Haptica API

curl https://api.haptica.io/v1/analyze \
  -H "Authorization: Bearer hp_live_..." \
  -F "video=@clip.mp4"

{
  "video_id": "a1b2c3d4e5...",
  "provenance": {
    "model_version": "v3.1",
    "encoder": "haptica-physics",
    "checkpoint": "v3.1-prod"
  },
  "input": {
    "fps_source": 30,
    "duration_ms": 4800,
    "window_frames": 16
  },
  "availability": {
    "force_index": "active",
    "contact": "active",
    "impact": "active",
    "rotation": "active",
    "bind_jam": { "status": "null", "reason": "no_context" },
    "human_risk": { "status": "null", "reason": "no_context" }
  },
  "windows": [{
    "index": 0,
    "timing": { "start_ms": 0, "end_ms": 1600, "canonical_fps": 10.0 },
    "physics": {
      "force_index": 0.723,
      "contact": { "detected": true, "confidence": 0.94 },
      "impact": { "detected": false, "confidence": 0.12 },
      "rotation": { "detected": true, "confidence": 0.87 },
      "bind_jam": null,
      "human_risk": null
    },
    "evidence": {
      "dominant_primitive": "contact",
      "dominant_candidate": "contact",
      "activity_regime": "clear",
      "dominant_margin": 0.07,
      "stability_score": 0.72,
      "tokens": { "contact": 0.94, "impact": 0.12, "rotation": 0.87 }
    }
  }]
}

Authorization: Bearer hp_live_abc123def456...

import requests

resp = requests.post(
    "https://api.haptica.io/v1/analyze",
    headers={"Authorization": "Bearer hp_live_..."},
    files={"video": open("clip.mp4", "rb")},
)
result = resp.json()

for w in result["windows"]:
    t = w["timing"]
    p = w["physics"]
    print(f"[{t['start_ms']}–{t['end_ms']}ms] "
          f"force={p['force_index']:.2f} "
          f"contact={p['contact']['detected']} "
          f"impact={p['impact']['detected']}")

{
  "model_version": "v3.1",
  "encoder": "haptica-physics",
  "checkpoint": "v3.1-prod",
  "signals": {
    "core": ["force_index", "contact", "impact", "rotation"],
    "configured": ["bind_jam", "human_risk"]
  },
  "auroc": { "contact": 0.78, "impact": 0.72, "rotation": 0.71 },
  "window_frames": 16,
  "canonical_fps": 10.0,
  "supported_formats": ["mp4", "mov", "avi", "webm"]
}

import haptica

client = haptica.Client("hp_live_...")
result = client.analyze(video="robot_arm.mp4")

for w in result.windows:
    p = w.physics
    if p.force_index > 0.7 and p.contact.detected:
        print(f"[{w.timing.start_ms}ms] HIGH FORCE CONTACT -- force={p.force_index:.2f}")
    if p.human_risk and p.human_risk > 0.8:
        print(f"[{w.timing.start_ms}ms] SAFETY ALERT -- risk={p.human_risk:.2f}")
        robot.trigger_safe_stop()

# Flag anomalous force patterns in warehouse footage
result = client.analyze(video=feed_url)

baseline = sum(w.physics.force_index for w in result.windows) / len(result.windows)
anomalies = [w for w in result.windows if w.physics.force_index > baseline * 2.5]

for w in anomalies:
    alert(f"Anomaly at {w.timing.start_ms}ms: force {w.physics.force_index:.2f} (baseline {baseline:.2f})")

# Use evidence scores for fine-grained decision making
result = client.analyze(video="assembly.mp4")

for w in result.windows:
    tokens = w.evidence.tokens
    # High contact evidence but low impact = sustained press (normal)
    if tokens["contact"] > 0.8 and tokens["impact"] < 0.2:
        log("Sustained contact -- normal assembly pressure")

    # High impact evidence = unexpected collision
    if tokens["impact"] > 0.7:
        log(f"Impact at {w.timing.start_ms}ms (evidence: {tokens['impact']:.2f})")
        queue_review(w)

{
  "type": "function",
  "function": {
    "name": "haptica_analyze",
    "description": "Analyze video for physical interactions. Returns force, contact, impact, rotation, and evidence scores per 1.6s window.",
    "parameters": {
      "type": "object",
      "properties": {
        "video": {
          "type": "string",
          "description": "URL or base64-encoded video clip"
        },
        "context": {
          "type": "string",
          "description": "Task context string (e.g. 'manufacturing_assembly')"
        }
      },
      "required": ["video"]
    }
  }
}