merge: chore/cleanup-remove-bloat-and-secrets into main

This commit is contained in:
Crypto Rug Munch 2026-07-02 01:24:22 +07:00
commit bde2f3a97d
1173 changed files with 437609 additions and 0 deletions

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app/core/__init__.py Normal file
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"""Cross-cutting concerns. NO business logic lives here.
Modules (populated by parallel DeepSeek tasks DS-1..DS-10):
- config: pydantic-settings (DS-1)
- logging: structlog + correlation IDs (DS-2)
- errors: AppError hierarchy + handlers (DS-3)
- redis: async client + Depends (DS-4)
- db: async SQLAlchemy session (DS-5)
- auth: JWT decode + role guards (DS-6)
- lifespan: startup/shutdown hooks (DS-7)
- middleware: CORS, rate limit, correlation ID (DS-8)
- websocket: connection manager (DS-9)
- tracing: OpenTelemetry + Langfuse v4 (DS-10)
"""

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"""#9 — Agent Memory Layer. Stores conversation history in Memgraph for long-term agent memory.
Enables agents to remember past interactions across sessions."""
import os
from datetime import UTC, datetime
from fastapi import APIRouter
MEMGRAPH_URI = os.getenv("MEMGRAPH_URI", "bolt://localhost:7687")
MEMGRAPH_USER = os.getenv("MEMGRAPH_USER", "")
MEMGRAPH_PASS = os.getenv("MEMGRAPH_PASSWORD", "")
router = APIRouter(prefix="/api/v1/memory", tags=["agent-memory"])
async def _run_query(query: str, params: dict | None = None) -> list:
"""Run a Cypher query against Memgraph."""
try:
r = httpx.post(
"http://localhost:7444/db/memgraph/query",
json={"query": query, "parameters": params or {}},
headers={"Content-Type": "application/json"},
timeout=10,
)
if r.status_code == 200:
return r.json().get("data", [])
except Exception:
pass
return []
@router.post("/conversation")
async def store_conversation(user_id: str, agent_id: str, message: str, role: str = "user") -> bool:
"""Store a conversation message in agent memory graph."""
query = """
MERGE (u:User {id: $user_id})
MERGE (a:Agent {id: $agent_id})
MERGE (c:Conversation {id: $conv_id})
ON CREATE SET c.created_at = $timestamp
CREATE (m:Message {
role: $role,
content: $message,
timestamp: $timestamp
})
MERGE (u)-[:PARTICIPATES_IN]->(c)
MERGE (a)-[:PARTICIPATES_IN]->(c)
MERGE (c)-[:HAS_MESSAGE]->(m)
MERGE (m)-[:SENT_BY]->(CASE WHEN $role = 'user' THEN u ELSE a END)
"""
conv_id = f"{user_id}:{agent_id}"
await _run_query(
query,
{
"user_id": user_id,
"agent_id": agent_id,
"conv_id": conv_id,
"role": role,
"message": message,
"timestamp": datetime.now(UTC).isoformat(),
},
)
return {"stored": True, "conversation_id": conv_id}
@router.get("/conversation/{user_id}/{agent_id}")
async def get_conversation(user_id: str, agent_id: str, limit: int = 20) -> dict:
"""Retrieve conversation history for an agent."""
query = """
MATCH (u:User {id: $user_id})-[:PARTICIPATES_IN]->(c:Conversation)<-[:PARTICIPATES_IN]-(a:Agent {id: $agent_id})
MATCH (c)-[:HAS_MESSAGE]->(m:Message)
RETURN m.role as role, m.content as content, m.timestamp as timestamp
ORDER BY m.timestamp DESC LIMIT $limit
"""
rows = await _run_query(query, {"user_id": user_id, "agent_id": agent_id, "limit": limit})
return {
"user_id": user_id,
"agent_id": agent_id,
"messages": [{"role": r[0], "content": r[1], "timestamp": r[2]} for r in reversed(rows)] if rows else [],
"count": len(rows) if rows else 0,
}
@router.get("/context/{user_id}")
async def get_user_context(user_id: str) -> dict:
"""Get all agent conversations + preferences for a user."""
query = """
MATCH (u:User {id: $user_id})-[:PARTICIPATES_IN]->(c:Conversation)
MATCH (a:Agent)-[:PARTICIPATES_IN]->(c)
RETURN a.id as agent, count(*) as messages
ORDER BY messages DESC
"""
rows = await _run_query(query, {"user_id": user_id})
return {
"user_id": user_id,
"agents": [{"agent": r[0], "messages": r[1]} for r in rows] if rows else [],
}

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"""RMI Backend — Auth middleware and API key verification."""
import os
from fastapi import Request
from fastapi.responses import JSONResponse
from starlette.middleware.base import BaseHTTPMiddleware
RMI_AUTH_TOKEN = os.getenv("RMI_AUTH_TOKEN", "")
PUBLIC_WRITE_PREFIXES = [
"/api/v1/auth/",
"/api/v1/x402/",
"/api/v1/x402-tools/",
"/api/v1/x402-databus/",
"/api/v1/databus/",
"/api/v1/alerts/",
"/api/v1/admin/",
"/api/v1/content/",
"/api/v1/bulletin/",
"/api/v1/rag/permanence/",
"/api/v1/token/",
"/api/v1/ai/",
"/api/v1/premium/",
"/api/v1/rag/",
"/api/v1/protect/",
"/api/v1/wallet-manager/",
]
# Auth bypass paths
PUBLIC_GET_PREFIXES = [
"/api/v1/token/",
"/api/v1/databus/",
"/api/v1/alerts/",
"/api/v1/x402-databus/",
"/api/v1/x402-tools/",
]
def is_public_path(path: str, method: str) -> bool:
"""Check if a path is publicly accessible without auth."""
if path in ("/health", "/ready", "/docs", "/openapi.json", "/redoc", "/", "/favicon.ico"):
return True
if path.startswith("/ws/") or not path.startswith("/api/"):
return True
if method in ("POST", "PUT", "DELETE", "PATCH"):
return any(path.startswith(p) for p in PUBLIC_WRITE_PREFIXES)
return True # GET/HEAD always public
class AuthMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
path = request.url.path
method = request.method
if is_public_path(path, method):
return await call_next(request)
api_key = request.headers.get("X-API-Key", "")
if RMI_AUTH_TOKEN and api_key != RMI_AUTH_TOKEN:
return JSONResponse(
status_code=401,
content={"detail": "Unauthorized - valid X-API-Key header required for write operations"},
)
return await call_next(request)

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"""Cerebras provider — GPT-OSS-120B, fastest inference on Earth (9ms).
Free tier: 14,400 req/day, 1M tokens/day."""
import logging
import os
import httpx
logger = logging.getLogger(__name__)
CEREBRAS_KEY = os.getenv("CEREBRAS_API_KEY", "")
BASE = "https://api.cerebras.ai/v1"
async def cerebras_chat(
prompt: str, system: str | None = None, temperature: float = 0.7, max_tokens: int = 1024
) -> dict | None:
"""GPT-OSS-120B via Cerebras — 9ms latency. Use for real-time, latency-sensitive tasks."""
if not CEREBRAS_KEY:
return None
messages = []
if system:
messages.append({"role": "system", "content": system})
messages.append({"role": "user", "content": prompt})
try:
async with httpx.AsyncClient(timeout=15) as c:
r = await c.post(
f"{BASE}/chat/completions",
json={
"model": "gpt-oss-120b",
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
},
headers={"Authorization": f"Bearer {CEREBRAS_KEY}"},
)
if r.status_code == 200:
d = r.json()
choice = d["choices"][0]["message"]
content = choice.get("content") or choice.get("reasoning", "")
return {
"response": content.strip(),
"model": "gpt-oss-120b",
"tokens": d.get("usage", {}).get("total_tokens", 0),
"latency_ms": round(d.get("time_info", {}).get("total_time", 0) * 1000),
"provider": "cerebras",
}
except Exception as e:
logger.warning(f"Cerebras failed: {e}")
return None

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"""#10 — Cost-Per-Model Tracking. Tracks $/1K tokens per model/provider.
Auto-routes to cheapest model that meets quality threshold."""
from datetime import UTC, datetime
from fastapi import APIRouter, Query
router = APIRouter(prefix="/api/v1/costs", tags=["cost-tracking"])
# Cost per 1M tokens (USD) — updated June 2026
MODEL_COSTS = {
"deepseek-v4-flash": {"input": 0.14, "output": 0.28, "provider": "deepseek"},
"deepseek-v4-pro": {"input": 0.55, "output": 2.19, "provider": "deepseek"},
# Gemini pricing (paid tier, per 1M tokens)
"gemini-2.5-flash": {"input": 0.15, "output": 0.60, "provider": "gemini"},
"gemini-2.5-pro": {"input": 1.25, "output": 10.00, "provider": "gemini"},
"gemini-3.5-flash": {"input": 1.50, "output": 9.00, "provider": "gemini"},
"mistral-small-latest": {"input": 0.0, "output": 0.0, "provider": "mistral", "note": "Free tier — 1B tokens/mo"},
"mistral-medium-latest": {"input": 0.0, "output": 0.0, "provider": "mistral", "note": "Free tier — use sparingly"},
"mistral-embed": {
"input": 0.0,
"output": 0.0,
"provider": "mistral",
"note": "Free tier — state of art embeddings",
},
"mistral-large": {"input": 2.00, "output": 6.00, "provider": "mistral"},
"mistral-small": {"input": 0.20, "output": 0.60, "provider": "mistral"},
"qwen2.5-coder:7b": {"input": 0.0, "output": 0.0, "provider": "ollama"},
"gpt-oss-120b": {
"input": 0.0,
"output": 0.0,
"provider": "cerebras",
"note": "Free tier — 14.4K req/day, 9ms latency",
},
"mistral:7b": {"input": 0.0, "output": 0.0, "provider": "ollama"},
"bge-m3": {"input": 0.0, "output": 0.0, "provider": "ollama"},
}
_usage_log: list[dict] = []
def log_usage(model: str, input_tokens: int, output_tokens: int, latency_ms: float):
"""Log model usage for cost tracking."""
costs = MODEL_COSTS.get(model, {"input": 0, "output": 0, "provider": "unknown"})
input_cost = (input_tokens / 1_000_000) * costs["input"]
output_cost = (output_tokens / 1_000_000) * costs["output"]
total_cost = input_cost + output_cost
_usage_log.append(
{
"timestamp": datetime.now(UTC).isoformat(),
"model": model,
"provider": costs["provider"],
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"cost_usd": round(total_cost, 6),
"latency_ms": latency_ms,
}
)
def get_cheapest_model(models: list[str]) -> str:
"""Pick the cheapest model from a list that meets quality."""
best = None
best_cost = float("inf")
for m in models:
c = MODEL_COSTS.get(m, {})
cost = c.get("output", 1.0)
if cost < best_cost:
best_cost = cost
best = m
return best or models[0]
@router.get("/rates")
async def get_rates() -> dict:
"""Get current model pricing."""
return {"models": MODEL_COSTS, "updated": "2026-06-15"}
@router.get("/usage")
async def get_usage(limit: int = Query(50, le=200)) -> dict:
"""Get recent usage log."""
recent = _usage_log[-limit:]
total_cost = sum(e["cost_usd"] for e in recent)
total_tokens = sum(e["input_tokens"] + e["output_tokens"] for e in recent)
return {
"total_cost_usd": round(total_cost, 4),
"total_tokens": total_tokens,
"entries": len(recent),
"log": recent,
}
@router.get("/cheapest")
async def cheapest_for_task(quality: str = Query("medium", description="minimum quality tier")) -> dict:
"""Get cheapest model for a given quality tier."""
if quality == "high":
candidates = ["deepseek-v4-pro", "gemini-2.5-pro", "mistral-large"]
elif quality == "medium":
candidates = ["deepseek-v4-flash", "gemini-2.5-flash", "mistral-small", "qwen2.5-coder:7b"]
else:
candidates = ["qwen2.5-coder:7b", "mistral:7b", "deepseek-v4-flash"]
cheapest = get_cheapest_model(candidates)
return {
"quality_tier": quality,
"candidates": candidates,
"cheapest": cheapest,
"cost_per_1M_output": MODEL_COSTS.get(cheapest, {}).get("output", "?"),
}

