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Add an AI Agent to your FastAPI application. The agent knows how to interact with your endpoints within a chat interface.

Project description

FastAPI Agent Logo

💬 Talk to your FastAPI app like it's a teammate.


FastAPI Agent integrates an AI Agent into your FastAPI application. It allows you to interact with your API endpoints through a chat interface or directly via the /agent/query route using an LLM (Large Language Model).


⚙️ Installation:

To install the package, run:

pip install fastapi_agent

🧪 Usage:

To use the FastAPI Agent, initialize it with your FastAPI app and AI model.
You can use the default agent routes or add custom ones to your FastAPI application to interact with the agent via a chat interface or API endpoint.

Here is a simple example of how to use the FastAPI Agent with your FastAPI application:

.env

OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

app.py

import uvicorn
from dotenv import load_dotenv

from fastapi import FastAPI
from fastapi_agent import FastAPIAgent

# load OPENAI_API_KEY from .env
load_dotenv()

# set your FastAPI app
app = FastAPI(
    title="YOUR APP TITLE",
    version="0.1.0",
    description="some app description",
)

# add routes
@app.get("/")
async def root():
    """Welcome endpoint that returns basic API information"""
    return {"message": "Welcome to Test API"}

# add the FastAPI Agent + default routes
FastAPIAgent(
    app,
    model="openai:gpt-4.1-mini",
    base_url="http://localhost:8000",
    include_router=True,
)

uvicorn.run(app, host="0.0.0.0", port=8000)

🧭 Default Routes

FastAPI Agent provides two default routes:

  1. /agent/query – Ask anything about your API using natural language. 🧠
curl -k -X POST "http://127.0.0.1:8000/agent/query" \
-H "Content-Type: application/json" \
-d '{"query": "show all endpoints"}'
  1. /agent/chat – A simple web-based chat interface to interact with your API. 💬

💡 You can also add custom routes using agent.chat() method - Example


🧩 Additional Arguments:

If your application routes use Depends (e.g., an API key), you can pass a dictionary of headers.
The agent will use them to call your routes and apply the same dependencies to the /agent/query route.

api_key = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

FastAPIAgent(
    app,
    model="openai:gpt-4.1-mini",
    base_url="https://localhost:8000",
    depends={"api-key": api_key},
    include_router=True,
)

You can control which routes the agent can access using the ignore_routes or allow_routes arguments:

  • Use ignore_routes to exclude specific routes from being accessible to the agent.
  • Use allow_routes to restrict the agent to only the specified routes.

Both ignore_routes and allow_routes must be a list of strings in the format: ["METHOD:/path"]

FastAPIAgent(
    app,
    model="openai:gpt-4.1-mini",
    base_url="https://localhost:8000",
    ignore_routes=["DELETE:/users/{user_id}"],
    include_router=True,
)

📁 Additional Examples:

Check out our examples for ai_agent, fastapi_discovery, and fastapi_agent.
All examples are available here.


If you're using Depends in your routes, make sure to pass the required headers when calling the /agent/query endpoint like the examples below:

python

import requests

res = requests.post(
    "http://127.0.0.1:8000/agent/query", 
    json={"query": "show all endpoints"},
    headers={"depends": '{"api-key": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"}'}
)
print(res.json())

curl

curl -k -X POST "http://127.0.0.1:8000/agent/query" \
  -H 'depends: {"api-key": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"}' \
  -H "Content-Type: application/json" \
  -d '{"query": "show all endpoints"}'

📜 License

This project is licensed under the MIT License.

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