<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
These changes are needed to expand AutoGen's memory capabilities with a
robust, production-ready integration with Mem0.ai.
<!-- Please give a short summary of the change and the problem this
solves. -->
This PR adds a new memory component for AutoGen that integrates with
Mem0.ai, providing a robust memory solution that supports both cloud and
local backends. The Mem0Memory class enables agents to store and
retrieve information persistently across conversation sessions.
## Key Features
- Seamless integration with Mem0.ai memory system
- Support for both cloud-based and local storage backends
- Robust error handling with detailed logging
- Full implementation of AutoGen's Memory interface
- Context updating for enhanced agent conversations
- Configurable search parameters for memory retrieval
## Related issue number
<!-- For example: "Closes #1234" -->
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Co-authored-by: Ricky Loynd <riloynd@microsoft.com>
Add OTel GenAI traces:
- `create_agent`
- `invoke_agnet`
- `execute_tool`
Introduces context manager helpers to create these traces. The helpers
also serve as instrumentation points for other instrumentation
libraries.
Resolves#6644
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
MCP Python-sdk has started to support a new transport protocol named
`Streamble HTTP` since
[v1.8.0](https://github.com/modelcontextprotocol/python-sdk/releases/tag/v1.8.0)
last month. I heard it supersedes the SSE transport. Therefore, AutoGen
have to support it as soon as possible.
## Related issue number
https://github.com/microsoft/autogen/discussions/6517
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
Co-authored-by: Victor Dibia <victor.dibia@gmail.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
Update autogenstudio version.
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
Closes#6580
<!-- For example: "Closes #1234" -->
## Checks
- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
There have been updates to the azure ai agent foundry sdk
(azure-ai-project). This PR updates the autogen `AzureAIAgent` which
wraps the azure ai agent. A list of some changes
- Update docstring samples to use `endpoint` (instead of connection
string previously)
- Update imports and arguments e.g, from `azure.ai.agents` etc
- Add a guide in ext docs showing Bing Search Grounding tool example.
<img width="1423" alt="image"
src="https://github.com/user-attachments/assets/0b7c8fa6-8aa5-4c20-831b-b525ac8243b7"
/>
## Why are these changes needed?
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
Closes#6601
<!-- For example: "Closes #1234" -->
## Checks
- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
- Added the support Azure AI Agent. The new agent is named AzureAIAgent.
- The agent supports Bing search, file search, and Azure search tools.
- Added a Jupiter notebook to demonstrate the usage of the AzureAIAgent.
## What's missing?
- AzureAIAgent support only text message responses
- Parallel execution for the custom functions.
## Related issue number
[5545](https://github.com/microsoft/autogen/issues/5545#event-16626859772)
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
This is an initial exploration of what could be a solution for #6214 .
It implements a simple text canvas using difflib and also a memory
component and a tool component for interacting with the canvas. Still in
early testing but would love feedback on the design.
## Related issue number
<!-- For example: "Closes #1234" -->
## Checks
- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
---------
Co-authored-by: Leonardo Pinheiro <lpinheiro@microsoft.com>
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
This PR introduces a safer and more controllable execution environment
for LLM code execution in version 0.4 by enabling the use of Jupyter
inside a container. This enhancement addresses security concerns and
provides a more robust execution context. In particular, it allows:
Isolation of code execution via containerized Jupyter environments.
Persistent memory of variables and their values throughout the
conversation.
Memory of code execution results to support more advanced reasoning and
follow-up tasks.
These improvements help build a more interactive and stateful LLM-agent
programming experience, especially for iterative code generation and
debugging scenarios.
## Related issue number
Open #6153
## Checks
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
Resolves#6232, #6198
This PR introduces an optional parameter `session` to `mcp_server_tools`
to support reuse of the same session.
```python
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.conditions import TextMentionTermination
from autogen_agentchat.teams import RoundRobinGroupChat
from autogen_agentchat.ui import Console
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import StdioServerParams, create_mcp_server_session, mcp_server_tools
async def main() -> None:
model_client = OpenAIChatCompletionClient(model="gpt-4o", parallel_tool_calls=False) # type: ignore
params = StdioServerParams(
command="npx",
args=["@playwright/mcp@latest"],
read_timeout_seconds=60,
)
async with create_mcp_server_session(params) as session:
await session.initialize()
tools = await mcp_server_tools(server_params=params, session=session)
print(f"Tools: {[tool.name for tool in tools]}")
agent = AssistantAgent(
name="Assistant",
model_client=model_client,
tools=tools, # type: ignore
)
termination = TextMentionTermination("TERMINATE")
team = RoundRobinGroupChat([agent], termination_condition=termination)
await Console(
team.run_stream(
task="Go to https://ekzhu.com/, visit the first link in the page, then tell me about the linked page."
)
)
asyncio.run(main())
```
Based on discussion in this thread: #6284, we will consider
serialization and deserialization of MCP server tools when used in this
manner in a separate issue.