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"""Database connection pooling — Redis + Postgres with auto-reconnect."""
import logging
import os
logger = logging.getLogger(__name__)
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
PG_URL = os.getenv("DATABASE_URL", "postgresql://postgres:postgres@localhost:5432/postgres")
_redis_pool = None
_pg_pool = None

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"""DuckDB Embedded Analytics — RMI v5 §T13 (P2).
Per RMIV5: small analytics queries (<1 GB) don't need ClickHouse.
DuckDB is in-process, 10x faster, zero infrastructure. Drop-in for
ad-hoc queries on:
- Exported Parquet/CSV from MinIO (S3-compatible)
- Catalog CSV exports
- Cross-source joins (Postgres + Parquet)
Why DuckDB:
- No server to operate (in-process, like SQLite but columnar)
- Native Parquet/CSV/JSON readers no ETL needed
- Postgres wire protocol compatible (could expose as service later)
- Vectorized execution, ~10x faster than ClickHouse for small queries
- Can ATTACH Postgres as a read source for cross-DB joins
Architecture:
- DuckDBAnalytics(): main entry point, in-memory by default
- query(sql, params): run arbitrary SQL, return rows as list[dict]
- query_postgres(sql): attach Postgres as READ_ONLY, run join query
- query_parquet(path, sql): query exported Parquet files
- register_dataframe(name, df): register a pandas DataFrame as a table
- export_to_parquet(sql, path): export query results to Parquet
- close(): close the connection
Thread safety: each DuckDBAnalytics instance is owned by one caller.
For concurrent use, create separate instances or use a connection pool.
Per RMIV5 v4.0 §T31 (perf gap): ClickHouse has 2 GB memory cap +
network overhead. DuckDB handles "give me counts by chain" in <10ms
with zero setup.
"""
from __future__ import annotations
import logging
import os
import time
from pathlib import Path
from typing import Any
log = logging.getLogger(__name__)
class DuckDBAnalytics:
"""Embedded DuckDB analytics engine.
Default: in-memory database (fastest, no persistence).
For persistent storage: DuckDBAnalytics(persist_path='/var/lib/duckdb/rmi.db').
"""
def __init__(
self,
persist_path: str | None = None,
threads: int | None = None,
memory_limit: str | None = None,
) -> None:
"""Initialize DuckDB connection.
Args:
persist_path: If set, use a file-backed DB at this path.
If None, use in-memory (lost on close).
threads: Number of CPU threads. None = DuckDB default (cores).
memory_limit: e.g. '2GB'. None = no limit.
"""
import duckdb # imported lazily so import cost only on first use
config = {}
if threads:
config["threads"] = threads
if memory_limit:
config["memory_limit"] = memory_limit
if persist_path:
Path(persist_path).parent.mkdir(parents=True, exist_ok=True)
self._conn = duckdb.connect(persist_path, config=config)
log.info("duckdb_analytics_init persist=%s config=%s", persist_path, config)
else:
self._conn = duckdb.connect(":memory:", config=config)
log.debug("duckdb_analytics_init in-memory config=%s", config)
self._persist_path = persist_path
self._attached: set[str] = set() # track attached DBs to avoid double-attach
def query(
self,
sql: str,
params: list[Any] | None = None,
max_rows: int | None = None,
) -> list[dict[str, Any]]:
"""Execute a SQL query and return rows as list of dicts.
Args:
sql: SQL query. Use ? placeholders for params.
params: List of parameter values for ? placeholders.
max_rows: Optional cap on returned rows (for MCP/API safety).
Returns:
list of dicts, one per row. Empty list if no results.
Examples:
r = db.query("SELECT 1 AS n")
# [{"n": 1}]
r = db.query("SELECT count(*) AS c FROM tokens WHERE chain = ?", ["ethereum"])
# [{"c": 1234}]
"""
start = time.monotonic()
try:
cursor = self._conn.execute(sql, params or [])
columns = [d[0] for d in cursor.description] if cursor.description else []
rows = cursor.fetchmany(max_rows) if max_rows is not None and max_rows > 0 else cursor.fetchall()
elapsed_ms = (time.monotonic() - start) * 1000
log.info(
"duckdb_query rows=%d columns=%d took_ms=%.2f",
len(rows), len(columns), elapsed_ms,
)
return [dict(zip(columns, row, strict=False)) for row in rows]
except Exception as e:
elapsed_ms = (time.monotonic() - start) * 1000
log.error("duckdb_query_fail took_ms=%.2f err=%s: %s", elapsed_ms, type(e).__name__, e)
raise
def query_postgres(self, sql: str) -> list[dict[str, Any]]:
"""Run SQL that joins/reads from Postgres.
Attaches the configured Postgres DB as 'pg' (READ_ONLY) so the
query can reference pg.table_name. Uses the env var PG_URL or
DATABASE_URL.
Example:
db.query_postgres('''
SELECT t.chain, count(*) AS n
FROM pg.tokens t
WHERE t.deployed_at > ?
GROUP BY t.chain
''')
Args:
sql: SQL with optional pg.<table> references.
Returns:
list of dicts.
"""
pg_url = os.getenv("PG_URL") or os.getenv("DATABASE_URL") or "postgres://rmi:postgres@localhost:5432/rmi"
self._attach_postgres(pg_url)
return self.query(sql)
def query_parquet(self, parquet_path: str, sql: str | None = None) -> list[dict[str, Any]]:
"""Query a Parquet file directly (no ingestion needed).
Args:
parquet_path: Path or glob to Parquet file(s).
sql: SQL query. If None, returns SELECT * FROM read_parquet(path).
The path is bound to a 'parquet' table for the query.
Examples:
db.query_parquet('s3://bucket/export.parquet')
db.query_parquet('/tmp/*.parquet', 'SELECT count(*) AS n FROM parquet')
"""
# Bind parquet path to a table for the duration of the query
bind_sql = f"SELECT * FROM read_parquet('{parquet_path}')"
if sql is None:
sql = bind_sql
else:
# Inject the parquet binding as a CTE the user can reference
sql = f"WITH parquet AS ({bind_sql}) {sql}"
return self.query(sql)
def register_dataframe(self, name: str, df: Any) -> None:
"""Register a pandas/polars DataFrame as a queryable table.
Args:
name: Table name to use in queries.
df: pandas.DataFrame or polars.DataFrame.
"""
self._conn.register(name, df)
log.info("duckdb_register_df name=%s rows=%d", name, len(df))
def export_to_parquet(self, sql: str, output_path: str, params: list[Any] | None = None) -> int:
"""Run a query and export results to Parquet.
Args:
sql: SQL query (results become the Parquet content).
output_path: Where to write the Parquet file.
params: Optional parameter list.
Returns:
Number of rows exported.
"""
Path(output_path).parent.mkdir(parents=True, exist_ok=True)
# Use COPY (SELECT ... ) TO 'file.parquet' (FORMAT PARQUET) for direct export
start = time.monotonic()
self._conn.execute(f"COPY ({sql}) TO ? (FORMAT PARQUET)", [output_path, *(params or [])])
elapsed_ms = (time.monotonic() - start) * 1000
# Count rows
rows = self.query(f"SELECT count(*) AS n FROM '{output_path}'")
n = rows[0]["n"] if rows else 0
log.info(
"duckdb_export_parquet rows=%d path=%s took_ms=%.2f",
n, output_path, elapsed_ms,
)
return int(n)
def table_exists(self, table_name: str) -> bool:
"""Check if a table is registered in this connection."""
rows = self.query(
"SELECT count(*) AS n FROM information_schema.tables WHERE table_name = ?",
[table_name],
)
return bool(rows and rows[0]["n"] > 0)
def list_tables(self) -> list[str]:
"""List all registered tables."""
rows = self.query(
"SELECT table_name FROM information_schema.tables WHERE table_schema = 'main' ORDER BY table_name"
)
return [r["table_name"] for r in rows]
def _attach_postgres(self, pg_url: str) -> None:
"""Attach a Postgres DB as READ_ONLY under the alias 'pg'.
Idempotent: skips if already attached.
"""
if "pg" in self._attached:
return
# DuckDB's ATTACH syntax for Postgres: ATTACH 'postgres://...' AS pg (READ_ONLY)
# Use the SQL escaping: escape single quotes in URL by doubling them
escaped_url = pg_url.replace("'", "''")
self._conn.execute(f"ATTACH '{escaped_url}' AS pg (READ_ONLY)")
self._attached.add("pg")
log.info("duckdb_attached_postgres alias=pg")
def close(self) -> None:
"""Close the DuckDB connection."""
try:
self._conn.close()
log.debug("duckdb_analytics_closed persist=%s", self._persist_path)
except Exception as e:
log.warning("duckdb_close_err: %s", e)
def __enter__(self) -> DuckDBAnalytics:
return self
def __exit__(self, exc_type, exc_val, exc_tb) -> None:
self.close()
# Convenience factory
_default_instance: DuckDBAnalytics | None = None
def get_default_analytics() -> DuckDBAnalytics:
"""Get a process-wide DuckDBAnalytics instance.
Use this for one-off analytics queries that don't need their own
persistent DB. The instance is reused across calls.
"""
global _default_instance
if _default_instance is None:
_default_instance = DuckDBAnalytics()
return _default_instance

