Merge pull request #90 from harishmohanraj/fix-upstream-conflicts-1

Fix upstream conflicts 1

autogen/agentchat/assistant_agent.py

@@ -6,8 +6,7 @@
 # SPDX-License-Identifier: MIT
 from typing import Callable, Literal, Optional, Union
 
-from autogen.runtime_logging import log_new_agent, logging_enabled
-
+from ..runtime_logging import log_new_agent, logging_enabled
 from .conversable_agent import ConversableAgent
 
 

autogen/agentchat/contrib/capabilities/generate_images.py

@@ -7,14 +7,17 @@
 import re
 from typing import Any, Literal, Optional, Protocol, Union
 
-from PIL.Image import Image
 from openai import OpenAI
 
-from autogen import Agent, ConversableAgent, code_utils
-from autogen.agentchat.contrib import img_utils
-from autogen.agentchat.contrib.capabilities.agent_capability import AgentCapability
-from autogen.agentchat.contrib.text_analyzer_agent import TextAnalyzerAgent
-from autogen.cache import AbstractCache
+from .... import Agent, ConversableAgent, code_utils
+from ....cache import AbstractCache
+from ....import_utils import optional_import_block, require_optional_import
+from .. import img_utils
+from ..capabilities.agent_capability import AgentCapability
+from ..text_analyzer_agent import TextAnalyzerAgent
+
+with optional_import_block():
+    from PIL.Image import Image
 
 SYSTEM_MESSAGE = "You've been given the special ability to generate images."
 DESCRIPTION_MESSAGE = "This agent has the ability to generate images."
@@ -34,7 +37,7 @@ class ImageGenerator(Protocol):
     NOTE: Current implementation does not allow you to edit a previously existing image.
     """
 
-    def generate_image(self, prompt: str) -> Image:
+    def generate_image(self, prompt: str) -> "Image":
         """Generates an image based on the provided prompt.
 
         Args:
@@ -62,6 +65,7 @@ def cache_key(self, prompt: str) -> str:
         ...
 
 
+@require_optional_import("PIL", "unknown")
 class DalleImageGenerator:
     """Generates images using OpenAI's DALL-E models.
 
@@ -94,7 +98,7 @@ def __init__(
         self._num_images = num_images
         self._dalle_client = OpenAI(api_key=config_list[0]["api_key"])
 
-    def generate_image(self, prompt: str) -> Image:
+    def generate_image(self, prompt: str) -> "Image":
         response = self._dalle_client.images.generate(
             model=self._model,
             prompt=prompt,
@@ -114,6 +118,7 @@ def cache_key(self, prompt: str) -> str:
         return ",".join([str(k) for k in keys])
 
 
+@require_optional_import("PIL", "unknown")
 class ImageGeneration(AgentCapability):
     """This capability allows a ConversableAgent to generate images based on the message received from other Agents.
 
@@ -253,15 +258,15 @@ def _extract_prompt(self, last_message) -> str:
         analysis = self._text_analyzer.analyze_text(last_message, self._text_analyzer_instructions)
         return self._extract_analysis(analysis)
 
-    def _cache_get(self, prompt: str) -> Optional[Image]:
+    def _cache_get(self, prompt: str) -> Optional["Image"]:
         if self._cache:
             key = self._image_generator.cache_key(prompt)
             cached_value = self._cache.get(key)
 
             if cached_value:
                 return img_utils.get_pil_image(cached_value)
 
-    def _cache_set(self, prompt: str, image: Image):
+    def _cache_set(self, prompt: str, image: "Image"):
         if self._cache:
             key = self._image_generator.cache_key(prompt)
             self._cache.set(key, img_utils.pil_to_data_uri(image))
@@ -272,7 +277,7 @@ def _extract_analysis(self, analysis: Union[str, dict, None]) -> str:
         else:
             return code_utils.content_str(analysis)
 
-    def _generate_content_message(self, prompt: str, image: Image) -> dict[str, Any]:
+    def _generate_content_message(self, prompt: str, image: "Image") -> dict[str, Any]:
         return {
             "content": [
                 {"type": "text", "text": f"I generated an image with the prompt: {prompt}"},

autogen/agentchat/contrib/img_utils.py

@@ -13,7 +13,11 @@
 from typing import Union
 
 import requests
-from PIL import Image
+
+from ...import_utils import optional_import_block, require_optional_import
+
+with optional_import_block():
+    from PIL import Image
 
 from autogen.agentchat import utils
 
@@ -37,7 +41,8 @@
 }
 
 
-def get_pil_image(image_file: Union[str, Image.Image]) -> Image.Image:
+@require_optional_import("PIL", "unknown")
+def get_pil_image(image_file: Union[str, "Image.Image"]) -> "Image.Image":
     """Loads an image from a file and returns a PIL Image object.
 
