tegwick c0615c2d50
Some checks failed
Test Suite / code-quality (push) Has been cancelled
Test Suite / security-scan (push) Has been cancelled
Test Suite / unit-tests (3.11) (push) Has been cancelled
Test Suite / unit-tests (3.12) (push) Has been cancelled
Test Suite / integration-tests (push) Has been cancelled
Test Suite / e2e-tests (push) Has been cancelled
Test Suite / performance-tests (push) Has been cancelled
Test Suite / test-summary (push) Has been cancelled
feat(infospace,llm): stabilize free-tier eval workflow
Five improvements that eliminate most of the agent-in-the-loop friction
observed while closing out the 988-entity WoN evaluation (C.1):

1. Gemini adapter now retries on 429 + 5xx with exponential backoff
   (same pattern already used by OpenRouter/OpenAI). Removes the need
   for shell-level retry wrappers when hitting free-tier rate limits.

2. evaluate CLI prints the underlying error ("ERROR — HTTP 503 …")
   instead of a bare "ERROR", so agents don't have to drop into Python
   to diagnose transient failures.

3. --entity/--chapter now respect existing evaluation files by default
   (previously only the full-collection pass did). New --force flag
   opts into re-evaluation. Stops silently burning free-tier quota on
   re-runs of the same slug.

4. --entity accepts hyphenated slugs (matching entity filenames) and
   normalizes them to the underscore form used on disk. On a miss the
   CLI suggests near matches instead of a bare "not found".

5. eval-summary --update-metrics is no longer destructive:
   read_metrics_file/write_metrics_file preserve structured values
   (type_distribution) and don't flatten ints to floats. Fixes a
   silent data loss observed on every run.

Bonus: the evaluator field in written evaluation frontmatter now
falls back from run_config.model_name to the adapter's resolved model
(or the model echoed back in the API response), so rows no longer
show `evaluator: null` when --model is omitted.

Tests: new tests/unit/llm/test_gemini.py covers retry behavior;
tests/unit/infospace/test_history.py gains a round-trip test that
pins the type_distribution / int-preservation invariants.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-22 00:51:00 +02:00
2025-12-17 23:08:02 +01:00
2025-10-03 03:39:43 +02:00
2025-10-03 03:39:43 +02:00
2026-03-25 00:11:46 +01:00

MarkiTect Documentation

Welcome to the MarkiTect documentation. This directory contains comprehensive documentation for developers, users, and contributors.

Documentation Structure

📐 Architecture Documentation (architecture/)

Deep technical documentation about system design, performance, and implementation details.

  • Capabilities Architecture - Critical: How capabilities work as independent git submodules and separation of concerns
  • Caching System - Why and how MarkiTect's AST caching delivers 60-85% performance improvements
  • Coming soon: Database Schema, CLI Architecture

👥 User Guides (user-guides/)

End-user documentation for working with MarkiTect CLI and features.

  • Coming soon: Getting Started, Command Reference, Best Practices

🔧 Development Documentation (development/)

Documentation for contributors and developers extending MarkiTect.

  • Coming soon: Contributing Guide, Testing Strategy, Release Process

For Users

For Developers

Project Management

Key Concepts

Core Architecture Principles

  1. Parse Once, Use Many Times - AST caching for 60-85% performance improvement
  2. Convention Over Configuration - Sensible defaults with minimal setup
  3. Schema-Driven Processing - Structured markdown with validation
  4. Relational Metadata - Database-powered document relationships

Performance Philosophy

MarkiTect treats markdown documents as structured, queryable data rather than plain text. This approach enables:

  • Lightning-fast document processing through intelligent caching
  • Complex querying and relationship management
  • Schema validation and consistency enforcement
  • Scalable performance that grows with your content

Contributing to Documentation

Documentation follows the same quality standards as code:

  1. Clear Structure - Logical organization and navigation
  2. Practical Examples - Real-world usage patterns
  3. Performance Context - Why architectural decisions matter
  4. User-Focused - Written for the intended audience

Documentation Standards

  • Use clear, concise language
  • Include practical examples
  • Explain the "why" behind design decisions
  • Keep technical accuracy as the highest priority
  • Update docs when changing functionality

This documentation is maintained alongside the codebase. For the most current information, always refer to the latest version in the repository.

Description
An advanced markdown engine
https://coulomb.social/open/MarkiTect
Readme 34 MiB
2025-11-08 20:34:42 +00:00
Languages
Python 84.7%
JavaScript 8%
HTML 5.6%
Makefile 1.3%
Shell 0.2%
Other 0.1%