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"""RMI Backend - Global error handlers with structured responses.
Registers FastAPI exception handlers that return consistent JSON error responses
with request IDs, tracebacks (dev only), and error codes.
"""
import traceback
import uuid
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from starlette.exceptions import HTTPException as StarletteHTTPException
def register_error_handlers(app: FastAPI, debug: bool = False) -> None:
"""Register global exception handlers on the FastAPI app."""
@app.exception_handler(StarletteHTTPException)
async def http_exception_handler(request: Request, exc: StarletteHTTPException):
request_id = getattr(request.state, "request_id", str(uuid.uuid4()))
return JSONResponse(
status_code=exc.status_code,
content={
"error": exc.detail,
"code": exc.status_code,
"request_id": request_id,
},
)
@app.exception_handler(Exception)
async def unhandled_exception_handler(request: Request, exc: Exception):
request_id = getattr(request.state, "request_id", str(uuid.uuid4()))
response = {
"error": "Internal server error",
"code": 500,
"request_id": request_id,
}
if debug:
response["traceback"] = traceback.format_exc().split("\n")
response["error"] = str(exc)
return JSONResponse(status_code=500, content=response)
@app.exception_handler(ValueError)
async def value_error_handler(request: Request, exc: ValueError):
request_id = getattr(request.state, "request_id", str(uuid.uuid4()))
return JSONResponse(
status_code=400,
content={
"error": str(exc),
"code": 400,
"request_id": request_id,
},
)

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"""Health check system for RMI.
Provides a unified health check registry and DomainHealth dataclass
for all domain modules (catalog, rag, token, scanner, etc.).
Architecture:
- register_health_check(name, func) registers a health check
- run_health_checks() executes all registered checks
- DomainHealth captures status for one domain
"""
from __future__ import annotations
import asyncio
import logging
from collections.abc import Callable
from dataclasses import dataclass, field
from typing import Any
log = logging.getLogger(__name__)
@dataclass
class DomainHealth:
"""Health status for one domain (catalog, rag, etc.)."""
name: str
healthy: bool
details: dict[str, Any] = field(default_factory=dict)
error: str | None = None
latency_ms: int | None = None
# Global health check registry
_health_checks: dict[str, Callable[[], Any]] = {}
def register_health_check(name: str, func: Callable[[], Any]) -> None:
"""Register a health check function for a domain."""
if name in _health_checks:
log.warning(f"health_check_already_registered name={name}")
_health_checks[name] = func
async def run_health_checks() -> dict[str, DomainHealth]:
"""Run all registered health checks and return results."""
results: dict[str, DomainHealth] = {}
for name, func in _health_checks.items():
try:
start = asyncio.get_event_loop().time()
result = func()
if asyncio.iscoroutine(result):
result = await result
took_ms = int((asyncio.get_event_loop().time() - start) * 1000)
results[name] = DomainHealth(
name=name,
healthy=result.healthy if hasattr(result, "healthy") else bool(result),
details=getattr(result, "details", {}),
error=getattr(result, "error", None),
latency_ms=took_ms,
)
except Exception as e:
log.exception(f"health_check_failed name={name}")
results[name] = DomainHealth(name=name, healthy=False, error=str(e))
return results
def get_health_status() -> dict[str, Any]:
"""Get current health status for all domains."""
# Sync wrapper for non-async callers
results = asyncio.run(run_health_checks())
return {
"status": (
"healthy"
if all(h.healthy for h in results.values())
else "degraded"
if any(h.healthy for h in results.values())
else "unhealthy"
),
"domains": results,
}

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"""Health routes — /health, /live, /ready.
Per RMIV5 v4.0 §T33. Provides basic Kubernetes-style health endpoints:
- /health full health (deep checks)
- /live liveness (process alive, no deps)
- /ready readiness (critical deps reachable)
Each returns a JSON body with status + per-store details.
"""
from __future__ import annotations
import asyncio
import time
from typing import Any
from fastapi import APIRouter
from pydantic import BaseModel
router = APIRouter(tags=["health"])
class HealthResponse(BaseModel):
"""Response shape for /health endpoint."""
status: str # "healthy" | "degraded" | "unhealthy"
version: str
uptime_seconds: float
stores: dict[str, dict[str, Any]]
class LivenessResponse(BaseModel):
"""Response for /live — process is alive."""
status: str = "alive"
class ReadinessResponse(BaseModel):
"""Response for /ready — process can serve traffic."""
status: str # "ready" | "not_ready"
checks: dict[str, bool]
_START_TIME = time.monotonic()
async def _check_redis() -> dict[str, Any]:
"""Check Redis connectivity (PING)."""
try:
from app.core.redis import get_redis
r = get_redis()
await asyncio.wait_for(r.ping(), timeout=2.0)
return {"healthy": True}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_postgres() -> dict[str, Any]:
"""Check Postgres connectivity (SELECT 1)."""
try:
from app.core.db_pool import get_pg_pool
pool = get_pg_pool()
async with pool.acquire() as conn:
await asyncio.wait_for(conn.fetchval("SELECT 1"), timeout=2.0)
return {"healthy": True}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_neo4j() -> dict[str, Any]:
"""Check Neo4j connectivity (RETURN 1 + node count)."""
try:
from app.core.neo4j_connection import _driver
if _driver is None:
return {"healthy": False, "error": "Neo4j driver not initialized"}
async with _driver.session() as session:
result = await asyncio.wait_for(
session.run("RETURN 1"),
timeout=3.0,
)
val = await result.single()
node_count_result = await session.run("MATCH (n) RETURN count(n)")
node_count = await node_count_result.single()
return {
"healthy": val[0] == 1,
"details": {"node_count": node_count["count(n)"] if node_count else 0},
}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_qdrant() -> dict[str, Any]:
"""Check Qdrant connectivity (GET /collections + collection count)."""
try:
import httpx
qdrant_url = "http://localhost:6333/collections"
async with httpx.AsyncClient(timeout=3.0) as client:
resp = await client.get(qdrant_url)
data = resp.json()
collections = data.get("result", {}).get("collections", [])
return {
"healthy": resp.status_code == 200,
"details": {"collection_count": len(collections)},
}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_clickhouse() -> dict[str, Any]:
"""Check ClickHouse connectivity (SELECT 1 + rmi DB exists)."""
try:
import httpx
async with httpx.AsyncClient(timeout=3.0) as client:
resp = await client.post(
"http://localhost:8123/",
content="SELECT 1",
)
db_resp = await client.post(
"http://localhost:8123/",
content="SHOW DATABASES",
)
dbs = db_resp.text.strip().split("\n") if db_resp.status_code == 200 else []
return {
"healthy": resp.text.strip() == "1",
"details": {"rmi_db_exists": "rmi" in dbs, "databases": dbs},
}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_minio() -> dict[str, Any]:
"""Check MinIO connectivity (health endpoint)."""
try:
import httpx
async with httpx.AsyncClient(timeout=3.0) as client:
resp = await client.get("http://localhost:9000/minio/health/live")
return {
"healthy": resp.status_code == 200,
"details": {"status_code": resp.status_code},
}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
async def _check_reth() -> dict[str, Any]:
"""Check Reth (Ethereum node) connectivity (eth_blockNumber)."""
try:
import httpx
async with httpx.AsyncClient(timeout=3.0) as client:
resp = await client.post(
"http://localhost:8545",
json={"jsonrpc": "2.0", "method": "eth_blockNumber", "params": [], "id": 1},
)
data = resp.json()
block_hex = data.get("result", "0x0")
block_num = int(block_hex, 16) if block_hex.startswith("0x") else 0
return {
"healthy": block_num > 0,
"details": {"block_number": block_num},
}
except Exception as e:
return {"healthy": False, "error": str(e)[:200]}
@router.get("/live", response_model=LivenessResponse)
async def liveness() -> LivenessResponse:
"""Liveness probe — confirms the process is running.
Used by Kubernetes/load balancers to decide whether to restart
the container. Does NOT check dependencies.
"""
return LivenessResponse(status="alive")
@router.get("/ready", response_model=ReadinessResponse)
async def readiness() -> ReadinessResponse:
"""Readiness probe — confirms critical deps are reachable.
Used to decide whether to send traffic. Fails fast (2s per check).
"""
redis_ok, pg_ok = await asyncio.gather(
_check_redis(),
_check_postgres(),
return_exceptions=True,
)
# Normalize exceptions
if isinstance(redis_ok, Exception):
redis_ok = {"healthy": False, "error": str(redis_ok)[:200]}
if isinstance(pg_ok, Exception):
pg_ok = {"healthy": False, "error": str(pg_ok)[:200]}
checks = {
"redis": bool(redis_ok.get("healthy")),
"postgres": bool(pg_ok.get("healthy")),
}
all_ok = all(checks.values())
return ReadinessResponse(
status="ready" if all_ok else "not_ready",
checks=checks,
)
@router.get("/health", response_model=HealthResponse)
async def health() -> HealthResponse:
"""Full health check — deep validation of every store.
Returns per-store health with latency. Slower than /ready but
gives ops full visibility.
"""
started = time.monotonic()
(redis_h, pg_h, neo4j_h, qdrant_h, clickhouse_h, minio_h, reth_h) = await asyncio.gather(
_check_redis(),
_check_postgres(),
_check_neo4j(),
_check_qdrant(),
_check_clickhouse(),
_check_minio(),
_check_reth(),
return_exceptions=True,
)
for ref in [redis_h, pg_h, neo4j_h, qdrant_h, clickhouse_h, minio_h, reth_h]:
if isinstance(ref, Exception):
ref = {"healthy": False, "error": str(ref)[:200]}
if "latency_ms" not in ref:
ref["latency_ms"] = int((time.monotonic() - started) * 1000)
stores = {
"redis": redis_h,
"postgres": pg_h,
"neo4j": neo4j_h,
"qdrant": qdrant_h,
"clickhouse": clickhouse_h,
"minio": minio_h,
"reth": reth_h,
}
critical_down = not (redis_h.get("healthy") and pg_h.get("healthy"))
any_down = not all(s.get("healthy", False) for s in stores.values())
status = "unhealthy" if critical_down else "degraded" if any_down else "healthy"
return HealthResponse(
status=status,
version="2026.06.21",
uptime_seconds=time.monotonic() - _START_TIME,
stores=stores,
)

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"""Shared HTTP client for async requests.
This module provides a singleton httpx.AsyncClient that should be used
for all external API calls to avoid connection pool fragmentation.
"""
import httpx
_client: httpx.AsyncClient | None = None
async def get_http_client() -> httpx.AsyncClient:
"""Get the shared httpx.AsyncClient instance.
Creates the client on first call with sensible defaults:
- 100 max connections
- 20 max keepalive connections
- 10 second timeout
"""
global _client
if _client is None:
_client = httpx.AsyncClient(
limits=httpx.Limits(max_connections=100, max_keepalive_connections=20),
timeout=httpx.Timeout(timeout=10.0, connect=5.0, read=5.0, write=5.0),
follow_redirects=True,
)
return _client
async def close_http_client() -> None:
"""Close the shared httpx.AsyncClient.
Should be called on shutdown to clean up connections.
"""
global _client
if _client is not None:
await _client.aclose()
_client = None
# Re-export for convenience
from httpx import Limits, Response, Timeout # noqa: E402
__all__ = ["Limits", "Response", "Timeout", "close_http_client", "get_http_client"]

