Merge branch 'main' into dotnet-signed

python/packages/autogen-agentchat/pyproject.toml

@@ -16,7 +16,6 @@ classifiers = [
 ]
 dependencies = [
     "autogen-core==0.4.1",
-    "aioconsole>=0.8.1"
 ]
 
 [tool.ruff]

python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py

@@ -5,7 +5,6 @@
 from inspect import iscoroutinefunction
 from typing import Any, AsyncGenerator, Awaitable, Callable, ClassVar, Generator, Optional, Sequence, Union, cast
 
-from aioconsole import ainput  # type: ignore
 from autogen_core import CancellationToken
 
 from ..base import Response
@@ -17,10 +16,9 @@
 InputFuncType = Union[SyncInputFunc, AsyncInputFunc]
 
 
-# TODO: ainput doesn't seem to play nicely with jupyter.
-#       No input window appears in this case.
+# TODO: check if using to_thread fixes this in jupyter
 async def cancellable_input(prompt: str, cancellation_token: Optional[CancellationToken]) -> str:
-    task: asyncio.Task[str] = asyncio.create_task(ainput(prompt))  # type: ignore
+    task: asyncio.Task[str] = asyncio.create_task(asyncio.to_thread(input, prompt))
     if cancellation_token is not None:
         cancellation_token.link_future(task)
     return await task

python/packages/autogen-agentchat/src/autogen_agentchat/ui/_console.py

@@ -5,7 +5,6 @@
 from inspect import iscoroutinefunction
 from typing import AsyncGenerator, Awaitable, Callable, Dict, List, Optional, TypeVar, Union, cast
 
-from aioconsole import aprint  # type: ignore
 from autogen_core import CancellationToken, Image
 from autogen_core.models import RequestUsage
 
@@ -70,6 +69,10 @@ def notify_event_received(self, request_id: str) -> None:
             self.input_events[request_id] = event
 
 
+def aprint(output: str, end: str = "\n") -> Awaitable[None]:
+    return asyncio.to_thread(print, output, end=end)
+
+
 async def Console(
     stream: AsyncGenerator[AgentEvent | ChatMessage | T, None],
     *,

python/packages/autogen-core/docs/src/reference/index.md

@@ -31,6 +31,7 @@ python/autogen_core.models
 python/autogen_core.model_context
 python/autogen_core.tools
 python/autogen_core.tool_agent
+python/autogen_core.memory
 python/autogen_core.exceptions
 python/autogen_core.logging
 ```
@@ -50,6 +51,7 @@ python/autogen_ext.teams.magentic_one
 python/autogen_ext.models.openai
 python/autogen_ext.models.replay
 python/autogen_ext.tools.langchain
+python/autogen_ext.tools.graphrag
 python/autogen_ext.tools.code_execution
 python/autogen_ext.code_executors.local
 python/autogen_ext.code_executors.docker

python/packages/autogen-core/docs/src/reference/python/autogen_core.memory.rst

@@ -0,0 +1,8 @@
+autogen\_core.memory
+====================
+
+
+.. automodule:: autogen_core.memory
+   :members:
+   :undoc-members:
+   :show-inheritance:

python/packages/autogen-core/docs/src/reference/python/autogen_ext.tools.graphrag.rst

@@ -0,0 +1,8 @@
+autogen\_ext.tools.graphrag
+===========================
+
+
+.. automodule:: autogen_ext.tools.graphrag
+   :members:
+   :undoc-members:
+   :show-inheritance:

python/packages/autogen-core/docs/src/user-guide/autogenstudio-user-guide/installation.md

@@ -57,61 +57,65 @@ conda deactivate
 
 ``````
 
-## Install Using pip (Recommended)
+## Install from PyPi (Recommended)
 
 You can install AutoGen Studio using pip, the Python package manager.
 
 ```bash
 pip install -U autogenstudio
 ```
 
-### Install from Source\*\*
+## Install from source
 
-> Note: This approach requires some familiarity with building interfaces in React.
+_Note: This approach requires some familiarity with building interfaces in React._
 
-If you prefer to install from source, ensure you have Python 3.10+ and Node.js (version above 14.15.0) installed. Here's how you get started:
+You have two options for installing from source: manually or using a dev container.
 
