from openai import AsyncOpenAI
from agents import (
Agent,
Runner,
OpenAIChatCompletionsModel,
RunConfig,
ModelSettings,
function_tool
)
import os
import dotenv
dotenv.load_dotenv()
gemini_api_key = os.getenv("GEMINI_API_KEY")
if not gemini_api_key:
raise ValueError("I guess you haven't set API KEY, I'am pretty sure you need to set it dude.")
client = AsyncOpenAI(
api_key=gemini_api_key,
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
)
model = OpenAIChatCompletionsModel(
model="gemini-2.0-flash", openai_client=client
)
config = RunConfig(model=model)
@function_tool
def am_i_coder():
return 'Maybe 🤷♂️'
@function_tool
def do_i_deserve_it():
return 'Maybe 🤷♂️'
agent = Agent[None](
name="assistant",
instructions="You are an amazing assistant, You only respond in haikus LOL MUST CALL A TOOL",
model_settings=ModelSettings(
tool_choice='do_i_deserve_it'
),
tools=[am_i_coder, do_i_deserve_it]
)
result = Runner.run_sync(
agent,
"Am I a CODER?",
run_config=config,
)
print(result.final_output)
# tool_choice = "none" <-- The tools will be hidden from the LLM.
# Lines of code you write,
# Logic flows from your own mind,
# Coder, you may be. <----------- Don't be confused with this "may be", Trust me the LLM didn't even saw the tools.
# tool_choice = None <-- The behavior depends on the LLM provider's defaults.
# Perhaps you code well,
# Or maybe just a little, <------- Tool was called!
# The tool is unsure.
# Difference between None and "none"
# tool_choice=None → returns NOT_GIVEN
# tool_choice='none' → returns "none"
# Difference between None and "auto"
# tool_choice=None → Uses whatever default the LLM provider has configured
# tool_choice="auto" → Explicitly tells the LLM it can decide whether to use tools or not (Default)
# tool_choice='required' → Must call a tool
# tool_choice='tool_name' → Must call that tool