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refactor: 移除 CLI 中过宽的异常捕获

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- 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
2025-12-21 17:19:54 +08:00
parent fa81793bea
commit f492f4839a
1 changed files with 246 additions and 250 deletions
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496
codex-lens/src/codexlens/cli/commands.py
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@@ -1546,26 +1546,25 @@ def model_delete(
Example: Example:
codexlens model-delete fast # Delete fast model codexlens model-delete fast # Delete fast model
""" """
try: from codexlens.cli.model_manager import delete_model
from codexlens.cli.model_manager import delete_model
if not json_mode: if not json_mode:
console.print(f"[bold yellow]Deleting model:[/bold yellow] {profile}") console.print(f"[bold yellow]Deleting model:[/bold yellow] {profile}")
result = delete_model(profile) result = delete_model(profile)
if json_mode: if json_mode:
print_json(**result) print_json(**result)
else: else:
if not result["success"]: if not result["success"]:
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}") console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
raise typer.Exit(code=1) raise typer.Exit(code=1)
data = result["result"] data = result["result"]
console.print(f"[green]✓[/green] Model deleted successfully!") console.print(f"[green]✓[/green] Model deleted successfully!")
console.print(f" Profile: {data['profile']}") console.print(f" Profile: {data['profile']}")
console.print(f" Model: {data['model_name']}") console.print(f" Model: {data['model_name']}")
console.print(f" Freed space: {data['deleted_size_mb']:.1f} MB") console.print(f" Freed space: {data['deleted_size_mb']:.1f} MB")
@app.command(name="model-info") @app.command(name="model-info")
@@ -1578,30 +1577,29 @@ def model_info(
Example: Example:
codexlens model-info code # Get code model details codexlens model-info code # Get code model details
""" """
try: from codexlens.cli.model_manager import get_model_info
from codexlens.cli.model_manager import get_model_info
result = get_model_info(profile) result = get_model_info(profile)
if json_mode: if json_mode:
print_json(**result) print_json(**result)
else:
if not result["success"]:
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
raise typer.Exit(code=1)
data = result["result"]
console.print(f"[bold]Model Profile:[/bold] {data['profile']}")
console.print(f" Model name: {data['model_name']}")
console.print(f" Dimensions: {data['dimensions']}")
console.print(f" Status: {'[green]Installed[/green]' if data['installed'] else '[dim]Not installed[/dim]'}")
if data['installed'] and data['actual_size_mb']:
console.print(f" Cache size: {data['actual_size_mb']:.1f} MB")
console.print(f" Location: [dim]{data['cache_path']}[/dim]")
else: else:
if not result["success"]: console.print(f" Estimated size: ~{data['estimated_size_mb']} MB")
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}") console.print(f"\n Description: {data['description']}")
raise typer.Exit(code=1) console.print(f" Use case: {data['use_case']}")
data = result["result"]
console.print(f"[bold]Model Profile:[/bold] {data['profile']}")
console.print(f" Model name: {data['model_name']}")
console.print(f" Dimensions: {data['dimensions']}")
console.print(f" Status: {'[green]Installed[/green]' if data['installed'] else '[dim]Not installed[/dim]'}")
if data['installed'] and data['actual_size_mb']:
console.print(f" Cache size: {data['actual_size_mb']:.1f} MB")
console.print(f" Location: [dim]{data['cache_path']}[/dim]")
else:
console.print(f" Estimated size: ~{data['estimated_size_mb']} MB")
console.print(f"\n Description: {data['description']}")
console.print(f" Use case: {data['use_case']}")
# ==================== Embedding Management Commands ==================== # ==================== Embedding Management Commands ====================
@@ -1627,113 +1625,112 @@ def embeddings_status(
codexlens embeddings-status ~/.codexlens/indexes/project/_index.db # Check specific index codexlens embeddings-status ~/.codexlens/indexes/project/_index.db # Check specific index
codexlens embeddings-status ~/projects/my-app # Check project (auto-finds index) codexlens embeddings-status ~/projects/my-app # Check project (auto-finds index)
""" """
try: from codexlens.cli.embedding_manager import check_index_embeddings, get_embedding_stats_summary
from codexlens.cli.embedding_manager import check_index_embeddings, get_embedding_stats_summary
# Determine what to check # Determine what to check
if path is None: if path is None:
# Check all indexes in default root # Check all indexes in default root
index_root = _get_index_root() index_root = _get_index_root()
result = get_embedding_stats_summary(index_root) result = get_embedding_stats_summary(index_root)
if json_mode:
print_json(**result)
else:
if not result["success"]:
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
raise typer.Exit(code=1)
data = result["result"]
total = data["total_indexes"]
with_emb = data["indexes_with_embeddings"]
total_chunks = data["total_chunks"]
console.print(f"[bold]Embedding Status Summary[/bold]")
console.print(f"Index root: [dim]{index_root}[/dim]\n")
