OpenAPI#
FastAgency can automatically create functions properly annotated for use with LLM-s from OpenAPI specification.
This example demonstrates how to integrate external REST API calls into AutoGen agents using FastAgency. We'll create a weather agent that interacts with a weather REST API and a user agent to facilitate the conversation. This example will help you understand how to set up agents and facilitate agent communication through an external REST API. To interact with the REST API, the AutoGen agent needs to understand the available routes, so it requires the OpenAPI specification (openapi.json file) for the external REST API.
In this example, we'll use a simple weather API and its specification available at https://weather.tools.fastagency.ai/openapi.json.
Note
The weather API has two routes: one for the daily weather forecast, which has no security, and another for the hourly forecast, which is secured. We will learn how to access external APIs that are secured in the next chapter.
Install#
To get started, you need to install FastAgency with OpenAPI submodule. You can do this using pip, Python's package installer.
Imports#
These imports are similar to the imports section we have already covered, with the only difference being the additional imports of the OpenAPI Client and UserProxyAgent:
import os
from autogen import UserProxyAgent
from autogen.agentchat import ConversableAgent
from fastagency import UI, FastAgency, Workflows
from fastagency.api.openapi import OpenAPI
from fastagency.runtime.autogen.base import AutoGenWorkflows
from fastagency.ui.console import ConsoleUI
Define Workflow#
In this workflow, the only difference is that we create a Python client for the external REST API by passing the URL of the openapi.json to the Client.create method. Then, we register the generated client with the agent using the methods register_for_llm and register_for_execution. Here's a simple example of a workflow definition:
llm_config = {
"config_list": [
{
"model": "gpt-4o",
"api_key": os.getenv("OPENAI_API_KEY"),
}
],
"temperature": 0.0,
}
WEATHER_OPENAPI_URL = "https://weather.tools.fastagency.ai/openapi.json"
weather_api = OpenAPI.create(openapi_url=WEATHER_OPENAPI_URL)
wf = AutoGenWorkflows()
@wf.register(name="simple_weather", description="Weather chat")
def weather_workflow(
wf: Workflows, ui: UI, initial_message: str, session_id: str
) -> str:
user_agent = UserProxyAgent(
name="User_Agent",
system_message="You are a user agent",
llm_config=llm_config,
human_input_mode="NEVER",
)
weather_agent = ConversableAgent(
name="Weather_Agent",
system_message="You are a weather agent",
llm_config=llm_config,
human_input_mode="NEVER",
)
wf.register_api(
api=weather_api,
callers=user_agent,
executors=weather_agent,
)
chat_result = user_agent.initiate_chat(
weather_agent,
message=initial_message,
summary_method="reflection_with_llm",
max_turns=3,
)
return chat_result.summary # type: ignore[no-any-return]
This code snippet sets up a simple weather agent that calls an external weather API using the registered functions generated from the openapi.json URL.
Define FastAgency Application#
Next, define your FastAgency application.
Complete Application Code#
main.py
import os
from autogen import UserProxyAgent
from autogen.agentchat import ConversableAgent
from fastagency import UI, FastAgency, Workflows
from fastagency.api.openapi import OpenAPI
from fastagency.runtime.autogen.base import AutoGenWorkflows
from fastagency.ui.console import ConsoleUI
llm_config = {
"config_list": [
{
"model": "gpt-4o",
"api_key": os.getenv("OPENAI_API_KEY"),
}
],
"temperature": 0.0,
}
WEATHER_OPENAPI_URL = "https://weather.tools.fastagency.ai/openapi.json"
weather_api = OpenAPI.create(openapi_url=WEATHER_OPENAPI_URL)
wf = AutoGenWorkflows()
@wf.register(name="simple_weather", description="Weather chat")
def weather_workflow(
wf: Workflows, ui: UI, initial_message: str, session_id: str
) -> str:
user_agent = UserProxyAgent(
name="User_Agent",
system_message="You are a user agent",
llm_config=llm_config,
human_input_mode="NEVER",
)
weather_agent = ConversableAgent(
name="Weather_Agent",
system_message="You are a weather agent",
llm_config=llm_config,
human_input_mode="NEVER",
)
wf.register_api(
api=weather_api,
callers=user_agent,
executors=weather_agent,
)
chat_result = user_agent.initiate_chat(
weather_agent,
message=initial_message,
summary_method="reflection_with_llm",
max_turns=3,
)
return chat_result.summary # type: ignore[no-any-return]
app = FastAgency(wf=wf, ui=ConsoleUI())
Run Application#
You can run this chapter's FastAgency application using the following command:
Output#
The output will vary based on the city and the current weather conditions:
╭─── Python package file structure ───╮
│ │
│ 📁 docs │
│ ├── 🐍 __init__.py │
│ └── 📁 docs_src │
│ ├── 🐍 __init__.py │
│ └── 📁 tutorial │
│ ├── 🐍 __init__.py │
│ └── 📁 external_rest_apis │
│ ├── 🐍 __init__.py │
│ └── 🐍 main.py │
│ │
╰─────────────────────────────────────╯
╭─────────────────── Importable FastAgency app ────────────────────╮
│ │
│ from docs.docs_src.tutorial.external_rest_apis.main import app │
│ │
╰──────────────────────────────────────────────────────────────────╯
╭─ FastAgency -> user [text_input] ────────────────────────────────────────────╮
│ │
│ Starting a new workflow 'simple_weather' with the following │
│ description: │
│ │
│ Weather chat │
│ │
│ Please enter an initial message: │
╰──────────────────────────────────────────────────────────────────────────────╯
Get me daily weather forecast for Chennai city
╭─ User_Agent -> Weather_Agent [text_message] ─────────────────────────────────╮
│ │
│ Get me daily weather forecast for Chennai city │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Weather_Agent -> User_Agent [suggested_function_call] ──────────────────────╮
│ │
│ { │
│ "function_name": "get_daily_weather_daily_get", │
│ "call_id": │
│ "call_VZ19VFNcTE9n8BnXa9aiMzFA", │
│ "arguments": { │
│ "city": │
│ "Chennai" │
│ } │
│ } │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ User_Agent -> Weather_Agent [function_call_execution] ──────────────────────╮
│ │
│ { │
│ "function_name": "get_daily_weather_daily_get", │
│ "call_id": │
│ "call_VZ19VFNcTE9n8BnXa9aiMzFA", │
│ "retval": "{\"city\": \"Chennai\", │
│ \"temperature\": 31, \"daily_forecasts\": [{\"forecast_date\": │
│ \"2024-09-10\", \"temperature\": 31, \"hourly_forecasts\": null}, │
│ {\"forecast_date\": \"2024-09-11\", \"temperature\": 30, │
│ \"hourly_forecasts\": null}, {\"forecast_date\": \"2024-09-12\", │
│ \"temperature\": 30, \"hourly_forecasts\": null}]}\n" │
│ } │
╰──────────────────────────────────────────────────────────────────────────────╯
╭─ Weather_Agent -> User_Agent [text_message] ─────────────────────────────────╮
│ │
│ The daily weather forecast for Chennai is as follows: │
│ │
│ - **September │
│ 10, 2024**: Temperature - 31°C │
│ - **September 11, 2024**: Temperature - │
│ 30°C │
│ - **September 12, 2024**: Temperature - 30°C │
│ │
│ If you need more │
│ details or forecasts for more days, feel free to ask! │
╰──────────────────────────────────────────────────────────────────────────────╯