mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-02-05 01:50:27 +08:00
feat: 添加全局模型锁定功能,防止不同模型混合使用,增强嵌入生成的稳定性
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@@ -1888,7 +1888,13 @@ def embeddings_generate(
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"""
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_configure_logging(verbose, json_mode)
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from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive, scan_for_model_conflicts
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from codexlens.cli.embedding_manager import (
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generate_embeddings,
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generate_embeddings_recursive,
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scan_for_model_conflicts,
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check_global_model_lock,
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set_locked_model_config,
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)
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# Validate backend
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valid_backends = ["fastembed", "litellm"]
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@@ -1956,6 +1962,31 @@ def embeddings_generate(
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console.print(f"Concurrency: [cyan]{max_workers} workers[/cyan]")
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console.print()
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# Check global model lock (prevents mixing different models)
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if not force:
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lock_result = check_global_model_lock(backend, model)
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if lock_result["has_conflict"]:
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locked = lock_result["locked_config"]
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if json_mode:
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print_json(
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success=False,
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error="Global model lock conflict",
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code="MODEL_LOCKED",
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locked_config=locked,
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target_config=lock_result["target_config"],
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hint="Use --force to override the lock and switch to a different model (will regenerate all embeddings)",
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)
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raise typer.Exit(code=1)
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else:
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console.print("[red]⛔ Global Model Lock Active[/red]")
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console.print(f" Locked model: [cyan]{locked['backend']}/{locked['model']}[/cyan]")
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console.print(f" Requested: [yellow]{backend}/{model}[/yellow]")
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console.print(f" Locked at: {locked.get('locked_at', 'unknown')}")
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console.print()
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console.print("[dim]All indexes must use the same embedding model.[/dim]")
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console.print("[dim]Use --force to switch models (will regenerate all embeddings).[/dim]")
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raise typer.Exit(code=1)
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# Pre-check for model conflicts (only if not forcing)
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if not force:
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# Determine the index root for conflict scanning
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@@ -1,13 +1,14 @@
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"""Embedding Manager - Manage semantic embeddings for code indexes."""
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import gc
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import json
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import logging
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import sqlite3
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import time
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from itertools import islice
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from pathlib import Path
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from typing import Dict, Generator, List, Optional, Tuple
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from typing import Any, Dict, Generator, List, Optional, Tuple
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try:
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from codexlens.semantic import SEMANTIC_AVAILABLE, is_embedding_backend_available
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@@ -1097,4 +1098,113 @@ def scan_for_model_conflicts(
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"target_config": {"backend": target_backend, "model": target_model},
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"conflicts": conflicts,
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"indexes_with_embeddings": indexes_with_embeddings,
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}
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def _get_global_settings_path() -> Path:
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"""Get the path to global embedding settings file."""
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return Path.home() / ".codexlens" / "embedding_lock.json"
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def get_locked_model_config() -> Optional[Dict[str, Any]]:
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"""Get the globally locked embedding model configuration.
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Returns:
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Dictionary with backend and model if locked, None otherwise.
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"""
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settings_path = _get_global_settings_path()
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if not settings_path.exists():
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return None
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try:
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with open(settings_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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if data.get("locked"):
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return {
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"backend": data.get("backend"),
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"model": data.get("model"),
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"locked_at": data.get("locked_at"),
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}
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except (json.JSONDecodeError, OSError):
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pass
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return None
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def set_locked_model_config(backend: str, model: str) -> None:
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"""Set the globally locked embedding model configuration.
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This is called after the first successful embedding generation
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to lock the model for all future operations.
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Args:
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backend: Embedding backend (fastembed or litellm)
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model: Model profile/name
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"""
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import datetime
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settings_path = _get_global_settings_path()
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settings_path.parent.mkdir(parents=True, exist_ok=True)
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data = {
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"locked": True,
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"backend": backend,
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"model": model,
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"locked_at": datetime.datetime.now().isoformat(),
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}
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with open(settings_path, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2)
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def clear_locked_model_config() -> bool:
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"""Clear the globally locked embedding model configuration.
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Returns:
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True if lock was cleared, False if no lock existed.
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"""
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settings_path = _get_global_settings_path()
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if settings_path.exists():
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settings_path.unlink()
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return True
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return False
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def check_global_model_lock(
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target_backend: str,
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target_model: str,
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) -> Dict[str, Any]:
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"""Check if the target model conflicts with the global lock.
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Args:
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target_backend: Requested embedding backend
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target_model: Requested model profile/name
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Returns:
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Dictionary with:
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- is_locked: True if a global lock exists
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- has_conflict: True if target differs from locked config
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- locked_config: The locked configuration (if any)
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- target_config: The requested configuration
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"""
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locked_config = get_locked_model_config()
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if locked_config is None:
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return {
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"is_locked": False,
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"has_conflict": False,
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"locked_config": None,
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"target_config": {"backend": target_backend, "model": target_model},
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}
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has_conflict = (
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locked_config["backend"] != target_backend or
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locked_config["model"] != target_model
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)
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return {
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"is_locked": True,
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"has_conflict": has_conflict,
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"locked_config": locked_config,
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"target_config": {"backend": target_backend, "model": target_model},
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}
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