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| # utils.py | |
| # Helper utilities for HyperLayer demo Space | |
| # - formatting helpers | |
| # - placeholder functions for RPC / model calls | |
| # - lightweight caching (in-memory) | |
| import time | |
| import random | |
| from typing import Dict, Any | |
| def nice_number(n: int) -> str: | |
| """Format number with commas.""" | |
| return f"{n:,}" | |
| def mock_trading_volume() -> Dict[str, Any]: | |
| """Return a simulated trading volume object (used in demo).""" | |
| vol = random.randint(30_000, 120_000) | |
| return { | |
| "timestamp": int(time.time()), | |
| "volume_usd": vol, | |
| "formatted": f"${nice_number(vol)}", | |
| "note": "Simulated data for demo purposes" | |
| } | |
| def simulate_agent_response(prompt: str, mode: str = "explain") -> str: | |
| """Return a deterministic-ish simulated response for UI demo.""" | |
| prefix = { | |
| "explain": "Explained:", | |
| "summarize": "Summary:", | |
| "detect": "Detected intent:", | |
| "tokenize": "Tokenized:" | |
| }.get(mode, "Response:") | |
| time.sleep(0.25) # tiny delay to mimic processing | |
| sample_responses = [ | |
| "Low-latency aggregation applied across shards.", | |
| "Agent orchestrated securely via MPC endpoints.", | |
| "Found 3 potential optimizations for throughput.", | |
| "Simulated policy verified; no anomalies detected." | |
| ] | |
| return f"{prefix} {random.choice(sample_responses)} (for: {prompt[:80]})" |