feat: Day 13 - root README, example agent scripts, and demo seed script
This commit is contained in:
Vectry
211
examples/customer_support_agent.py
Normal file
211
examples/customer_support_agent.py
Normal file
@@ -0,0 +1,211 @@
|
||||
"""
|
||||
AgentLens Customer Support Example — Realistic support ticket workflow.
|
||||
|
||||
Demonstrates:
|
||||
- Ticket classification with ROUTING decisions
|
||||
- Specialist routing with TOOL_SELECTION
|
||||
- Escalation decisions with ESCALATION type
|
||||
- Error handling — traces capture exceptions automatically
|
||||
- Multiple real-world decision patterns
|
||||
|
||||
Usage:
|
||||
pip install vectry-agentlens
|
||||
python customer_support_agent.py
|
||||
"""
|
||||
|
||||
import agentlens
|
||||
import time
|
||||
import random
|
||||
|
||||
# Initialize
|
||||
agentlens.init(
|
||||
api_key="your-api-key-here",
|
||||
endpoint="http://localhost:4200",
|
||||
)
|
||||
|
||||
# Simulated ticket data
|
||||
TICKETS = [
|
||||
{
|
||||
"id": "TKT-4021",
|
||||
"subject": "Cannot access billing portal after password reset",
|
||||
"priority": "high",
|
||||
"customer_tier": "enterprise",
|
||||
"body": "After resetting my password, I get a 403 error on the billing page. "
|
||||
"I need to update our payment method before end of month.",
|
||||
},
|
||||
{
|
||||
"id": "TKT-4022",
|
||||
"subject": "Feature request: dark mode for dashboard",
|
||||
"priority": "low",
|
||||
"customer_tier": "free",
|
||||
"body": "Would love to have a dark mode option. My eyes hurt during late-night sessions.",
|
||||
},
|
||||
{
|
||||
"id": "TKT-4023",
|
||||
"subject": "API returning 500 errors intermittently",
|
||||
"priority": "critical",
|
||||
"customer_tier": "enterprise",
|
||||
"body": "Our production integration is failing ~20% of requests with 500 errors. "
|
||||
"Started about 2 hours ago. This is blocking our release.",
|
||||
},
|
||||
]
|
||||
|
||||
|
||||
def simulate_llm(prompt: str, delay: float = 0.15) -> str:
|
||||
"""Fake LLM — replace with real calls."""
|
||||
time.sleep(delay)
|
||||
return f"[Response to: {prompt[:60]}]"
|
||||
|
||||
|
||||
def process_ticket(ticket: dict) -> None:
|
||||
"""Process a single support ticket through the agent pipeline."""
|
||||
|
||||
with agentlens.trace(
|
||||
"customer-support-bot",
|
||||
tags=["support", ticket["priority"], ticket["customer_tier"]],
|
||||
):
|
||||
# Step 1: Classify the ticket
|
||||
agentlens.log_decision(
|
||||
type="ROUTING",
|
||||
chosen={
|
||||
"name": "classify_ticket",
|
||||
"confidence": 0.91,
|
||||
"params": {
|
||||
"ticket_id": ticket["id"],
|
||||
"predicted_category": (
|
||||
"billing"
|
||||
if "billing" in ticket["subject"].lower()
|
||||
else "bug"
|
||||
if "error" in ticket["body"].lower() or "500" in ticket["body"]
|
||||
else "feature_request"
|
||||
),
|
||||
},
|
||||
},
|
||||
alternatives=[
|
||||
{
|
||||
"name": "ask_customer_for_clarification",
|
||||
"confidence": 0.2,
|
||||
"reason_rejected": "Ticket subject and body are clear enough",
|
||||
},
|
||||
],
|
||||
reasoning=f"Ticket '{ticket['subject']}' clearly maps to a known category.",
|
||||
)
|
||||
|
||||
classification = simulate_llm(f"Classify: {ticket['subject']}")
|
||||
|
||||
# Step 2: Route to specialist
|
||||
is_critical = ticket["priority"] in ("critical", "high")
|
||||
is_enterprise = ticket["customer_tier"] == "enterprise"
|
||||
|
||||
if is_critical and is_enterprise:
|
||||
specialist = "senior_engineer"
|
||||
