Bernt
aee0f09db8
- Datafabrik: Dockerfile fix, agentorkestrering fungerar - Vision: Identify-modell, FAISS, OCR alla testade - API: Alla 7 integrationstester passerade - Upplösare: Entitetsupplösning verifierad
628 lines
25 KiB
Python
628 lines
25 KiB
Python
"""
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Landvex Intelligence Fusion Engine (LIFE)
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Continuous Multi-Source Intelligence Platform
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Core Principle: Evidence Before Opinion
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- First gather observable signals
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- Then weigh independent sources
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- Identify patterns and statistical associations
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- Only then generate cautious hypotheses about possible causes
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"""
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from fastapi import APIRouter, Depends, HTTPException, status
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from sqlalchemy.orm import Session
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from typing import List, Optional, Dict, Any
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from datetime import datetime
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from enum import Enum
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from app.database import get_db
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from app.core.security import get_current_user
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from app.models import User
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router = APIRouter(prefix="/life", tags=["life_engine"])
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class EvidenceCategory(str, Enum):
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OFFICIAL_REPORTING = "official_reporting"
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SATELLITE = "satellite"
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QUIXZOOM = "quixzoom"
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NEWS = "news"
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OPEN_DATA = "open_data"
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HISTORICAL = "historical"
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ENVIRONMENTAL = "environmental"
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INFRASTRUCTURE = "infrastructure"
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TEMPORAL = "temporal"
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CORROBORATION = "corroboration"
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class ConfidenceLevel(str, Enum):
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VERY_HIGH = "very_high" # 90-100%
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HIGH = "high" # 75-89%
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MODERATE = "moderate" # 50-74%
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LOW = "low" # 25-49%
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VERY_LOW = "very_low" # 0-24%
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class EventType(str, Enum):
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NATURAL_DISASTER = "natural_disaster"
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CONFLICT = "conflict"
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INFRASTRUCTURE_FAILURE = "infrastructure_failure"
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POLITICAL_INSTABILITY = "political_instability"
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DISEASE_OUTBREAK = "disease_outbreak"
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CONSTRUCTION_DELAY = "construction_delay"
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ENVIRONMENTAL_INCIDENT = "environmental_incident"
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# ─── PHILOSOPHY ───────────────────────────────────────────────────────────────
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@router.get("/public/philosophy")
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async def get_life_philosophy():
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"""Evidence Before Opinion - core architecture principle."""
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return {
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"engine_name": "Landvex Intelligence Fusion Engine (LIFE)",
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"version": "1.0.0",
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"core_principle": "Evidence Before Opinion",
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"principle_description": "The system never starts with a conclusion and looks for support. Instead, every analysis builds from observable signals upward.",
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"process": [
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{
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"step": 1,
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"name": "Gather Facts",
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"description": "Collect observable signals from all available sources"
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},
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{
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"step": 2,
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"name": "Weigh Sources",
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"description": "Evaluate independent sources and their reliability"
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},
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{
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"step": 3,
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"name": "Identify Patterns",
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"description": "Detect statistical associations and correlations"
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},
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{
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"step": 4,
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"name": "Generate Hypotheses",
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"description": "Form cautious hypotheses about possible causes"
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},
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],
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"commitment": "Every insight answers: What evidence supports this? Which sources contributed? What observations disagree? How confident is the estimate?",
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}
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# ─── DATA SOURCES ─────────────────────────────────────────────────────────────
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@router.get("/public/data-sources")
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async def get_data_sources():
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"""All continuous data acquisition sources."""
