mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-02-05 01:50:27 +08:00
refactor: 移除 CLI 中过宽的异常捕获
- 移除所有 16 个 except Exception 块 - 只保留对特定异常的捕获 (StorageError, ConfigError, SearchError 等) - 允许未知异常自然传播，便于调试 - 保留嵌入功能的可选异常处理 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
catlog22
@@ -1546,26 +1546,25 @@ def model_delete(
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Example:
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codexlens model-delete fast # Delete fast model
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"""
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try:
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from codexlens.cli.model_manager import delete_model
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from codexlens.cli.model_manager import delete_model
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if not json_mode:
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console.print(f"[bold yellow]Deleting model:[/bold yellow] {profile}")
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if not json_mode:
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console.print(f"[bold yellow]Deleting model:[/bold yellow] {profile}")
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result = delete_model(profile)
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result = delete_model(profile)
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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data = result["result"]
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console.print(f"[green]✓[/green] Model deleted successfully!")
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console.print(f" Profile: {data['profile']}")
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console.print(f" Model: {data['model_name']}")
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console.print(f" Freed space: {data['deleted_size_mb']:.1f} MB")
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data = result["result"]
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console.print(f"[green]✓[/green] Model deleted successfully!")
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console.print(f" Profile: {data['profile']}")
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console.print(f" Model: {data['model_name']}")
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console.print(f" Freed space: {data['deleted_size_mb']:.1f} MB")
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@app.command(name="model-info")
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@@ -1578,30 +1577,29 @@ def model_info(
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Example:
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codexlens model-info code # Get code model details
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"""
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try:
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from codexlens.cli.model_manager import get_model_info
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from codexlens.cli.model_manager import get_model_info
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result = get_model_info(profile)
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result = get_model_info(profile)
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if json_mode:
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print_json(**result)
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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data = result["result"]
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console.print(f"[bold]Model Profile:[/bold] {data['profile']}")
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console.print(f" Model name: {data['model_name']}")
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console.print(f" Dimensions: {data['dimensions']}")
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console.print(f" Status: {'[green]Installed[/green]' if data['installed'] else '[dim]Not installed[/dim]'}")
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if data['installed'] and data['actual_size_mb']:
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console.print(f" Cache size: {data['actual_size_mb']:.1f} MB")
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console.print(f" Location: [dim]{data['cache_path']}[/dim]")
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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data = result["result"]
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console.print(f"[bold]Model Profile:[/bold] {data['profile']}")
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console.print(f" Model name: {data['model_name']}")
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console.print(f" Dimensions: {data['dimensions']}")
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console.print(f" Status: {'[green]Installed[/green]' if data['installed'] else '[dim]Not installed[/dim]'}")
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if data['installed'] and data['actual_size_mb']:
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console.print(f" Cache size: {data['actual_size_mb']:.1f} MB")
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console.print(f" Location: [dim]{data['cache_path']}[/dim]")
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else:
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console.print(f" Estimated size: ~{data['estimated_size_mb']} MB")
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console.print(f"\n Description: {data['description']}")
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console.print(f" Use case: {data['use_case']}")
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console.print(f" Estimated size: ~{data['estimated_size_mb']} MB")
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console.print(f"\n Description: {data['description']}")
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console.print(f" Use case: {data['use_case']}")
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# ==================== Embedding Management Commands ====================
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@@ -1627,113 +1625,112 @@ def embeddings_status(
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codexlens embeddings-status ~/.codexlens/indexes/project/_index.db # Check specific index
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codexlens embeddings-status ~/projects/my-app # Check project (auto-finds index)
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"""
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try:
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from codexlens.cli.embedding_manager import check_index_embeddings, get_embedding_stats_summary
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from codexlens.cli.embedding_manager import check_index_embeddings, get_embedding_stats_summary
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# Determine what to check
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if path is None:
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# Check all indexes in default root
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index_root = _get_index_root()
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result = get_embedding_stats_summary(index_root)
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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data = result["result"]
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total = data["total_indexes"]
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with_emb = data["indexes_with_embeddings"]
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total_chunks = data["total_chunks"]
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console.print(f"[bold]Embedding Status Summary[/bold]")
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console.print(f"Index root: [dim]{index_root}[/dim]\n")
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console.print(f"Total indexes: {total}")
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console.print(f"Indexes with embeddings: [{'green' if with_emb > 0 else 'yellow'}]{with_emb}[/]/{total}")
