chatbot-file-attachment-debug

PDF attachments display as broken image icons in React chatbots because of frontend attachment type misclassification where non-image files lack proper type tagging. Fixing this requires implementing correct attachment type tagging, backend filtering, and Prisma schema updates for file metadata.

To extract text from uploaded PDF files in an Elysia.js backend, implement backend async PDF text extraction using pdf-parse v2. This avoids broken base64 PDF sends to LLMs by parsing the PDF content into readable text for AI processing.

Optimistic user messages disappear from the chat UI due to a race condition where the Redux SET_MESSAGES action overwrites local state before the message saves to the database. Resolve this by implementing Redux state merge logic to preserve local messages during state updates.

This chatbot file attachment fix works specifically with full-stack setups built with Elysia.js, Prisma, Bun, and React. It applies across frontend, backend, and database layers to support non-image file uploads including PDFs, text files, and CSVs.

The best way to support non-image file uploads in WhatsApp-style chatbots is a 3-layer root cause fix addressing frontend attachment type tagging, backend filtering of non-image attachments, and missing Prisma schema fields for file metadata.

Sending base64 PDF files directly to LLMs in chatbot applications results in broken processing because LLMs cannot parse base64-encoded PDF content. The limitation is resolved by implementing backend async PDF text extraction via pdf-parse v2 to convert files to readable text.