rmi-backend/app/domain/x402/tools/report_tools.py

220 lines
5.1 KiB
Python

"""x402 report tools - generate_report, get_report."""
from typing import Any
async def generate_report(subject_type: str, subject_id: str, model: str = "deepseek-v3") -> dict[str, Any]:
"""Generate a research report."""
return {
"report_id": "pending",
"subject_type": subject_type,
"subject_id": subject_id,
"sections": {},
"risk_score": 50,
"markdown": "# Pending Report\n\n[Report generation pending]",
}
async def get_report(report_id: str) -> dict[str, Any]:
"""Get a previously generated report."""
return {
"report_id": report_id,
"status": "pending",
"result": {},
}
async def social_sentiment(token: str, chain: str = "solana") -> dict[str, Any]:
"""Get social sentiment analysis."""
return {
"token": token,
"chain": chain,
"sentiment": "neutral",
"mentions": 0,
}
async def cluster_detection(wallet_address: str, chain: str = "solana") -> dict[str, Any]:
"""Run cluster detection."""
return {
"wallet_address": wallet_address,
"chain": chain,
"clusters": [],
}
async def insider_tracker(creator: str, chain: str = "solana") -> dict[str, Any]:
"""Track insider activity."""
return {
"creator": creator,
"chain": chain,
"insider_activity": [],
}
async def twitter_profile(query: str) -> dict[str, Any]:
"""Get Twitter profile."""
return {
"query": query,
"profile": {},
}
async def twitter_timeline(query: str) -> dict[str, Any]:
"""Get Twitter timeline."""
return {
"query": query,
"tweets": [],
}
async def twitter_search(query: str) -> dict[str, Any]:
"""Search Twitter."""
return {
"query": query,
"results": [],
}
async def launch_radar(chain: str = "solana", window_minutes: int = 5) -> dict[str, Any]:
"""Get launch radar."""
return {
"chain": chain,
"window_minutes": window_minutes,
"launches": [],
}
async def launch_intel(chain: str = "solana", hours: int = 24) -> dict[str, Any]:
"""Get launch intelligence."""
return {
"chain": chain,
"hours": hours,
"launches": [],
}
async def token_pulse(token_address: str, chain: str = "solana") -> dict[str, Any]:
"""Get token pulse."""
return {
"token_address": token_address,
"chain": chain,
"pulse": "pending",
}
async def anomaly_detector(chain: str = "solana") -> dict[str, Any]:
"""Run anomaly detection."""
return {
"chain": chain,
"anomalies": [],
}
async def whale_decoder(address: str, chain: str = "solana") -> dict[str, Any]:
"""Decode whale activity."""
return {
"address": address,
"chain": chain,
"whale_activity": [],
}
async def chain_health(chain: str = "solana") -> dict[str, Any]:
"""Check chain health."""
return {
"chain": chain,
"health": "pending",
}
async def portfolio_tracker(addresses: list[str], chain: str = "solana") -> dict[str, Any]:
"""Track portfolio."""
return {
"addresses": addresses,
"chain": chain,
"portfolio": [],
}
async def copy_trade_finder(chain: str = "solana") -> dict[str, Any]:
"""Find copy trade opportunities."""
return {
"chain": chain,
"opportunities": [],
}
async def risk_monitor(address: str, chain: str = "solana") -> dict[str, Any]:
"""Monitor risk."""
return {
"address": address,
"chain": chain,
"risk_level": "pending",
}
async def defi_yield_scanner(chain: str = "solana") -> dict[str, Any]:
"""Scan DeFi yield opportunities."""
return {
"chain": chain,
"opportunities": [],
}
async def nft_wash_detector(collection: str) -> dict[str, Any]:
"""Detect NFT wash trading."""
return {
"collection": collection,
"wash_trading": False,
}
async def bridge_security() -> dict[str, Any]:
"""Check bridge security."""
return {
"bridge_security": "pending",
}
async def gas_forecast(chain: str = "solana") -> dict[str, Any]:
"""Forecast gas prices."""
return {
"chain": chain,
"gas_forecast": "pending",
}
async def sniper_alert(chain: str = "solana", hours: int = 24) -> dict[str, Any]:
"""Get sniper alerts."""
return {
"chain": chain,
"hours": hours,
"sniper_alerts": [],
}
async def liquidity_flow(address: str, chain: str = "solana") -> dict[str, Any]:
"""Track liquidity flow."""
return {
"address": address,
"chain": chain,
"liquidity_flow": [],
}
async def rug_pull_predictor(address: str, chain: str = "solana") -> dict[str, Any]:
"""Predict rug pull risk."""
return {
"address": address,
"chain": chain,
"risk_score": 50,
}
async def airdrop_finder(chain: str = "solana") -> dict[str, Any]:
"""Find airdrop opportunities."""
return {
"chain": chain,
"airdrops": [],
}