How to Build Production-Grade Workflows with GraphBit Using Deterministic Tools, Validated Workflow Graphs, and Optional LLM Orchestration

!pip -q install graphbit rich pydantic numpy


import os
import time
import json
import random
from dataclasses import dataclass
from typing import Dict, Any, List, Optional
import numpy as np
from rich import print as rprint
from rich.panel import Panel
from rich.table import Table

from graphbit import init, shutdown, configure_runtime, get_system_info, health_check, version
from graphbit import Workflow, Node, Executor, LlmConfig
from graphbit import tool, ToolExecutor, ExecutorConfig
from graphbit import get_tool_registry, clear_tools


configure_runtime(worker_threads=4, max_blocking_threads=8, thread_stack_size_mb=2)
init(log_level="warn", enable_tracing=False, debug=False)


info = get_system_info()
health = health_check()


sys_table = Table(title="System Info / Health")
sys_table.add_column("Key", style="bold")
sys_table.add_column("Value")
for k in ["version", "python_binding_version", "cpu_count", "runtime_worker_threads", "runtime_initialized", "build_target", "build_profile"]:
   sys_table.add_row(k, str(info.get(k)))
sys_table.add_row("graphbit_version()", str(version()))
sys_table.add_row("overall_healthy", str(health.get("overall_healthy")))
rprint(sys_table)

@dataclass
class Ticket:
   ticket_id: str
   user_id: str
   text: str
   created_at: float


def make_tickets(n: int = 10) -> List[Ticket]:
   seeds = [
       "My card payment failed twice, what should I do?",
       "I want to cancel my subscription immediately.",
       "Your app crashes when I open the dashboard.",
       "Please update my email address on the account.",
       "Refund not received after 7 days.",
       "My delivery is delayed and tracking is stuck.",
       "I suspect fraudulent activity on my account.",
       "How can I change my billing cycle date?",
       "The website is very slow and times out.",
       "I forgot my password and cannot login.",
       "Chargeback process details please.",
       "Need invoice for last month’s payment."
   ]
   random.shuffle(seeds)
   out = []
   for i in range(n):
       out.append(
           Ticket(
               ticket_id=f"T-{1000+i}",
               user_id=f"U-{random.randint(100,999)}",
               text=seeds[i % len(seeds)],
               created_at=time.time() - random.randint(0, 7 * 24 * 3600),
           )
       )
   return out


tickets = make_tickets(10)
rprint(Panel.fit("n".join([f"- {t.ticket_id}: {t.text}" for t in tickets]), title="Sample Tickets"))

clear_tools()


@tool(_description="Classify a support ticket into a coarse category.")
def classify_ticket(text: str) -> Dict[str, Any]:
   t = text.lower()
   if "fraud" in t or "fraudulent" in t:
       return {"category": "fraud", "priority": "p0"}
   if "cancel" in t:
       return {"category": "cancellation", "priority": "p1"}
   if "refund" in t or "chargeback" in t:
       return {"category": "refunds", "priority": "p1"}
   if "password" in t or "login" in t:
       return {"category": "account_access", "priority": "p2"}
   if "crash" in t or "slow" in t or "timeout" in t:
       return {"category": "bug", "priority": "p2"}
   if "payment" in t or "billing" in t or "invoice" in t:
       return {"category": "billing", "priority": "p2"}
   if "delivery" in t or "tracking" in t:
       return {"category": "delivery", "priority": "p3"}
   return {"category": "general", "priority": "p3"}


@tool(_description="Route a ticket to a queue (returns queue id and SLA hours).")
def route_ticket(category: str, priority: str) -> Dict[str, Any]:
   queue_map = {
       "fraud": ("risk_ops", 2),
       "cancellation": ("retention", 8),
       "refunds": ("payments_ops", 12),
       "account_access": ("identity", 12),
       "bug": ("engineering_support", 24),
       "billing": ("billing_support", 24),
       "delivery": ("logistics_support", 48),
       "general": ("support_general", 48),
   }
   q, sla = queue_map.get(category, ("support_general", 48))
   if priority == "p0":
       sla = min(sla, 2)
   elif priority == "p1":
       sla = min(sla, 8)
   return {"queue": q, "sla_hours": sla}


