[onkark][develop] [onkark][rebased] Autogen Integration

Signed-off-by: Onkar Kulkarni <onkark@synopsys.com>

Author: onkark-snps

examples/frameworks/nat_autogen_demo/README.md

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+<!--
+SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-License-Identifier: Apache-2.0
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+<!-- path-check-skip-file -->
+
+# AutoGen Framework Example
+
+A minimal example using Microsoft's AutoGen framework showcasing a multi-agent weather and time information system where agents collaborate through AutoGen's conversation system to provide accurate weather and time data for specified cities.
+
+## Key Features
+
+- **AutoGen Framework Integration:** Demonstrates NeMo Agent Toolkit support for Microsoft's AutoGen framework alongside other frameworks like LangChain/LangGraph and Semantic Kernel.
+- **Multi-Agent Collaboration:** Shows two specialized agents working together - a WeatherAndTimeAgent for data retrieval and a FinalResponseAgent for response formatting.
+- **MCP Server Integration:** Demonstrates how NAT can interact with MCP (Model Context Protocol) servers to provide time information through external services.
+- **Tool Integration:** Showcases integration of both local tools (weather updates) and remote tools (MCP time service) within the AutoGen framework.
+- **Round-Robin Group Chat:** Uses AutoGen's RoundRobinGroupChat for structured agent communication with termination conditions.
+
+## Installation and Setup
+
+If you have not already done so, follow the instructions in the [Install Guide](../../../docs/source/quick-start/installing.md#install-from-source) to create the development environment and install NeMo Agent Toolkit.
+
+### Install this Workflow
+
+From the root directory of the NAT library, run the following commands:
+
+```bash
+uv pip install -e examples/getting_started/simple_calculator  # required to run the current_datetime MCP tool used in example workflow.
+uv pip install -e examples/frameworks/nat_autogen_demo
+```
+
+### Export required ENV variables
+If you have not already done so, follow the [Obtaining API Keys](../../../docs/source/quick-start/installing.md#obtaining-api-keys) instructions to obtain API keys.
+
+For OpenAI Export these:
+- OPENAI_MODEL_NAME
+- OPENAI_API_KEY
+- OPENAI_API_BASE
+
+### Run the Workflow
+
+#### Set up the MCP server
+This example demonstrates how NAT can interact with MCP servers on behalf of AutoGen agents.
+
+First run the MCP server with this command:
+
+```bash
+nat mcp serve --config_file examples/getting_started/simple_calculator/configs/config.yml --tool_names current_datetime
+```
+
+Then run the workflow with the NAT CLI:
+
+```bash
+nat run --config_file examples/frameworks/nat_autogen_demo/configs/config.yml --input "What is the weather and time in New York today?"
+```
+
+### Expected output
+
+```console
+2025-10-07 14:34:28,122 - nat.cli.commands.start - INFO - Starting NAT from config file: 'examples/frameworks/nat_autogen_demo/configs/config.yml'
+2025-10-07 14:34:30,285 - mcp.client.streamable_http - INFO - Received session ID: 652a05b6646c4ddb945cf2adf0b3ec18
+Received session ID: 652a05b6646c4ddb945cf2adf0b3ec18
+2025-10-07 14:34:30,287 - mcp.client.streamable_http - INFO - Negotiated protocol version: 2025-06-18
+Negotiated protocol version: 2025-06-18
+
+Configuration Summary:
+--------------------
+Workflow Type: autogen_team
+Number of Functions: 1
+Number of Function Groups: 0
+Number of LLMs: 1
+Number of Embedders: 0
+Number of Memory: 0
+Number of Object Stores: 0
+Number of Retrievers: 0
+Number of TTC Strategies: 0
+Number of Authentication Providers: 0
+
+2025-10-07 14:34:30,301 - nat.observability.exporter_manager - INFO - Started exporter 'otelcollector'
+2025-10-07 14:34:46,704 - nat.front_ends.console.console_front_end_plugin - INFO -
+.
+.
+.
+<snipped for brevity>
+.
+.
+.
+--------------------------------------------------
+Workflow Result:
+['New York weather: Sunny, around 25°C (77°F).\nCurrent local time in New York: 5:34 PM EDT (UTC−4) on October 7, 2025.\n\nAPPROVE']
+--------------------------------------------------
+
+--------------------------------------------------
+Workflow Result:
+['New York weather: Sunny, around 25°C (77°F).\nCurrent local time in New York: 5:34 PM EDT (UTC−4) on October 7, 2025.\n\nAPPROVE']
+--------------------------------------------------
+
+```
+
+## Architecture
+
+The AutoGen workflow consists of two main agents:
+
+1. **WeatherAndTimeAgent**: Retrieves weather and time information using tools
+   - Uses the `weather_update_tool` for current weather conditions
+   - Connects to MCP server for accurate time information
+   - Responds with "DONE" when task is completed
+
+2. **FinalResponseAgent**: Formats and presents the final response
+   - Consolidates information from other agents
+   - Provides clear, concise answers to user queries
+   - Terminates the conversation with "APPROVE".
+
+The agents communicate through AutoGen's RoundRobinGroupChat system, which manages the conversation flow and ensures proper termination when the task is complete.

