Python SDK for AngoraPay Mesh market-agent service routing, receipts, and reconciliation.
Project description
angorapay
Python SDK for AngoraPay Mesh, the paid-intelligence routing, policy, payment-boundary, receipt, and reconciliation layer for market agents.
Use it from a backend, research job, trading pipeline, or agent runtime. Keep API keys server-side.
Install
pip install angorapay
For the current repository build before registry publication:
cd sdk/python
python -m build
Configure
from angorapay import AngoraPay
client = AngoraPay(
base_url="https://your-angora-gateway.example",
api_key="ag_live_...",
)
Run A Market-Intelligence Mission
result = client.run_agent_mission(
userGoal="Check whether this BTC prediction market is mispriced after the news shift.",
module="prediction_market",
paymentMode="arc_testnet",
budgetUSDC="0.05",
)
print(result["recommendation"])
print(result["receipts"])
Route One Paid Provider Call
route = client.call_market_service(
missionId="agent_mission_123",
agentId="prediction-market-intelligence-agent",
consumerId="enterprise-workspace",
intent="Fetch prediction-market odds",
category="odds",
maxPrice="0.01",
idempotencyKey="agent_mission_123:odds:001",
)
Inspect Proof And Reconciliation
payments = client.payment_intents(missionId="agent_mission_123")
runs = client.reconciliation_runs(missionId="agent_mission_123")
traces = client.agent_traces(missionId="agent_mission_123")
Enterprise Notes
- Use API-key auth for production gateways.
- Treat
demo_fallback,arc_testnet, andreal_x402as distinct execution modes. - Do not represent fallback receipts as real settlement.
- Store receipt IDs, route scores, provider decisions, output hashes, and reconciliation state with every market recommendation.
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