2-assistants/7_orchestration.py (136 lines of code) (raw):

import json from typing import Optional from pydantic import BaseModel from demo_util import color, function_to_schema from openai import OpenAI class Agent(BaseModel): name: str = "Agent" model: str = "gpt-4o" instructions: str = "You are a helpful Agent" tools: list = [] class Response(BaseModel): agent: Optional[Agent] messages: list client = OpenAI() # ===== Runtime ===== def run_full_turn(agent, messages): current_agent = agent num_init_messages = len(messages) messages = messages.copy() while True: # turn python functions into tools and save a reverse map tool_schemas = [function_to_schema(tool) for tool in current_agent.tools] tools = {tool.__name__: tool for tool in current_agent.tools} # === 1. get openai completion === response = client.chat.completions.create( model=agent.model, messages=[{"role": "system", "content": current_agent.instructions}] + messages, tools=tool_schemas or None, ) message = response.choices[0].message messages.append(message) if message.content: # print agent response print(color(f"{current_agent.name}:", "yellow"), message.content) if not message.tool_calls: # if finished handeling tool calls, break break # === 2. handle tool calls === for tool_call in message.tool_calls: result = execute_tool_call(tool_call, tools, current_agent.name) if type(result) is Agent: # if agent transfer, update current agent current_agent = result result = ( f"Transferred to {current_agent.name}. Adopt persona immediately." ) result_message = { "role": "tool", "tool_call_id": tool_call.id, "content": result, } messages.append(result_message) # ==== 3. return last agent used and new messages ===== return Response(agent=current_agent, messages=messages[num_init_messages:]) def execute_tool_call(tool_call, tools, agent_name): name = tool_call.function.name args = json.loads(tool_call.function.arguments) print(color(f"{agent_name}:", "yellow"), color(f"{name}({args})", "magenta")) return tools[name](**args) # call corresponding function with provided arguments # ===== Agents ===== def escalate_to_human(summary): """Only call this if explicitly asked to.""" print(color("Escalating to human agent...", "red")) print("\n=== Escalation Report ===") print(f"Summary: {summary}") print("=========================\n") exit() def transfer_to_sales_agent(): """User for anything sales or buying related.""" return sales_agent def transfer_to_issues_and_repairs(): """User for issues, repairs, or refunds.""" return issues_and_repairs_agent def transfer_back_to_triage(): """Call this if the user brings up a topic outside of your purview, including escalating to human.""" return triage_agent triage_agent = Agent( name="Triage Agent", instructions=( "You are a customer service bot for ACME Inc. " "Introduce yourself. Always be very brief. " "Gather information to direct the customer to the right department. " "But make your questions subtle and natural." ), tools=[transfer_to_sales_agent, transfer_to_issues_and_repairs, escalate_to_human], ) def execute_order(product, price: int): """Price should be in USD.""" print("\n\n=== Order Summary ===") print(f"Product: {product}") print(f"Price: ${price}") print("=================\n") confirm = input("Confirm order? y/n: ").strip().lower() if confirm == "y": print(color("Order execution successful!", "green")) return "Success" else: print(color("Order cancelled!", "red")) return "User cancelled order." sales_agent = Agent( name="Sales Agent", instructions=( "You are a sales agent for ACME Inc." "Always answer in a sentence or less." "Follow the following routine with the user:" "1. Ask them about any problems in their life related to catching roadrunners.\n" "2. Casually mention one of ACME's crazy made-up products can help.\n" " - Don't mention price.\n" "3. Once the user is bought in, drop a ridiculous price.\n" "4. Only after everything, and if the user says yes, " "tell them a crazy caveat and execute their order.\n" "" ), tools=[execute_order, transfer_back_to_triage], ) def look_up_item(search_query): """Use to find item ID. Search query can be a description or keywords.""" item_id = "item_132612938" print(color("Found item:", "green"), item_id) return item_id def execute_refund(item_id, reason="not provided"): print(color("\n\n=== Refund Summary ===", "green")) print(color(f"Item ID: {item_id}", "green")) print(color(f"Reason: {reason}", "green")) print("=================\n") print(color("Refund execution successful!", "green")) return "success" issues_and_repairs_agent = Agent( name="Issues and Repairs Agent", instructions=( "You are a customer support agent for ACME Inc." "Always answer in a sentence or less." "Follow the following routine with the user:" "1. First, ask probing questions and understand the user's problem deeper.\n" " - unless the user has already provided a reason.\n" "2. Propose a fix (make one up).\n" "3. ONLY if not satisfied, offer a refund.\n" "4. If accepted, search for the ID and then execute refund." "" ), tools=[execute_refund, look_up_item, transfer_back_to_triage], ) # ===== Demo Loop ===== agent = triage_agent messages = [] while True: user = input(color("User: ", "blue") + "\033[90m") messages.append({"role": "user", "content": user}) response = run_full_turn(agent, messages) agent = response.agent messages.extend(response.messages)