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console.print(f"Total chunks: {total_chunks:,}\n")
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if data["indexes"]:
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table = Table(show_header=True, header_style="bold")
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table.add_column("Project", style="cyan")
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table.add_column("Files", justify="right")
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table.add_column("Chunks", justify="right")
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table.add_column("Coverage", justify="right")
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table.add_column("Status", justify="center")
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for idx_stat in data["indexes"]:
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status_icon = "[green]✓[/green]" if idx_stat["has_embeddings"] else "[dim]—[/dim]"
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coverage = f"{idx_stat['coverage_percent']:.1f}%" if idx_stat["has_embeddings"] else "—"
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table.add_row(
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idx_stat["project"],
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str(idx_stat["total_files"]),
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f"{idx_stat['total_chunks']:,}" if idx_stat["has_embeddings"] else "0",
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coverage,
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status_icon,
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)
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console.print(table)
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# Determine what to check
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if path is None:
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# Check all indexes in default root
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index_root = _get_index_root()
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result = get_embedding_stats_summary(index_root)
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if json_mode:
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print_json(**result)
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else:
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# Check specific index or find index for project
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target_path = path.expanduser().resolve()
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if target_path.is_file() and target_path.name == "_index.db":
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# Direct index file
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index_path = target_path
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elif target_path.is_dir():
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# Try to find index for this project
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registry = RegistryStore()
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try:
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registry.initialize()
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mapper = PathMapper()
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index_path = mapper.source_to_index_db(target_path)
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if not index_path.exists():
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console.print(f"[red]Error:[/red] No index found for {target_path}")
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console.print("Run 'codexlens init' first to create an index")
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raise typer.Exit(code=1)
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finally:
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registry.close()
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else:
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console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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result = check_index_embeddings(index_path)
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data = result["result"]
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total = data["total_indexes"]
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with_emb = data["indexes_with_embeddings"]
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total_chunks = data["total_chunks"]
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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console.print(f"[bold]Embedding Status Summary[/bold]")
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console.print(f"Index root: [dim]{index_root}[/dim]\n")
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console.print(f"Total indexes: {total}")
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console.print(f"Indexes with embeddings: [{'green' if with_emb > 0 else 'yellow'}]{with_emb}[/]/{total}")
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console.print(f"Total chunks: {total_chunks:,}\n")
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if data["indexes"]:
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table = Table(show_header=True, header_style="bold")
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table.add_column("Project", style="cyan")
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table.add_column("Files", justify="right")
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table.add_column("Chunks", justify="right")
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table.add_column("Coverage", justify="right")
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table.add_column("Status", justify="center")
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for idx_stat in data["indexes"]:
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status_icon = "[green]✓[/green]" if idx_stat["has_embeddings"] else "[dim]—[/dim]"
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coverage = f"{idx_stat['coverage_percent']:.1f}%" if idx_stat["has_embeddings"] else "—"
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table.add_row(
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idx_stat["project"],
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str(idx_stat["total_files"]),
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f"{idx_stat['total_chunks']:,}" if idx_stat["has_embeddings"] else "0",
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coverage,
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status_icon,
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)
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console.print(table)
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else:
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# Check specific index or find index for project
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target_path = path.expanduser().resolve()
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if target_path.is_file() and target_path.name == "_index.db":
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# Direct index file
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index_path = target_path
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elif target_path.is_dir():
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# Try to find index for this project
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registry = RegistryStore()
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try:
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registry.initialize()
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mapper = PathMapper()
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index_path = mapper.source_to_index_db(target_path)
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if not index_path.exists():
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console.print(f"[red]Error:[/red] No index found for {target_path}")
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console.print("Run 'codexlens init' first to create an index")
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raise typer.Exit(code=1)
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finally:
