Autogen (DEPRECATED)

This Integration is DEPRECATED

Click here to check out the latest integration of Autogen with Prisma AIRS AI Gateway

Quick Start Integration

Autogen supports a concept of config\_list which allows definitions of the LLM provider and model to be used. The AI Gateway seamlessly integrates into the Autogen framework through a custom config we create.

Example using minimal configuration

from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

config_list = [
    {
        "api_key": 'Your OpenAI Key',
        "model": "@openai/gpt-3.5-turbo",
        "base_url": "https://aigw.portkey.ai/v1",
        "api_type": "openai",
    }
]

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) # IMPORTANT: set to True to run code in docker, recommended
user_proxy.initiate_chat(assistant, message="Say this is also a test - part 2.")
# This initiates an automated chat between the two agents to solve the task

Notice that we updated the base_url to AI Gateway and then added default_headers to enable the AI Gateway specific features. When we execute this script, it would yield the same results as without the AI Gateway, but every request can now be inspected in the AI Gateway Analytics & Logs UI - including token, cost, accuracy calculations. All the config parameters supported in the AI Gateway are available for use as part of the headers. Let’s look at some examples:

Using 3,000+ models in Autogen through the AI Gateway

Since the AI Gateway seamlessly connects to 3,000+ models across providers, you can easily connect any of these to now run with Autogen. Let’s see an example using Mistral-7B on Anyscale running with Autogen seamlessly:

from autogen import AssistantAgent, UserProxyAgent, config_list_from_json

config_list = [
    {
        "api_key": 'Your Anyscale API Key',
        "model": "@anyscale/mistralai/Mistral-7B-Instruct-v0.1",
        "base_url": "https://aigw.portkey.ai/v1",
        "api_type": "openai", # the AI Gateway conforms to the openai api_type
    }
]

assistant = AssistantAgent("assistant", llm_config={"config_list": config_list})
user_proxy = UserProxyAgent("user_proxy", code_execution_config={"work_dir": "coding", "use_docker": False}) # IMPORTANT: set to True to run code in docker, recommended
user_proxy.initiate_chat(assistant, message="Say this is also a test - part 2.")
# This initiates an automated chat between the two agents to solve the task

Using Model Catalog

Model Catalog in the AI Gateway lets you manage provider credentials centrally. Add your Anyscale API key to Model Catalog and use the AI Provider slug in your config.

Using Configs

Configs in the AI Gateway unlock advanced management and routing functionality including load balancing, fallbacks, canary testing, switching models and more. You can use AI Gateway configs in Autogen like this:

Last modified on September 15, 2026

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This Integration is DEPRECATED

Quick Start Integration

Example using minimal configuration

Using 3,000+ models in Autogen through the AI Gateway

Using Model Catalog

Using Configs

This Integration is DEPRECATED

​Quick Start Integration

​Example using minimal configuration

​Using 3,000+ models in Autogen through the AI Gateway

​Using Model Catalog

​Using Configs

Quick Start Integration

Example using minimal configuration

Using 3,000+ models in Autogen through the AI Gateway

Using Model Catalog

Using Configs