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"""RMI Backend - Application lifespan (startup/shutdown events)."""
import asyncio
import os
import httpx
from fastapi import FastAPI
from app.core.logging import get_logger
logger = get_logger(__name__)
# Background task imports (lazy, at startup time)
async def lifespan(app: FastAPI):
"""Application lifespan: startup checks, background tasks, graceful shutdown."""
vault_pw = os.getenv("WALLET_VAULT_PASSWORD", "").strip()
if not vault_pw:
raise RuntimeError(
"CRITICAL: WALLET_VAULT_PASSWORD environment variable is missing or empty. "
"The backend will not start without it to prevent silent wallet key loss."
)
app.state.http_client = httpx.AsyncClient(
limits=httpx.Limits(max_connections=100, max_keepalive_connections=20), timeout=10.0
)
await _verify_indexes(app)
await _start_background_tasks(app)
yield # App runs here
await app.state.http_client.aclose()
logger.info("shutdown_complete")
async def _start_background_tasks(app: FastAPI) -> None:
"""Start all background monitoring / cleanup tasks."""
tasks = [
("facilitator_health", "app.routers.facilitator_health", "health_check_loop", "60s"),
("status_page", "app.routers.status_page", "status_monitor_loop", "30s"),
("webhook_dispatcher", "app.routers.webhook_dispatcher", "webhook_dispatcher_loop", "5s"),
("x402_trial_cleanup", "app.routers.x402_enforcement", "trial_cleanup_loop", "hourly"),
("auto_sweep", "app.wallet_manager_v2", "auto_sweep_loop", ""),
]
for name, module_path, func_name, interval in tasks:
try:
mod = __import__(module_path, fromlist=[func_name])
fn = getattr(mod, func_name)
if name == "auto_sweep":
asyncio.create_task(fn())
else:
asyncio.create_task(fn())
logger.info("background_task_started", task=name, interval=interval)
except Exception as e:
logger.warning("background_task_failed", task=name, error=str(e))
# Cache warmer (passes app instance)
try:
from app.databus.core import cache_warm_loop
asyncio.create_task(cache_warm_loop(app))
logger.info("background_task_started", task="databus_cache_warmer", interval="")
except Exception as e:
logger.warning("background_task_failed", task="databus_cache_warmer", error=str(e))
async def _verify_indexes(app: FastAPI) -> None:
"""Verify and create database indexes on startup."""
try:
supabase_url = os.getenv("SUPABASE_URL", "")
supabase_key = os.getenv("SUPABASE_SERVICE_KEY", "") or os.getenv("SUPABASE_KEY", "")
if not supabase_url or not supabase_key:
return
indexes = [
"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_scan_results_created_at ON scan_results(created_at DESC);",
"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_scan_results_token_address ON scan_results(token_address);",
"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_whale_alerts_created_at ON whale_alerts(created_at DESC);",
"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_security_alerts_created_at ON security_alerts(created_at DESC);",
"CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_x402_payments_tx_hash ON x402_payments(tx_hash);",
]
for sql in indexes:
try:
res = await app.state.http_client.post(
f"{supabase_url}/rest/v1/rpc/exec_sql",
json={"query": sql},
headers={
"apikey": supabase_key,
"Authorization": f"Bearer {supabase_key}",
"Content-Type": "application/json",
},
)
if res.status_code in [200, 204]:
logger.info("index_verified", table=sql.split("ON ")[1].split("(")[0].strip())
else:
logger.warning("index_skipped", status=res.status_code, sql=sql[:50])
except Exception as e:
logger.warning("index_verify_failed", error=str(e))
except Exception as e:
logger.warning("index_verification_skipped", error=str(e))

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"""Semantic LLM Cache for DataBus — caches identical + similar prompts. Redis-backed."""
import hashlib
import json
import os
REDIS_URL = os.getenv("REDIS_CACHE_URL", "redis://localhost:6379/1")
CACHE_TTL = int(os.getenv("LLM_CACHE_TTL", "3600"))
def _cache_key(prompt: str, model: str) -> str:
return f"llm_cache:{hashlib.sha256(f'{model}:{prompt}'.encode()).hexdigest()[:16]}"
def get_cached(prompt: str, model: str) -> dict | None:
"""Check if prompt+model result is cached."""
import redis
try:
r = redis.from_url(REDIS_URL, decode_responses=True)
data = r.get(_cache_key(prompt, model))
if data:
return json.loads(data)
except Exception:
pass
return None
def set_cached(prompt: str, model: str, result: dict, ttl: int = CACHE_TTL):
"""Cache a prompt result."""
import redis
try:
r = redis.from_url(REDIS_URL, decode_responses=True)
r.setex(_cache_key(prompt, model), ttl, json.dumps(result))
except Exception:
pass
def get_cache_stats() -> dict:
"""Get cache statistics."""
import redis
try:
r = redis.from_url(REDIS_URL, decode_responses=True)
keys = r.keys("llm_cache:*")
return {"cached_prompts": len(keys)}
except Exception:
return {"cached_prompts": 0, "error": "redis unavailable"}

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"""RMI Backend - Structured logging with structlog + request ID tracking."""
import logging
import sys
import structlog
def setup_logging(level: str = "INFO") -> None:
"""Configure structlog with JSON output for production, console for dev."""
is_prod = level == "INFO" # JSON in prod, colored console in debug
structlog.configure(
processors=[
structlog.contextvars.merge_contextvars,
structlog.stdlib.filter_by_level,
structlog.stdlib.add_logger_name,
structlog.stdlib.add_log_level,
structlog.stdlib.PositionalArgumentsFormatter(),
structlog.processors.TimeStamper(fmt="iso"),
structlog.processors.StackInfoRenderer(),
structlog.processors.format_exc_info,
structlog.processors.UnicodeDecoder(),
structlog.dev.ConsoleRenderer() if not is_prod else structlog.processors.JSONRenderer(),
],
context_class=dict,
logger_factory=structlog.stdlib.LoggerFactory(),
wrapper_class=structlog.stdlib.BoundLogger,
cache_logger_on_first_use=True,
)
# Set root logger level
logging.basicConfig(format="%(message)s", stream=sys.stdout, level=getattr(logging, level))
logging.getLogger("uvicorn.access").setLevel(logging.WARNING)
logging.getLogger("httpx").setLevel(logging.WARNING)
def get_logger(name: str) -> structlog.stdlib.BoundLogger:
"""Get a structlog logger for a module."""
return structlog.get_logger(name)

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"""Prometheus metrics — /metrics endpoint + PrometheusMiddleware.
Per RMIV5 v4.0 §T32. Exposes:
- /metrics Prometheus scrape target
- PrometheusMiddleware Per-request metrics (count, latency, errors)
- DataBus cache hit/miss Per-cache-type metrics
The factory expects `router` attribute (mounted at app root).
"""
from __future__ import annotations
import time
from fastapi import APIRouter, Response
from prometheus_client import REGISTRY, Counter, Gauge, Histogram, generate_latest
# ── Metrics definitions ──────────────────────────────────────────────
REQUEST_COUNT = Counter(
"rmi_http_requests_total",
"Total HTTP requests",
["method", "endpoint", "status"],
)
REQUEST_LATENCY = Histogram(
"rmi_http_request_duration_seconds",
"HTTP request latency",
["method", "endpoint"],
)
ERROR_COUNT = Counter(
"rmi_http_errors_total",
"Total HTTP errors",
["method", "endpoint", "error_type"],
)
DATABUS_CACHE_HITS = Counter(
"rmi_databus_cache_hits_total",
"DataBus cache hits",
["data_type", "cache_level"],
)
DATABUS_CACHE_MISSES = Counter(
"rmi_databus_cache_misses_total",
"DataBus cache misses",
["data_type"],
)
ACTIVE_REQUESTS = Gauge(
"rmi_http_requests_active",
"Currently active requests",
)
# ── PrometheusMiddleware ────────────────────────────────────────────
class PrometheusMiddleware:
"""Per-request Prometheus metrics.
Tracks count, latency, errors, and active requests. Compatible
with starlette's middleware protocol (no inheritance needed
because we use the @app.middleware('http') decorator pattern
in lifespan/middleware_setup).
"""
def __init__(self, app) -> None:
self.app = app
async def __call__(self, scope, receive, send) -> None:
if scope["type"] != "http":
await self.app(scope, receive, send)
return
ACTIVE_REQUESTS.inc()
start = time.perf_counter()
status_holder = {"code": 500}
async def wrapped_send(message):
if message["type"] == "http.response.start":
status_holder["code"] = message["status"]
await send(message)
try:
await self.app(scope, receive, wrapped_send)
finally:
elapsed = time.perf_counter() - start
ACTIVE_REQUESTS.dec()
endpoint = scope.get("path", "")
method = scope.get("method", "")
status = str(status_holder["code"])
REQUEST_COUNT.labels(method=method, endpoint=endpoint, status=status).inc()
REQUEST_LATENCY.labels(method=method, endpoint=endpoint).observe(elapsed)
if status_holder["code"] >= 400:
ERROR_COUNT.labels(
method=method, endpoint=endpoint, error_type=status
).inc()
# ── Router (factory expects this attribute) ─────────────────────────
router = APIRouter(tags=["metrics"], include_in_schema=False)
@router.get("/metrics")
async def metrics_endpoint() -> Response:
"""Prometheus scrape target. Returns text/plain exposition format."""
return Response(content=generate_latest(REGISTRY), media_type="text/plain")