     Parameters:
@@ -75,7 +80,8 @@ def get_pil_image(image_file: Union[str, Image.Image]) -> Image.Image:
     return image.convert("RGB")
 
 
-def get_image_data(image_file: Union[str, Image.Image], use_b64=True) -> bytes:
+@require_optional_import("PIL", "unknown")
+def get_image_data(image_file: Union[str, "Image.Image"], use_b64=True) -> bytes:
     """Loads an image and returns its data either as raw bytes or in base64-encoded format.
 
     This function first loads an image from the specified file, URL, or base64 string using
@@ -105,6 +111,7 @@ def get_image_data(image_file: Union[str, Image.Image], use_b64=True) -> bytes:
         return content
 
 
+@require_optional_import("PIL", "unknown")
 def llava_formatter(prompt: str, order_image_tokens: bool = False) -> tuple[str, list[str]]:
     """Formats the input prompt by replacing image tags and returns the new prompt along with image locations.
 
@@ -149,7 +156,8 @@ def llava_formatter(prompt: str, order_image_tokens: bool = False) -> tuple[str,
     return new_prompt, images
 
 
-def pil_to_data_uri(image: Image.Image) -> str:
+@require_optional_import("PIL", "unknown")
+def pil_to_data_uri(image: "Image.Image") -> str:
     """Converts a PIL Image object to a data URI.
 
     Parameters:
@@ -184,6 +192,7 @@ def _get_mime_type_from_data_uri(base64_image):
     return data_uri
 
 
+@require_optional_import("PIL", "unknown")
 def gpt4v_formatter(prompt: str, img_format: str = "uri") -> list[Union[str, dict]]:
     """Formats the input prompt by replacing image tags and returns a list of text and images.
 
@@ -251,7 +260,8 @@ def extract_img_paths(paragraph: str) -> list:
     return img_paths
 
 
-def _to_pil(data: str) -> Image.Image:
+@require_optional_import("PIL", "unknown")
+def _to_pil(data: str) -> "Image.Image":
     """Converts a base64 encoded image data string to a PIL Image object.
 
     This function first decodes the base64 encoded string to bytes, then creates a BytesIO object from the bytes,
@@ -266,6 +276,7 @@ def _to_pil(data: str) -> Image.Image:
     return Image.open(BytesIO(base64.b64decode(data)))
 
 
+@require_optional_import("PIL", "unknown")
 def message_formatter_pil_to_b64(messages: list[dict]) -> list[dict]:
     """Converts the PIL image URLs in the messages to base64 encoded data URIs.
 
@@ -321,8 +332,9 @@ def message_formatter_pil_to_b64(messages: list[dict]) -> list[dict]:
     return new_messages
 
 
+@require_optional_import("PIL", "unknown")
 def num_tokens_from_gpt_image(
-    image_data: Union[str, Image.Image], model: str = "gpt-4-vision", low_quality: bool = False
+    image_data: Union[str, "Image.Image"], model: str = "gpt-4-vision", low_quality: bool = False
 ) -> int:
     """Calculate the number of tokens required to process an image based on its dimensions
     after scaling for different GPT models. Supports "gpt-4-vision", "gpt-4o", and "gpt-4o-mini".

autogen/agentchat/realtime_agent/oai_realtime_client.py

@@ -13,10 +13,12 @@
 from openai import DEFAULT_MAX_RETRIES, NOT_GIVEN, AsyncOpenAI
 from openai.resources.beta.realtime.realtime import AsyncRealtimeConnection
 
+from ...import_utils import optional_import_block
 from .realtime_client import Role
 
 if TYPE_CHECKING:
-    from fastapi.websockets import WebSocket
+    with optional_import_block():
+        from fastapi.websockets import WebSocket
 
     from .realtime_client import RealtimeClientProtocol
 

autogen/agentchat/realtime_agent/realtime_agent.py

@@ -3,12 +3,12 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from logging import Logger, getLogger
-from typing import Any, Callable, Optional, TypeVar, Union
+from typing import TYPE_CHECKING, Any, Callable, Optional, TypeVar, Union
 
 import anyio
 from asyncer import asyncify, create_task_group, syncify
-from fastapi import WebSocket
 
+from ...import_utils import optional_import_block
 from ...tools import Tool
 from .. import SwarmAgent
 from ..agent import Agent
@@ -19,6 +19,10 @@
 from .realtime_client import RealtimeClientProtocol
 from .realtime_observer import RealtimeObserver
 
+if TYPE_CHECKING:
+    with optional_import_block():
+        from fastapi import WebSocket
+
 F = TypeVar("F", bound=Callable[..., Any])
 
 global_logger = getLogger(__name__)
@@ -49,7 +53,7 @@ def __init__(
         llm_config: dict[str, Any],
         voice: str = "alloy",
         logger: Optional[Logger] = None,
-        websocket: Optional[WebSocket] = None,
+        websocket: Optional["WebSocket"] = None,
     ):
         """(Experimental) Agent for interacting with the Realtime Clients.
 

autogen/agentchat/realtime_agent/twilio_audio_adapter.py

@@ -7,10 +7,12 @@
 from logging import Logger
 from typing import TYPE_CHECKING, Any, Optional
 
