Dashboard

Launch

pip install "plyra-guard[sidecar]"
plyra-guard serve
# → http://localhost:8765

Or start from code:

guard.serve(host="0.0.0.0", port=8080)

The default sidecar port in config is 8080. The CLI command plyra-guard serve uses port 8765. You can override both via the sidecar section in your YAML config.

What you can see

Live action feed — every tool call as it happens, with verdict and latency
Policy hit rates — which rules fire most
Session replay — reconstruct any agent session from the audit log
Block details — full context on every blocked call: action type, intent, matched rule, and reason

The default CORS setting (allow_origins=["*"]) is fine for local development. Lock it down before exposing the dashboard beyond localhost.

Run plyra-guard serve to launch the dashboard at localhost:8765. The dashboard shows a live action feed, policy hit rates, session replay, and full block context — no configuration required beyond the sidecar install.

Query the audit log

from plyra_guard import AuditFilter, Verdict

# Get the 20 most recent blocked actions
entries = guard.get_audit_log(AuditFilter(
    verdict=Verdict.BLOCK,
    limit=20,
))

for entry in entries:
    print(f"{entry.action_type} | {entry.verdict.value} | {entry.duration_ms}ms")

AuditFilter fields

Field	Type	Default	Description
`agent_id`	`str \| None`	`None`	Filter by agent
`task_id`	`str \| None`	`None`	Filter by task
`verdict`	`Verdict \| None`	`None`	Filter by verdict type
`action_type`	`str \| None`	`None`	Filter by action type
`from_time`	`datetime \| None`	`None`	Start of time range
`to_time`	`datetime \| None`	`None`	End of time range
`limit`	`int`	`100`	Max entries to return

Explain a decision

from plyra_guard import ActionIntent

intent = ActionIntent(
    action_type="file.delete",
    tool_name="delete_file",
    parameters={"path": "/etc/passwd"},
    agent_id="default",
)

explanation = guard.explain(intent)
print(explanation)
# Human-readable description of which evaluators ran,
# which rule matched, and why the verdict was reached

Metrics snapshot

metrics = guard.get_metrics()
print(f"Total: {metrics.total_actions}")
print(f"Blocked: {metrics.blocked_actions}")
print(f"Avg risk: {metrics.avg_risk_score:.2f}")
print(f"Avg latency: {metrics.avg_duration_ms:.1f}ms")

Export as Prometheus text format:

print(metrics.to_prometheus())

Getting started

Core concepts

Integrations

Reference

Launch

What you can see

Query the audit log

AuditFilter fields

Explain a decision

Metrics snapshot

​Launch

​What you can see

​Query the audit log

​AuditFilter fields

​Explain a decision

​Metrics snapshot

Launch

What you can see

Query the audit log

AuditFilter fields

Explain a decision

Metrics snapshot