# Agent tools

In this example, we will use the `openai-agents` library to create a simple agent that can use tools to perform tasks.
This example is based on the [basic tools example](https://github.com/openai/openai-agents-python/blob/main/examples/basic/tools.py) example from the `openai-agents-python` repo.

First, create an OpenAI API key, which you can get from the [OpenAI website](https://platform.openai.com/account/api-keys).
Then, create a secret on your Flyte cluster with:

```
flyte create secret OPENAI_API_KEY --value <your-api-key>
```

Then, we'll use `uv script` to specify our dependencies.

```
"""OpenAI Agents with Flyte, basic tool example.

Usage:

Create secret:

```
flyte create secret openai_api_key
uv run agents_tools.py
```
"""
# {{docs-fragment uv-script}}

# /// script
# requires-python = "==3.13"
# dependencies = [
#    "flyte>=2.0.0b52",
#    "flyteplugins-openai>=2.0.0b7",
#    "openai-agents>=0.2.4",
#    "pydantic>=2.10.6",
# ]
# main = "main"
# params = ""
# ///

# {{/docs-fragment uv-script}}

# {{docs-fragment imports-task-env}}
from agents import Agent, Runner
from pydantic import BaseModel

import flyte
from flyteplugins.openai.agents import function_tool

env = flyte.TaskEnvironment(
    name="openai_agents_tools",
    resources=flyte.Resources(cpu=1, memory="250Mi"),
    image=flyte.Image.from_uv_script(__file__, name="openai_agents_image"),
    secrets=flyte.Secret("openai_api_key", as_env_var="OPENAI_API_KEY"),
)

# {{/docs-fragment imports-task-env}}

# {{docs-fragment tools}}
class Weather(BaseModel):
    city: str
    temperature_range: str
    conditions: str

@function_tool
@env.task
async def get_weather(city: str) -> Weather:
    """Get the weather for a given city."""
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

# {{/docs-fragment tools}}

# {{docs-fragment agent}}
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)

@env.task
async def main() -> str:
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
    return result.final_output

# {{/docs-fragment agent}}

# {{docs-fragment main}}
if __name__ == "__main__":
    flyte.init_from_config()
    run = flyte.run(main)
    print(run.url)
    run.wait()
# {{/docs-fragment main}}
```

*Source: https://github.com/unionai/unionai-examples/blob/main/v2/integrations/flyte-plugins/openai/openai/agents_tools.py*

Next, we'll import the libraries and create a `TaskEnvironment`, which we need to run the example:

```
"""OpenAI Agents with Flyte, basic tool example.

Usage:

Create secret:

```
flyte create secret openai_api_key
uv run agents_tools.py
```
"""
# {{docs-fragment uv-script}}

# /// script
# requires-python = "==3.13"
# dependencies = [
#    "flyte>=2.0.0b52",
#    "flyteplugins-openai>=2.0.0b7",
#    "openai-agents>=0.2.4",
#    "pydantic>=2.10.6",
# ]
# main = "main"
# params = ""
# ///

# {{/docs-fragment uv-script}}

# {{docs-fragment imports-task-env}}
from agents import Agent, Runner
from pydantic import BaseModel

import flyte
from flyteplugins.openai.agents import function_tool

env = flyte.TaskEnvironment(
    name="openai_agents_tools",
    resources=flyte.Resources(cpu=1, memory="250Mi"),
    image=flyte.Image.from_uv_script(__file__, name="openai_agents_image"),
    secrets=flyte.Secret("openai_api_key", as_env_var="OPENAI_API_KEY"),
)

# {{/docs-fragment imports-task-env}}

# {{docs-fragment tools}}
class Weather(BaseModel):
    city: str
    temperature_range: str
    conditions: str

@function_tool
@env.task
async def get_weather(city: str) -> Weather:
    """Get the weather for a given city."""
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

# {{/docs-fragment tools}}

# {{docs-fragment agent}}
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)

@env.task
async def main() -> str:
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
    return result.final_output

# {{/docs-fragment agent}}

# {{docs-fragment main}}
if __name__ == "__main__":
    flyte.init_from_config()
    run = flyte.run(main)
    print(run.url)
    run.wait()
# {{/docs-fragment main}}
```

*Source: https://github.com/unionai/unionai-examples/blob/main/v2/integrations/flyte-plugins/openai/openai/agents_tools.py*

## Define the tools

We'll define a tool that can get weather information for a
given city. In this case, we'll use a toy function that returns a hard-coded `Weather` object.

```
"""OpenAI Agents with Flyte, basic tool example.

Usage:

Create secret:

```
flyte create secret openai_api_key
uv run agents_tools.py
```
"""
# {{docs-fragment uv-script}}

# /// script
# requires-python = "==3.13"
# dependencies = [
#    "flyte>=2.0.0b52",
#    "flyteplugins-openai>=2.0.0b7",
#    "openai-agents>=0.2.4",
#    "pydantic>=2.10.6",
# ]
# main = "main"
# params = ""
# ///

# {{/docs-fragment uv-script}}

# {{docs-fragment imports-task-env}}
from agents import Agent, Runner
from pydantic import BaseModel

import flyte
from flyteplugins.openai.agents import function_tool

env = flyte.TaskEnvironment(
    name="openai_agents_tools",
    resources=flyte.Resources(cpu=1, memory="250Mi"),
    image=flyte.Image.from_uv_script(__file__, name="openai_agents_image"),
    secrets=flyte.Secret("openai_api_key", as_env_var="OPENAI_API_KEY"),
)

# {{/docs-fragment imports-task-env}}

# {{docs-fragment tools}}
class Weather(BaseModel):
    city: str
    temperature_range: str
    conditions: str

@function_tool
@env.task
async def get_weather(city: str) -> Weather:
    """Get the weather for a given city."""
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

# {{/docs-fragment tools}}

# {{docs-fragment agent}}
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)

@env.task
async def main() -> str:
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
    return result.final_output

# {{/docs-fragment agent}}

# {{docs-fragment main}}
if __name__ == "__main__":
    flyte.init_from_config()
    run = flyte.run(main)
    print(run.url)
    run.wait()
# {{/docs-fragment main}}
```

