Leonid Pershin
2ab32a8ab5
- Removed references to llamacpp from configuration files, scripts, and documentation, streamlining the LLM setup process to focus solely on Ollama. - Updated environment variables and paths to eliminate llamacpp-related entries, ensuring clarity in the configuration. - Adjusted CLI commands and help messages to reflect the removal of llamacpp, enhancing user experience and reducing confusion. - Revised documentation to provide clear guidance on using Ollama exclusively, including updates to setup instructions and runtime options.
111 lines
3.4 KiB
Python
111 lines
3.4 KiB
Python
"""Interactive setup wizard: files + LLM_RUNTIME + optional watchdog."""
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from __future__ import annotations
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import shutil
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from collections.abc import Callable
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from pathlib import Path
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from gpu_rent.llm_runtime import (
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append_vars_llm_runtime,
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ensure_ollama_manifest_from_example,
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llm_runtime_menu,
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normalize_runtime,
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ollama_preset_menu,
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write_ollama_models_preset,
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)
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from gpu_rent.paths import (
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app_root,
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env_path,
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extensions_manifest_path,
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models_manifest_path,
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ollama_models_example_path,
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ollama_models_manifest_path,
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vars_example_path,
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vars_path,
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)
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from gpu_rent.prompts import prompt_menu
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Log = Callable[[str], None]
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def _copy_if_missing(src: Path, dst: Path, label: str, log: Log) -> None:
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if dst.is_file():
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log(f"есть {label}")
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return
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if src.is_file():
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shutil.copy2(src, dst)
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log(f"создал {label} из example")
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else:
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log(f"нет example для {label}: {src}")
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def run_setup(
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*,
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llm: str | None = None,
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ollama_preset: str | None = None,
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install_watchdog: bool | None = None,
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confirm: Callable[[str], bool] | None = None,
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ask: Callable[[str, str], str] | None = None,
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log: Log = print,
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) -> None:
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root = app_root()
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log(f"setup в {root}")
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_copy_if_missing(root / "env.example", env_path(), ".env", log)
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_copy_if_missing(root / "models.example.yaml", models_manifest_path(), "models.yaml", log)
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_copy_if_missing(
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root / "extensions.example.yaml", extensions_manifest_path(), "extensions.yaml", log
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)
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_copy_if_missing(vars_example_path(), vars_path(), "gpu-rent.vars", log)
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_copy_if_missing(
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ollama_models_example_path(), ollama_models_manifest_path(), "ollama-models.yaml", log
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)
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runtime = llm
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if runtime is None:
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if ask:
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runtime = prompt_menu(
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"LLM runtime",
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llm_runtime_menu(),
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default="none",
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ask=ask,
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show=log,
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)
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else:
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runtime = "none"
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runtime = normalize_runtime(runtime)
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append_vars_llm_runtime(vars_path(), runtime)
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log(f"LLM_RUNTIME={runtime} → gpu-rent.vars")
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if runtime == "ollama":
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preset = ollama_preset
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if preset is None and ask:
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preset = prompt_menu(
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"Ollama preset",
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ollama_preset_menu(include_keep=False),
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default="recommended",
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ask=ask,
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show=log,
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)
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if preset is None:
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preset = "recommended"
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if preset.strip().lower() in {"keep", "example", ""}:
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ensure_ollama_manifest_from_example()
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log("ollama-models.yaml из example")
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else:
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write_ollama_models_preset(ollama_models_manifest_path(), preset)
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log(f"ollama-models.yaml пресет={preset}")
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do_wd = install_watchdog
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if do_wd is None and confirm:
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do_wd = confirm("Установить local-watchdog (аварийный stop без Ctrl+C)?")
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if do_wd:
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from gpu_rent.local_watchdog import install_watchdog as _install
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_install(log=log)
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elif do_wd is False:
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log("local-watchdog: skip")
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log("готово. Заполни .env (OS_*), потом: gpu-rent doctor && gpu-rent up")
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