.5,<1.0.0",
 ]
 
-[tool.poetry.dependencies]
-python = "^3.12"
-stringcase = "^1.2.0"
-loguru = "^0.7.2"
-openai = "^1.36.0"
-pydantic-settings = "^2.3.4"
-pydantic = "^2.8.2"
-dj-redis-url = "^0.1.4"
-redis = "^5.0.7"
-tortoise-orm = {extras = ["asyncpg"], version = "^0.21.5"}
-aerich = "^0.7.2"
-tenacity = "^8.5.0"
-py-cord = {git = "https://github.com/mykolasolodukha/pycord.git", rev = "d8070a90a8ec12dbc64b703513c14fa80834861d"}
-aioboto3 = "^13.1.1"
-azure-storage-blob = "^12.23.1"
-azure-identity = "^1.18.0"
-fastapi = {extras = ["standard"], version = "^0.115.5"}
+[dependency-groups]
+dev = [
+    "black>=24.8.0,<25",
+    "isort>=5.13.2,<6",
+    "pylint>=3.2.6,<4",
+    "pydocstyle[toml]>=6.3.0,<7",
+    "sphinx>=8.2.0,<9",
+    "sphinx-rtd-theme>=3.0.2,<4",
+    "autodoc-pydantic>=2.2.0,<3",
+    "sphinx-autodoc-typehints>=3.0.1,<4",
+]
+
+[tool.uv]
+
+[tool.uv.sources]
+py-cord = { git = "https://github.com/mykolasolodukha/pycord.git", rev = "d8070a90a8ec12dbc64b703513c14fa80834861d" }
 
+[tool.hatch.build.targets.sdist]
+include = ["./electro"]
 
-[tool.poetry.group.dev.dependencies]
-black = "^24.8.0"
-isort = "^5.13.2"
-pylint = "^3.2.6"
-pydocstyle = {extras = ["toml"], version = "^6.3.0"}
-sphinx = "^8.2.0"
-sphinx-rtd-theme = "^3.0.2"
-autodoc-pydantic = "^2.2.0"
-sphinx-autodoc-typehints = "^3.0.1"
+[tool.hatch.build.targets.wheel]
+include = ["./electro"]
 
+[tool.hatch.build.targets.wheel.sources]
+"./electro" = "electro"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
 
 [tool.black]
 line-length = 120
@@ -62,14 +77,8 @@ ignore-patterns = ["tests", "migrations"]  # ignore the tests and migrations fol
 [tool.pydocstyle]
 match-dir = "(?!tests|migrations).*"  # exclude the tests and migrations folders
 
-
 [tool.aerich]
 tortoise_orm = "electro.toolkit.tortoise_orm.TORTOISE_ORM_CONFIG"
 location = "./migrations"
 src_folder = "./../electro"
 
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
-
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..8207de3
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1723 @@
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+revision = 3
+requires-python = "==3.12.*"
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+version = "0.7.2"
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+]
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