Praxis CI
47e24dbe59
server/services/base.py defines three abstract base classes with type annotations: TTSProvider (async synthesize/synthesize_all, voice_id), LLMProvider (async chat/chat_full, roleplay_model, debrief_model), Guardrail (async check, session_start_disclaimer). GuardrailVerdict/Context/TTSResult/LLMStreamChunk dataclasses carry typed metadata. server/services/registry.py resolves the active adapter from env (PRAXIS_TTS, PRAXIS_GUARDRAIL) so the pipeline never imports a concrete adapter directly — D-014/D-019/D-020 swap wiring. Verified: 'from server.services import TTSProvider, LLMProvider, Guardrail' succeeds. ---ci--- phase: 1 milestone: v0.1 plan: 02 task: 02-01 status: execute persona: backend-engineer requirements: covered: [REQ-VOICE-02, REQ-LLM-01, REQ-ORCH-02] ---/ci---
36 lines
795 B
Python
36 lines
795 B
Python
"""Praxis service interfaces and adapter registry.
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Public API:
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from server.services import TTSProvider, LLMProvider, Guardrail
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from server.services import get_tts, get_llm, get_guardrail
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Adapters are resolved from env vars:
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PRAXIS_TTS=cartesia|piper
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OLLAMA_ROLEPLAY_MODEL / OLLAMA_DEBRIEF_MODEL
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"""
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from __future__ import annotations
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from server.services.base import (
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Guardrail,
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GuardrailContext,
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GuardrailVerdict,
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LLMProvider,
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LLMStreamChunk,
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TTSProvider,
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TTSResult,
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)
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from server.services.registry import get_guardrail, get_llm, get_tts
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__all__ = [
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"TTSProvider",
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"TTSResult",
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"LLMProvider",
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"LLMStreamChunk",
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"Guardrail",
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"GuardrailVerdict",
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"GuardrailContext",
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"get_tts",
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"get_llm",
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"get_guardrail",
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] |