Oracle Scribe
A voice assistant skill that acts as a creative co-pilot, using layered, dream-like narrative exercises to help writers and creators overcome creative blocks and build unique worlds.
Whispers of the Market
A voice-controlled assistant that leverages real-time e-commerce price scraping to deliver dynamic deal alerts and price predictions inspired by the shadowy dealings of Neuromancer and the resourcefulness of the Star Wars universe.
Inspired by the relentless pursuit of valuable data in 'Neuromancer' and the scrappy, opportunistic nature of acquiring resources in 'Star Wars: A New Hope,' this project, 'Whispers of the Market,' is a niche voice assistant focused on e-commerce price intelligence. The core functionality revolves around voice commands to track specific products across various online retailers. Users can ask, 'Hey MarketWhisper, what's the best price for a 'DeWalt 20V drill kit' today?' or 'MarketWhisper, alert me when the 'Sony WH-1000XM5' headphones drop below $300.'
The 'Neuromancer' influence comes from the discreet, efficient gathering of information in the digital underworld. The assistant will constantly and subtly scrape e-commerce websites for pre-defined products. The 'Star Wars' element is in the user's ability to be an independent operator, making informed decisions based on the 'intelligence' gathered, much like Luke Skywalker using the Force or R2-D2's diagnostic capabilities. It’s about empowering the individual consumer to find hidden value.
How it works:
1. Voice Input & NLP: A simple, lightweight Natural Language Processing (NLP) model (e.g., using libraries like `speech_recognition` and `nltk` or cloud-based services like Google Cloud Speech-to-Text) will interpret user commands for product tracking and price queries.
2. Scraping Engine: Python scripts utilizing libraries like `BeautifulSoup` and `Requests` (or more advanced headless browsers like `Selenium` for complex sites) will be scheduled to periodically scrape designated e-commerce product pages for current prices.
3. Database/Storage: A simple database (e.g., SQLite) will store product tracking information, historical price data, and user preferences.
4. Alerting System: When a price threshold is met or a significant drop is detected, the assistant will use text-to-speech (e.g., `pyttsx3` or cloud-based TTS) to deliver a spoken alert to the user. This could be integrated with simple push notifications or email for more persistent users.
5. Price Prediction (Niche Feature): A very basic predictive element could be introduced by analyzing past price trends for highly fluctuating items, offering a speculative 'buy now or wait' suggestion. This would be a subtle nudge, not definitive financial advice.
Low-Cost Implementation: The project can be built using open-source Python libraries, a Raspberry Pi or a low-tier cloud VM for hosting the scraper, and free tiers of cloud NLP/TTS services. The primary cost would be development time.
Niche: Focusing on specific product categories (e.g., electronics, tools, collectibles) or even a single retailer can make it more manageable and targeted. The 'deal hunter' or 'smart shopper' persona is a well-defined niche.
High Earning Potential:
- Affiliate Marketing: Integrate affiliate links into the price alerts and product suggestions. When a user clicks and purchases through the link, the developer earns a commission.
- Premium Features: Offer subscription tiers for advanced features like more aggressive scraping frequency, price trend analysis, price prediction accuracy improvements, or tracking a larger number of items.
- B2B Data Insights: Aggregate anonymized pricing data for specific product categories and sell these insights to small businesses or market researchers.
- Partnerships: Collaborate with e-commerce platforms or brands for featured deal promotions.
The 'Neuromancer' influence comes from the discreet, efficient gathering of information in the digital underworld. The assistant will constantly and subtly scrape e-commerce websites for pre-defined products. The 'Star Wars' element is in the user's ability to be an independent operator, making informed decisions based on the 'intelligence' gathered, much like Luke Skywalker using the Force or R2-D2's diagnostic capabilities. It’s about empowering the individual consumer to find hidden value.
How it works:
1. Voice Input & NLP: A simple, lightweight Natural Language Processing (NLP) model (e.g., using libraries like `speech_recognition` and `nltk` or cloud-based services like Google Cloud Speech-to-Text) will interpret user commands for product tracking and price queries.
2. Scraping Engine: Python scripts utilizing libraries like `BeautifulSoup` and `Requests` (or more advanced headless browsers like `Selenium` for complex sites) will be scheduled to periodically scrape designated e-commerce product pages for current prices.
3. Database/Storage: A simple database (e.g., SQLite) will store product tracking information, historical price data, and user preferences.
4. Alerting System: When a price threshold is met or a significant drop is detected, the assistant will use text-to-speech (e.g., `pyttsx3` or cloud-based TTS) to deliver a spoken alert to the user. This could be integrated with simple push notifications or email for more persistent users.
5. Price Prediction (Niche Feature): A very basic predictive element could be introduced by analyzing past price trends for highly fluctuating items, offering a speculative 'buy now or wait' suggestion. This would be a subtle nudge, not definitive financial advice.
Low-Cost Implementation: The project can be built using open-source Python libraries, a Raspberry Pi or a low-tier cloud VM for hosting the scraper, and free tiers of cloud NLP/TTS services. The primary cost would be development time.
Niche: Focusing on specific product categories (e.g., electronics, tools, collectibles) or even a single retailer can make it more manageable and targeted. The 'deal hunter' or 'smart shopper' persona is a well-defined niche.
High Earning Potential:
- Affiliate Marketing: Integrate affiliate links into the price alerts and product suggestions. When a user clicks and purchases through the link, the developer earns a commission.
- Premium Features: Offer subscription tiers for advanced features like more aggressive scraping frequency, price trend analysis, price prediction accuracy improvements, or tracking a larger number of items.
- B2B Data Insights: Aggregate anonymized pricing data for specific product categories and sell these insights to small businesses or market researchers.
- Partnerships: Collaborate with e-commerce platforms or brands for featured deal promotions.