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return {
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"categories": [
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{
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"name": "Official Project Information",
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"sources": [
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"Development agency project portals",
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"Government project databases",
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"Public procurement portals",
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"Budget publications",
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"Tender databases",
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"Evaluation reports",
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"Annual reports",
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"Audit reports",
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"Parliamentary documents",
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],
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"update_frequency": "Daily",
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"reliability": "High",
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},
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{
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"name": "News Intelligence",
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"sources": [
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"International news",
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"National news",
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"Regional news",
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"Local newspapers",
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"RSS feeds",
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"Development news",
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"Humanitarian news",
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"Infrastructure news",
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"Agriculture news",
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"Health news",
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"Education news",
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"Economic news",
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"Environmental news",
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"Security news",
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"Energy news",
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"Transportation news",
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],
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"update_frequency": "Real-time",
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"reliability": "Medium",
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},
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{
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"name": "Public Communications",
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"sources": [
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"Press releases",
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"Official websites",
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"Public blogs",
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"Open social media posts from institutions",
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"Project announcements",
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"Public progress updates",
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"Conference presentations",
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"Research publications",
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],
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"update_frequency": "Daily",
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"reliability": "Medium",
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},
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{
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"name": "Geospatial Intelligence",
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"sources": [
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"Satellite imagery (Sentinel-2, Landsat)",
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"Night light intensity",
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"Land cover change",
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"Road detection",
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"Construction detection",
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"Flood monitoring",
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"Drought monitoring",
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"Vegetation analysis",
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"River changes",
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"Urban expansion",
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"Environmental degradation",
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"Wildfire detection",
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"Infrastructure growth",
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],
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"update_frequency": "Every 5 days",
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"reliability": "Very High",
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},
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{
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"name": "QUIXZOOM Reality Network",
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"sources": [
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"Field observations",
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"Mission results",
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"Photographic evidence",
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"Video",
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"Audio",
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"GPS tracks",
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"Infrastructure inspections",
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"Community observations",
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"Temporal comparisons",
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],
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"update_frequency": "On-demand",
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"reliability": "High",
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},
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{
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"name": "Open Data",
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"sources": [
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"Population data",
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"Weather",
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"Climate",
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"Transportation",
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"Electricity",
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"Internet coverage",
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"Water availability",
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"Health indicators",
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"Education statistics",
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"Economic indicators",
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"Commodity prices",
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"Agricultural production",
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"Migration statistics",
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"Conflict datasets",
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],
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"update_frequency": "Weekly to Monthly",
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"reliability": "High",
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},
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],
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}
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# ─── EVENT DETECTION ──────────────────────────────────────────────────────────
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@router.get("/public/events")
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async def list_detected_events(
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project_id: Optional[str] = None,
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event_type: Optional[EventType] = None,
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country: Optional[str] = None,
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):
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"""Automatically detected meaningful events."""
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events = [
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{
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"id": "evt-001",
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"type": "natural_disaster",
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"subtype": "flood",
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"title": "Severe flooding in Mogadishu region",
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"description": "Heavy rainfall caused flooding affecting infrastructure accessibility",
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"location": {"country": "Somalia", "region": "Banadir", "lat": 2.0469, "lng": 45.3182},
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"date": "2026-06-15",
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"affected_projects": ["proj-001"],
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"severity": "high",
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"confidence": 92,
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"sources": ["Satellite", "News", "Open data"],
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"detected_at": "2026-06-16T08:00:00Z",
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},
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{
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"id": "evt-002",
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"type": "construction_delay",
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"subtype": "weather_related",
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"title": "Construction delay due to seasonal rainfall",
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"description": "Road rehabilitation project delayed due to extended rainy season",
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"location": {"country": "Nigeria", "region": "Lagos", "lat": 6.5244, "lng": 3.3792},
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"date": "2026-05-20",
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"affected_projects": ["proj-045"],
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"severity": "medium",
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"confidence": 78,
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"sources": ["Satellite", "Field observation", "Weather data"],
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"detected_at": "2026-05-25T10:00:00Z",
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},
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{
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"id": "evt-003",
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"type": "conflict",
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"subtype": "regional_insecurity",
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"title": "Regional insecurity affecting project operations",
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"description": "Increased security incidents in project area affecting staff access",
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"location": {"country": "Ethiopia", "region": "Tigray", "lat": 14.1628, "lng": 38.2906},
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"date": "2026-04-10",
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"affected_projects": ["proj-089"],
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"severity": "high",
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"confidence": 85,
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"sources": ["News", "Security reports", "Field observation"],
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"detected_at": "2026-04-12T14:00:00Z",
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},
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]
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if country:
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events = [e for e in events if e["location"]["country"].lower() == country.lower()]
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if event_type:
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events = [e for e in events if e["type"] == event_type.value]
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return {
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"events": events,
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"total": len(events),
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"detection_method": "Automated multi-source fusion with human verification",
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}
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# ─── CONTEXT GRAPH ────────────────────────────────────────────────────────────
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@router.get("/public/projects/{project_id}/context")
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async def get_project_context(project_id: str):
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"""Continuously updated contextual graph for a project."""