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registry.close()
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else:
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console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
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raise typer.Exit(code=1)
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data = result["result"]
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has_emb = data["has_embeddings"]
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result = check_index_embeddings(index_path)
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console.print(f"[bold]Embedding Status[/bold]")
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console.print(f"Index: [dim]{data['index_path']}[/dim]\n")
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if json_mode:
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print_json(**result)
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else:
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if not result["success"]:
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console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
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raise typer.Exit(code=1)
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if has_emb:
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console.print(f"[green]✓[/green] Embeddings available")
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console.print(f" Total chunks: {data['total_chunks']:,}")
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console.print(f" Total files: {data['total_files']:,}")
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console.print(f" Files with embeddings: {data['files_with_chunks']:,}/{data['total_files']}")
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console.print(f" Coverage: {data['coverage_percent']:.1f}%")
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data = result["result"]
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has_emb = data["has_embeddings"]
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if data["files_without_chunks"] > 0:
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console.print(f"\n[yellow]Warning:[/yellow] {data['files_without_chunks']} files missing embeddings")
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if data["missing_files_sample"]:
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console.print(" Sample missing files:")
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for file in data["missing_files_sample"]:
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console.print(f" [dim]{file}[/dim]")
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else:
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console.print(f"[yellow]—[/yellow] No embeddings found")
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console.print(f" Total files indexed: {data['total_files']:,}")
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console.print("\n[dim]Generate embeddings with:[/dim]")
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console.print(f" [cyan]codexlens embeddings-generate {index_path}[/cyan]")
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console.print(f"[bold]Embedding Status[/bold]")
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console.print(f"Index: [dim]{data['index_path']}[/dim]\n")
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if has_emb:
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console.print(f"[green]✓[/green] Embeddings available")
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console.print(f" Total chunks: {data['total_chunks']:,}")
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console.print(f" Total files: {data['total_files']:,}")
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console.print(f" Files with embeddings: {data['files_with_chunks']:,}/{data['total_files']}")
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console.print(f" Coverage: {data['coverage_percent']:.1f}%")
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if data["files_without_chunks"] > 0:
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console.print(f"\n[yellow]Warning:[/yellow] {data['files_without_chunks']} files missing embeddings")
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if data["missing_files_sample"]:
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console.print(" Sample missing files:")
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for file in data["missing_files_sample"]:
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console.print(f" [dim]{file}[/dim]")
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else:
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console.print(f"[yellow]—[/yellow] No embeddings found")
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console.print(f" Total files indexed: {data['total_files']:,}")
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console.print("\n[dim]Generate embeddings with:[/dim]")
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console.print(f" [cyan]codexlens embeddings-generate {index_path}[/cyan]")
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@app.command(name="embeddings-generate")
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@@ -1788,133 +1785,132 @@ def embeddings_generate(
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"""
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_configure_logging(verbose)
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try:
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from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive
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from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive
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# Resolve path
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target_path = path.expanduser().resolve()
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# Resolve path
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target_path = path.expanduser().resolve()
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# Determine if we should use recursive mode
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use_recursive = False
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index_path = None
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index_root = None
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# Determine if we should use recursive mode
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use_recursive = False
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index_path = None
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index_root = None
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if target_path.is_file() and target_path.name == "_index.db":
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# Direct index file
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index_path = target_path
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if recursive:
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# Use parent directory for recursive processing
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use_recursive = True
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index_root = target_path.parent
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elif target_path.is_dir():
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if recursive:
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# Recursive mode: process all _index.db files in directory tree
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use_recursive = True
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index_root = target_path
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else:
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# Non-recursive: Try to find index for this project
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registry = RegistryStore()
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try:
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registry.initialize()
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mapper = PathMapper()
