AI WhatsApp Message Parser
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About this role
Python, Data Processing, Node.js, Data Extraction, Relational Databases, Database Design, API Integration, Large Language Model · My existing scraper is already funneling every post from more than 500 WhatsApp groups into a single “raw_messages” table. Each row carries the full text, a group-id, timestamp, and sender phone, but that is where the structure ends.
I now need a new script that will read each incoming row, pass the text to an AI model (OpenAI GPT-4 or a comparable LLM), and pull out three kinds of information: product details, customer inquiries, and any sales data mentioned. The extracted pieces must then be normalised and inserted into a well-designed relational schema, separate from the raw table, so that I can query products, track enquiries, and generate sales reports without wading through free-form chat logs.
Key points • High throughput: the flow can spike to thousands of messages per hour; the solution needs batching or async processing so the backlog never grows. • Accuracy matters more than sentiment; mis-classified fields should remain traceable to the original message id for quick correction. • Use standard tech—Python with SQLAlchemy, Node + Prisma, or anything equally maintainable—and keep prompts, parsing rules, and DB migrations in the repo.
Deliverables 1. Clean,