Use Jev for crash report screening

curl -sS https://router.flatkey.ai/api/alpha/decisions \
  -H "Authorization: Bearer $FLATKEY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "typesafe/jev-1.13",
  "state": "Coded severity: property damage only. Narrative: V1 was northbound on SR-9 when the driver looked down at a phone and struck the rear of V2, which was stopped for a red light. The V2 driver complained of neck pain at the scene and was transported by EMS. Both vehicles were towed.",
  "questions": {
    "crash_type": {
      "type": "choice",
      "instructions": "What kind of collision does the narrative describe?",
      "criteria": {
        "rear_end": "One vehicle strikes the back of another travelling in the same direction",
        "angle": "Vehicles collide at an angle, typically at an intersection or driveway",
        "head_on": "Front-to-front collision between vehicles travelling in opposite directions",
        "sideswipe": "Side-to-side contact between vehicles travelling in parallel",
        "single_vehicle": "One vehicle leaves the road or hits a fixed object or animal",
        "ped_cyclist": "A pedestrian or cyclist is struck"
      }
    },
    "injury_severity": {
      "type": "score",
      "instructions": "Most severe injury the narrative describes (KABCO-style scale).",
      "criteria": [
        "no_injury",
        "possible",
        "minor",
        "serious",
        "fatal"
      ]
    },
    "primary_factor": {
      "type": "choice",
      "instructions": "Which contributing factor does the narrative point to most?",
      "criteria": {
        "distraction": "Phone use, looking away or other inattention",
        "speed": "Speeding or driving too fast for conditions",
        "impairment": "Alcohol, drugs or fatigue",
        "road_weather": "Road surface, visibility or weather",
        "unknown": "The narrative does not indicate a factor"
      }
    },
    "contradicts_coding": {
      "type": "noul",
      "instructions": "The narrative describes an injury, fatality or factor that the coded fields in the state do not reflect."
    }
  }
}'

// Node.js 18+ (built-in fetch). Run: FLATKEY_API_KEY=... node jev.mjs
const body = {
  "model": "typesafe/jev-1.13",
  "state": "Coded severity: property damage only. Narrative: V1 was northbound on SR-9 when the driver looked down at a phone and struck the rear of V2, which was stopped for a red light. The V2 driver complained of neck pain at the scene and was transported by EMS. Both vehicles were towed.",
  "questions": {
    "crash_type": {
      "type": "choice",
      "instructions": "What kind of collision does the narrative describe?",
      "criteria": {
        "rear_end": "One vehicle strikes the back of another travelling in the same direction",
        "angle": "Vehicles collide at an angle, typically at an intersection or driveway",
        "head_on": "Front-to-front collision between vehicles travelling in opposite directions",
        "sideswipe": "Side-to-side contact between vehicles travelling in parallel",
        "single_vehicle": "One vehicle leaves the road or hits a fixed object or animal",
        "ped_cyclist": "A pedestrian or cyclist is struck"
      }
    },
    "injury_severity": {
      "type": "score",
      "instructions": "Most severe injury the narrative describes (KABCO-style scale).",
      "criteria": [
        "no_injury",
        "possible",
        "minor",
        "serious",
        "fatal"
      ]
    },
    "primary_factor": {
      "type": "choice",
      "instructions": "Which contributing factor does the narrative point to most?",
      "criteria": {
        "distraction": "Phone use, looking away or other inattention",
        "speed": "Speeding or driving too fast for conditions",
        "impairment": "Alcohol, drugs or fatigue",
        "road_weather": "Road surface, visibility or weather",
        "unknown": "The narrative does not indicate a factor"
      }
    },
    "contradicts_coding": {
      "type": "noul",
      "instructions": "The narrative describes an injury, fatality or factor that the coded fields in the state do not reflect."
    }
  }
};

const res = await fetch("https://router.flatkey.ai/api/alpha/decisions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.FLATKEY_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify(body),
});
if (!res.ok) throw new Error(`Jev request failed: ${res.status} ${await res.text()}`);
const { answers, usage } = await res.json();
console.log(JSON.stringify(answers, null, 2), usage);

# Python 3.8+ (pip install requests). Run: FLATKEY_API_KEY=... python jev.py
import json, os, requests

body = json.loads(r"""{
  "model": "typesafe/jev-1.13",
  "state": "Coded severity: property damage only. Narrative: V1 was northbound on SR-9 when the driver looked down at a phone and struck the rear of V2, which was stopped for a red light. The V2 driver complained of neck pain at the scene and was transported by EMS. Both vehicles were towed.",
  "questions": {
    "crash_type": {
      "type": "choice",
      "instructions": "What kind of collision does the narrative describe?",
      "criteria": {
        "rear_end": "One vehicle strikes the back of another travelling in the same direction",
        "angle": "Vehicles collide at an angle, typically at an intersection or driveway",
        "head_on": "Front-to-front collision between vehicles travelling in opposite directions",
        "sideswipe": "Side-to-side contact between vehicles travelling in parallel",
        "single_vehicle": "One vehicle leaves the road or hits a fixed object or animal",
        "ped_cyclist": "A pedestrian or cyclist is struck"
      }
    },
    "injury_severity": {
      "type": "score",
      "instructions": "Most severe injury the narrative describes (KABCO-style scale).",
      "criteria": [
        "no_injury",
        "possible",
        "minor",
        "serious",
        "fatal"
      ]
    },
    "primary_factor": {
      "type": "choice",
      "instructions": "Which contributing factor does the narrative point to most?",
      "criteria": {
        "distraction": "Phone use, looking away or other inattention",
        "speed": "Speeding or driving too fast for conditions",
        "impairment": "Alcohol, drugs or fatigue",
        "road_weather": "Road surface, visibility or weather",
        "unknown": "The narrative does not indicate a factor"
      }
    },
    "contradicts_coding": {
      "type": "noul",
      "instructions": "The narrative describes an injury, fatality or factor that the coded fields in the state do not reflect."
    }
  }
}""")

res = requests.post(
    "https://router.flatkey.ai/api/alpha/decisions",
    headers={"Authorization": f"Bearer {os.environ['FLATKEY_API_KEY']}"},
    json=body,
    timeout=60,
)
res.raise_for_status()
data = res.json()
print(json.dumps(data["answers"], indent=2), data.get("usage"))

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