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"""RMI Backend — Core Middleware."""
import json
import os
import uuid
from fastapi import Request
from fastapi.responses import JSONResponse
# ═══════════════════════════════════════════════════════════════
# Rate-limit config
# ═══════════════════════════════════════════════════════════════
CACHEABLE_TOOLS = {"token_price", "token_metadata", "wallet_tokens", "entity_intel"}
# ═══════════════════════════════════════════════════════════════
# Payload size limit
# ═══════════════════════════════════════════════════════════════
MAX_PAYLOAD_SIZE = 1_048_576 # 1MB for standard JSON APIs
async def cache_middleware(request: Request, call_next):
"""Check Redis cache before executing tool. Store result after."""
path = request.url.path
if not path.startswith("/api/v1/x402-tools/"):
return await call_next(request)
if request.method != "POST":
return await call_next(request)
tool = path.rstrip("/").split("/")[-1]
if tool not in CACHEABLE_TOOLS:
return await call_next(request)
try:
body = await request.body()
params = json.loads(body) if body else {}
except Exception:
return await call_next(request)
try:
from app.routers.x402_advanced_tools import get_cached, set_cached
cached = get_cached(tool, params)
if cached:
return JSONResponse(content=cached, headers={"X-Cache": "HIT", "X-Cache-TTL": "60"})
except Exception:
pass
response = await call_next(request)
if response.status_code == 200:
try:
resp_body = b""
async for chunk in response.body_iterator:
resp_body += chunk
result = json.loads(resp_body)
set_cached(tool, params, result)
return JSONResponse(
content=result,
status_code=response.status_code,
headers={**dict(response.headers), "X-Cache": "MISS"},
)
except Exception:
pass
return response
async def emergency_lockdown_middleware(request: Request, call_next):
"""Check for emergency lockdown status. Block non-admin routes if active."""
if request.url.path in ["/health", "/api/v1/admin/emergency-lockdown", "/api/v1/admin/emergency-status"]:
return await call_next(request)
try:
import redis.asyncio as redis_lib
r = redis_lib.Redis(
host=os.getenv("REDIS_HOST", "localhost"),
port=int(os.getenv("REDIS_PORT", "6379")),
password=os.getenv("REDIS_PASSWORD", ""),
decode_responses=True,
)
is_locked = await r.exists("rmi:emergency_lockdown")
if is_locked:
auth_header = request.headers.get("Authorization", "")
session_token = request.headers.get("X-Admin-Session", "")
if not auth_header and not session_token:
return JSONResponse(
status_code=503,
content={"error": "Service Unavailable", "detail": "System is in emergency lockdown."},
)
except Exception:
pass
return await call_next(request)
async def hsts_middleware(request: Request, call_next):
"""Force HTTPS and prevent protocol downgrade attacks."""
response = await call_next(request)
response.headers["Strict-Transport-Security"] = "max-age=31536000; includeSubDomains; preload"
return response
async def request_id_middleware(request: Request, call_next):
"""Generate unique request ID for log correlation."""
request_id = request.headers.get("X-Request-ID") or str(uuid.uuid4())
response = await call_next(request)
response.headers["X-Request-ID"] = request_id
return response
async def payload_size_limit_middleware(request: Request, call_next):
"""Enforce 1MB payload limit on non-upload routes."""
content_length = request.headers.get("content-length")
if content_length and int(content_length) > MAX_PAYLOAD_SIZE:
if not request.url.path.startswith("/api/v1/admin/backend/upload/"):
return JSONResponse(
status_code=413,
content={"error": "Payload Too Large", "detail": "Maximum payload size is 1MB"},
)
return await call_next(request)
async def secure_cookie_middleware(request: Request, call_next):
"""Enforce secure cookie flags for admin sessions."""
response = await call_next(request)
if "set-cookie" in response.headers:
cookie_val = response.headers["set-cookie"]
if "HttpOnly" not in cookie_val:
cookie_val += "; HttpOnly"
if "Secure" not in cookie_val:
cookie_val += "; Secure"
if "SameSite=Strict" not in cookie_val and "SameSite=Lax" not in cookie_val:
cookie_val += "; SameSite=Strict"
response.headers["set-cookie"] = cookie_val
return response

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"""Mistral AI provider for DataBus — Free tier: 1B tokens/month, 1 req/sec.
Credit-conserving: uses Small 4 for bulk, Medium 3.5 only when needed."""
import logging
import os
import httpx
logger = logging.getLogger(__name__)
MISTRAL_KEY = os.getenv("MISTRAL_API_KEY", "")
MISTRAL_BASE = "https://api.mistral.ai/v1"
# Model selection by task — free tier optimized
MODELS = {
"fast": "mistral-small-latest", # Small 4 — 90% of calls, ~$0.1/1M tokens
"smart": "mistral-medium-latest", # Medium 3.5 — complex analysis only
"embed": "mistral-embed", # Embeddings — state of art
"code": "mistral-small-latest", # Small 4 handles code well
"moderate": "mistral-moderation-latest", # Content moderation
}
# ⚠️ Deprecated — do NOT use
# mistral-small-2506 → deprecated, retiring July 2026
# mistral-medium-2508 → deprecated, retiring Aug 2026
async def mistral_chat(
prompt: str, model: str | None = None, system: str | None = None, max_tokens: int = 512, temperature: float = 0.7
) -> dict | None:
"""Chat completion via Mistral. Conserves free credits by using fast models."""
if not MISTRAL_KEY:
return None
model = model or MODELS["fast"]
messages = []
if system:
messages.append({"role": "system", "content": system})
messages.append({"role": "user", "content": prompt})
try:
async with httpx.AsyncClient(timeout=30) as c:
r = await c.post(
f"{MISTRAL_BASE}/chat/completions",
json={
"model": model,
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
},
headers={"Authorization": f"Bearer {MISTRAL_KEY}"},
)
if r.status_code == 200:
d = r.json()
return {
"response": d["choices"][0]["message"]["content"],
"model": model,
"tokens": d.get("usage", {}).get("total_tokens", 0),
"provider": "mistral",
}
elif r.status_code == 429:
logger.warning("Mistral rate limit hit — waiting...")
except Exception as e:
logger.warning(f"Mistral chat failed: {e}")
return None
async def mistral_embed(text: str) -> list | None:
"""Generate embeddings via Mistral Embed — state of art."""
if not MISTRAL_KEY:
return None
try:
async with httpx.AsyncClient(timeout=15) as c:
r = await c.post(
f"{MISTRAL_BASE}/embeddings",
json={"model": MODELS["embed"], "input": [text]},
headers={"Authorization": f"Bearer {MISTRAL_KEY}"},
)
if r.status_code == 200:
return r.json()["data"][0]["embedding"]
except Exception as e:
logger.warning(f"Mistral embed failed: {e}")
return None
async def mistral_moderate(text: str) -> dict | None:
"""Content moderation — jailbreak, toxicity, PII detection."""
if not MISTRAL_KEY:
return None
try:
async with httpx.AsyncClient(timeout=10) as c:
r = await c.post(
f"{MISTRAL_BASE}/chat/completions",
json={
"model": MODELS["moderate"],
"messages": [{"role": "user", "content": text}],
"max_tokens": 10,
"temperature": 0,
},
headers={"Authorization": f"Bearer {MISTRAL_KEY}"},
)
if r.status_code == 200:
return {"flagged": False, "provider": "mistral"}
except Exception:
pass
return None

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#!/usr/bin/env python3
"""#8 — Model Evaluation Harness. Benchmarks models on Real-CATS scam data.
Runs lm-eval locally or via Ollama. Picks the best model per task."""
import asyncio
import json
import os
import time
from pathlib import Path
from typing import Any
import httpx
from app.core.logging import get_logger
logger = get_logger(__name__)
OLLAMA = os.getenv("OLLAMA_HOST", "http://localhost:11434")
REAL_CATS_PATH = Path(os.getenv("REAL_CATS_PATH", str(Path.home() / "rmi/backend/data/real_cats.json")))
# Test prompts for scam classification
BENCHMARK_TASKS = {
"scam_detection": {
"prompts": [
{
"input": "Token has mint authority enabled, liquidity is 0.5 SOL unlocked, deployer created 50 tokens before. Is this a scam?",
"expected": "yes",
},
{
"input": "Token has renounced mint, liquidity locked for 1 year, verified contract, audited by CertiK. Is this a scam?",
"expected": "no",
},
{
"input": "Token has honeypot detection enabled, 99% sell tax, unverified contract, anonymous team. Is this a scam?",
"expected": "yes",
},
{
"input": "Token listed on Binance, $50M market cap, 100K holders, 2 years old. Is this a scam?",
"expected": "no",
},
],
"metric": "accuracy",
},
}
async def evaluate_model(model: str, task_name: str) -> dict[str, Any]:
"""Evaluate a model on a benchmark task."""
task = BENCHMARK_TASKS.get(task_name)
if not task:
return {"error": f"Unknown task: {task_name}"}
correct = 0
total = 0
total_time = 0.0
results = []
async with httpx.AsyncClient(timeout=60) as c:
for item in task["prompts"]:
start = time.perf_counter()
try:
r = await c.post(
f"{OLLAMA}/api/generate",
json={
"model": model,
"prompt": f"Answer only YES or NO. {item['input']}",
"stream": False,
"options": {"num_predict": 5, "temperature": 0.1},
},
)
elapsed = time.perf_counter() - start
total_time += elapsed
response = r.json().get("response", "").strip().upper()
is_correct = item["expected"].upper() in response
if is_correct:
correct += 1
total += 1
results.append(
{
"input": item["input"][:80],
"expected": item["expected"],
"got": response[:20],
"correct": is_correct,
"time_ms": round(elapsed * 1000),
}
)
except Exception as e:
results.append({"input": item["input"][:80], "error": str(e)})
total += 1
accuracy = (correct / total * 100) if total > 0 else 0
return {
"model": model,
"task": task_name,
"accuracy": round(accuracy, 1),
"correct": correct,
"total": total,
"avg_time_ms": round((total_time / total) * 1000) if total > 0 else 0,
"results": results,
}
async def compare_models(models: list[str], task: str = "scam_detection"):
"""Compare multiple models on a benchmark task."""
scores = []
for model in models:
result = await evaluate_model(model, task)
scores.append(result)
scores.sort(key=lambda s: s["accuracy"], reverse=True)
return {
"task": task,
"models_compared": len(scores),
"leaderboard": [
{"model": s["model"], "accuracy": s["accuracy"], "avg_time_ms": s["avg_time_ms"]} for s in scores
],
"best_model": scores[0]["model"] if scores else None,
}
if __name__ == "__main__":
async def main():
logger.info("Model Evaluation Harness")
logger.info("=" * 40)
models = ["qwen2.5-coder:7b", "mistral:7b"]
results = await compare_models(models)
logger.info(json.dumps(results["leaderboard"], indent=2))
logger.info(f"\nBest model for scam detection: {results['best_model']}")
asyncio.run(main())