+from ...import_utils import optional_import_block
 from .realtime_observer import RealtimeObserver
 
 if TYPE_CHECKING:
-    from fastapi.websockets import WebSocket
+    with optional_import_block():
+        from fastapi.websockets import WebSocket
 
 
 LOG_EVENT_TYPES = [
@@ -144,5 +146,5 @@ async def initialize_session(self) -> None:
 
 if TYPE_CHECKING:
 
-    def twilio_audio_adapter(websocket: WebSocket) -> RealtimeObserver:
+    def twilio_audio_adapter(websocket: "WebSocket") -> RealtimeObserver:
         return TwilioAudioAdapter(websocket)

autogen/agentchat/realtime_agent/websocket_audio_adapter.py

@@ -7,12 +7,13 @@
 from logging import Logger
 from typing import TYPE_CHECKING, Any, Optional
 
-if TYPE_CHECKING:
-    from fastapi.websockets import WebSocket
-
-
+from ...import_utils import optional_import_block
 from .realtime_observer import RealtimeObserver
 
+if TYPE_CHECKING:
+    with optional_import_block():
+        from fastapi.websockets import WebSocket
+
 LOG_EVENT_TYPES = [
     "error",
     "response.content.done",
@@ -138,5 +139,5 @@ async def run_loop(self) -> None:
 
 if TYPE_CHECKING:
 
-    def websocket_audio_adapter(websocket: WebSocket) -> RealtimeObserver:
+    def websocket_audio_adapter(websocket: "WebSocket") -> RealtimeObserver:
         return WebSocketAudioAdapter(websocket)

autogen/cache/cache.py

@@ -6,18 +6,12 @@
 # SPDX-License-Identifier: MIT
 from __future__ import annotations
 
-import sys
 from types import TracebackType
 from typing import Any
 
 from .abstract_cache_base import AbstractCache
 from .cache_factory import CacheFactory
 
-if sys.version_info >= (3, 11):
-    pass
-else:
-    pass
-
 
 class Cache(AbstractCache):
     """A wrapper class for managing cache configuration and instances.

autogen/cache/cosmos_db_cache.py

@@ -9,20 +9,24 @@
 import pickle
 from typing import Any, Optional, TypedDict, Union
 
-from azure.cosmos import CosmosClient, PartitionKey
-from azure.cosmos.exceptions import CosmosResourceNotFoundError
+from ..import_utils import optional_import_block, require_optional_import
+from .abstract_cache_base import AbstractCache
 
-from autogen.cache.abstract_cache_base import AbstractCache
+with optional_import_block():
+    from azure.cosmos import CosmosClient, PartitionKey
+    from azure.cosmos.exceptions import CosmosResourceNotFoundError
 
 
+@require_optional_import("azure", "cosmosdb")
 class CosmosDBConfig(TypedDict, total=False):
     connection_string: str
     database_id: str
     container_id: str
     cache_seed: Optional[Union[str, int]]
-    client: Optional[CosmosClient]
+    client: Optional["CosmosClient"]
 
 
+@require_optional_import("azure", "cosmosdb")
 class CosmosDBCache(AbstractCache):
     """Synchronous implementation of AbstractCache using Azure Cosmos DB NoSQL API.
 
@@ -75,7 +79,7 @@ def from_connection_string(cls, seed: Union[str, int], connection_string: str, d
         return cls(str(seed), config)
 
     @classmethod
-    def from_existing_client(cls, seed: Union[str, int], client: CosmosClient, database_id: str, container_id: str):
+    def from_existing_client(cls, seed: Union[str, int], client: "CosmosClient", database_id: str, container_id: str):
         config = {"client": client, "database_id": database_id, "container_id": container_id}
         return cls(str(seed), config)
 

autogen/cache/redis_cache.py

@@ -9,16 +9,19 @@
 from types import TracebackType
 from typing import Any, Optional, Union
 
-import redis
-
-from .abstract_cache_base import AbstractCache
-
 if sys.version_info >= (3, 11):
     from typing import Self
 else:
     from typing_extensions import Self
 
+from ..import_utils import optional_import_block, require_optional_import
+from .abstract_cache_base import AbstractCache
+
+with optional_import_block():
+    import redis
+
 
+@require_optional_import("redis", "redis")
 class RedisCache(AbstractCache):
     """Implementation of AbstractCache using the Redis database.
 

autogen/code_utils.py

@@ -20,8 +20,7 @@
 
 import docker
 
-from autogen import oai
-
+from . import oai
 from .types import UserMessageImageContentPart, UserMessageTextContentPart
 
 SENTINEL = object()

autogen/coding/jupyter/docker_jupyter_server.py

@@ -17,14 +17,12 @@
 
 import docker
 
-from ..docker_commandline_code_executor import _wait_for_ready
-
 if sys.version_info >= (3, 11):
     from typing import Self
 else:
     from typing_extensions import Self
 
-
+from ..docker_commandline_code_executor import _wait_for_ready
 from .base import JupyterConnectable, JupyterConnectionInfo
 from .jupyter_client import JupyterClient