examples/frameworks/nat_autogen_demo/configs/config.yml

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+# SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+general:
+  front_end:
+    _type: console
+    cors:
+      allow_origins: ["*"]
+  telemetry:
+    logging:
+      console:
+        _type: console
+        level: debug
+    tracing:
+      otelcollector:
+        _type: otelcollector
+        endpoint: ${OTEL_ENDPOINT:-http://localhost:6006/v1/traces}
+        project: nat_autogen_demo
+
+llms:
+  openai_llm:
+    _type: openai
+    model_name: ${OPENAI_MODEL_NAME:-gpt-5}
+    api_key: ${OPENAI_API_KEY}
+    base_url: ${OPENAI_API_BASE}
+
+functions:
+  weather_update_tool:
+    _type: nat_autogen_demo/weather_update_autogen
+    description: "Get the current weather for a specified city"
+
+workflow:
+  _type: autogen_team
+  llm_name: openai_llm
+  description: "To get the current weather and time in a specific city"
+  tool_names: [weather_update_tool]
+  query_processing_agent_name: WeatherAndTimeAgent
+  query_processing_agent_instructions: |
+    You are an agent that provides the current weather and time information.
+    When asked about the weather, provide the current weather conditions.
+    When asked about the time, provide the current local time.
+    If asked about anything else, respond with 'I can only provide weather and time information.'
+    Once you are done, reply with the text 'DONE'.
+  final_response_agent_name: FinalResponseAgent
+  final_response_agent_instructions: |
+    You are the final response agent.
+    Your role is to provide a concise and clear answer based on the information provided by other agents.
+    Once you are done, reply with the final answer and then say 'APPROVE'.

examples/frameworks/nat_autogen_demo/pyproject.toml

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+[build-system]
+build-backend = "setuptools.build_meta"
+requires = ["setuptools >= 64", "setuptools-scm>=8"]
+
+[tool.setuptools_scm]
+git_describe_command = "git describe --long --first-parent"
+root = "../../.."
+
+[project]
+name = "nat_autogen_demo"
+dynamic = ["version"]
+dependencies = [
+  "nvidia-nat[autogen]~=1.4",
+]
+requires-python = ">=3.11,<3.14"
+description = "AutoGen Workflow Example"
+keywords = ["ai", "rag", "agents", "autogen", "multi-agent"]
+classifiers = ["Programming Language :: Python"]
+
+[tool.uv.sources]
+nvidia-nat = { path = "../../..", editable = true }
+
+[project.entry-points.'nat.components']
+nat_autogen_demo = "nat_autogen_demo.register"

examples/frameworks/nat_autogen_demo/src/nat_autogen_demo/__init__.py

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+# SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