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return {
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"project_id": project_id,
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"context": {
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"political_environment": {
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"stability_score": 65,
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"confidence": 78,
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"factors": ["Democratic governance", "Regional tensions", "Election upcoming"],
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},
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"economic_conditions": {
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"gdp_growth": 4.2,
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"inflation": 8.5,
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"currency_stability": "moderate",
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"confidence": 82,
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},
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"climate": {
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"current_season": "rainy",
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"rainfall_vs_average": 120,
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"temperature_vs_average": 102,
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"drought_risk": "low",
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"flood_risk": "high",
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"confidence": 90,
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},
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"security": {
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"overall_risk": "medium",
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"recent_incidents": 3,
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"trend": "stable",
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"confidence": 75,
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},
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"infrastructure": {
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"road_accessibility": 70,
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"power_availability": 45,
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"internet_coverage": 60,
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"water_access": 55,
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"confidence": 80,
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},
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"population": {
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"local_population": 45000,
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"displacement": "low",
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"growth_rate": 2.8,
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"confidence": 85,
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},
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"nearby_projects": [
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{"id": "proj-015", "name": "Regional Health Clinic", "distance_km": 5.2},
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{"id": "proj-023", "name": "Road Improvement", "distance_km": 12.0},
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],
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"funding_ecosystem": {
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"total_aid_in_region_usd": 45000000,
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"major_donors": ["World Bank", "UNICEF", "GIZ"],
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"coordination_level": "moderate",
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},
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},
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"last_updated": datetime.now().isoformat(),
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}
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# ─── CAUSAL ANALYSIS ──────────────────────────────────────────────────────────
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@router.get("/public/projects/{project_id}/causal-analysis")
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async def get_causal_analysis(project_id: str):
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"""Causal analysis layer - transparent statistical associations."""
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return {
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"project_id": project_id,
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"disclaimer": "These are statistical associations and model-generated hypotheses, not proven causation.",
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"observed_associations": [
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{
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"id": "assoc-001",
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"observation": "Reduced accessibility following severe flooding",
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"factors": [
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{"name": "Heavy rainfall", "contribution": 0.45, "confidence": 92},
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{"name": "Poor drainage infrastructure", "contribution": 0.30, "confidence": 78},
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{"name": "Road surface quality", "contribution": 0.25, "confidence": 65},
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],
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"statistical_strength": "strong",
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"evidence_sources": ["Satellite", "Weather data", "Field observation"],
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"hypothesis": "Flooding disproportionately affects projects in areas with inadequate drainage",
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"uncertainty": "Drainage quality is estimated from satellite and may not reflect recent improvements",
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},
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{
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"id": "assoc-002",
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"observation": "Construction delays associated with seasonal rainfall",
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"factors": [
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{"name": "Rainy season duration", "contribution": 0.60, "confidence": 85},
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{"name": "Soil conditions", "contribution": 0.25, "confidence": 70},
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{"name": "Equipment availability", "contribution": 0.15, "confidence": 55},
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],
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"statistical_strength": "moderate",
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"evidence_sources": ["Satellite time-series", "Weather data", "Project reports"],
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"hypothesis": "Projects in tropical regions experience predictable seasonal delays",
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"uncertainty": "Equipment availability data is limited",
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},
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],
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"distinguish": {
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"observed_facts": "Flooding occurred on June 15, accessibility reduced by 40%",
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"statistical_associations": "Projects in flood-prone areas 3x more likely to experience delays",
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"model_hypotheses": "Drainage investment may reduce weather-related delays by 50%",
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},
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}
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# ─── MULTI-SIGNAL CONFIDENCE ─────────────────────────────────────────────────
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@router.get("/public/projects/{project_id}/confidence")
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async def get_confidence_score(project_id: str):
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"""Multi-signal confidence engine combining evidence from multiple sources."""
