# Tech Gadget Price & Launch Tracker (`hookedontech/tech-gadget-price-launch-tracker`) Actor Daily tech gadget price & launch tracker for Amazon, Product Hunt & more. Get new releases, discounts & POD ideas instantly. - **URL**: https://apify.com/hookedontech/tech-gadget-price-launch-tracker.md - **Developed by:** [Nav](https://apify.com/hookedontech) (community) - **Categories:** AI, E-commerce, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $750.00 / 1,000 report generateds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Python CrewAI template A template for [CrewAI](https://www.crewai.com/) projects in Python for building AI agents with [Apify Actors](https://apify.com/actors). The template provides a basic structure and an example [agent](https://docs.crewai.com/concepts/agents) that calls [Actors](https://apify.com/actors) via `ApifyActorsTool` in a workflow using the [CrewAI Apify Actors integration](https://docs.apify.com/platform/integrations/crewai). For a detailed guide, visit the [How to build an AI agent](https://blog.apify.com/how-to-build-an-ai-agent/) article. ### How it works An [agent](https://docs.crewai.com/concepts/agents) is created and given a set of tools to accomplish a task. The agent receives a query from the user and decides which tools to use and in what order to complete the task. In this template, the agent uses `ApifyActorsTool('apify/instagram-scraper')` from `crewai_tools` to run the [Instagram Scraper Actor](https://apify.com/apify/instagram-scraper) and analyze scraped posts. The agent produces textual output, which is saved to a dataset. ### How to use Tools are provided via `crewai_tools` and configured in `src/main.py`. To change tools, edit the `tools` list in `src/main.py`. You can also update the agent prompts in `src/main.py`. For more information, refer to the [CrewAI agent documentation](https://docs.crewai.com/concepts/agents) and the [CrewAI tools documentation](https://docs.crewai.com/concepts/tools). ##### Pay Per Event This template uses the [Pay Per Event (PPE)](https://docs.apify.com/platform/actors/publishing/monetize#pay-per-event-pricing-model) monetization model, which provides flexible pricing based on defined events. To charge users, define events in JSON format and save them on the Apify platform. Here is an example schema with the `task-completed` event: ```json [ { "task-completed": { "eventTitle": "Task completed", "eventDescription": "Cost per query answered.", "eventPriceUsd": 0.1 } } ] ```` In the Actor, trigger the event with: ```python await Actor.charge(event_name='task-completed') ``` This approach allows you to programmatically charge users directly from your Actor, covering the costs of execution and related services, such as LLM input/output tokens. To set up the PPE model for this Actor: - **Configure the OpenAI API key environment variable**: provide your OpenAI API key to the `OPENAI_API_KEY` in the Actor's **Environment variables**. - **Configure Pay Per Event**: establish the Pay Per Event pricing schema in the Actor's **Monetization settings**. First, set the **Pricing model** to `Pay per event` and add the schema. An example schema can be found in [pay\_per\_event.json](.actor/pay_per_event.json). ### Included features - **[Apify SDK](https://docs.apify.com/sdk/python/)** for Python - a toolkit for building Apify [Actors](https://apify.com/actors) and scrapers in Python - **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input - **[Dataset](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-datasets)** - store structured data where each object stored has the same attributes - **[Key-value store](https://docs.apify.com/platform/storage/key-value-store)** - store any kind of data, such as JSON documents, images, or text files ### Resources - [What are AI agents?](https://blog.apify.com/what-are-ai-agents/) - [Python tutorials in Academy](https://docs.apify.com/academy/python) - [Apify Python SDK documentation](https://docs.apify.com/sdk/python/) - [CrewAI documentation](https://docs.crewai.com/introduction) - [Integration with Make, GitHub, Zapier, Google Drive, and other apps](https://apify.com/integrations) ### Getting started For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the Actor use the following command: ```bash apify run ``` ### Deploy to Apify #### Connect Git repository to Apify If you've created a Git repository for the project, you can easily connect to Apify: 1. Go to [Actor creation page](https://console.apify.com/actors/new) 2. Click on **Link Git Repository** button #### Push project on your local machine to Apify You can also deploy the project on your local machine to Apify without the need for the Git repository. 1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action. ```bash apify login ``` 2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my). ```bash apify push ``` ### Documentation reference To learn more about Apify and Actors, take a look at the following resources: - [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js) - [Apify SDK for Python documentation](https://docs.apify.com/sdk/python) - [Apify Platform documentation](https://docs.apify.com/platform) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## `categories` (type: `array`): Array of tech gadget categories to track (e.g. \["AI hardware", "smart wearables"]) ## `keywords` (type: `string`): Optional keywords to refine the search (e.g. "new launch" or "2026 release") ## `max_results` (type: `integer`): Maximum number of gadget results to return per run ## `sites` (type: `array`): List of sites to monitor for prices, launches and discounts ## `modelName` (type: `string`): OpenAI model name to use for the CrewAI agent ## Actor input object example ```json { "max_results": 15, "sites": [ "amazon", "producthunt", "bestbuy", "aliexpress", "newegg", "walmart" ], "modelName": "gpt-4o-mini" } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("hookedontech/tech-gadget-price-launch-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("hookedontech/tech-gadget-price-launch-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call hookedontech/tech-gadget-price-launch-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=hookedontech/tech-gadget-price-launch-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tech Gadget Price & Launch Tracker", "description": "Daily tech gadget price & launch tracker for Amazon, Product Hunt & more. Get new releases, discounts & POD ideas instantly.", "version": "0.0", "x-build-id": "NR2lROdFzdlZHLuhH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/hookedontech~tech-gadget-price-launch-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-hookedontech-tech-gadget-price-launch-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/hookedontech~tech-gadget-price-launch-tracker/runs": { "post": { "operationId": "runs-sync-hookedontech-tech-gadget-price-launch-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/hookedontech~tech-gadget-price-launch-tracker/run-sync": { "post": { "operationId": "run-sync-hookedontech-tech-gadget-price-launch-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "categories" ], "properties": { "categories": { "title": "Categories", "minItems": 1, "type": "array", "description": "Array of tech gadget categories to track (e.g. [\"AI hardware\", \"smart wearables\"])", "items": { "type": "string" } }, "keywords": { "title": "Keywords", "type": "string", "description": "Optional keywords to refine the search (e.g. \"new launch\" or \"2026 release\")" }, "max_results": { "title": "Max Results", "minimum": 5, "maximum": 100, "type": "integer", "description": "Maximum number of gadget results to return per run", "default": 15 }, "sites": { "title": "Sites", "type": "array", "description": "List of sites to monitor for prices, launches and discounts", "items": { "type": "string" }, "default": [ "amazon", "producthunt", "bestbuy", "aliexpress", "newegg", "walmart" ] }, "modelName": { "title": "LLM Model", "type": "string", "description": "OpenAI model name to use for the CrewAI agent", "default": "gpt-4o-mini" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```