examples/frameworks/nat_autogen_demo/src/nat_autogen_demo/autogen_team.py

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+# SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+from collections.abc import AsyncGenerator
+
+from pydantic import Field
+
+from nat.builder.builder import Builder
+from nat.builder.framework_enum import LLMFrameworkEnum
+from nat.builder.function_info import FunctionInfo
+from nat.cli.register_workflow import register_function
+from nat.data_models.component_ref import LLMRef
+from nat.data_models.function import FunctionBaseConfig
+
+logger = logging.getLogger(__name__)
+
+
+class AutoGenFunctionConfig(FunctionBaseConfig, name="autogen_team"):
+    """Configuration for AutoGen Agent workflow."""
+
+    llm_name: LLMRef = Field(description="The LLM model to use with AutoGen agents.")
+    tool_names: list[str] = Field(default_factory=list, description="List of tool names to be used by the agents.")
+    mcp_server_url: str = Field(
+        default="http://0.0.0.0:9901/mcp",
+        description="URL for the MCP time server.",
+    )
+    query_processing_agent_name: str = Field(description="Name of the query processing agent")
+    query_processing_agent_instructions: str = Field(description="Instructions for the query processing agent")
+    final_response_agent_name: str = Field(description="Name of the final response agent")
+    final_response_agent_instructions: str = Field(description="Instructions for the final response agent")
+
+
+@register_function(config_type=AutoGenFunctionConfig, framework_wrappers=[LLMFrameworkEnum.AUTOGEN])
+async def autogen_team(config: AutoGenFunctionConfig, builder: Builder) -> AsyncGenerator[FunctionInfo, None]:
+    """
+    AutoGen multi-agent workflow that demonstrates collaborative agents in a team.
+    The agents communicate through AutoGen's conversation system to produce output.
+
+    Args:
+        config (AutoGenFunctionConfig): Configuration for the workflow.
+        builder (Builder): The NAT workflow builder to access registered components.
+
+    Yields:
+        AsyncGenerator[FunctionInfo, None]: Yields a FunctionInfo object encapsulating the workflow.
+    """
+
+    from autogen_agentchat.agents import AssistantAgent
+    from autogen_agentchat.conditions import TextMentionTermination
+    from autogen_agentchat.teams import RoundRobinGroupChat
+    from autogen_ext.tools.mcp import StreamableHttpMcpToolAdapter
+    from autogen_ext.tools.mcp import StreamableHttpServerParams
+
+    try:
+        llm_client = await builder.get_llm(config.llm_name, wrapper_type=LLMFrameworkEnum.AUTOGEN)
+        tools = await builder.get_tools(config.tool_names, wrapper_type=LLMFrameworkEnum.AUTOGEN)
+
+        time_server_params = StreamableHttpServerParams(
+            url=config.mcp_server_url,
+            headers={"Content-Type": "application/json"},
+            timeout=30,
+        )
+        adapter = await StreamableHttpMcpToolAdapter.from_server_params(time_server_params, "current_datetime")
+        tools.append(adapter)
+
+        query_processing_agent = AssistantAgent(name=config.query_processing_agent_name,
+                                                model_client=llm_client,
+                                                tools=tools,
+                                                system_message=config.query_processing_agent_instructions)
+        final_response_agent = AssistantAgent(name=config.final_response_agent_name,
+                                              model_client=llm_client,
+                                              system_message=config.final_response_agent_instructions)
+
+        team = RoundRobinGroupChat(participants=[query_processing_agent, final_response_agent],
+                                   termination_condition=TextMentionTermination("APPROVE"))
+
+        async def _autogen_team_workflow(user_input: str) -> str:
+            """Execute the workflow with the given input.
+
+            Args:
+                user_input (str): User's query
+
+            Returns:
+                str: The final response generated by the team.
+            """
+            try:
+                result = await team.run(task=user_input)
+
+                if hasattr(result, 'messages') and result.messages:
+                    return result.messages[-1].content
+                else:
+                    return "The workflow finished but no output was generated."
+
+            except Exception as e:
+                logger.exception("Error in AutoGen workflow")
+                return f"Error occurred during AutoGen workflow: {e!s}"
+
+        # Yield the function info
+        yield FunctionInfo.create(single_fn=_autogen_team_workflow)
+
+    except GeneratorExit:
+        logger.info("AutoGen workflow exited early")
+    except Exception as _e:
+        logger.exception("Failed to initialize AutoGen workflow")
+        raise
+    finally:
+        logger.debug("AutoGen workflow cleanup completed")

examples/frameworks/nat_autogen_demo/src/nat_autogen_demo/register.py

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+# SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from . import autogen_team  # noqa: F401 # pylint: disable=W0611     #imported for side effects (registration)
+from . import weather_update_tool  # noqa: F401 # pylint: disable=W0611     #imported for side effects (registration)