-- Clone the AutoGen Studio repository and install its Python dependencies:
+### A) Install from source manually
 
-  ```bash
-  pip install -e .
-  ```
-
-- Navigate to the `samples/apps/autogen-studio/frontend` directory, install dependencies, and build the UI:
+1. Ensure you have Python 3.10+ and Node.js (version above 14.15.0) installed.
+2. Clone the AutoGen Studio repository and install its Python dependencies using `pip install -e .`
+3. Navigate to the `python/packages/autogen-studio/frontend` directory, install the dependencies, and build the UI:
 
   ```bash
   npm install -g gatsby-cli
   npm install --global yarn
   cd frontend
   yarn install
   yarn build
+  # Windows users may need alternative commands to build the frontend:
+  gatsby clean && rmdir /s /q ..\\autogenstudio\\web\\ui 2>nul & (set \"PREFIX_PATH_VALUE=\" || ver>nul) && gatsby build --prefix-paths && xcopy /E /I /Y public ..\\autogenstudio\\web\\ui
   ```
 
-For Windows users, to build the frontend, you may need alternative commands to build the frontend.
-
-```bash
+### B)  Install from source using a dev container
 
-  gatsby clean && rmdir /s /q ..\\autogenstudio\\web\\ui 2>nul & (set \"PREFIX_PATH_VALUE=\" || ver>nul) && gatsby build --prefix-paths && xcopy /E /I /Y public ..\\autogenstudio\\web\\ui
+1. Follow the [Dev Containers tutorial](https://code.visualstudio.com/docs/devcontainers/tutorial) to install VS Code, Docker and relevant extensions.
+2. Clone the AutoGen Studio repository.
+3. Open `python/packages/autogen-studio/`in VS Code. Click the blue button in bottom the corner or press F1 and select _"Dev Containers: Reopen in Container"_.
+4. Build the UI:
 
-```
+  ```bash
+  cd frontend
+  yarn build
+  ```
 
 ## Running the Application
 
-Once installed, run the web UI by entering the following in a terminal:
+Once installed, run the web UI by entering the following in your terminal:
 
 ```bash
-autogenstudio ui --port 8081 --appdir /path/to/folder
+autogenstudio ui --port 8081
 ```
 
-This will start the application on the specified port. Open your web browser and go to `http://localhost:8081/` to begin using AutoGen Studio.
+This command will start the application on the specified port. Open your web browser and go to <http://localhost:8081/> to use AutoGen Studio.
 
 AutoGen Studio also takes several parameters to customize the application:
 
 - `--host <host>` argument to specify the host address. By default, it is set to `localhost`.
-- `--appdir <appdir>` argument to specify the directory where the app files (e.g., database and generated user files) are stored. By default, it is set to the a `.autogenstudio` directory in the user's home directory.
+- `--appdir <appdir>` argument to specify the directory where the app files (e.g., database and generated user files) are stored. By default, it is set to the `.autogenstudio` directory in the user's home directory.
 - `--port <port>` argument to specify the port number. By default, it is set to `8080`.
-- `--upgrade-database` argument to force-upgrade it's internal database schema (assuming there are changes in the version you are installing). By default, it is set to `False`.
 - `--reload` argument to enable auto-reloading of the server when changes are made to the code. By default, it is set to `False`.
-- `--database-uri` argument to specify the database URI. Example values include `sqlite:///database.sqlite` for SQLite and `postgresql+psycopg://user:password@localhost/dbname` for PostgreSQL. If this is not specified, the database URI defaults to a `autogen.db` file in the `--appdir` directory.
+- `--database-uri` argument to specify the database URI. Example values include `sqlite:///database.sqlite` for SQLite and `postgresql+psycopg://user:password@localhost/dbname` for PostgreSQL. If this is not specified, the database URL defaults to a `database.sqlite` file in the `--appdir` directory.
+- `--upgrade-database` argument to upgrade the database schema to the latest version. By default, it is set to `False`.
 