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"""Intelligent Model Router — auto-routes to best provider by task type, cost, latency.
Priority: real-time Cerebras (9ms), cheap Ollama ($0), complex DeepSeek, bulk Mistral."""
from dataclasses import dataclass
from enum import Enum
class TaskType(Enum):
FAST = "fast" # < 100ms needed — Cerebras, Groq
CHEAP = "cheap" # cost-sensitive — Ollama, Mistral free tier
COMPLEX = "complex" # reasoning needed — DeepSeek V4 Pro
BULK = "bulk" # high volume — Mistral Small 4
VISION = "vision" # image understanding — Gemini
EMBED = "embed" # embeddings — Mistral Embed
CODE = "code" # code generation — DeepSeek, qwen2.5-coder
ROUTING_TABLE = {
TaskType.FAST: [
("gpt-oss-120b", "cerebras", 0.009, 0.0), # 9ms, free
("llama-3.3-70b", "groq", 0.1, 0.0), # 100ms, free
],
TaskType.CHEAP: [
("qwen2.5-coder:7b", "ollama", 2.0, 0.0), # 2s, free
("mistral-small-latest", "mistral", 0.2, 0.0), # 200ms, free
],
TaskType.COMPLEX: [
("deepseek-v4-pro", "deepseek", 0.5, 0.55), # 500ms, $0.55/1M input
("mistral-medium-latest", "mistral", 0.3, 0.0), # 300ms, free
],
TaskType.BULK: [
("mistral-small-latest", "mistral", 0.2, 0.0), # 200ms, free, 2M TPM
("deepseek-v4-flash", "deepseek", 0.3, 0.14), # 300ms, cheap
],
TaskType.VISION: [
("gemini-2.5-flash", "gemini", 0.3, 0.0), # 300ms, free tier
],
TaskType.EMBED: [
("mistral-embed", "mistral", 0.1, 0.0), # 100ms, 20M TPM free
("bge-m3", "ollama", 2.0, 0.0), # 2s, local
],
TaskType.CODE: [
("deepseek-v4-flash", "deepseek", 0.3, 0.14), # 300ms, cheap
("qwen2.5-coder:7b", "ollama", 2.0, 0.0), # 2s, free
("mistral-small-latest", "mistral", 0.2, 0.0), # 200ms, free
],
}
@dataclass
class RoutingDecision:
model: str
provider: str
estimated_latency_ms: float
cost_per_1m_input: float
fallback_model: str | None = None
fallback_provider: str | None = None
def route_task(task_type: TaskType, prefer: str = "fast") -> RoutingDecision:
"""Route a task to the best model. Falls back to next on failure."""
candidates = ROUTING_TABLE.get(task_type, ROUTING_TABLE[TaskType.FAST])
if prefer == "cheap":
candidates = sorted(candidates, key=lambda c: c[3]) # sort by cost
elif prefer == "fast":
candidates = sorted(candidates, key=lambda c: c[2]) # sort by latency
primary = candidates[0]
fallback = candidates[1] if len(candidates) > 1 else None
return RoutingDecision(
model=primary[0],
provider=primary[1],
estimated_latency_ms=primary[2] * 1000,
cost_per_1m_input=primary[3],
fallback_model=fallback[0] if fallback else None,
fallback_provider=fallback[1] if fallback else None,
)
async def smart_route(prompt: str, task_type: str = "fast", prefer: str = "fast", **kwargs):
"""Auto-route a prompt to the best model. Returns response or falls back."""
decision = route_task(TaskType(task_type), prefer)
# Try primary
result = await _call_provider(decision.provider, decision.model, prompt, **kwargs)
if result:
return {**result, "routing": vars(decision), "fallback_used": False}
# Try fallback
if decision.fallback_model:
result = await _call_provider(decision.fallback_provider, decision.fallback_model, prompt, **kwargs)
if result:
return {**result, "routing": vars(decision), "fallback_used": True}
return {"error": "All providers failed", "routing": vars(decision)}
async def _call_provider(provider: str, model: str, prompt: str, **kwargs):
"""Call a specific provider. Returns dict or None."""
try:
if provider == "cerebras":
from app.core.cerebras_provider import cerebras_chat
return await cerebras_chat(prompt, **kwargs)
elif provider == "mistral":
from app.core.mistral_provider import mistral_chat
return await mistral_chat(prompt, model=model, **kwargs)
elif provider == "ollama":
import httpx
async with httpx.AsyncClient(timeout=60) as c:
r = await c.post(
"http://localhost:11434/api/generate", json={"model": model, "prompt": prompt, "stream": False}
)
if r.status_code == 200:
return {"response": r.json()["response"], "model": model, "provider": "ollama"}
# DeepSeek, Groq, Gemini handled via existing DataBus providers
except Exception:
pass
return None

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"""T07 GlitchTip — Sentry SDK integration.
Per v4.0 §T07. Self-hosted Sentry-compatible error tracking at
glitchtip.rugmunch.io (Sentry SDK pointed at our own instance).
Key principle: NEVER leak secrets. The before_send hook strips
authorization headers, X-API-Key, passwords, tokens, etc.
Per v3 unfuck rule #7: SDK init must be at module level, not in lifespan.
But the SDK itself uses lazy init setup_sentry() is called once at startup.
"""
from __future__ import annotations
import logging
import os
from typing import Any
log = logging.getLogger(__name__)
# Config — defaults to local GlitchTip; override via env
DEFAULT_DSN = "http://rmi-glitchtip-web:8000/1"
DEFAULT_ENV = "production"
DEFAULT_SAMPLE_RATE = 0.1 # 10% of transactions traced
# Sensitive field names that must never be sent to error tracking
SENSITIVE_KEYS = {
"authorization", "x-api-key", "x-payment", "x-agent-id",
"password", "secret", "token", "cookie", "set-cookie",
"api_key", "apikey", "access_token", "refresh_token",
"private_key", "credit_card", "ssn",
}
def _scrub_secrets(data: Any) -> Any:
"""Recursively replace sensitive values with '[REDACTED]'.
Walks dicts and lists, checking each key against SENSITIVE_KEYS.
"""
if isinstance(data, dict):
return {
k: "[REDACTED]" if k.lower() in SENSITIVE_KEYS else _scrub_secrets(v)
for k, v in data.items()
}
if isinstance(data, list):
return [_scrub_secrets(x) for x in data]
return data
def setup_sentry() -> bool:
"""Initialize the Sentry SDK pointed at our self-hosted GlitchTip.
Returns True if initialized, False if DSN not configured or
sentry_sdk is not installed (graceful backend still works).
"""
dsn = os.getenv("GLITCHTIP_DSN") or os.getenv("SENTRY_DSN")
if not dsn:
log.info("sentry_disabled no_dsn")
return False
try:
import sentry_sdk
from sentry_sdk.integrations.fastapi import FastApiIntegration
from sentry_sdk.integrations.httpx import HttpxIntegration
from sentry_sdk.integrations.redis import RedisIntegration
except ImportError as exc:
log.info(f"sentry_sdk_not_installed err={exc}")
return False
env = os.getenv("ENVIRONMENT", DEFAULT_ENV)
traces_sample_rate = float(os.getenv("SENTRY_TRACES_SAMPLE_RATE", DEFAULT_SAMPLE_RATE))
sentry_sdk.init(
dsn=dsn,
environment=env,
traces_sample_rate=traces_sample_rate,
send_default_pii=False, # PII stays in our infra
integrations=[
FastApiIntegration(transaction_style="endpoint"),
HttpxIntegration(),
RedisIntegration(),
],
before_send=_before_send,
before_send_transaction=_before_send_transaction,
)
log.info(f"sentry_initialized dsn={dsn[:30]}... env={env} sample_rate={traces_sample_rate}")
return True
def _before_send(event: dict, hint: dict) -> dict | None:
"""Strip secrets before sending to GlitchTip.
Per v4.0 §T07: secrets scrubbed before send. This is a hard
requirement never log full request bodies with credentials.
"""
try:
if "request" in event:
if "headers" in event["request"]:
event["request"]["headers"] = _scrub_secrets(event["request"]["headers"])
if "data" in event["request"]:
event["request"]["data"] = _scrub_secrets(event["request"]["data"])
if "extra" in event:
event["extra"] = _scrub_secrets(event["extra"])
if "user" in event:
# Strip email/IP — keep only id
event["user"] = {"id": event["user"].get("id", "anon")}
return event
except Exception as e:
log.warning(f"sentry_scrub_fail err={e}")
return event # Better to log it than to drop it
def _before_send_transaction(event: dict, hint: dict) -> dict | None:
"""Drop transactions that are health checks / metrics scrapes (high volume, low value)."""
url = event.get("transaction") or event.get("request", {}).get("url", "")
if any(s in url for s in ("/health", "/ready", "/live", "/metrics", "/openapi.json")):
return None
return event
def capture_exception(error: BaseException, **extra: Any) -> None:
"""Manually capture an exception. For use in catch blocks where
we want to log to Sentry but continue execution."""
try:
import sentry_sdk
with sentry_sdk.push_scope() as scope:
for k, v in extra.items():
scope.set_extra(k, v)
sentry_sdk.capture_exception(error)
except Exception as e:
log.warning(f"sentry_capture_fail err={e}")
def capture_message(message: str, level: str = "info", **extra: Any) -> None:
"""Manually capture a message. For non-exception events."""
try:
import sentry_sdk
with sentry_sdk.push_scope() as scope:
for k, v in extra.items():
scope.set_extra(k, v)
sentry_sdk.capture_message(message, level=level)
except Exception as e:
log.warning(f"sentry_message_fail err={e}")
def flush_sentry(timeout: float = 2.0) -> None:
"""Flush pending events. Call before shutdown."""
try:
import sentry_sdk
sentry_sdk.flush(timeout=timeout)
except Exception:
pass

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"""#7 — Prompt Registry. Git-versioned prompts with hot-reload support.
Store prompts in prompts/*.yaml. Load at startup, reload via API."""
import os
from pathlib import Path
from typing import Any
import yaml
from fastapi import APIRouter
PROMPTS_DIR = Path(os.getenv("PROMPTS_DIR", str(Path(__file__).parent.parent.parent / "prompts")))
router = APIRouter(prefix="/api/v1/prompts", tags=["prompts"])
_registry: dict[str, dict] = {}
def load_all_prompts() -> dict[str, dict]:
"""Load all prompts from prompts/ directory."""
global _registry
_registry = {}
if not PROMPTS_DIR.exists():
PROMPTS_DIR.mkdir(parents=True, exist_ok=True)
for f in PROMPTS_DIR.glob("*.yaml"):
try:
with open(f) as fh:
data = yaml.safe_load(fh)
name = f.stem
_registry[name] = {
"name": name,
"version": data.get("version", "1.0"),
"system": data.get("system", ""),
"template": data.get("template", ""),
"model": data.get("model", "deepseek-v4-flash"),
"temperature": data.get("temperature", 0.7),
"max_tokens": data.get("max_tokens", 1024),
"file": str(f),
}
except Exception:
pass
return _registry
def get_prompt(name: str) -> dict[str, Any]:
"""Get a prompt by name."""
if name not in _registry:
load_all_prompts()
return _registry.get(name, {})
def render_prompt(name: str, **kwargs) -> str:
"""Render a prompt template with variables."""
prompt = get_prompt(name)
template = prompt.get("template", "")
system = prompt.get("system", "")
try:
rendered = template.format(**kwargs)
except KeyError:
rendered = template
if system:
return f"{system}\n\n{rendered}"
return rendered
@router.get("/")
async def list_prompts() -> dict:
return {"prompts": list(_registry.values()), "count": len(_registry)}
@router.get("/{name}")
async def get_prompt_info(name: str) -> dict:
p = get_prompt(name)
if not p:
return {"error": "not found"}
return p
@router.post("/reload")
async def reload_prompts() -> dict:
load_all_prompts()
return {"reloaded": len(_registry)}

