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Update Python library to support AI Dark Factory agent requirements

Abierto
#609 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Nueva funcionalidad
Claridad
Necesita aclaración
Estado de actividad
Estancado
Stack tecnológico
python, rust
Área
ai, backend-api-design, documentation, testing

Línea de trabajo

Read projects/ai-dark-factory-gitea-fork.md and docs/terraphim-agent-command-reference.md first, then identify the existing Python bindings and terraphim-agent CLI entry points. Done means the four requested classes and operations work for all listed agents, with documentation examples and unit tests covering them.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

Background

Building an AI Dark Factory with 10 specialized agents maintaining a Gitea fork. Each agent needs to capture learnings and interact with the Terraphim knowledge graph.

Current State

  • terraphim-agent CLI (Rust) works well: search, learn capture, query, list
  • Python wrapper needed for agent integration
  • Current Python bindings limited

Requirements

1. Agent Learning Capture

Each of 10 agents needs:

2. Knowledge Graph Operations
3. Multi-Agent Coordination
4. Learning Audit

Agent-Specific Requirements

Agent Primary Use Special Needs
Security Sentinel CVE patterns Vulnerability node types
Upstream Sync Merge strategies Git operation patterns
Extension Architect AI optimizations Model performance data
Test Guardian Flaky test causes Test pattern nodes
Code Reviewer Security anti-patterns Code pattern nodes
Scenario Tester Chaos recovery Failure pattern nodes
Product Development Feature prioritization Compound-RICE data
Release Engineer Deployment patterns Canary/rollback data
Market Research Content performance Engagement pattern nodes
Meta-Coordinator Coordination patterns Escalation pattern nodes

Proposed API Design

Implementation Notes

  1. Backend: Can wrap existing Rust CLI via subprocess or use direct bindings
  2. Storage: JSONL files in /data/kg/ with optional graph database
  3. Performance: Agents run locally, low latency required (< 100ms)
  4. Concurrency: Multiple agents may write simultaneously

Acceptance Criteria

  • AgentLearning class functional for all 10 agents
  • KnowledgeGraph add_node/search working
  • MultiAgentCoordination broadcast working
  • LearningAudit spot_check working
  • Documentation with examples
  • Unit tests covering all classes

Timeline

Needed for AI Dark Factory Week 2-3 implementation.

Related

Lenguaje dominante
Rust
Estrellas
62
Forks
5
Merge medio
2 h 27 min
PR fusionados (30 d)
1

Guía de contribución

Abrir la guía de contribución

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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