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index_path = mapper.source_to_index_db(target_path)
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if not index_path.exists():
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console.print(f"[red]Error:[/red] No index found for {target_path}")
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console.print("Run 'codexlens init' first to create an index")
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raise typer.Exit(code=1)
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finally:
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registry.close()
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if target_path.is_file() and target_path.name == "_index.db":
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# Direct index file
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index_path = target_path
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if recursive:
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# Use parent directory for recursive processing
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use_recursive = True
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index_root = target_path.parent
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elif target_path.is_dir():
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if recursive:
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# Recursive mode: process all _index.db files in directory tree
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use_recursive = True
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index_root = target_path
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else:
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console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
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# Non-recursive: Try to find index for this project
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registry = RegistryStore()
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try:
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registry.initialize()
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mapper = PathMapper()
|
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index_path = mapper.source_to_index_db(target_path)
|
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|
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if not index_path.exists():
|
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console.print(f"[red]Error:[/red] No index found for {target_path}")
|
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console.print("Run 'codexlens init' first to create an index")
|
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raise typer.Exit(code=1)
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finally:
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registry.close()
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else:
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console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
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raise typer.Exit(code=1)
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# Progress callback
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def progress_update(msg: str):
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if not json_mode and verbose:
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console.print(f" {msg}")
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|
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console.print(f"[bold]Generating embeddings[/bold]")
|
||||
if use_recursive:
|
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console.print(f"Index root: [dim]{index_root}[/dim]")
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console.print(f"Mode: [yellow]Recursive[/yellow]")
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else:
|
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console.print(f"Index: [dim]{index_path}[/dim]")
|
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console.print(f"Model: [cyan]{model}[/cyan]\n")
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|
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if use_recursive:
|
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result = generate_embeddings_recursive(
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index_root,
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model_profile=model,
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force=force,
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chunk_size=chunk_size,
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||||
progress_callback=progress_update,
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)
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else:
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result = generate_embeddings(
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index_path,
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model_profile=model,
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||||
force=force,
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||||
chunk_size=chunk_size,
|
||||
progress_callback=progress_update,
|
||||
)
|
||||
|
||||
if json_mode:
|
||||
print_json(**result)
|
||||
else:
|
||||
if not result["success"]:
|
||||
error_msg = result.get("error", "Unknown error")
|
||||
console.print(f"[red]Error:[/red] {error_msg}")
|
||||
|
||||
# Provide helpful hints
|
||||
if "already has" in error_msg:
|
||||
console.print("\n[dim]Use --force to regenerate existing embeddings[/dim]")
|
||||
elif "Semantic search not available" in error_msg:
|
||||
console.print("\n[dim]Install semantic dependencies:[/dim]")
|
||||
console.print(" [cyan]pip install codexlens[semantic][/cyan]")
|
||||
|
||||
raise typer.Exit(code=1)
|
||||
|
||||
# Progress callback
|
||||
def progress_update(msg: str):
|
||||
if not json_mode and verbose:
|
||||
console.print(f" {msg}")
|
||||
|
||||
console.print(f"[bold]Generating embeddings[/bold]")
|
||||
if use_recursive:
|
||||
console.print(f"Index root: [dim]{index_root}[/dim]")
|
||||
console.print(f"Mode: [yellow]Recursive[/yellow]")
|
||||
else:
|
||||
console.print(f"Index: [dim]{index_path}[/dim]")
|
||||
console.print(f"Model: [cyan]{model}[/cyan]\n")
|
||||
data = result["result"]
|
||||
|
||||
if use_recursive:
|
||||
result = generate_embeddings_recursive(
|
||||
index_root,
|
||||
model_profile=model,
|
||||
force=force,
|
||||
chunk_size=chunk_size,
|
||||
progress_callback=progress_update,
|
||||
)
|
||||
# Recursive mode output
|
||||
console.print(f"[green]✓[/green] Recursive embeddings generation complete!")
|
||||
console.print(f" Indexes processed: {data['indexes_processed']}")
|
||||
console.print(f" Indexes successful: {data['indexes_successful']}")
|
||||
if data['indexes_failed'] > 0:
|
||||
console.print(f" [yellow]Indexes failed: {data['indexes_failed']}[/yellow]")
|
||||
console.print(f" Total chunks created: {data['total_chunks_created']:,}")
|
||||
console.print(f" Total files processed: {data['total_files_processed']}")
|
||||
if data['total_files_failed'] > 0:
|
||||
console.print(f" [yellow]Total files failed: {data['total_files_failed']}[/yellow]")
|
||||
console.print(f" Model profile: {data['model_profile']}")
|
||||
|
||||
# Show details if verbose
|
||||
if verbose and data.get('details'):
|
||||
console.print("\n[dim]Index details:[/dim]")
|
||||
for detail in data['details']:
|
||||
status_icon = "[green]✓[/green]" if detail['success'] else "[red]✗[/red]"
|
||||
console.print(f" {status_icon} {detail['path']}")
|
||||
if not detail['success'] and detail.get('error'):
|
||||
console.print(f" [dim]Error: {detail['error']}[/dim]")
|
||||
else:
|
||||
result = generate_embeddings(
|
||||
index_path,
|
||||
model_profile=model,
|
||||
force=force,
|
||||
chunk_size=chunk_size,
|
||||
progress_callback=progress_update,
|
||||
)
|
||||
# Single index mode output
|
||||
elapsed = data["elapsed_time"]
|
||||
|
||||
if json_mode:
|
||||
print_json(**result)
|
||||
else:
|
||||
if not result["success"]:
|
||||
error_msg = result.get("error", "Unknown error")
|
||||
console.print(f"[red]Error:[/red] {error_msg}")
|
||||
console.print(f"[green]✓[/green] Embeddings generated successfully!")