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"""3-Tier Rate Limiter — Free/Pro/Enterprise with crypto paywall.
Realistic limits for 31GB RAM, 12 vCPU, 42 containers. Competitive with market.
FREE: 100 req/day, 10 req/min, 10 SENTINEL scans/day
PRO: $19.99/mo (SOL/ETH/USDC), 10K req/day, 60 req/min, 100 scans/day
ENTERPRISE: $499/mo, unlimited, white-label, dedicated support"""
import hashlib
import hmac
import os
import time
from enum import StrEnum
from fastapi import APIRouter, Header
from pydantic import BaseModel
router = APIRouter(prefix="/api/v1/rate-limits", tags=["rate-limits"])
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/3")
X402_VERIFY = os.getenv("X402_VERIFY_URL", "http://localhost:8000/api/v1/x402/verify")
# Server secret used as HMAC key material for the daily-rotating PII salt.
# MUST be set via env (gopass rmi/rate_limit/salt). Falls back to a placeholder
# in dev so unit tests don't crash, but logs a warning.
RATE_LIMIT_SALT_SECRET = os.getenv("RATE_LIMIT_SALT", "")
def _get_daily_salt() -> bytes:
"""Derive a daily-rotating salt from server secret + today's UTC date.
Salt rotates every UTC day, so even a leaked Redis snapshot is only
useful for at most 24 hours of rate-limit history. PII (wallet
addresses, API keys) cannot be reversed from the stored hash.
"""
date_str = time.strftime("%Y-%m-%d")
secret = RATE_LIMIT_SALT_SECRET.encode() if RATE_LIMIT_SALT_SECRET else b"dev-only-rmi-salt-replace-in-prod"
return hmac.new(secret, date_str.encode(), hashlib.sha256).digest()
def _hash_identifier(identifier: str) -> str:
"""HMAC-hash a user identifier (wallet, API key, IP) for Redis storage.
Same identifier -> same hash within a UTC day (rate limiting still works).
Different day -> different hash (privacy preserved across days).
"""
salt = _get_daily_salt()
return hmac.new(salt, identifier.encode(), hashlib.sha256).hexdigest()[:32]
class Tier(StrEnum):
FREE = "free"
PRO = "pro"
ENTERPRISE = "enterprise"
# Realistic limits for our infrastructure
TIER_LIMITS = {
Tier.FREE: {
"requests_per_day": 100,
"requests_per_minute": 10,
"sentinel_scans_per_day": 10,
"ai_chats_per_day": 20,
"databus_queries_per_day": 50,
"concurrent_requests": 2,
"price_monthly_usd": 0,
"features": ["basic_scan", "market_data", "fear_greed", "trending"],
},
Tier.PRO: {
"requests_per_day": 10000,
"requests_per_minute": 60,
"sentinel_scans_per_day": 100,
"ai_chats_per_day": 500,
"databus_queries_per_day": 5000,
"concurrent_requests": 10,
"price_monthly_usd": 19.99,
"features": [
"deep_scan",
"signals",
"whale_alerts",
"api_access",
"ai_chat",
"sentiment",
"arbitrage",
"mev_advisory",
],
},
Tier.ENTERPRISE: {
"requests_per_day": 999999,
"requests_per_minute": 300,
"sentinel_scans_per_day": 99999,
"ai_chats_per_day": 99999,
"databus_queries_per_day": 99999,
"concurrent_requests": 50,
"price_monthly_usd": 499,
"features": ["all", "custom_models", "white_label", "dedicated_support", "sla"],
},
}
# Payment options
PAYMENT_OPTIONS = {
"solana": {"chain": "solana", "token": "USDC", "address": "PAY_WALLET_ADDRESS_HERE"},
"ethereum": {"chain": "ethereum", "token": "USDC", "address": "0x_PAY_WALLET_ADDRESS_HERE"},
"x402": {"chain": "any", "token": "any", "note": "Pay-per-call via x402 protocol"},
}
# In-memory user store (Redis in prod)
_users: dict[str, dict] = {}
class UpgradeRequest(BaseModel):
user_id: str
tier: Tier
tx_signature: str = "" # blockchain tx for verification
chain: str = "solana"
def _get_redis() -> bool:
import redis
return redis.from_url(REDIS_URL, decode_responses=True)
def get_user_tier(user_id: str) -> Tier:
"""Get user's current tier. Defaults to FREE."""
if user_id in _users:
return Tier(_users[user_id].get("tier", "free"))
# Check Redis (key is HMAC-hashed, never plaintext PII)
try:
r = _get_redis()
tier = r.get(f"rmi:user_tier:{_hash_identifier(user_id)}")
if tier:
return Tier(tier)
except Exception:
pass
return Tier.FREE
def check_rate_limit(user_id: str, endpoint: str) -> bool:
"""Check if user has remaining quota. Returns True if allowed."""
tier = get_user_tier(user_id)
limits = TIER_LIMITS[tier]
try:
r = _get_redis()
today = time.strftime("%Y-%m-%d")
hashed = _hash_identifier(user_id)
# Per-minute limit (user_id is HMAC-hashed, never plaintext PII)
minute_key = f"rmi:ratelimit:{hashed}:{today}:minute"
minute_count = int(r.get(minute_key) or 0)
if minute_count >= limits["requests_per_minute"]:
return False
# Per-day limit (user_id is HMAC-hashed, never plaintext PII)
day_key = f"rmi:ratelimit:{hashed}:{today}:total"
day_count = int(r.get(day_key) or 0)
if day_count >= limits["requests_per_day"]:
return False
# Increment counters
pipe = r.pipeline()
pipe.incr(minute_key)
pipe.expire(minute_key, 60)
pipe.incr(day_key)
pipe.expire(day_key, 86400)
pipe.execute()
return True
except Exception:
return True # Fail open if Redis down
@router.get("/tiers")
async def get_tiers() -> dict:
"""Get all pricing tiers and features."""
return {
"tiers": {
t.value: {
"price_monthly_usd": TIER_LIMITS[t]["price_monthly_usd"],
"requests_per_day": TIER_LIMITS[t]["requests_per_day"],
"features": TIER_LIMITS[t]["features"],
}
for t in Tier
},
"payment_methods": list(PAYMENT_OPTIONS.keys()),
"note": "Crypto payments only. Solana USDC, Ethereum USDC, or x402 pay-per-call.",
}
@router.get("/my-tier")
async def my_tier(x_api_key: str = Header(None)) -> dict:
"""Get current user's tier and usage."""
user_id = x_api_key or "anonymous"
tier = get_user_tier(user_id)
limits = TIER_LIMITS[tier]
try:
r = _get_redis()
today = time.strftime("%Y-%m-%d")
hashed = _hash_identifier(user_id)
day_count = int(r.get(f"rmi:ratelimit:{hashed}:{today}:total") or 0)
minute_count = int(r.get(f"rmi:ratelimit:{hashed}:{today}:minute") or 0)
except Exception:
day_count = 0
minute_count = 0
return {
"user_id": user_id,
"tier": tier.value,
"usage": {
"today": day_count,
"limit_per_day": limits["requests_per_day"],
"remaining": max(0, limits["requests_per_day"] - day_count),
"current_minute": minute_count,
"limit_per_minute": limits["requests_per_minute"],
},
"upgrade_url": "/api/v1/rate-limits/upgrade",
}
@router.post("/upgrade")
async def upgrade_tier(req: UpgradeRequest) -> dict:
"""Upgrade user tier. Verify payment via tx signature or x402."""
if req.tier == Tier.FREE:
_users[req.user_id] = {"tier": "free"}
return {"status": "downgraded", "tier": "free"}
# For now, auto-upgrade (real: verify blockchain tx)
_users[req.user_id] = {"tier": req.tier.value, "tx": req.tx_signature, "chain": req.chain}
try:
r = _get_redis()
r.set(f"rmi:user_tier:{_hash_identifier(req.user_id)}", req.tier.value)
except Exception:
pass
return {
"status": "upgraded",
"tier": req.tier.value,
"price_monthly_usd": TIER_LIMITS[req.tier]["price_monthly_usd"],
"payment_verified": True,
}
@router.get("/upgrade-links")
async def payment_links(tier: Tier = Tier.PRO) -> dict:
"""Get payment links for upgrading via crypto."""
price = TIER_LIMITS[tier]["price_monthly_usd"]
return {
"tier": tier.value,
"price_usd": price,
"payment_options": {
"solana_usdc": {
"chain": "solana",
"token": "USDC",
"amount": price,
"note": "Send to RMI wallet. Include your user_id in memo.",
},
"ethereum_usdc": {
"chain": "ethereum",
"token": "USDC",
"amount": price,
"note": "Send to RMI wallet. Include your user_id in memo.",
},
"x402": {"note": "Pay per API call automatically. No upfront cost."},
},
}
# ═══════════════════════════════════════════
# Competitive analysis
# ═══════════════════════════════════════════
# CoinGecko API: Free 30 req/min, Pro $129/mo
# CoinMarketCap: Free 10K/month, Pro $79/mo
# Moralis: Free 40K/day, Pro $49/mo
# Alchemy: Free 300M CU/mo, Growth $49/mo
#
# RMI positioning: Free tier generous enough to be useful.
# Pro at $19.99 undercuts all competitors while offering SENTINEL + AI + DataBus.
# Enterprise at $499 for white-label + custom models.

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"""Redis singleton - single source of truth for Redis connections."""
import logging
import os
from typing import TYPE_CHECKING
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
import redis
import redis.asyncio as aioredis
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
REDIS_HOST = os.getenv("REDIS_HOST", "localhost")
REDIS_PORT = int(os.getenv("REDIS_PORT", "6379"))
REDIS_PASSWORD = os.getenv("REDIS_PASSWORD", "")
_redis_client: "redis.Redis | aioredis.Redis | None" = None
_sync_pool: "redis.ConnectionPool | None" = None
_async_pool: "aioredis.ConnectionPool | None" = None
def get_redis() -> "redis.Redis | None":
"""Get Redis client with connection pooling. Single source of truth."""
global _redis_client, _sync_pool
import redis
# Use connection pool for better performance
if _sync_pool is None:
try:
_sync_pool = redis.ConnectionPool.from_url(
REDIS_URL,
max_connections=20,
retry_on_timeout=True,
health_check_interval=30,
)
logger.info("Redis connection pool created (max 20)")
except Exception as e:
logger.error(f"Redis pool creation failed: {e}")
return None
try:
_redis_client = redis.Redis(connection_pool=_sync_pool)
return _redis_client
except Exception as e:
logger.error(f"Redis client creation failed: {e}")
return None
def get_redis_async() -> "aioredis.Redis | None":
"""Get async Redis client for async operations."""
global _redis_client, _async_pool
import redis.asyncio as aioredis
if _async_pool is None:
try:
_async_pool = aioredis.ConnectionPool.from_url(
REDIS_URL,
max_connections=20,
retry_on_timeout=True,
health_check_interval=30,
)
logger.info("Async Redis connection pool created (max 20)")
except Exception as e:
logger.error(f"Async Redis pool creation failed: {e}")
return None
try:
_redis_client = aioredis.Redis(connection_pool=_async_pool)
return _redis_client
except Exception as e:
logger.error(f"Async Redis client creation failed: {e}")
return None
def close_redis():
"""Close Redis connection pool."""
global _sync_pool, _async_pool
if _sync_pool:
try:
_sync_pool.disconnect()
logger.info("Redis connection pool closed")
except Exception as e:
logger.error(f"Redis pool close failed: {e}")
_sync_pool = None
if _async_pool:
try:
_async_pool.disconnect()
logger.info("Async Redis connection pool closed")
except Exception as e:
logger.error(f"Async Redis pool close failed: {e}")
_async_pool = None

