✓ Environment OK
✓
exec() available
✓
Python binary
— /home/kb-engine.dv9.com/public_html/.venv/bin/python3
✓
pdf_ingestor.py
— /home/kb-engine.dv9.com/public_html/pdf_ingestor.py
✓
storage/app writable
— /home/kb-engine.dv9.com/public_html/storage/app
✓
Python version
— Python 3.12.3
✓
open_basedir
— (not set)
✓
sys_get_temp_dir
— /tmp
✓
file_uploads
— 1
✓
upload_max_filesize
— 50M
✓
post_max_size
— 55M
✓
max_file_uploads
— 20
Upload PDF Document
The PDF will be chunked (~400 tokens per chunk, 200-char overlap) and embedded using
nomic-embed-text-v1.5. Chunks are stored in the
rag_docs
Qdrant collection and used as a fallback when no structured KB article matches.
Ingested Documents (18)
⚙ Environment
Python: /home/kb-engine.dv9.com/public_html/.venv/bin/python3
Ingestor: /home/kb-engine.dv9.com/public_html/pdf_ingestor.py
Qdrant: http://84.247.146.89:6333/
Embedding: http://84.247.146.89:8183
Collection: rag_docs
Ingestor: /home/kb-engine.dv9.com/public_html/pdf_ingestor.py
Qdrant: http://84.247.146.89:6333/
Embedding: http://84.247.146.89:8183
Collection: rag_docs