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Agents sdk examples (#979)
* notebook 1 * added new agent * laast notebook
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‎examples/openai_agents_sdk/customer_service_agent.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Install dependencies. \n",
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"!pip install -U agentops openai-agents"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Set the API keys for your AgentOps and OpenAI accounts.\n",
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"import os\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = ''\n",
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"os.environ[\"AGENTOPS_API_KEY\"] = ''\n",
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"\n",
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"if os.environ[\"OPENAI_API_KEY\"] == '':\n",
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" raise ValueError(\"OPENAI_API_KEY is not set. You can get one at https://platform.openai.com/api-keys\")\n",
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"if os.environ[\"AGENTOPS_API_KEY\"] == '':\n",
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" raise ValueError(\"AGENTOPS_API_KEY is not set. You can get one at https://app.agentops.ai/\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from __future__ import annotations as _annotations\n",
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"\n",
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"import random\n",
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"import uuid\n",
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"from pydantic import BaseModel\n",
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"import agentops\n",
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"\n",
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"# API key is automatically read from the environment variable\n",
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"agentops.init(tags=[\"customer-service-agent\", \"agentops-example\"])\n",
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"\n",
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"from agents import (\n",
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" Agent,\n",
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" HandoffOutputItem,\n",
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" ItemHelpers,\n",
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" MessageOutputItem,\n",
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" RunContextWrapper,\n",
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" Runner,\n",
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" ToolCallItem,\n",
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" ToolCallOutputItem,\n",
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" TResponseInputItem,\n",
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" function_tool,\n",
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" handoff,\n",
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" trace,\n",
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")\n",
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"from agents.extensions.handoff_prompt import RECOMMENDED_PROMPT_PREFIX\n",
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"\n",
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"### CONTEXT\n",
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"\n",
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"\n",
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"class AirlineAgentContext(BaseModel):\n",
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" passenger_name: str | None = None\n",
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" confirmation_number: str | None = None\n",
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" seat_number: str | None = None\n",
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" flight_number: str | None = None\n",
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"\n",
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"\n",
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"### TOOLS\n",
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"\n",
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"\n",
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"@function_tool(\n",
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" name_override=\"faq_lookup_tool\", description_override=\"Lookup frequently asked questions.\"\n",
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")\n",
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"async def faq_lookup_tool(question: str) -> str:\n",
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" if \"bag\" in question or \"baggage\" in question:\n",
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" return (\n",
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" \"You are allowed to bring one bag on the plane. \"\n",
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" \"It must be under 50 pounds and 22 inches x 14 inches x 9 inches.\"\n",
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" )\n",
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" elif \"seats\" in question or \"plane\" in question:\n",
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" return (\n",
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" \"There are 120 seats on the plane. \"\n",
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" \"There are 22 business class seats and 98 economy seats. \"\n",
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" \"Exit rows are rows 4 and 16. \"\n",
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" \"Rows 5-8 are Economy Plus, with extra legroom. \"\n",
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" )\n",
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" elif \"wifi\" in question:\n",
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" return \"We have free wifi on the plane, join Airline-Wifi\"\n",
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" return \"I'm sorry, I don't know the answer to that question.\"\n",
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"\n",
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"\n",
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"@function_tool\n",
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"async def update_seat(\n",
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" context: RunContextWrapper[AirlineAgentContext], confirmation_number: str, new_seat: str\n",
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") -> str:\n",
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" \"\"\"\n",
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" Update the seat for a given confirmation number.\n",
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"\n",
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" Args:\n",
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" confirmation_number: The confirmation number for the flight.\n",
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" new_seat: The new seat to update to.\n",
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" \"\"\"\n",
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" # Update the context based on the customer's input\n",
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" context.context.confirmation_number = confirmation_number\n",
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" context.context.seat_number = new_seat\n",
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" # Ensure that the flight number has been set by the incoming handoff\n",
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" assert context.context.flight_number is not None, \"Flight number is required\"\n",
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" return f\"Updated seat to {new_seat} for confirmation number {confirmation_number}\"\n",
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"\n",
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"\n",
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"### HOOKS\n",
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"\n",
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"\n",
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"async def on_seat_booking_handoff(context: RunContextWrapper[AirlineAgentContext]) -> None:\n",
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" flight_number = f\"FLT-{random.randint(100, 999)}\"\n",
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" context.context.flight_number = flight_number\n",
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"\n",
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"\n",
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"### AGENTS\n",
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"\n",
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"faq_agent = Agent[AirlineAgentContext](\n",
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" name=\"FAQ Agent\",\n",
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" handoff_description=\"A helpful agent that can answer questions about the airline.\",\n",
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" instructions=f\"\"\"{RECOMMENDED_PROMPT_PREFIX}\n",
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" You are an FAQ agent. If you are speaking to a customer, you probably were transferred to from the triage agent.\n",
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" Use the following routine to support the customer.\n",
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" # Routine\n",
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" 1. Identify the last question asked by the customer.\n",
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" 2. Use the faq lookup tool to answer the question. Do not rely on your own knowledge.\n",
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" 3. If you cannot answer the question, transfer back to the triage agent.\"\"\",\n",
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" tools=[faq_lookup_tool],\n",
