Phase 6: AI Integration
Phase 6: AI Integration
Feed extracted data into local models for classification, summarization, and pattern detection. Ties directly into the Ollama + local AI stack.
Document Summarization
# Extract text then summarize with local model
pdftotext -layout report.pdf - | \
ollama run mistral "Summarize this document in 3 bullet points:"
# Batch summarize all PDFs
find /data/docs -name '*.pdf' -exec sh -c '
text=$(pdftotext -layout "$1" - 2>/dev/null)
if [ -n "$text" ]; then
summary=$(echo "$text" | head -500 | ollama run mistral "Summarize in 2 sentences:")
echo "$1: $summary"
fi
' _ {} \; > summaries.txt
Image Classification
# Classify image content with vision model
ollama run llava "What is in this image?" < photo.jpg
# Batch classify and tag
find ~/Photos -name '*.jpg' -exec sh -c '
desc=$(ollama run llava "Describe this image briefly:" < "$1")
echo "$1|$desc"
' _ {} \; > classifications.csv
Log Analysis
# Feed anomalous log entries to model for explanation
journalctl --since "1 hour ago" -p err | \
ollama run codellama "Explain these Linux system errors and suggest fixes:"
# Correlate timeline anomalies
awk -F',' '$3 ~ /\.exe/ && $1 ~ /2026-03-1[0-2]/' timeline.csv | \
ollama run mistral "Analyze these filesystem events for signs of compromise:"
Pattern Detection
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Train local embeddings on known-good vs known-bad file metadata
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Cluster photos by visual similarity for dedup beyond perceptual hashing
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Classify documents by topic for automated filing
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Anomaly detection on filesystem timelines