Costa Rica

Update: Here's an easy, actionable task, for almost anyone who claims to be any kind of technologist in 2025:Deploy the two notebooks 6 and 8 in the Perplexity resources list to Colab, so that you can share them to me.In a Google Doc and via Loom video (5 minutes), explain how 6 and 8 could be part of the recommendation system for a given marketplace, especially given the Apify scraper mentioned later. Here, for your convenience are 6 and 8 :[6] https://www.kaggle.com/code/abdelrahmanahmed110/cars-recommendation-system[8] https://www.kaggle.com/code/khotijahs1/recommender-system-for-vehicle-selection It appears that maybe 6 would let me find the TYPE of car and MODELS I want (hatchback, 5 passenger comfort, high MPG) &gt;&gt;&gt; Suzuki Swift, Suzuki Alto, Suzuki Celerio, Hyundai i10, Honda Fit, etc and8 might let me find the EXACT INSTANCES of the vehicles, i.e. HIGH model year (Yellow) and LOW price (pink).If you do this well, I should be able to use it on Monday, 1/6/25.If you claim to be any kind of technologist, you MUST be able to do this task. Otherwise, quit and drive a yak cart or something. I AM ***NOT*** LOOKING FOR BULLSH*T IN ANY FORM. DO THE WORK, DON'T SEND ME GPT SPEW. I WILL NOT BE ANSWERING STUPID QUESTIONS. I WILL PAY THE FIRST TWO PEOPLE WHO EXECUTE THE ABOVE WELL IN THE NEXT 12 HOURS. PERIOD. ====Random CoincidenceThis article on AI matchmaking came in my Medium feed an hour after my last update to this task:https://towardsdatascience.com/ai-powered-information-extraction-and-matchmaking-0408c93ec1b9?sk=623aaf8837df5630ed60c40e66766553 ============================================ HERE'S THE CONTEXTThis is a genius business idea for the right professional. I am shopping for a used car on Facebook Marketplace Costa Rica. I really like Suzuki, but Toyota, Hyundai, and Honda, in that order would be OK. I have owned 4 Geo/Suzuki Metros, which is aka the Suzuki Swift. But we want more space, for 3 passengers in back, so a 4 door would be best. I like hatchbacks. I would like geographically close to me, obviously, but am more concerned with value. I find that I can ask Llama, via Straico:Act as a marketplace researcher and conduct a search on Facebook Marketplace in Costa Rica for the five newest cars priced under 2,500,000 CRC in order of most undervalued to least undervalued. Only include CURRENT and AVAILABLE Listings. Please ensure to exclude any listings that contain the terms 'deuda', 'cuota', 'financiamiento', or similar, as these indicate that the car may not be free and clear of financing. Include details such as make, model, year, and notable features for each car. Provide links to each listing. It answers well, but does not have current real-time data. That's the task. Simply, looking for a great deal that meets my specifications. There are multiple Facebook Marketplace scrapers on Apify, including one by Apify itself, which works well, apify/facebook-marketplace-scraper, https://console.apify.com/actors/U5DUNxhH3qKt5PnCf/input If I can find a competent professional, there is clearly a business here. I would pay something like $100 a month for some number of saved scrapers with notification. Obviously, this is a global phenomenon, and applies to eBay Motors, as well. There is a phenomenon where idiots upload vehicles without prices and without the model and/or year. I am not interested in dealing with idiots, so any Free listings can be ignored. Obviously, to answer the "undervalued" question, a second, deeper round of reading the year from the listing title and/or from the description, and maybe from the images, as well as details like mileage, transmission type, air conditioning, tinted windows (polarizado), electric windows, etc. For lookup to something like Kelley Blue Book. One car mentioned missing airbags, which is up to $1000 expense, although the car has probably been discounted sufficiently to compensate. It would be easiest to flag such cars as "Project" cars or just ignore them - UNLESS, maybe the user has some mechanical skills, and wants Project cars. This should be pretty easy to turn into a SaaS. I have BuilderKit Pro, as well as a one user DronaHQ account. The deliverable would be a live Scoreboard that always shows my top N cars, in order, if I haven't rejected them, in which case, I don't want to see them again unless they become among the most undervalued. The options would be like Block, Reject for Value. What I am suggesting here is a partnership where I have provided the idea, research, tools and general genius. I need a human capable of executing. Nice.&nbsp;This is not really a gig for which I was thinking to hire.&nbsp;I don't know your English proficiency, but I am looking for a partner.&nbsp;Show me something, that you are even remotely qualified to do this project. Here are some resources from a Perplexity response:There are several matchmaking and recommendation services available for automobiles that can be integrated with existing databases or platforms like Facebook Marketplace or eBay Motors. Here’s a summary of some relevant options: ## Car Database APIs 1. **Smartcar API**:&nbsp;&nbsp;- Smartcar offers a comprehensive API that allows developers to access real-time data from connected vehicles. This API can be used to build applications that interact with user preferences and vehicle functionalities, making it suitable for creating personalized car recommendation systems[1]. 