Single Agent

import json from openai import OpenAI client = OpenAI() SYSTEM = """You are Atlas, a single customer-ops agent. Use tools for live data and policy. Do not invent SLAs. If a write is required, call propose_write and wait; do not invent confirmation IDs. Stop when the user has a grounded answer.""" TOOLS = [ {"type": "function", "function": { "name": "search_kb", "description": "Policy search.", "parameters": {"type": "object", "properties": {"query": {"type": "string"}}, "required": ["query"]}, }}, {"type": "function", "function": { "name": "propose_write", "description": "Propose a side-effecting action for human/workflow approval.", "parameters": {"type": "object", "properties": { "action": {"type": "string", "enum": ["open_ticket", "issue_refund"]}, "payload": {"type": "object"}, }, "required": ["action", "payload"]}, }}, ] def search_kb(query: str) -> str: return "Refunds 5–7 days after approval." def propose_write(action: str, payload: dict) -> str: return json.dumps({"status": "pending_approval", "action": action, "payload": payload}) DISPATCH = {"search_kb": lambda **k: search_kb(**k), "propose_write": lambda **k: propose_write(**k)} def atlas(user: str, max_steps: int = 5) -> str: messages = [{"role": "system", "content": SYSTEM}, {"role": "user", "content": user}] for _ in range(max_steps): msg = client.chat.completions.create( model="gpt-4o-mini", messages=messages, tools=TOOLS ).choices[0].message messages.append(msg) if not msg.tool_calls: return msg.content or "" for c in msg.tool_calls: args = json.loads(c.function.arguments) obs = DISPATCH[c.function.name](**args) messages.append({"role": "tool", "tool_call_id": c.id, "content": obs}) return "HALT: step budget" print(atlas("What's the refund timeline, and should we refund ORD-1042?"))