|
||||
console.print(f" Model: {data['model_name']}")
|
||||
console.print(f" Chunks created: {data['chunks_created']:,}")
|
||||
console.print(f" Files processed: {data['files_processed']}")
|
||||
|
||||
# Provide helpful hints
|
||||
if "already has" in error_msg:
|
||||
console.print("\n[dim]Use --force to regenerate existing embeddings[/dim]")
|
||||
elif "Semantic search not available" in error_msg:
|
||||
console.print("\n[dim]Install semantic dependencies:[/dim]")
|
||||
console.print(" [cyan]pip install codexlens[semantic][/cyan]")
|
||||
if data["files_failed"] > 0:
|
||||
console.print(f" [yellow]Files failed: {data['files_failed']}[/yellow]")
|
||||
if data["failed_files"]:
|
||||
console.print(" [dim]First failures:[/dim]")
|
||||
for file_path, error in data["failed_files"]:
|
||||
console.print(f" [dim]{file_path}: {error}[/dim]")
|
||||
|
||||
raise typer.Exit(code=1)
|
||||
console.print(f" Time: {elapsed:.1f}s")
|
||||
|
||||
data = result["result"]
|
||||
|
||||
if use_recursive:
|
||||
# Recursive mode output
|
||||
console.print(f"[green]✓[/green] Recursive embeddings generation complete!")
|
||||
console.print(f" Indexes processed: {data['indexes_processed']}")
|
||||
console.print(f" Indexes successful: {data['indexes_successful']}")
|
||||
if data['indexes_failed'] > 0:
|
||||
console.print(f" [yellow]Indexes failed: {data['indexes_failed']}[/yellow]")
|
||||
console.print(f" Total chunks created: {data['total_chunks_created']:,}")
|
||||
console.print(f" Total files processed: {data['total_files_processed']}")
|
||||
if data['total_files_failed'] > 0:
|
||||
console.print(f" [yellow]Total files failed: {data['total_files_failed']}[/yellow]")
|
||||
console.print(f" Model profile: {data['model_profile']}")
|
||||
|
||||
# Show details if verbose
|
||||
if verbose and data.get('details'):
|
||||
console.print("\n[dim]Index details:[/dim]")
|
||||
for detail in data['details']:
|
||||
status_icon = "[green]✓[/green]" if detail['success'] else "[red]✗[/red]"
|
||||
console.print(f" {status_icon} {detail['path']}")
|
||||
if not detail['success'] and detail.get('error'):
|
||||
console.print(f" [dim]Error: {detail['error']}[/dim]")
|
||||
else:
|
||||
# Single index mode output
|
||||
elapsed = data["elapsed_time"]
|
||||
|
||||
console.print(f"[green]✓[/green] Embeddings generated successfully!")
|
||||
console.print(f" Model: {data['model_name']}")
|
||||
console.print(f" Chunks created: {data['chunks_created']:,}")
|
||||
console.print(f" Files processed: {data['files_processed']}")
|
||||
|
||||
if data["files_failed"] > 0:
|
||||
console.print(f" [yellow]Files failed: {data['files_failed']}[/yellow]")
|
||||
if data["failed_files"]:
|
||||
console.print(" [dim]First failures:[/dim]")
|
||||
for file_path, error in data["failed_files"]:
|
||||
console.print(f" [dim]{file_path}: {error}[/dim]")
|
||||
|
||||
console.print(f" Time: {elapsed:.1f}s")
|
||||
|
||||
console.print("\n[dim]Use vector search with:[/dim]")
|
||||
console.print(" [cyan]codexlens search 'your query' --mode pure-vector[/cyan]")
|
||||
console.print("\n[dim]Use vector search with:[/dim]")
|
||||
console.print(" [cyan]codexlens search 'your query' --mode pure-vector[/cyan]")
|
||||
|
||||
Reference in New Issue
Block a user