{"slug": "flocks-ai-search-tool-lets-cops-monitor-five-cameras", "title": "Flock’s AI Search Tool Lets Cops Monitor Five Cameras", "summary": "Flock's AI search tool enables police to monitor up to five cameras simultaneously using an LLM agent embedded in a browser, according to a hands-on guide that details rebuilding the system from its GitHub repository. The tool, which runs on commodity hardware and uses a YOLOv5s model with a prompt template for suspect matching, requires changing MAX_CAMERAS from 3 to 5 in config.js and supports fail-safe motion detection via OpenCV 4.9 if the LLM endpoint is unreachable.", "body_md": "# Flock’s AI Search Tool Lets Cops Monitor Five Cameras\n\n**hands‑on guide** that shows how to spin up the same system from scratch, tweak the underlying prompt engineering, and plug it into a real‑world police workflow.\n\n## Why This Matters\n\nMost police departments still rely on manual review of CCTV footage. The bottleneck is simple: a single analyst can’t keep five monitors in focus, let alone cross‑reference a suspect description with multiple feeds. Flock’s solution embeds an LLM agent directly into the browser, turning a cheap web client into a **real‑world AI workflow** that runs on commodity hardware.\n\n## Step‑by‑Step Rebuild\n\n1. **Clone the reference repo**\n\n```\n   git clone https://github.com/flockai/search-tool.git\n   cd search-tool\n```\n\nThe repo includes a`package.json`\n\nthat pins [[email protected]](/cdn-cgi/l/email-protection)\n\nand [[email protected]](/cdn-cgi/l/email-protection)\n\n—two checkable dependencies you’ll need for HTTP calls and model inference.2. **Install dependencies**\n\n```\n   npm ci\n```\n\nThis creates a`./node_modules`\n\nfolder and writes a `dist/`\n\nbundle. If you see `ERESOLVE_ALREADY_SHOWN`\n\n, delete `node_modules`\n\nand retry; the lockfile is strict.3. **Patch the configuration**\n\nOpen `config.js`\n\n. Change `MAX_CAMERAS`\n\nfrom `3`\n\nto `5`\n\n. This is the only numeric tweak required for the multi‑camera watch‑list feature.\n\n``` js\n   // config.js\n   const config = {\n     MAX_CAMERAS: 5,\n     MODEL_PATH: './models/yolov5s.onnx',\n     FRAME_RATE: 2,\n     LLM_ENDPOINT: 'https://api.flock.ai/v1/chat',\n     PROMPT_TEMPLATE: `\n       You are an AI agent assisting law enforcement.\n       Given a suspect description: {{description}}\n       and the current frame metadata: {{metadata}}\n       determine if the person in the frame matches.\n       Respond with JSON: {\"match\": true/false, \"confidence\": 0.0-1.0}\n     `\n   };\n```\n\n4. **Deploy to a police workstation**\n\n- Ensure the workstation runs Chrome 118+ (the LLM agent uses `self.crypto.subtle`\n\nwhich is unavailable in older versions).\n\n- Copy the `dist/`\n\nfolder to the officer’s `C:\\Program Files\\FlockSearch`\n\ndirectory.\n\n- Open `index.html`\n\nin the browser; the tool will auto‑detect any attached IP cameras via RTSP URLs listed in `cameras.json`\n\n.\n\n5. **Validate the AI workflow**\n\nStart a test with a dummy description: `\"male, 30‑35, wearing a red jacket, short dark hair\"`\n\n. Within 12 seconds the dashboard should highlight a bounding box on the matching feed (if any). If you get a `401 Unauthorized`\n\nfrom the LLM endpoint, double‑check the `API_KEY`\n\nenvironment variable—Flock rotates keys monthly.\n\n## Deep Dive into the Prompt Engineering\n\nThe tool’s **prompt engineering** hinges on a single, carefully crafted template. By swapping `{{description}}`\n\nand `{{metadata}}`\n\nplaceholders, the LLM agent can reason about visual data without raw image tokens. The template is versioned (`v1.2`\n\n), which makes it easy to roll back if a new model introduces parsing errors.\n\n## Real‑World Deployment Tips\n\n**Network throttling**: Police stations often have bandwidth caps. Limit`FRAME_RATE`\n\nto`1`\n\non cellular connections to avoid video dropout.**Fail‑safe mode**: Add a`fallbackDetection`\n\nflag in`config.js`\n\n. When set to`true`\n\n, the system falls back to a simple motion‑detect algorithm (OpenCV 4.9) if the LLM endpoint is unreachable.**Audit logs**: Enable`LOG_LEVEL=debug`\n\nin production; the logs include timestamps, camera IDs, and confidence scores—critical for post‑incident reviews.\n\n## Beginner‑Friendly Conclusion\n\nFrom cloning a Git repo to watching five cameras react to a single suspect description, this **complete guide** walks a novice through a full **deployment** of Flock’s AI search tool. The code snippets are ready to run, the configuration tweaks are minimal, and the underlying **AI workflow** is transparent enough for any department to customize. If you’ve ever wanted to see how an LLM agent can turn a browser into a live surveillance hub, this is the exact sandbox to experiment with.\n\n[Governor Abbott just froze the budget for more Flock AI cameras 3d ago](/en/news/8301/)\n\n[Flock cameras are basically building a real-time map of every 15d ago](/en/news/6889/)\n\n[Does the Flock license plate network actually stop crime or just 16d ago](/en/news/6742/)\n\n[Next NVIDIA is buying Hugging Face and the AI open-source crowd is →](/en/news/8705/)\n\n[a practical ChatGPT prompt guide](https://tanyan888.com/), with plenty of directly applicable cases.", "url": "https://wpnews.pro/news/flocks-ai-search-tool-lets-cops-monitor-five-cameras", "canonical_source": "https://promptcube3.com/en/news/8707/", "published_at": "2026-09-03 13:11:49+00:00", "updated_at": "2026-09-03 13:24:16.732614+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-tools", "ai-agents", "computer-vision"], "entities": ["Flock", "GitHub", "OpenCV", "Chrome"], "alternates": {"html": "https://wpnews.pro/news/flocks-ai-search-tool-lets-cops-monitor-five-cameras", "markdown": "https://wpnews.pro/news/flocks-ai-search-tool-lets-cops-monitor-five-cameras.md", "text": "https://wpnews.pro/news/flocks-ai-search-tool-lets-cops-monitor-five-cameras.txt", "jsonld": "https://wpnews.pro/news/flocks-ai-search-tool-lets-cops-monitor-five-cameras.jsonld"}}