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Add .ragignore for AI-friendly repository indexing#1

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llorracc wants to merge 5 commits intomainfrom
ai-ignore-update
Open

Add .ragignore for AI-friendly repository indexing#1
llorracc wants to merge 5 commits intomainfrom
ai-ignore-update

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This PR adds a .ragignore file to configure the repository for optimal AI/RAG system indexing.

What this does:

  • Defines source file priority (markdown, notebooks, Python code)
  • Specifies files to ignore (generated, temporary, binary files)
  • Sets up master file relationships
  • Configures careful processing rules for different file types

Benefits:

  • Improves search quality for AI tools
  • Reduces index size by excluding irrelevant files
  • Prioritizes source files over generated content
  • Enables better AI-powered code analysis

This is part of the Econ-ARK AI-friendly repository initiative.

llorracc added 5 commits June 29, 2025 08:42
This commit adds a complete reproduction workflow and overhauls documentation.

Key changes
- README.md: expanded to full project overview, quick-start guides, model description, results.
- reproduce.sh: converted from a one-liner to an end-to-end script that detects the active environment, executes both notebooks with nbconvert, stores outputs, and writes a JSON summary (mode changed to executable).
- binder/environment.yml: named the Conda env, added econ-ark channel, pinned Python 3.11, and extended package list (numpy, pandas, scipy, matplotlib, jupyter, etc.) to ensure out-of-the-box execution.
- AiyagariMarkovHARK.ipynb: minor metadata update only.

Impact
- `./reproduce.sh` now reproduces all results locally or in CI with a single command.
- Clearer onboarding for new users; Binder badge enables cloud execution.
- Pinned dependencies improve reproducibility across platforms.
Auto-generated README-IF-YOU-ARE-AN-AI.md to make repository more accessible to AI systems.
Includes repository analysis, usage guidance, and search recommendations.
This file configures the repository for optimal AI/RAG system indexing by:
- Defining source file priority (markdown, notebooks, Python code)
- Specifying files to ignore (generated, temporary, binary files)
- Setting up master file relationships
- Configuring careful processing rules for different file types

This improves search quality and reduces index size for AI tools.
- Convert existing .ragignore to new SST format
- Maintains backward compatibility with dual-mode support
- Enables future migration to Elasticsearch-compatible configuration
- Part of the .ragignore system evolution toward standards
- Move rag_config.yaml from root to config/ directory
- Keeps root directory clean and organized
- Follows common configuration file organization practices
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