*Source: https://github.com/unionai/unionai-examples/blob/main/v2/integrations/flyte-plugins/openai/openai/agents_tools.py*

In this code snippet, the `@function_tool` decorator is imported from `flyteplugins.openai.agents`, which is a drop-in replacement for the `@function_tool` decorator from `openai-agents` library.

## Define the agent

Then, we'll define the agent, which calls the tool:

```
"""OpenAI Agents with Flyte, basic tool example.

Usage:

Create secret:

```
flyte create secret openai_api_key
uv run agents_tools.py
```
"""
# {{docs-fragment uv-script}}

# /// script
# requires-python = "==3.13"
# dependencies = [
#    "flyte>=2.0.0b52",
#    "flyteplugins-openai>=2.0.0b7",
#    "openai-agents>=0.2.4",
#    "pydantic>=2.10.6",
# ]
# main = "main"
# params = ""
# ///

# {{/docs-fragment uv-script}}

# {{docs-fragment imports-task-env}}
from agents import Agent, Runner
from pydantic import BaseModel

import flyte
from flyteplugins.openai.agents import function_tool

env = flyte.TaskEnvironment(
    name="openai_agents_tools",
    resources=flyte.Resources(cpu=1, memory="250Mi"),
    image=flyte.Image.from_uv_script(__file__, name="openai_agents_image"),
    secrets=flyte.Secret("openai_api_key", as_env_var="OPENAI_API_KEY"),
)

# {{/docs-fragment imports-task-env}}

# {{docs-fragment tools}}
class Weather(BaseModel):
    city: str
    temperature_range: str
    conditions: str

@function_tool
@env.task
async def get_weather(city: str) -> Weather:
    """Get the weather for a given city."""
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

# {{/docs-fragment tools}}

# {{docs-fragment agent}}
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)

@env.task
async def main() -> str:
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
    return result.final_output

# {{/docs-fragment agent}}

# {{docs-fragment main}}
if __name__ == "__main__":
    flyte.init_from_config()
    run = flyte.run(main)
    print(run.url)
    run.wait()
# {{/docs-fragment main}}
```

*Source: https://github.com/unionai/unionai-examples/blob/main/v2/integrations/flyte-plugins/openai/openai/agents_tools.py*

## Run the agent

Finally, we'll run the agent. Create `config.yaml` file, which the `flyte.init_from_config()` function will use to connect to
the Flyte cluster:

```bash
flyte create config \
--output ~/.flyte/config.yaml \
--endpoint demo.hosted.unionai.cloud/ \
--project flytesnacks \
--domain development \
--builder remote
```

```
"""OpenAI Agents with Flyte, basic tool example.

Usage:

Create secret:

```
flyte create secret openai_api_key
uv run agents_tools.py
```
"""
# {{docs-fragment uv-script}}

# /// script
# requires-python = "==3.13"
# dependencies = [
#    "flyte>=2.0.0b52",
#    "flyteplugins-openai>=2.0.0b7",
#    "openai-agents>=0.2.4",
#    "pydantic>=2.10.6",
# ]
# main = "main"
# params = ""
# ///

# {{/docs-fragment uv-script}}

# {{docs-fragment imports-task-env}}
from agents import Agent, Runner
from pydantic import BaseModel

import flyte
from flyteplugins.openai.agents import function_tool

env = flyte.TaskEnvironment(
    name="openai_agents_tools",
    resources=flyte.Resources(cpu=1, memory="250Mi"),
    image=flyte.Image.from_uv_script(__file__, name="openai_agents_image"),
    secrets=flyte.Secret("openai_api_key", as_env_var="OPENAI_API_KEY"),
)

# {{/docs-fragment imports-task-env}}

# {{docs-fragment tools}}
class Weather(BaseModel):
    city: str
    temperature_range: str
    conditions: str

@function_tool
@env.task
async def get_weather(city: str) -> Weather:
    """Get the weather for a given city."""
    return Weather(city=city, temperature_range="14-20C", conditions="Sunny with wind.")

# {{/docs-fragment tools}}

# {{docs-fragment agent}}
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)

@env.task
async def main() -> str:
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
    return result.final_output

# {{/docs-fragment agent}}

# {{docs-fragment main}}
if __name__ == "__main__":
    flyte.init_from_config()
    run = flyte.run(main)
    print(run.url)
    run.wait()
# {{/docs-fragment main}}
```

*Source: https://github.com/unionai/unionai-examples/blob/main/v2/integrations/flyte-plugins/openai/openai/agents_tools.py*

## Conclusion

In this example, we've seen how to use the `openai-agents` library to create a simple agent that can use tools to perform tasks.

The full code is available [here](https://github.com/unionai/unionai-examples/tree/main/v2/integrations/flyte-plugins/openai/openai).

---
**Source**: https://github.com/unionai/unionai-docs/blob/main/content/integrations/openai/agent_tools.md
**HTML**: https://www.union.ai/docs/v2/union/integrations/openai/agent_tools/