Closes the last functional parity gap with rust. Python now has voice-driven
Ollama↔Groq switching, persistent across restarts.
llm_backend.py (new, ~130 lines)
Singleton module:
current_client() → active OpenAI client (or None)
current_backend() → 'groq' | 'ollama' | 'none'
current_model() → active model name
swap_to(name) → hot-swap + persist to <here>/llm_backend.txt
parse_backend(name) → ru/en alias normaliser ('облако'→groq, 'локальный'→ollama)
Backends:
- Groq: config.GROQ_TOKEN + GROQ_BASE_URL + GROQ_MODEL (defaults)
- Ollama: OLLAMA_BASE_URL (default http://localhost:11434/v1) +
OLLAMA_MODEL (default qwen2.5:3b). api_key='ollama' (placeholder,
openai lib insists on a non-empty string; Ollama ignores it).
Init precedence (idempotent _ensure_init):
1. Persisted choice from llm_backend.txt
2. JARVIS_LLM env var
3. Auto-detect: Groq if token present, else Ollama
Voice commands (commands.yaml, +3 entries → 151)
llm_switch_local → ollama
llm_switch_cloud → groq
llm_status → speaks current backend
extensions.py
+ do_llm_switch / do_llm_status handlers
+ llm_backend import
do_interesting_fact migrated off direct OpenAI(...) to use llm_backend.current_*
dev_handlers.py
+ llm_backend import
do_codebase_ask + do_github_summarize_pr migrated to llm_backend.current_*
vision_handler.py
Vision call documented as Groq-specific (Ollama doesn't expose vision via
OpenAI-compat in our stack), kept direct config.GROQ_TOKEN reading.
Tests: ast.parse passes for all 5 modules. yaml.safe_load = 151 entries.
PYTHON PARITY VS RUST IS NOW FUNCTIONALLY COMPLETE.
Only remaining rust-only feature: the Tauri GUI (python is console-only).
152 lines
4.5 KiB
Python
152 lines
4.5 KiB
Python
"""LLM backend singleton — Python port of `crates/jarvis-core/src/llm/mod.rs`.
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Supports two backends:
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- Groq (cloud) — uses config.GROQ_TOKEN
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- Ollama (local) — connects to OLLAMA_BASE_URL (default localhost:11434/v1)
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Active choice persists in `<here>/llm_backend.txt`. Loaded on first call.
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Public API:
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current_client() -> OpenAI client for the active backend, or None
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current_backend() -> 'groq' | 'ollama' | 'none'
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current_model() -> model name string
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swap_to(name) -> 'groq' | 'ollama', persists choice
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parse_backend(name) -> normalized 'groq' | 'ollama' | None
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"""
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import os
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import threading
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_HERE = os.path.dirname(os.path.abspath(__file__))
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_CHOICE_FILE = os.path.join(_HERE, 'llm_backend.txt')
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_lock = threading.Lock()
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_client = None
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_backend = 'none'
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_model = ''
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_initialized = False
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def _read_persisted() -> str:
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try:
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with open(_CHOICE_FILE, encoding='utf-8') as f:
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return f.read().strip().lower()
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except OSError:
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return ''
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def _persist(name: str) -> None:
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try:
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with open(_CHOICE_FILE, 'w', encoding='utf-8') as f:
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f.write(name)
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except OSError as exc:
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print(f"[llm] persist: {exc}")
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def parse_backend(name: str) -> str | None:
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"""Normalize a user-facing name to 'groq' / 'ollama' / None."""
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n = (name or '').strip().lower()
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if n in ('groq', 'cloud', 'облако', 'клауд'):
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return 'groq'
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if n in ('ollama', 'local', 'локал', 'локальн', 'локальный'):
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return 'ollama'
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return None
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def _build_groq():
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"""Try to construct a Groq client. Returns (client, model) or raises."""
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try:
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import config as cfg
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except ImportError:
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raise RuntimeError("config.py не найден")
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if not getattr(cfg, 'GROQ_TOKEN', None):
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raise RuntimeError("GROQ_TOKEN отсутствует в config")
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from openai import OpenAI
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base = getattr(cfg, 'GROQ_BASE_URL', 'https://api.groq.com/openai/v1')
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model = getattr(cfg, 'GROQ_MODEL', 'llama-3.3-70b-versatile')
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return OpenAI(api_key=cfg.GROQ_TOKEN, base_url=base), model
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def _build_ollama():
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"""Construct an Ollama-talking OpenAI-compatible client."""
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from openai import OpenAI
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base = os.environ.get('OLLAMA_BASE_URL', 'http://localhost:11434/v1')
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model = os.environ.get('OLLAMA_MODEL', 'qwen2.5:3b')
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# Ollama doesn't need a real key, but openai lib insists on a non-empty string.
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return OpenAI(api_key='ollama', base_url=base), model
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def _build_for(backend: str):
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if backend == 'groq':
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return _build_groq()
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if backend == 'ollama':
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return _build_ollama()
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raise ValueError(f"unknown backend: {backend}")
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def _auto_detect_backend() -> str:
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"""Pick a default backend if none persisted: Groq if token present, else Ollama."""
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try:
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import config as cfg
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if getattr(cfg, 'GROQ_TOKEN', None):
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return 'groq'
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except ImportError:
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pass
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return 'ollama'
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def _ensure_init():
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"""Build the client based on persisted choice, env, or auto-detect."""
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global _client, _backend, _model, _initialized
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if _initialized:
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return
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persisted = _read_persisted()
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env_choice = os.environ.get('JARVIS_LLM', '').strip().lower()
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backend = persisted or env_choice or _auto_detect_backend()
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try:
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client, model = _build_for(backend)
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_client = client
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_backend = backend
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_model = model
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except Exception as exc:
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print(f"[llm] init {backend} failed: {exc}")
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_client = None
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_backend = 'none'
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_model = ''
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_initialized = True
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def current_client():
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"""Get the active client (or None if uninitialised). Cheap after first call."""
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with _lock:
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_ensure_init()
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return _client
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def current_backend() -> str:
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with _lock:
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_ensure_init()
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return _backend
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def current_model() -> str:
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with _lock:
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_ensure_init()
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return _model
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def swap_to(name: str) -> str:
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"""Hot-swap to a different backend. Persists to disk. Returns new name."""
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target = parse_backend(name)
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if not target:
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raise ValueError(f"unknown backend: {name}")
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with _lock:
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global _client, _backend, _model, _initialized
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client, model = _build_for(target) # may raise
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_client = client
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_backend = target
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_model = model
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_initialized = True
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_persist(target)
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print(f"[llm] swapped → {target} ({model})")
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return target
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