This PR also replaces the `json_schema_to_pydantic` dependency with
built-in utils.
## Description
This PR pins opentelemetry-proto version to >=1.28.0, which uses
protobuf > 5.0, < 6.0 to generate protobuf files.
## Related issue number
Closes#6304
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
`IncludeEnum` was removed in ChromaDB when it was updated to `1.0.0`.
This caused issues when using `ChromaDBVectorMemory`. This PR fixes
those issues
## Related issue number
Closes#6241
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
<!-- Thank you for your contribution! Please review
https://microsoft.github.io/autogen/docs/Contribute before opening a
pull request. -->
<!-- Please add a reviewer to the assignee section when you create a PR.
If you don't have the access to it, we will shortly find a reviewer and
assign them to your PR. -->
## Why are these changes needed?
https://github.com/user-attachments/assets/e160f16d-f42d-49e2-a6c6-687e4e6786f4
Enable file upload/paste as a task in AGS. Enables tasks like
- Can you research and fact check the ideas in this screenshot?
- Summarize this file
Only text and images supported for now
Underneath, it constructs TextMessage and Multimodal messages as the
task.
<!-- Please give a short summary of the change and the problem this
solves. -->
## Related issue number
<!-- For example: "Closes #1234" -->
Closes#5773
## Checks
- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [ ] I've made sure all auto checks have passed.
---------
Co-authored-by: Jack Gerrits <jackgerrits@users.noreply.github.com>
# Azure AI Search Tool Implementation
This PR adds a new tool for Azure AI Search integration to autogen-ext,
enabling agents to search and retrieve information from Azure AI Search
indexes.
## Why Are These Changes Needed?
AutoGen currently lacks native integration with Azure AI Search, which
is a powerful enterprise search service that supports semantic, vector,
and hybrid search capabilities. This integration enables agents to:
1. Retrieve relevant information from large document collections
2. Perform semantic search with AI-powered ranking
3. Execute vector similarity search using embeddings
4. Combine text and vector approaches for optimal results
This tool complements existing retrieval capabilities and provides a
seamless way to integrate with Azure's search infrastructure.
## Features
- **Multiple Search Types**: Support for text, semantic, vector, and
hybrid search
- **Flexible Configuration**: Customizable search parameters and fields
- **Robust Error Handling**: User-friendly error messages with
actionable guidance
- **Performance Optimizations**: Configurable caching and retry
mechanisms
- **Vector Search Support**: Built-in embedding generation with
extensibility
## Usage Example
```python
from autogen_ext.tools.azure import AzureAISearchTool
from azure.core.credentials import AzureKeyCredential
from autogen import AssistantAgent, UserProxyAgent
# Create the search tool
search_tool = AzureAISearchTool.load_component({
"provider": "autogen_ext.tools.azure.AzureAISearchTool",
"config": {
"name": "DocumentSearch",
"description": "Search for information in the knowledge base",
"endpoint": "https://your-service.search.windows.net",
"index_name": "your-index",
"credential": {"api_key": "your-api-key"},
"query_type": "semantic",
"semantic_config_name": "default"
}
})
# Create an agent with the search tool
assistant = AssistantAgent(
"assistant",
llm_config={"tools": [search_tool]}
)
# Create a user proxy agent
user_proxy = UserProxyAgent(
"user_proxy",
human_input_mode="TERMINATE",
max_consecutive_auto_reply=10,
code_execution_config={"work_dir": "coding"}
)
# Start the conversation
user_proxy.initiate_chat(
assistant,
message="What information do we have about quantum computing in our knowledge base?"
)
```
## Testing
- Added unit tests for all search types (text, semantic, vector, hybrid)
- Added tests for error handling and cancellation
- All tests pass locally
## Documentation
- Added comprehensive docstrings with examples
- Included warnings about placeholder embedding implementation
- Added links to Azure AI Search documentation
## Related issue number
Closes#5419
## Checks
- [x] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [x] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [x] I've made sure all auto checks have passed.
---------
Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
## Why are these changes needed?
This PR fixes a `TypeError: Cannot instantiate typing.Union` that occurs
when using the `MultimodalWebSurfer_agent` with Anthropic models. The
error was caused by the incorrect usage of `typing.Union` as a class
constructor instead of a type hint within the `_anthropic_client.py`
file. The code was attempting to instantiate `typing.Union`, which is
not allowed. The fix correctly uses `typing.Union` within type hints,
and uses the correct `Base64ImageSourceParam` type. It also updates the
`pyproject.toml` dependency.
## Related issue number
Closes#6035
## Checks
- [ ] I've included any doc changes needed for
<https://microsoft.github.io/autogen/>. See
<https://github.com/microsoft/autogen/blob/main/CONTRIBUTING.md> to
build and test documentation locally.
- [ ] I've added tests (if relevant) corresponding to the changes
introduced in this PR.
- [v] I've made sure all auto checks have passed.
---------
Co-authored-by: Victor Dibia <victordibia@microsoft.com>
