qyra

Python SDK for the Qyra AI infrastructure layer.

Qyra runs production AI Modules (AIMs) on the HyperCycle network — covering scoring, routing, research, document intelligence, personal memory, benchmarking, telemetry, and certification. This SDK lets you call any AIM, track costs, and log telemetry from your own Python code or agent pipelines.

Installation

pip install qyra

Quick start

from qyra import QyraClient

client = QyraClient(base_url="https://api.qyratech.com")

# Call an AIM
result = client.call("aim-smart-router", {"query": "Summarise this document", "payload": "..."})
print(result)

# Track a call with telemetry
client.track(
    aim_id="aim-smart-router",
    latency_ms=142,
    cost_usd=0.0028,
    status="success"
)

Telemetry

The SDK ships with a built-in telemetry client that posts structured call data to qyra-ingest. Every call can log latency, cost, model used, and outcome — visible in real time on the Qyra dashboard.

from qyra.telemetry import TelemetryClient

tel = TelemetryClient(ingest_url="https://api.qyratech.com/ingest")
tel.track(aim_id="aim-scoring", latency_ms=88, cost_usd=0.0086, status="success")

Production AIMs

Links

• Website: qyratech.com
• Book a call: cal.eu/qyratech/discovery
• GitHub: github.com/qyrahub

Changelog

v0.1.5

• Corrected telemetry ingest URL
• Server-side UUID fallback for older clients
• Real cost derivation in aggregate endpoint

v0.1.2

• Fixed telemetry URL pointing to production ingest
• P50/P95/P99 latency percentiles in dashboard

v0.1.0

• Initial release
• QyraClient with AIM call support
• Telemetry client with structured logging

Built in South Africa. Infrastructure for the agentic age.