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Evaluate: Extract standalone LLM interaction crate (Pi layered architecture pattern)

Abierto
#684 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
5/5
Tiempo estimado
Más de una semana
Aptitud para principiantes
35/100
Tipo de issue
Refactorización
Claridad
Bastante claro
Estado de actividad
Estancado
Stack tecnológico
rust

Línea de trabajo

Start by mapping LLM interaction points across the 54-crate workspace, including terraphim_orchestrator, terraphim_multi_agent, terraphim_llm_proxy, and cto-executive-system/automation/. Read the referenced Pi pi-ai package and compare existing model routing and agent configurations. Done means a proposed crate boundary, overlap assessment, and a documented extract, refactor, or reject decision with rationale.

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

Descripción

enhancement

Parent Epic

#682 -- Evaluate Pi architectural patterns

Pattern

Pi uses a 3-layer architecture where each layer is independently usable:

pi-ai (unified LLM API, multi-provider streaming, token/cost tracking)
    |
pi-agent-core (stateful agent loop, tool execution, events, state management)
    |
pi-coding-agent (TUI, sessions, extensions, skills, themes)

Any consumer can use pi-ai alone for LLM streaming, pi-agent-core for an agent without UI, or the full stack.

Current State

LLM interaction code in terraphim-ai is scattered across:

  • terraphim_orchestrator -- spawns CLI agents (subprocess management)
  • terraphim_multi_agent -- agent configurations and model routing
  • terraphim_llm_proxy -- HTTP proxy with model routing
  • Ad-hoc scripts in cto-executive-system/automation/

There is no standalone crate for "call an LLM, get a response, track tokens/cost" that other crates can depend on without pulling in the full orchestrator or multi-agent machinery.

Evaluation Questions

  1. What belongs in a standalone LLM crate? Candidates: provider abstraction, streaming response types, token counting, cost calculation, context serialisation, model registry.
  2. Does this overlap with existing crates? Check terraphim_llm_proxy (already has model routing) and terraphim_multi_agent (has agent configs).
  3. Would this simplify ADF? Currently terraphim_orchestrator shells out to claude -p and codex exec. A Rust-native LLM crate could replace some subprocess calls.
  4. What about the Claude Agent SDK? The Agent SDK (#682 context) provides a Python/TypeScript library for Claude. A Rust LLM crate would serve a different purpose (direct API calls, multi-provider, no agent loop).

Acceptance Criteria

  • Map all LLM interaction points across the 54-crate workspace
  • Define proposed crate boundary (what goes in, what stays out)
  • Assess overlap with terraphim_llm_proxy and terraphim_multi_agent
  • Decision: extract, refactor existing, or reject with rationale

References

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

Guía de contribución

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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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