Autogen

pip install -U "autogen-agentchat" "autogen-ext[openai,azure]" portkey-ai

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_core.models import ModelFamily

from autogen_ext.models.openai import OpenAIChatCompletionClient
import asyncio

# Define a model client that talks to Portkey's OpenAI-compatible endpoint.
# Use a Model Catalog model string: "@provider_slug/model_name"
model_client = OpenAIChatCompletionClient(
    base_url="https://api.portkey.ai/v1",
    api_key="YOUR_PORTKEY_API_KEY",
    model="@your-provider-slug/gpt-4o",
    model_info={
        "vision": True,
        "function_calling": True,
        "json_output": True,
        "structured_output": True,
        # Use GPT family for gpt-4o to allow tools + system message
        "family": ModelFamily.GPT_45,
    },
    # Optional headers: attach Portkey Configs, tracing, or metadata
    default_headers={
        "x-portkey-config": "pc-xxxx",
        "x-portkey-trace-id": "trace-id",
    }
)


# Define a simple function tool that the agent can use.
async def get_weather(city: str) -> str:
    """Get the weather for a given city."""
    return f"The weather in {city} is 73 degrees and Sunny."


# Create an AssistantAgent with the Portkey-backed model client
agent = AssistantAgent(
    name="weather_agent",
    model_client=model_client,
    tools=[get_weather],
    system_message="You are a helpful assistant.",
    reflect_on_tool_use=True,
    model_client_stream=True,  # Enable token streaming
)


async def main() -> None:
    await Console(agent.run_stream(task="What is the weather in New York?"))
    await model_client.close()


if __name__ == "__main__":
    asyncio.run(main())

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_core.models import ModelFamily
from portkey_ai import createHeaders

# Create a config with fallbacks (recommend creating this in Portkey App)
config = {
  "strategy": {"mode": "fallback"},
  "targets": [
    {"override_params": {"model": "@your-provider-slug/gpt-4o"}},
    {"override_params": {"model": "@your-anthropic-provider/claude-3-opus-20240229"}}
  ]
}

model_client = OpenAIChatCompletionClient(
    base_url="https://api.portkey.ai/v1",
    api_key="YOUR_PORTKEY_API_KEY",
    model="@your-provider-slug/gpt-4o",
    model_info={"family": ModelFamily.GPT_45},
    default_headers=createHeaders(config=config)
)

agent = AssistantAgent(
    name="resilient_agent",
    model_client=model_client,
    system_message="You are a helpful assistant."
)

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_core.models import ModelFamily
from portkey_ai import createHeaders

# Create a config with input and output guardrails (recommend using Portkey App)
config = {
    "input_guardrails": ["guardrails-id-xxx", "guardrails-id-yyy"],
    "output_guardrails": ["guardrails-id-xxx"]
}

model_client = OpenAIChatCompletionClient(
    base_url="https://api.portkey.ai/v1",
    api_key="YOUR_PORTKEY_API_KEY",
    model="@your-provider-slug/gpt-4o",
    model_info={"family": ModelFamily.GPT_45},
    default_headers=createHeaders(config=config)
)

agent = AssistantAgent(
    name="safe_agent",
    model_client=model_client,
    system_message="You are a helpful assistant that provides safe responses."
)

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_core.models import ModelFamily
from portkey_ai import createHeaders

model_client = OpenAIChatCompletionClient(
    base_url="https://api.portkey.ai/v1",
    api_key="YOUR_PORTKEY_API_KEY",
    model="@your-provider-slug/gpt-4o",
    model_info={"family": ModelFamily.GPT_45},
    default_headers=createHeaders(
        metadata={
            "_user": "user_123",
            "user_name": "John Doe",
            "user_tier": "premium",
            "user_company": "Acme Corp"
        }
    )
)

agent = AssistantAgent(
    name="personalized_agent",
    model_client=model_client,
    system_message="You are a personalized assistant."
)