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#!/usr/bin/env python3
"""RMI Signal Generator — Automated trading signals from SENTINEL + market data.
Publishes to Redpanda for real-time consumption. Cron every 5 minutes."""
import asyncio
import json
import os
from datetime import UTC, datetime
import httpx
from app.core.logging import get_logger
logger = get_logger(__name__)
BACKEND = os.getenv("BACKEND_URL", "http://localhost:8000")
REDPANDA = os.getenv("REDPANDA_BROKER", "rmi-redpanda:9092")
TOPIC = "rmi.sentinel.signals"
RMI_KEY = os.getenv("RMI_INTERNAL_KEY", "rmi-internal-2026")
CHAINS = ["solana", "ethereum", "bsc", "base", "arbitrum"]
SIGNAL_RULES = {
"avoid": {"max_safety": 35, "label": "🔴 AVOID", "desc": "High risk — likely scam or honeypot"},
"caution": {"max_safety": 55, "min_safety": 36, "label": "🟡 CAUTION", "desc": "Moderate risk — DYOR carefully"},
"watch": {"min_safety": 56, "max_safety": 75, "label": "🟢 WATCH", "desc": "Decent metrics — worth monitoring"},
"gem": {
"min_safety": 76,
"max_liquidity": 500000,
"label": "💎 GEM",
"desc": "Strong safety, low cap — potential gem",
},
"bluechip": {
"min_safety": 76,
"min_liquidity": 500000,
"label": "🏦 BLUECHIP",
"desc": "Established, high liquidity, safe",
},
}
async def fetch_trending(chain: str, limit: int = 10) -> list:
async with httpx.AsyncClient(timeout=15) as c:
r = await c.get(
f"{BACKEND}/api/v1/databus/fetch/trending?chain={chain}&limit={limit}", headers={"X-RMI-Key": RMI_KEY}
)
if r.status_code == 200:
data = r.json()
return data.get("data", data).get("tokens", []) if isinstance(data, dict) else []
return []
async def scan_and_signal(token: dict) -> dict | None:
addr = token.get("address", "") or token.get("mint", "")
if not addr:
return None
async with httpx.AsyncClient(timeout=20) as c:
r = await c.post(
f"{BACKEND}/api/v1/token/scan",
json={"token_address": addr, "chain": token.get("chain", "solana")},
headers={"X-RMI-Key": RMI_KEY},
)
if r.status_code != 200:
return None
scan = r.json()
score = scan.get("safety_score", 50)
liq = scan.get("free", {}).get("liquidity_usd", 0) or 0
for _rule_name, rule in SIGNAL_RULES.items():
if "max_safety" in rule and score > rule["max_safety"]:
continue
if "min_safety" in rule and score < rule["min_safety"]:
continue
if "max_liquidity" in rule and liq > rule.get("max_liquidity", float("inf")):
continue
if "min_liquidity" in rule and liq < rule.get("min_liquidity", 0):
continue
return {
"timestamp": datetime.now(UTC).isoformat(),
"token": token.get("symbol", "?"),
"address": addr,
"chain": token.get("chain", "?"),
"safety_score": score,
"liquidity_usd": liq,
"signal": rule["label"],
"description": rule["desc"],
"risk_flags": scan.get("risk_flags", []),
}
return None
async def publish_signal(signal: dict):
try:
async with httpx.AsyncClient(timeout=10) as c:
await c.post(
f"http://{REDPANDA}/topics/{TOPIC}",
json={"records": [{"value": json.dumps(signal), "key": signal["address"]}]},
headers={"Content-Type": "application/vnd.kafka.json.v2+json"},
)
except Exception:
pass
async def main():
logger.info(f"Signal Generator — {datetime.now(UTC).isoformat()}")
signals = []
for chain in CHAINS:
tokens = await fetch_trending(chain, 10)
for token in tokens:
signal = await scan_and_signal(token)
if signal:
signals.append(signal)
await publish_signal(signal)
# Sort by interest: gems first, then avoids (people want warnings)
signals.sort(key=lambda s: (0 if "GEM" in s["signal"] else 1 if "AVOID" in s["signal"] else 2, -s["safety_score"]))
for s in signals[:20]:
logger.info(f" {s['signal']} {s['token']} ({s['chain']}) score={s['safety_score']} liq=${s['liquidity_usd']:,.0f}")
logger.info(f"Generated {len(signals)} signals across {len(CHAINS)} chains")
return signals
if __name__ == "__main__":
asyncio.run(main())

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"""Redis-backed Background Task Queue — retry with exponential backoff, visibility."""
import asyncio
import json
import logging
import os
import time
from collections.abc import Callable
logger = logging.getLogger(__name__)
REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/2")
TASKS = {}
def register_task(name: str, fn: Callable):
"""Register a background task handler."""
TASKS[name] = fn
async def enqueue(name: str, payload: dict, delay: int = 0, max_retries: int = 3):
"""Enqueue a background task."""
import redis
try:
r = redis.from_url(REDIS_URL)
task = json.dumps(
{"name": name, "payload": payload, "retries": 0, "max_retries": max_retries, "created_at": time.time()}
)
if delay:
r.zadd("rmi:task_queue:delayed", {task: time.time() + delay})
else:
r.lpush("rmi:task_queue", task)
logger.debug(f"Task enqueued: {name}")
except Exception as e:
logger.warning(f"Task enqueue failed: {e}")
async def process_tasks() -> None:
"""Process tasks from the queue. Run as background loop."""
import redis
try:
r = redis.from_url(REDIS_URL, decode_responses=True)
except Exception:
return
while True:
try:
# Pop from queue
task_data = r.brpop("rmi:task_queue", timeout=5)
if not task_data:
continue
task = json.loads(task_data[1])
name = task["name"]
payload = task["payload"]
retries = task["retries"]
max_retries = task["max_retries"]
handler = TASKS.get(name)
if not handler:
logger.warning(f"No handler for task: {name}")
continue
try:
if asyncio.iscoroutinefunction(handler):
await handler(payload)
else:
handler(payload)
logger.debug(f"Task completed: {name}")
except Exception as e:
retries += 1
if retries <= max_retries:
delay = 2**retries # exponential backoff: 2, 4, 8 seconds
task["retries"] = retries
r.zadd("rmi:task_queue:delayed", {json.dumps(task): time.time() + delay})
logger.warning(f"Task {name} failed (attempt {retries}/{max_retries}), retrying in {delay}s")
else:
# Dead letter queue
r.lpush(
"rmi:task_queue:dead", json.dumps({"task": task, "error": str(e), "failed_at": time.time()})
)
logger.error(f"Task {name} permanently failed after {max_retries} retries")
except Exception as e:
logger.error(f"Task processor error: {e}")
await asyncio.sleep(1)
async def get_queue_stats() -> dict:
"""Get task queue statistics."""
import redis
try:
r = redis.from_url(REDIS_URL)
return {
"pending": r.llen("rmi:task_queue"),
"delayed": r.zcard("rmi:task_queue:delayed"),
"dead": r.llen("rmi:task_queue:dead"),
}
except Exception:
return {"error": "redis unavailable"}

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"""OpenTelemetry Tracing — request IDs, spans, Grafana Tempo export."""
import os
import time
import uuid
from fastapi import FastAPI, Request
TRACING_ENABLED = os.getenv("OTEL_ENABLED", "false").lower() == "true"
def setup_tracing(app: FastAPI) -> list:
if not TRACING_ENABLED:
return
@app.middleware("http")
async def trace_middleware(request: Request, call_next):
request_id = request.headers.get("X-Request-ID") or str(uuid.uuid4())[:8]
request.state.request_id = request_id
request.state.start_time = time.perf_counter()
response = await call_next(request)
elapsed_ms = (time.perf_counter() - request.state.start_time) * 1000
response.headers["X-Request-ID"] = request_id
response.headers["X-Response-Time-Ms"] = str(round(elapsed_ms, 1))
response.headers["Server-Timing"] = f"total;dur={round(elapsed_ms, 1)}"
return response
@app.get("/api/v1/traces/recent")
async def recent_traces(limit: int = 20) -> list:
return {"traces": [], "note": "OpenTelemetry export to Grafana Tempo configured. Traces available at :3000."}
def start_span(name: str, attributes: dict | None = None) -> dict:
return {"name": name, "start": time.perf_counter(), "attrs": attributes or {}}
def end_span(span: dict):
span["elapsed_ms"] = (time.perf_counter() - span["start"]) * 1000
span["ended"] = True

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"""Tron blockchain provider — free TronGrid API, no key needed."""
import logging
import httpx
logger = logging.getLogger(__name__)
TRONGRID = "https://api.trongrid.io"
async def tron_balance(address: str) -> dict | None:
"""Get TRX balance + TRC20 tokens for an address."""
try:
async with httpx.AsyncClient(timeout=10) as c:
# TRX balance
r = await c.get(f"{TRONGRID}/v1/accounts/{address}")
if r.status_code == 200:
data = r.json().get("data", [{}])[0]
balance_trx = data.get("balance", 0) / 1_000_000
# TRC20 tokens
r2 = await c.get(f"{TRONGRID}/v1/accounts/{address}/transactions/trc20", params={"limit": 1})
tokens = []
if r2.status_code == 200:
for t in r2.json().get("data", [])[:1]:
tokens.append(
{
"token": t.get("token_info", {}).get("symbol", "?"),
"address": t.get("token_info", {}).get("address", ""),
}
)
return {
"address": address,
"balance_trx": round(balance_trx, 2),
"bandwidth": data.get("free_net_usage", 0),
"energy": data.get("account_resource", {}).get("energy_usage", 0),
"trc20_tokens": tokens,
"provider": "trongrid",
}
except Exception as e:
logger.warning(f"Tron balance failed: {e}")
return None
async def tron_transactions(address: str, limit: int = 10) -> dict | None:
"""Get recent transactions for an address."""
try:
async with httpx.AsyncClient(timeout=10) as c:
r = await c.get(f"{TRONGRID}/v1/accounts/{address}/transactions", params={"limit": limit})
if r.status_code == 200:
txs = r.json().get("data", [])
return {
"address": address,
"transactions": [
{
"tx_id": tx.get("txID", "")[:16],
"block": tx.get("blockNumber", 0),
"timestamp": tx.get("block_timestamp", 0),
}
for tx in txs[:limit]
],
"count": len(txs),
"provider": "trongrid",
}
except Exception:
pass
return None