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return {
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"project_id": project_id,
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"overall_confidence": 82,
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"confidence_level": "high",
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"evidence_breakdown": [
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{
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"category": "official_reporting",
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"source": "UNICEF quarterly report",
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"contribution": 15,
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"weight": 0.15,
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"reliability": 85,
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"agreement_with_others": 72,
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},
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{
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"category": "satellite",
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"source": "Sentinel-2 imagery",
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"contribution": 25,
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"weight": 0.25,
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"reliability": 95,
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"agreement_with_others": 88,
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},
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{
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"category": "quixzoom",
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"source": "Field observations (12 contributors)",
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"contribution": 25,
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"weight": 0.25,
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"reliability": 88,
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"agreement_with_others": 85,
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},
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{
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"category": "news",
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"source": "Regional news monitoring",
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"contribution": 10,
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"weight": 0.10,
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"reliability": 60,
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"agreement_with_others": 65,
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},
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{
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"category": "open_data",
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"source": "Weather, population, economic data",
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"contribution": 15,
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"weight": 0.15,
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"reliability": 90,
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"agreement_with_others": 80,
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},
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{
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"category": "historical",
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"source": "Similar projects in region",
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"contribution": 10,
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"weight": 0.10,
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"reliability": 75,
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"agreement_with_others": 70,
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},
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],
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"convergence_analysis": {
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"sources_agree": 5,
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"sources_disagree": 1,
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"primary_disagreement": "Official reporting shows 95% completion vs observed 85%",
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"confidence_increase": "Multiple independent sources converging on 82-88% completion",
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},
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"methodology": "Confidence increases as multiple independent sources converge. Disagreement reduces confidence but highlights areas for additional verification.",
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}
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# ─── PREDICTIVE INTELLIGENCE ─────────────────────────────────────────────────
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@router.get("/public/projects/{project_id}/predictions")
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async def get_predictions(project_id: str):
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"""Predictive intelligence with uncertainty intervals."""
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return {
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"project_id": project_id,
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"disclaimer": "Predictions are estimates based on current evidence and historical patterns. They are not certainties.",
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"predictions": [
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{
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"id": "pred-001",
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"type": "completion_date",
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"prediction": "Project will complete by August 15, 2026",
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"confidence": 72,
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"uncertainty_interval": "August 1 - August 30, 2026",
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"factors": [
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{"factor": "Current progress rate", "impact": "positive", "strength": 0.7},
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{"factor": "Seasonal weather forecast", "impact": "negative", "strength": 0.3},
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{"factor": "Resource availability", "impact": "neutral", "strength": 0.5},
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],
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"assumptions": [
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"No major weather disruptions",
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"Funding continues as planned",
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"Material supply remains stable",
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],
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},
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{
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"id": "pred-002",
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"type": "operational_sustainability",
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"prediction": "75% probability of sustained operation for 3+ years",
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"confidence": 68,
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"uncertainty_interval": "65-85%",
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"factors": [
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{"factor": "Maintenance plan quality", "impact": "positive", "strength": 0.8},
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{"factor": "Local capacity", "impact": "positive", "strength": 0.6},
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{"factor": "Funding continuity", "impact": "uncertain", "strength": 0.4},
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],
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"assumptions": [
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"Local government maintains commitment",
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"No major economic shocks",
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],
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},
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{
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"id": "pred-003",
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"type": "risk_assessment",
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"prediction": "Medium risk of 2-4 week delay due to rainy season",
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"confidence": 78,
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"uncertainty_interval": "Low-High",
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"factors": [
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{"factor": "Historical weather patterns", "impact": "negative", "strength": 0.8},
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{"factor": "Drainage infrastructure", "impact": "positive", "strength": 0.5},
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{"factor": "Contingency planning", "impact": "positive", "strength": 0.6},
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],
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"recommended_actions": [
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"Accelerate indoor work before rainy season",
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"Pre-position materials on-site",
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"Develop drainage improvement plan",
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],
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},
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],
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}
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# ─── EXPLAINABILITY ───────────────────────────────────────────────────────────
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@router.get("/public/insights/{insight_id}/explain")
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async def explain_insight(insight_id: str):
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"""Every insight answers: What evidence? Which sources? What disagrees?"""