@tool(_description="Generate a playbook response based on category + priority.")
def draft_response(category: str, priority: str, ticket_text: str) -> Dict[str, Any]:
   templates = {
       "fraud": "We’ve temporarily secured your account. Please confirm last 3 transactions and reset credentials.",
       "cancellation": "We can help cancel your subscription. Please confirm your plan and the effective date you want.",
       "refunds": "We’re checking the refund status. Please share the order/payment reference and date.",
       "account_access": "Let’s get you back in. Please use the password reset link; if blocked, we’ll verify identity.",
       "bug": "Thanks for reporting. Please share device/browser + a screenshot; we’ll attempt reproduction.",
       "billing": "We can help with billing. Please confirm the last 4 digits and the invoice period you need.",
       "delivery": "We’re checking shipment status. Please share your tracking ID and delivery address PIN/ZIP.",
       "general": "Thanks for reaching out."
   }
   base = templates.get(category, templates["general"])
   tone = "urgent" if priority == "p0" else ("fast" if priority == "p1" else "standard")
   return {
       "tone": tone,
       "message": f"{base}nnContext we received: '{ticket_text}'",
       "next_steps": ["request_missing_info", "log_case", "route_to_queue"]
   }


registry = get_tool_registry()
tools_list = registry.list_tools() if hasattr(registry, "list_tools") else []
rprint(Panel.fit(f"Registered tools: {tools_list}", title="Tool Registry"))

tool_exec_cfg = ExecutorConfig(
   max_execution_time_ms=10_000,
   max_tool_calls=50,
   continue_on_error=False,
   store_results=True,
   enable_logging=False
)
tool_executor = ToolExecutor(config=tool_exec_cfg) if "config" in ToolExecutor.__init__.__code__.co_varnames else ToolExecutor()


def offline_triage(ticket: Ticket) -> Dict[str, Any]:
   c = classify_ticket(ticket.text)
   rt = route_ticket(c["category"], c["priority"])
   dr = draft_response(c["category"], c["priority"], ticket.text)
   return {
       "ticket_id": ticket.ticket_id,
       "user_id": ticket.user_id,
       "category": c["category"],
       "priority": c["priority"],
       "queue": rt["queue"],
       "sla_hours": rt["sla_hours"],
       "draft": dr["message"],
       "tone": dr["tone"],
       "steps": [
           ("classify_ticket", c),
           ("route_ticket", rt),
           ("draft_response", dr),
       ]
   }


offline_results = [offline_triage


res_table = Table(title="Offline Pipeline Results")
res_table.add_column("Ticket", style="bold")
res_table.add_column("Category")
res_table.add_column("Priority")
res_table.add_column("Queue")
res_table.add_column("SLA (h)")
for r in offline_results:
   res_table.add_row(r["ticket_id"], r["category"], r["priority"], r["queue"], str(r["sla_hours"]))
rprint(res_table)


prio_counts: Dict[str, int] = {}
sla_vals: List[int] = []
for r in offline_results:
   prio_counts[r["priority"]] = prio_counts.get(r["priority"], 0) + 1
   sla_vals.append(int(r["sla_hours"]))


metrics = {
   "offline_mode": True,
   "tickets": len(offline_results),
   "priority_distribution": prio_counts,
   "sla_mean": float(np.mean(sla_vals)) if sla_vals else None,
   "sla_p95": float(np.percentile(sla_vals, 95)) if sla_vals else None,
}


rprint(Panel.fit(json.dumps(metrics, indent=2), title="Offline Metrics"))

SYSTEM_POLICY = "You are a reliable support ops agent. Return STRICT JSON only."


workflow = Workflow("Ticket Triage Workflow (GraphBit)")


summarizer = Node.agent(
   name="Summarizer",
   agent_id="summarizer",
   system_prompt=SYSTEM_POLICY,
   prompt="Summarize this ticket in 1-2 lines. Return JSON: {"summary":"..."}nTicket: {input}",
   temperature=0.2,
   max_tokens=200
)


router_agent = Node.agent(
   name="RouterAgent",
   agent_id="router",
   system_prompt=SYSTEM_POLICY,
   prompt=(
       "You MUST use tools.n"
       "Call classify_ticket(text), route_ticket(category, priority), draft_response(category, priority, ticket_text).n"
       "Return JSON with fields: category, priority, queue, sla_hours, message.n"
       "Ticket: {input}"
   ),
   tools=[classify_ticket, route_ticket, draft_response],
   temperature=0.1,
   max_tokens=700
)