elif is_critical:
|
||||
specialist = "engineer"
|
||||
elif "billing" in ticket["subject"].lower():
|
||||
specialist = "billing_team"
|
||||
else:
|
||||
specialist = "general_support"
|
||||
|
||||
agentlens.log_decision(
|
||||
type="ROUTING",
|
||||
chosen={
|
||||
"name": specialist,
|
||||
"confidence": 0.87,
|
||||
"params": {
|
||||
"ticket_id": ticket["id"],
|
||||
"priority": ticket["priority"],
|
||||
"sla_minutes": 30 if is_enterprise else 240,
|
||||
},
|
||||
},
|
||||
alternatives=[
|
||||
{
|
||||
"name": "general_support",
|
||||
"confidence": 0.4,
|
||||
"reason_rejected": "Ticket requires specialized handling"
|
||||
if specialist != "general_support"
|
||||
else "This is general support already",
|
||||
},
|
||||
],
|
||||
reasoning=f"Priority={ticket['priority']}, Tier={ticket['customer_tier']} -> route to {specialist}.",
|
||||
)
|
||||
|
||||
# Step 3: Specialist handles ticket (nested trace)
|
||||
with agentlens.trace(f"specialist-{specialist}", tags=[specialist]):
|
||||
# Tool selection for the specialist
|
||||
agentlens.log_decision(
|
||||
type="TOOL_SELECTION",
|
||||
chosen={
|
||||
"name": "search_knowledge_base",
|
||||
"confidence": 0.82,
|
||||
"params": {"query": ticket["subject"], "limit": 5},
|
||||
},
|
||||
alternatives=[
|
||||
{
|
||||
"name": "search_past_tickets",
|
||||
"confidence": 0.7,
|
||||
"reason_rejected": "KB is more authoritative for known issues",
|
||||
},
|
||||
{
|
||||
"name": "check_status_page",
|
||||
"confidence": 0.6,
|
||||
"reason_rejected": "Already checked — no ongoing incidents posted",
|
||||
},
|
||||
],
|
||||
reasoning="Knowledge base has resolution guides for common issues.",
|
||||
)
|
||||
|
||||
kb_result = simulate_llm(f"Search KB for: {ticket['subject']}")
|
||||
|
||||
# Step 4: Escalation decision for critical tickets
|
||||
if ticket["priority"] == "critical":
|
||||
agentlens.log_decision(
|
||||
type="ESCALATION",
|
||||
chosen={
|
||||
"name": "escalate_to_engineering",
|
||||
"confidence": 0.94,
|
||||
"params": {
|
||||
"severity": "P1",
|
||||
"team": "platform-reliability",
|
||||
"ticket_id": ticket["id"],
|
||||
},
|
||||
},
|
||||
alternatives=[
|
||||
{
|
||||
"name": "resolve_at_support_level",
|
||||
"confidence": 0.15,
|
||||
"reason_rejected": "500 errors suggest infrastructure issue beyond support scope",
|
||||
},
|
||||
],
|
||||
reasoning="Intermittent 500s on enterprise account = immediate P1 escalation.",
|
||||
)
|
||||
|
||||
# Simulate escalation failure for the critical ticket (shows error handling)
|
||||
if random.random() < 0.3:
|
||||
raise RuntimeError(
|
||||
f"Escalation service unavailable for {ticket['id']}"
|
||||
)
|
||||
|
||||
# Generate response
|
||||
response = simulate_llm(
|
||||
f"Draft response for {ticket['id']}: {ticket['subject']}",
|
||||
delay=0.3,
|
||||
)
|
||||
|
||||
print(f" [{ticket['id']}] Processed -> routed to {specialist}")
|
||||
|
||||
|
||||
# Process all tickets
|
||||
print("Processing support tickets...\n")
|
||||
|
||||
for ticket in TICKETS:
|
||||
try:
|
||||
process_ticket(ticket)
|
||||
except Exception as e:
|
||||
# The trace context manager captures the error automatically
|
||||
print(f" [{ticket['id']}] Error during processing: {e}")
|
||||
|
||||
# Shutdown
|
||||
agentlens.shutdown()
|
||||
|
||||
print("\nDone! Check AgentLens dashboard for 'customer-support-bot' traces.")
|
||||
print("Look for the ERROR trace — it shows how failures are captured.")
|
||||
Reference in New Issue
Block a user