!uv pip install openai-agents==0.4.2 gradio==5.49.1Resolved 190 packages in 1ms Installed 10 packages in 33ms12.0 + colorama==0.4.6 + cryptography==46.0.3 + griffe==1.15.0 + httpx-sse==0.4.3 + mcp==1.25.0 + openai-agents==0.4.2 + pydantic-settings==2.12.0 + pyjwt==2.10.1 + sse-starlette==3.1.2 + types-requests==2.32.4.20260107
import sys
import os
from dotenv import load_dotenv
if 'google.colab' in sys.modules:
from google.colab import userdata # type:ignore
OPENAI_API_KEY = userdata.get('OPENAI_API_KEY')
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
else:
load_dotenv()from agents import Agent, Runner, FileSearchToolfrom agents import function_tool
@function_tool
def get_bytes_cafe_menu(date: str) -> any:
return {
f"{date}": {
"daily byte": {
"name": "Steak Quesadilla",
"price": 12,
"description": "Flank steak, mixed cheese in a flour tortilla served with air fried potatoes, sour cream and salsa",
},
"vegetarian": {
"name": "Impossible Quesadilla",
"price": 12,
"description": "Impossible plant based product, mixed cheese in a flour tortilla served with air fried potatoes, sour cream and salsa",
},
"international": {
"name": "Chicken Curry",
"price": 12,
"description": "Chicken thighs, onion, carrot, potato, curry sauce served over rice",
},
}
}cafe_agent = Agent(
name="Cafe Agent",
instructions="You help students locate and provide information about the Bytes Cafe.",
tools=[
get_bytes_cafe_menu,
],
)VECTOR_STORE_ID = "vs_6896d8c959008191981d645850b42313"building_agent = Agent(
name="Building Agent",
instructions="You help students locate and provide information about buildings and rooms on campus. Be descriptive when giving locations.",
tools=[
FileSearchTool(
max_num_results=3,
vector_store_ids=[VECTOR_STORE_ID],
include_search_results=True,
)
],
)course_agent = Agent(
name="Course Agent",
instructions="You help students find out information about courses held at DigiPen.",
tools=[
FileSearchTool(
max_num_results=5,
vector_store_ids=[VECTOR_STORE_ID],
include_search_results=True,
)
],
)handbook_agent = Agent(
name="Handbook Agent",
instructions="You help students navigate the school handbook, providing information about campus policies and student conduct.",
tools=[
FileSearchTool(
max_num_results=5,
vector_store_ids=[VECTOR_STORE_ID],
include_search_results=True,
)
],
)agent = Agent(
name="DigiPen Campus Agent",
instructions="You are a helpful campus agent that can plan and execute tasks for students at DigiPen. Please be concise and accurate in handing off tasks to other agents as needed.",
handoffs=[building_agent, course_agent, handbook_agent, cafe_agent],
)from gradio import ChatMessage
async def chat_with_agent(user_msg: str, history: list):
messages = [{"role": msg["role"], "content": msg["content"]} for msg in history]
messages.append({"role": "user", "content": user_msg})
responses = []
reply_created = False
active_agent = None
result = Runner.run_streamed(agent, messages)
async for event in result.stream_events():
if event.type == "raw_response_event":
if event.data.type == "response.output_text.delta":
if not reply_created:
responses.append(ChatMessage(role="assistant", content=""))
reply_created = True
responses[-1].content += event.data.delta
elif event.type == "agent_updated_stream_event":
active_agent = event.new_agent.name
responses.append(
ChatMessage(
content=event.new_agent.name,
metadata={"title": "Agent Now Running", "id": active_agent},
)
)
elif event.type == "run_item_stream_event":
if event.item.type == "tool_call_item":
if event.item.raw_item.type == "file_search_call":
responses.append(
ChatMessage(
content=f"Query used: {event.item.raw_item.queries}",
metadata={
"title": "File Search Completed",
"parent_id": active_agent,
},
)
)
else:
tool_name = getattr(event.item.raw_item, "name", "unknown_tool")
tool_args = getattr(event.item.raw_item, "arguments", {})
responses.append(
ChatMessage(
content=f"Calling tool {tool_name} with arguments {tool_args}",
metadata={"title": "Tool Call", "parent_id": active_agent},
)
)
if event.item.type == "tool_call_output_item":
responses.append(
ChatMessage(
content=f"Tool output: '{event.item.raw_item['output']}'",
metadata={"title": "Tool Output", "parent_id": active_agent},
)
)
if event.item.type == "handoff_call_item":
responses.append(
ChatMessage(
content=f"Name: {event.item.raw_item.name}",
metadata={
"title": "Handing Off Request",
"parent_id": active_agent,
},
)
)
yield responsesimport gradio as gr
demo = gr.ChatInterface(
chat_with_agent,
title="DigiPen Campus Agent",
theme=gr.themes.Soft(
primary_hue="red", secondary_hue="slate", font=[gr.themes.GoogleFont("Inter")]
),
examples=[
"I'm trying to find the WANIC classrooms. Can you help?",
"What's the policy for eating in auditoriums?",
"What's today's vegetarian dish at the Bytes Cafe?",
"What are the prerequisites for FLM201?"
],
submit_btn=True,
flagging_mode="manual",
flagging_options=["Like", "Spam", "Inappropriate", "Other"],
type="messages",
save_history=False,
)
demo.launch(share=False, debug=True)* Running on local URL: http://127.0.0.1:7863
* To create a public link, set `share=True` in `launch()`.Keyboard interruption in main thread... closing server.