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")\n",
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"\n",
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"seat_booking_agent = Agent[AirlineAgentContext](\n",
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" name=\"Seat Booking Agent\",\n",
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" handoff_description=\"A helpful agent that can update a seat on a flight.\",\n",
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" instructions=f\"\"\"{RECOMMENDED_PROMPT_PREFIX}\n",
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" You are a seat booking agent. If you are speaking to a customer, you probably were transferred to from the triage agent.\n",
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" Use the following routine to support the customer.\n",
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" # Routine\n",
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" 1. Ask for their confirmation number.\n",
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" 2. Ask the customer what their desired seat number is.\n",
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" 3. Use the update seat tool to update the seat on the flight.\n",
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" If the customer asks a question that is not related to the routine, transfer back to the triage agent. \"\"\",\n",
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" tools=[update_seat],\n",
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")\n",
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"\n",
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"triage_agent = Agent[AirlineAgentContext](\n",
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" name=\"Triage Agent\",\n",
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" handoff_description=\"A triage agent that can delegate a customer's request to the appropriate agent.\",\n",
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" instructions=(\n",
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" f\"{RECOMMENDED_PROMPT_PREFIX} \"\n",
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" \"You are a helpful triaging agent. You can use your tools to delegate questions to other appropriate agents.\"\n",
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" ),\n",
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" handoffs=[\n",
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" faq_agent,\n",
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" handoff(agent=seat_booking_agent, on_handoff=on_seat_booking_handoff),\n",
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" ],\n",
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")\n",
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"\n",
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"faq_agent.handoffs.append(triage_agent)\n",
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"seat_booking_agent.handoffs.append(triage_agent)\n",
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"\n",
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"\n",
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"### RUN\n",
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"\n",
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"\n",
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"async def main():\n",
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" current_agent: Agent[AirlineAgentContext] = triage_agent\n",
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" input_items: list[TResponseInputItem] = []\n",
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" context = AirlineAgentContext()\n",
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"\n",
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" # Normally, each input from the user would be an API request to your app, and you can wrap the request in a trace()\n",
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" # Here, we'll just use a random UUID for the conversation ID\n",
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" conversation_id = uuid.uuid4().hex[:16]\n",
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"\n",
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" while True:\n",
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" user_input = input(\"Enter your message: \")\n",
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" with trace(\"Customer service\", group_id=conversation_id):\n",
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" input_items.append({\"content\": user_input, \"role\": \"user\"})\n",
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" result = await Runner.run(current_agent, input_items, context=context)\n",
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"\n",
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" for new_item in result.new_items:\n",
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" agent_name = new_item.agent.name\n",
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" if isinstance(new_item, MessageOutputItem):\n",
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" print(f\"{agent_name}: {ItemHelpers.text_message_output(new_item)}\")\n",
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" elif isinstance(new_item, HandoffOutputItem):\n",
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" print(\n",
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" f\"Handed off from {new_item.source_agent.name} to {new_item.target_agent.name}\"\n",
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" )\n",
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" elif isinstance(new_item, ToolCallItem):\n",
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" print(f\"{agent_name}: Calling a tool\")\n",
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" elif isinstance(new_item, ToolCallOutputItem):\n",
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" print(f\"{agent_name}: Tool call output: {new_item.output}\")\n",
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" else:\n",
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" print(f\"{agent_name}: Skipping item: {new_item.__class__.__name__}\")\n",
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" input_items = result.to_input_list()\n",
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" current_agent = result.last_agent\n",
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"\n",
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"\n",
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"await main()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can check the trace in the AgentOps UI: https://app.agentops.ai/traces"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎examples/openai_agents_sdk/web_search_agent.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Install dependencies. \n",
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"!pip install -U agentops openai-agents"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Set the API keys for your AgentOps and OpenAI accounts.\n",
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"import os\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = ''\n",
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"os.environ[\"AGENTOPS_API_KEY\"] = ''\n",
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"\n",
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"if os.environ[\"OPENAI_API_KEY\"] == '':\n",
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" raise ValueError(\"OPENAI_API_KEY is not set. You can get one at https://platform.openai.com/api-keys\")\n",
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"if os.environ[\"AGENTOPS_API_KEY\"] == '':\n",
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" raise ValueError(\"AGENTOPS_API_KEY is not set. You can get one at https://app.agentops.ai/\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from agents import Agent, Runner, WebSearchTool, trace\n",
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"import agentops\n",
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"\n",
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"# AgentOps automatically reads the API key from the environment variable\n",
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"agentops.init(tags=[\"web-search-agent\", \"agentops-example\"])\n",
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"\n",
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"async def main():\n",
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" agent = Agent(\n",
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" name=\"Web searcher\",\n",
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" instructions=\"You are a helpful agent.\",\n",
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" tools=[WebSearchTool(user_location={\"type\": \"approximate\", \"city\": \"New York\"})],\n",
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" )\n",
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"\n",
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" with trace(\"Web search example\"):\n",
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" result = await Runner.run(\n",
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" agent,\n",
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" \"search the web for 'local sports news' and give me 1 interesting update in a sentence.\",\n",
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" )\n",
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" print(result.final_output)\n",
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" # The New York Giants are reportedly pursuing quarterback Aaron Rodgers after his ...\n",
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"\n",
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"await main()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can check the trace in the AgentOps UI: https://app.agentops.ai/traces"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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