 Now that you have AutoGen Studio installed and running, you are ready to explore its capabilities, including defining and modifying agent workflows, interacting with agents and sessions, and expanding agent skills.

python/packages/autogen-core/src/autogen_core/memory/_base_memory.py

@@ -1,4 +1,3 @@
-from datetime import datetime
 from enum import Enum
 from typing import Any, Dict, List, Protocol, Union, runtime_checkable
 
@@ -23,32 +22,47 @@ class MemoryMimeType(Enum):
 
 
 class MemoryContent(BaseModel):
+    """A memory content item."""
+
     content: ContentType
+    """The content of the memory item. It can be a string, bytes, dict, or :class:`~autogen_core.Image`."""
+
     mime_type: MemoryMimeType | str
+    """The MIME type of the memory content."""
+
     metadata: Dict[str, Any] | None = None
-    timestamp: datetime | None = None
-    source: str | None = None
-    score: float | None = None
+    """Metadata associated with the memory item."""
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
 
 class MemoryQueryResult(BaseModel):
+    """Result of a memory :meth:`~autogen_core.memory.Memory.query` operation."""
+
     results: List[MemoryContent]
 
 
 class UpdateContextResult(BaseModel):
+    """Result of a memory :meth:`~autogen_core.memory.Memory.update_context` operation."""
+
     memories: MemoryQueryResult
 
 
 @runtime_checkable
 class Memory(Protocol):
-    """Protocol defining the interface for memory implementations."""
+    """Protocol defining the interface for memory implementations.
 
-    @property
-    def name(self) -> str | None:
-        """The name of this memory implementation."""
-        ...
+    A memory is the storage for data that can be used to enrich or modify the model context.
+
+    A memory implementation can use any storage mechanism, such as a list, a database, or a file system.
+    It can also use any retrieval mechanism, such as vector search or text search.
+    It is up to the implementation to decide how to store and retrieve data.
+
+    It is also a memory implementation's responsibility to update the model context
+    with relevant memory content based on the current model context and querying the memory store.
+
+    See :class:`~autogen_core.memory.ListMemory` for an example implementation.
+    """
 
     async def update_context(
         self,

python/packages/autogen-core/src/autogen_core/memory/_list_memory.py

@@ -17,32 +17,43 @@ class ListMemory(Memory):
     allowing external applications to manage memory contents directly.
 
     Example:
-         .. code-block:: python
-             # Initialize memory
-             memory = ListMemory(name="chat_history")
 
-             # Add memory content
-             content = MemoryContent(content="User prefers formal language")
-             await memory.add(content)
+        .. code-block:: python
 
-             # Directly modify memory contents
-             memory.content = [MemoryContent(content="New preference")]
+            import asyncio
+            from autogen_core.memory import ListMemory, MemoryContent
+            from autogen_core.model_context import BufferedChatCompletionContext
 
-             # Update a model context with memory
-             memory_contents = await memory.update_context(model_context)
 
+            async def main() -> None:
+                # Initialize memory
+                memory = ListMemory(name="chat_history")
+
+                # Add memory content
+                content = MemoryContent(content="User prefers formal language", mime_type="text/plain")
+                await memory.add(content)
+
+                # Directly modify memory contents
+                memory.content = [MemoryContent(content="New preference", mime_type="text/plain")]
+
+                # Create a model context
+                model_context = BufferedChatCompletionContext(buffer_size=10)
+
+                # Update a model context with memory
+                await memory.update_context(model_context)
+
+                # See the updated model context
+                print(await model_context.get_messages())
+
+
+            asyncio.run(main())
+
+    Args:
+        name: Optional identifier for this memory instance
 