formatter = Node.agent(
   name="FinalFormatter",
   agent_id="final_formatter",
   system_prompt=SYSTEM_POLICY,
   prompt=(
       "Validate the JSON and output STRICT JSON only:n"
       "{"ticket_id":"...","category":"...","priority":"...","queue":"...","sla_hours":0,"customer_message":"..."}n"
       "Input: {input}"
   ),
   temperature=0.0,
   max_tokens=500
)


sid = workflow.add_node(summarizer)
rid = workflow.add_node(router_agent)
fid = workflow.add_node(formatter)


workflow.connect(sid, rid)
workflow.connect(rid, fid)
workflow.validate()


rprint(Panel.fit("Workflow validated: Summarizer -> RouterAgent -> FinalFormatter", title="Workflow Graph"))

def pick_llm_config() -> Optional[Any]:
   if os.getenv("OPENAI_API_KEY"):
       return LlmConfig.openai(os.getenv("OPENAI_API_KEY"), "gpt-4o-mini")
   if os.getenv("ANTHROPIC_API_KEY"):
       return LlmConfig.anthropic(os.getenv("ANTHROPIC_API_KEY"), "claude-sonnet-4-20250514")
   if os.getenv("DEEPSEEK_API_KEY"):
       return LlmConfig.deepseek(os.getenv("DEEPSEEK_API_KEY"), "deepseek-chat")
   if os.getenv("MISTRALAI_API_KEY"):
       return LlmConfig.mistralai(os.getenv("MISTRALAI_API_KEY"), "mistral-large-latest")
   return None


def run_agent_flow_once(ticket_text: str) -> Dict[str, Any]:
   llm_cfg = pick_llm_config()
   if llm_cfg is None:
       return {
           "mode": "offline",
           "note": "Set OPENAI_API_KEY / ANTHROPIC_API_KEY / DEEPSEEK_API_KEY / MISTRALAI_API_KEY to enable execution.",
           "input": ticket_text
       }
   executor = Executor(llm_cfg, lightweight_mode=True, timeout_seconds=90, debug=False) if "lightweight_mode" in Executor.__init__.__code__.co_varnames else Executor(llm_cfg)
   if hasattr(executor, "configure"):
       executor.configure(timeout_seconds=90, max_retries=2, enable_metrics=True, debug=False)
   wf = Workflow("Single Ticket Run")
   s = Node.agent(
       name="Summarizer",
       agent_id="summarizer",
       system_prompt=SYSTEM_POLICY,
       prompt=f"Summarize this ticket in 1-2 lines. Return JSON: {{"summary":"..."}}nTicket: {ticket_text}",
       temperature=0.2,
       max_tokens=200
   )
   r = Node.agent(
       name="RouterAgent",
       agent_id="router",
       system_prompt=SYSTEM_POLICY,
       prompt=(
           "You MUST use tools.n"
           "Call classify_ticket(text), route_ticket(category, priority), draft_response(category, priority, ticket_text).n"
           "Return JSON with fields: category, priority, queue, sla_hours, message.n"
           f"Ticket: {ticket_text}"
       ),
       tools=[classify_ticket, route_ticket, draft_response],
       temperature=0.1,
       max_tokens=700
   )
   f = Node.agent(
       name="FinalFormatter",
       agent_id="final_formatter",
       system_prompt=SYSTEM_POLICY,
       prompt=(
           "Validate the JSON and output STRICT JSON only:n"
           "{"ticket_id":"...","category":"...","priority":"...","queue":"...","sla_hours":0,"customer_message":"..."}n"
           "Input: {input}"
       ),
       temperature=0.0,
       max_tokens=500
   )
   sid = wf.add_node(s)
   rid = wf.add_node(r)
   fid = wf.add_node(f)
   wf.connect(sid, rid)
   wf.connect(rid, fid)
   wf.validate()
   t0 = time.time()
   result = executor.execute(wf)
   dt_ms = int((time.time() - t0) * 1000)
   out = {"mode": "online", "execution_time_ms": dt_ms, "success": bool(result.is_success()) if hasattr(result, "is_success") else None}
   if hasattr(result, "get_all_variables"):
       out["variables"] = result.get_all_variables()
   else:
       out["raw"] = str(result)[:3000]
   return out


sample = tickets[0]
agent_run = run_agent_flow_once(sample.text)
rprint(Panel.fit(json.dumps(agent_run, indent=2)[:3000], title="Agent Workflow Run"))


rprint(Panel.fit("Done", title="Complete"))