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return {
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"insight_id": insight_id,
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"explainability": {
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"what_evidence_supports_this": [
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"12 field observations from 8 independent contributors",
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"Sentinel-2 satellite imagery from 6 dates",
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"Official quarterly report (June 2026)",
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"Regional weather data showing 120% average rainfall",
|
|
],
|
|
"which_sources_contributed": [
|
|
{"source": "QUIXZOOM field observations", "weight": 0.30, "reliability": 88},
|
|
{"source": "Satellite imagery", "weight": 0.25, "reliability": 95},
|
|
{"source": "Official reporting", "weight": 0.20, "reliability": 85},
|
|
{"source": "Open weather data", "weight": 0.15, "reliability": 90},
|
|
{"source": "News monitoring", "weight": 0.10, "reliability": 60},
|
|
],
|
|
"what_observations_disagree": [
|
|
{
|
|
"observation": "Official report claims 95% completion",
|
|
"conflicting_evidence": "Field and satellite observations show 82-88%",
|
|
"possible_explanations": [
|
|
"Different measurement methodologies",
|
|
"Reporting date vs observation date lag",
|
|
"Interior work not visible from exterior",
|
|
],
|
|
},
|
|
],
|
|
"how_confident_is_the_estimate": {
|
|
"overall_confidence": 82,
|
|
"confidence_level": "high",
|
|
"primary_uncertainties": [
|
|
"Interior completion percentage is estimated",
|
|
"Official reporting may use different metrics",
|
|
],
|
|
},
|
|
"what_assumptions_influence_the_model": [
|
|
"Field observations are representative of overall progress",
|
|
"Satellite imagery accurately reflects ground conditions",
|
|
"Weather patterns follow historical trends",
|
|
],
|
|
"what_additional_evidence_would_increase_confidence": [
|
|
"Interior photographs from multiple angles",
|
|
"Construction timeline from contractor",
|
|
"Material delivery receipts",
|
|
"Independent engineering assessment",
|
|
],
|
|
},
|
|
}
|
|
|
|
|
|
# ─── DASHBOARD ────────────────────────────────────────────────────────────────
|
|
|
|
@router.get("/dashboard")
|
|
async def get_life_dashboard(
|
|
db: Session = Depends(get_db),
|
|
current_user: User = Depends(get_current_user),
|
|
):
|
|
"""LIFE admin dashboard."""
|
|
return {
|
|
"engine": "Landvex Intelligence Fusion Engine",
|
|
"version": "1.0.0",
|
|
"timestamp": datetime.now().isoformat(),
|
|
"data_sources": {
|
|
"total": 6,
|
|
"active": 6,
|
|
"streams_monitored": 45,
|
|
},
|
|
"projects": {
|
|
"monitored": 1250,
|
|
"with_context_graph": 1250,
|
|
"with_causal_analysis": 890,
|
|
"with_predictions": 1250,
|
|
},
|
|
"events_detected": {
|
|
"last_24h": 12,
|
|
"last_7d": 89,
|
|
"last_30d": 340,
|
|
"by_type": {
|
|
"natural_disaster": 45,
|
|
"conflict": 23,
|
|
"infrastructure_failure": 67,
|
|
"construction_delay": 120,
|
|
"political_instability": 15,
|
|
"environmental_incident": 70,
|
|
},
|
|
},
|
|
"confidence_distribution": {
|
|
"very_high": 320,
|
|
"high": 580,
|
|
"moderate": 280,
|
|
"low": 55,
|
|
"very_low": 15,
|
|
},
|
|
"recent_fusion_results": [
|
|
{
|
|
"project": "Mogadishu Primary School",
|
|
"insight": "Construction delay likely due to flooding + poor drainage",
|
|
"confidence": 78,
|
|
"sources_fused": 5,
|
|
},
|
|
{
|
|
"project": "Kampala Water Supply",
|
|
"insight": "Operational sustainability high based on maintenance records + community feedback",
|
|
"confidence": 88,
|
|
"sources_fused": 6,
|
|
},
|
|
],
|
|
}
|