Brand Mention Monitor
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from $2.00 / 1,000 results
Brand Mention Monitor returns normalized, review-ready API data with robust inputs, consistent outputs, and pay-per-result pricing.
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from $2.00 / 1,000 results
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Virtual Footprint LLC
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FROM apify/actor-python:3.11COPY requirements.txt ./RUN pip install --no-cache-dir -r requirements.txtCOPY . ./CMD ["python", "main.py"]1<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 256 256" width="256" height="256">2 <rect width="256" height="256" rx="48" fill="#0d1117"/>3 <!-- Icon -->4 <g transform="translate(128, 110)">5 <g transform="translate(-64, -64) scale(5.33)">6 <path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm0 18c-4.41 0-8-3.59-8-8s3.59-8 8-8 8 3.59 8 8-3.59 8-8 8zm-1-13h2v6h-2zm0 8h2v2h-2z" fill="white" stroke="none"/>7 </g>8 </g>9 <!-- Label badge -->10 <rect x="20" y="190" width="216" height="40" rx="8" fill="#ea4335" opacity="0.9"/>11 <text x="128" y="216" text-anchor="middle" dominant-baseline="middle"12 font-family="Arial, sans-serif" font-size="20" font-weight="bold" fill="white">MENTIONS</text>13 <!-- PRO badge -->14 <rect x="200" y="10" width="46" height="28" rx="6" fill="#34a853" opacity="0.9"/>15 <text x="223" y="27" text-anchor="middle" dominant-baseline="middle"16 font-family="Arial, sans-serif" font-size="14" font-weight="bold" fill="white">PRO</text>17</svg>1"""2Brand Mention Monitor (Multi-Platform) — Premium Multi-API Actor3
4This actor is a thin wrapper that calls the multi-api-orchestrator with the5'brand_mention_monitor' workflow. The orchestrator handles all multi-step6conditional logic via LangGraph (or async fallback).7
8AI-DLC: Part of multi-api-orchestration-spec.md9"""10import asyncio11import json12import os13import time14
15import httpx16from apify import Actor17
18ORCHESTRATOR_ACTOR_ID = "multi-api-orchestrator" # Replace with actual ID after push19APIFY_API = "https://api.apify.com/v2"20
21
22def get_token() -> str:23 return os.environ.get("APIFY_TOKEN", os.environ.get("APIFY_API_TOKEN", ""))24
25
26async def call_orchestrator(workflow: str, query: dict) -> list[dict]:27 """Call the multi-api-orchestrator actor and return results."""28 token = get_token()29 headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}30 input_data = {"workflow": workflow, "query": query}31
32 async with httpx.AsyncClient(timeout=180) as client:33 resp = await client.post(34 f"{APIFY_API}/acts/{ORCHESTRATOR_ACTOR_ID}/runs?token={token}",35 json=input_data,36 headers=headers,37 )38 resp.raise_for_status()39 run_id = resp.json()["data"]["id"]40
41 # Poll for completion42 started = time.time()43 while time.time() - started < 150:44 await asyncio.sleep(5)45 status_resp = await client.get(f"{APIFY_API}/actor-runs/{run_id}?token={token}")46 status_resp.raise_for_status()47 status = status_resp.json()["data"]["status"]48 if status in ("SUCCEEDED", "FAILED", "TIMED-OUT", "ABORTED"):49 if status != "SUCCEEDED":50 raise RuntimeError(f"Orchestrator run {status}")51 dataset_id = status_resp.json()["data"]["defaultDatasetId"]52 items_resp = await client.get(53 f"{APIFY_API}/datasets/{dataset_id}/items?token={token}&clean=true"54 )55 items_resp.raise_for_status()56 return items_resp.json() or []57 raise TimeoutError("Orchestrator timed out")58
59
60async def main() -> None:61 async with Actor:62 actor_input = await Actor.get_input() or {}63 query = {k: v for k, v in actor_input.items() if k != "webhookUrl"}64 results = await call_orchestrator("brand_mention_monitor", query)65 await Actor.push_data(results)66
67if __name__ == "__main__":68 asyncio.run(main())1apify>=2.0.02httpx>=0.25.0{ "actorSpecification": 1, "name": "brand-mention-monitor", "title": "Brand Mention Monitor (Multi-Platform)", "description": "Monitor brand mentions across Instagram, TikTok, Twitter/X, and LinkedIn in one run. Aggregated, sorted by engagement, with platform attribution.", "version": "1.0", "buildTag": "latest", "meta": { "templateId": "starter-python" }, "categories": [ "MARKETING", "BUSINESS" ], "input": "./input_schema.json", "dockerfile": "../Dockerfile", "pricingInfos": [ { "pricingModel": "PAY_PER_EVENT", "apifyMarginPercentage": 0.2, "pricingPerEvent": { "actorChargeEvents": { "apify-actor-start": { "eventTitle": "Actor Start", "eventPriceUsd": 5e-05, "isOneTimeEvent": true, "eventDescription": "One-time charge when the Actor run starts." }, "apify-default-dataset-item": { "eventTitle": "Result", "eventPriceUsd": 0.00536, "isPrimaryEvent": true, "eventDescription": "Charge per result. $5.36/1K results -- 25% cheaper than top competitors." } } }, "reasonForChange": "Premium multi-API: 25% cheaper than buying 4 actors separately ($7.15/1K combined)." } ], "readme": "../README.md", "output": "./output_schema.json"}{ "title": "Brand Mention Monitor (Multi-Platform) Input", "description": "Brand name to monitor across platforms", "type": "object", "properties": { "brandName": { "type": "string", "description": "Brand name or hashtag to monitor", "default": "nike", "title": "Brandname", "editor": "textfield" }, "maxResults": { "type": "integer", "minimum": 1, "maximum": 1000, "default": 25, "description": "Max results per platform", "title": "Maxresults", "editor": "number" }, "webhookUrl": { "type": "string", "default": "", "description": "Optional webhook URL for result delivery", "title": "Webhookurl", "editor": "textfield" } }, "required": [ "brandName", "maxResults" ], "schemaVersion": 1}{ "actorOutputSchemaVersion": 1, "title": "Brand Mention Monitor Output", "properties": { "results": { "type": "string", "title": "Results", "template": "{{links.apiDefaultDatasetUrl}}/items" } }}