2. **Edmunds Vehicle API**:&nbsp;&nbsp;- This API provides access to a wide range of automotive datasets, including specifications, maintenance schedules, and consumer ratings. Developers can use this data to create applications that recommend vehicles based on user-defined criteria[1]. 3. **CarQuery API**:&nbsp;&nbsp;- CarQuery offers a JSON-based API that provides detailed information about various cars, including make, model, and trim. This can be useful for building a recommendation engine that filters vehicles based on user preferences[1]. 4. **CIS Automotive API**:&nbsp;&nbsp;- This API provides extensive data on vehicle sales and market trends, which can help in developing applications that analyze user preferences against market availability[1]. ## Recommendation Systems 1. **Car Recommendation System on GitHub**:&nbsp;&nbsp;- A project utilizing consumer reviews from Edmunds.com to recommend cars based on user preferences. It employs natural language processing techniques to analyze reviews and generate recommendations[2]. 2. **Used Car Project**:&nbsp;&nbsp;- This project focuses on developing a recommendation and price prediction system for used cars using machine learning techniques. It utilizes content-based filtering to suggest vehicles similar to those specified by the user[3]. 3. **Kaggle Projects**:&nbsp;&nbsp;- Various projects on Kaggle demonstrate how to build car recommendation systems using datasets that allow users to input preferences such as make, model, age, and price. These systems typically use algorithms like cosine similarity to find the best matches[6][8]. ## SummaryFor building a matchmaking or recommendation service for automobiles, developers can utilize APIs like Smartcar, Edmunds, and CarQuery to access vehicle data. Additionally, existing projects on platforms like GitHub and Kaggle provide frameworks for creating personalized recommendation systems based on user input and preferences. By integrating these tools with platforms like Facebook Marketplace or eBay Motors, you can enhance the search experience for users looking for specific vehicles. Citations:[1] https://smartcar.com/blog/car-database-api[2] https://github.com/matthewtom04/Car-Recommendation-System[3] https://github.com/olisauzondu/Used_Car_Project[4] https://smartcar.com/repair-maintenance-guide[5] https://www.api.org/products-and-services/engine-oil/eolcs-categories-and-classifications/oil-categories[6] https://www.kaggle.com/code/abdelrahmanahmed110/cars-recommendation-system[7] https://www.linkedin.com/pulse/best-vin-decoder-api-recommendation-automotive-pjsmc[8] https://www.kaggle.com/code/khotijahs1/recommender-system-for-vehicle-selection And, regarding Apify and Make.com, in case we need some integration:Apify provides modules for integration with Make.com (formerly Integromat), enabling users to run Apify Actors and monitor their execution within Make scenarios. Here are the key features and functionalities of the Apify modules on Make: ## Key Features of Apify Modules in Make 1. **Run Actors and Tasks**:&nbsp;&nbsp;&nbsp;- You can run specific Apify Actors or tasks directly from your Make scenarios. This includes options to run tasks synchronously, allowing you to wait for the task to complete before proceeding with subsequent actions[1][2]. 2. **Monitoring Actor Runs**:&nbsp;&nbsp;- The modules allow you to set up triggers that notify you when a selected Actor or task run has finished. This is useful for automating workflows based on the completion of web scraping tasks[1][2]. 3. **Configuration Requirements**:&nbsp;&nbsp;- To use these modules, you need an Apify account and a corresponding API token, which can be obtained from the Apify Console under Settings &gt; Integrations[1][2]. 4. **Input Customization**:&nbsp;&nbsp;- Users can provide JSON input overrides for both actors and tasks, allowing for dynamic configurations based on specific needs during execution[1][2]. 5. **Data Retrieval**:&nbsp;&nbsp;- The modules support fetching dataset items from completed runs, making it easier to process and utilize the data collected by your Actors[2]. ## Steps to Integrate Apify with Make 1. **Add the Apify Module**: Search for "Apify" in the module search bar within Make and add it to your scenario.2. **Create a Connection**: Enter your Apify API token in the connection configuration window to link your accounts.3. **Set Up Triggers and Actions**: Choose from available triggers (e.g., Watch Actor Runs) and actions (e.g., Run a Task) based on your automation requirements. ## Considerations - Users have reported occasional issues with the "Run an Actor" module, such as unexpected stops during execution or difficulties retrieving dataset items, indicating potential limitations or bugs that may need attention[3][4][5].- It's recommended to ensure that JSON inputs are correctly formatted to avoid errors during execution[5]. Overall, the integration of Apify with Make.com allows for powerful automation capabilities, enabling users to streamline their web scraping tasks effectively. Citations:[1] https://docs.apify.com/platform/integrations/make[2] https://www.make.com/en/help/app/apify[3] https://community.make.com/t/run-an-actor-module-stops-suddenly/63953[4] https://community.make.com/t/apify-module-get-dataset-items-returns-empty/37980[5] https://community.make.com/t/apify-run-an-actor-operation-1-imlerror/61212[6] https://community.make.com/t/http-get-module-is-not-fetching-any-output-data-after-successful-run/55403[7] https://www.make.com/en/integrations/apify[8] https://www.make.com/en/integrations/apify/feedier

Scraping the Most Undervalued Vehicles

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