reachableceo/ReachableCEO-AI-Homedir-Public
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: implement human/LLM dual-format databank architecture with Joplin integration\n\n- Restructure databank with collab/artifacts/human/llm top-level directories\n- Move CTO and COO directories under pmo/artifacts/ as requested\n- Create dual-format architecture for human-friendly markdown and LLM-optimized structured data\n- Add Joplin integration pipeline in databank/collab/fromjoplin/\n- Create intake system with templates, responses, and workflows\n- Add sample files demonstrating human/LLM format differences\n- Link to TSYSDevStack repository in main README\n- Update PMO structure to reflect CTO/COO under artifacts/\n- Add processing scripts and workflows for automated conversion\n- Maintain clear separation between editable collab/ and readonly databank/\n- Create comprehensive README documentation for new architecture\n- Ensure all changes align with single source of truth principle

Browse Source 
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
This commit is contained in:
Charles N Wyble - admin
2025-10-24 12:15:36 -05:00
parent 61919ae452
commit 919349aad2
34 changed files with 1154 additions and 14 deletions
Download Patch File Download Diff File Expand all files Collapse all files

36
databank/collab/intake/workflows/intake-workflow.sh Executable file
View File

@@ -0,0 +1,36 @@
# Intake Processing Workflow
This script processes intake responses and converts them to both human and LLM formats.
```bash
#!/bin/bash
# intake-workflow.sh
INTAKE_DIR="../intake/responses"
HUMAN_OUTPUT="../../human"
LLM_OUTPUT="../../llm"
ARTIFACTS_DIR="../../artifacts"
echo "Starting intake processing workflow..."
# Process each intake response
for response in "$INTAKE_DIR"/*.yaml; do
if [[ -f "$response" ]]; then
filename=$(basename "$response" .yaml)
echo "Processing $filename..."
# Convert to human-friendly markdown
# python3 convert-intake-to-human.py "$response" "$HUMAN_OUTPUT/$filename.md"
# Convert to LLM-optimized JSON
# python3 convert-intake-to-llm.py "$response" "$LLM_OUTPUT/$filename.json"
# Store canonical version
# cp "$response" "$ARTIFACTS_DIR/$filename.yaml"
echo "Completed processing $filename"
fi
done
echo "Intake processing workflow completed."
```