-    Attributes:
-        name (str): Identifier for this memory instance
-        content (List[MemoryContent]): Direct access to memory contents
     """
 
     def __init__(self, name: str | None = None) -> None:
-        """Initialize ListMemory.
-
-        Args:
-            name: Optional identifier for this memory instance
-        """
         self._name = name or "default_list_memory"
         self._contents: List[MemoryContent] = []
 

python/packages/autogen-core/tests/test_memory.py

@@ -1,5 +1,3 @@
-from datetime import datetime
-
 import pytest
 from autogen_core import CancellationToken
 from autogen_core.memory import (
@@ -16,7 +14,6 @@
 def test_memory_protocol_attributes() -> None:
     """Test that Memory protocol has all required attributes."""
     # No changes needed here
-    assert hasattr(Memory, "name")
     assert hasattr(Memory, "update_context")
     assert hasattr(Memory, "query")
     assert hasattr(Memory, "add")
@@ -76,8 +73,8 @@ async def test_list_memory_add_and_query() -> None:
     """Test adding and querying memory contents."""
     memory = ListMemory()
 
-    content1 = MemoryContent(content="test1", mime_type=MemoryMimeType.TEXT, timestamp=datetime.now())
-    content2 = MemoryContent(content={"key": "value"}, mime_type=MemoryMimeType.JSON, timestamp=datetime.now())
+    content1 = MemoryContent(content="test1", mime_type=MemoryMimeType.TEXT)
+    content2 = MemoryContent(content={"key": "value"}, mime_type=MemoryMimeType.JSON)
 
     await memory.add(content1)
     await memory.add(content2)

python/packages/autogen-ext/pyproject.toml

@@ -27,6 +27,7 @@ file-surfer = [
     "autogen-agentchat==0.4.1",
     "markitdown>=0.0.1a2",
 ]
+graphrag = ["graphrag>=1.0.1"]
 web-surfer = [
     "autogen-agentchat==0.4.1",
     "playwright>=1.48.0",
@@ -57,6 +58,7 @@ packages = ["src/autogen_ext"]
 dev = [
     "autogen_test_utils",
     "langchain-experimental",
+    "pandas-stubs>=2.2.3.241126",
 ]
 
 [tool.ruff]

python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py

@@ -30,13 +30,13 @@
     Image,
     MessageHandlerContext,
 )
-from autogen_core.models import FinishReasons
 from autogen_core.logging import LLMCallEvent
 from autogen_core.models import (
     AssistantMessage,
     ChatCompletionClient,
     ChatCompletionTokenLogprob,
     CreateResult,
+    FinishReasons,
     FunctionExecutionResultMessage,
     LLMMessage,
     ModelCapabilities,  # type: ignore

python/packages/autogen-ext/src/autogen_ext/tools/graphrag/__init__.py

@@ -0,0 +1,25 @@
+from ._config import (
+    GlobalContextConfig,
+    GlobalDataConfig,
+    LocalContextConfig,
+    LocalDataConfig,
+    MapReduceConfig,
+    SearchConfig,
+)
+from ._global_search import GlobalSearchTool, GlobalSearchToolArgs, GlobalSearchToolReturn
+from ._local_search import LocalSearchTool, LocalSearchToolArgs, LocalSearchToolReturn
+
+__all__ = [
+    "GlobalSearchTool",
+    "LocalSearchTool",
+    "GlobalDataConfig",
+    "LocalDataConfig",
+    "GlobalContextConfig",
+    "GlobalSearchToolArgs",
+    "GlobalSearchToolReturn",
+    "LocalContextConfig",
+    "LocalSearchToolArgs",
+    "LocalSearchToolReturn",
+    "MapReduceConfig",
+    "SearchConfig",
+]