console.print(f"Total indexes: {total}")
console.print(f"Indexes with embeddings: [{'green' if with_emb > 0 else 'yellow'}]{with_emb}[/]/{total}")
console.print(f"Total chunks: {total_chunks:,}\n")
if data["indexes"]:
table = Table(show_header=True, header_style="bold")
table.add_column("Project", style="cyan")
table.add_column("Files", justify="right")
table.add_column("Chunks", justify="right")
table.add_column("Coverage", justify="right")
table.add_column("Status", justify="center")
for idx_stat in data["indexes"]:
status_icon = "[green]✓[/green]" if idx_stat["has_embeddings"] else "[dim]—[/dim]"
coverage = f"{idx_stat['coverage_percent']:.1f}%" if idx_stat["has_embeddings"] else "—"
table.add_row(
idx_stat["project"],
str(idx_stat["total_files"]),
f"{idx_stat['total_chunks']:,}" if idx_stat["has_embeddings"] else "0",
coverage,
status_icon,
)
console.print(table)
if json_mode:
print_json(**result)
else: else:
# Check specific index or find index for project if not result["success"]:
target_path = path.expanduser().resolve() console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
if target_path.is_file() and target_path.name == "_index.db":
# Direct index file
index_path = target_path
elif target_path.is_dir():
# Try to find index for this project
registry = RegistryStore()
try:
registry.initialize()
mapper = PathMapper()
index_path = mapper.source_to_index_db(target_path)
if not index_path.exists():
console.print(f"[red]Error:[/red] No index found for {target_path}")
console.print("Run 'codexlens init' first to create an index")
raise typer.Exit(code=1)
finally:
registry.close()
else:
console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
raise typer.Exit(code=1) raise typer.Exit(code=1)
result = check_index_embeddings(index_path) data = result["result"]
total = data["total_indexes"]
with_emb = data["indexes_with_embeddings"]
total_chunks = data["total_chunks"]
if json_mode: console.print(f"[bold]Embedding Status Summary[/bold]")
print_json(**result) console.print(f"Index root: [dim]{index_root}[/dim]\n")
else: console.print(f"Total indexes: {total}")
if not result["success"]: console.print(f"Indexes with embeddings: [{'green' if with_emb > 0 else 'yellow'}]{with_emb}[/]/{total}")
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}") console.print(f"Total chunks: {total_chunks:,}\n")
if data["indexes"]:
table = Table(show_header=True, header_style="bold")
table.add_column("Project", style="cyan")
table.add_column("Files", justify="right")
table.add_column("Chunks", justify="right")
table.add_column("Coverage", justify="right")
table.add_column("Status", justify="center")
for idx_stat in data["indexes"]:
status_icon = "[green]✓[/green]" if idx_stat["has_embeddings"] else "[dim]—[/dim]"
coverage = f"{idx_stat['coverage_percent']:.1f}%" if idx_stat["has_embeddings"] else "—"
table.add_row(
idx_stat["project"],
str(idx_stat["total_files"]),
f"{idx_stat['total_chunks']:,}" if idx_stat["has_embeddings"] else "0",
coverage,
status_icon,
)
console.print(table)
else:
# Check specific index or find index for project
target_path = path.expanduser().resolve()
if target_path.is_file() and target_path.name == "_index.db":
# Direct index file
index_path = target_path
elif target_path.is_dir():
# Try to find index for this project
registry = RegistryStore()
try:
registry.initialize()
mapper = PathMapper()
index_path = mapper.source_to_index_db(target_path)
if not index_path.exists():
console.print(f"[red]Error:[/red] No index found for {target_path}")
console.print("Run 'codexlens init' first to create an index")
raise typer.Exit(code=1) raise typer.Exit(code=1)
finally:
registry.close()
else:
console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
raise typer.Exit(code=1)
data = result["result"] result = check_index_embeddings(index_path)
has_emb = data["has_embeddings"]
console.print(f"[bold]Embedding Status[/bold]") if json_mode:
console.print(f"Index: [dim]{data['index_path']}[/dim]\n") print_json(**result)
else:
if not result["success"]:
console.print(f"[red]Error:[/red] {result.get('error', 'Unknown error')}")
raise typer.Exit(code=1)
if has_emb: data = result["result"]
console.print(f"[green]✓[/green] Embeddings available") has_emb = data["has_embeddings"]
console.print(f" Total chunks: {data['total_chunks']:,}")
console.print(f" Total files: {data['total_files']:,}")
console.print(f" Files with embeddings: {data['files_with_chunks']:,}/{data['total_files']}")
console.print(f" Coverage: {data['coverage_percent']:.1f}%")
if data["files_without_chunks"] > 0: console.print(f"[bold]Embedding Status[/bold]")
console.print(f"\n[yellow]Warning:[/yellow] {data['files_without_chunks']} files missing embeddings") console.print(f"Index: [dim]{data['index_path']}[/dim]\n")
if data["missing_files_sample"]:
console.print(" Sample missing files:") if has_emb:
for file in data["missing_files_sample"]: console.print(f"[green]✓[/green] Embeddings available")
console.print(f" [dim]{file}[/dim]") console.print(f" Total chunks: {data['total_chunks']:,}")
else: console.print(f" Total files: {data['total_files']:,}")
console.print(f"[yellow]—[/yellow] No embeddings found") console.print(f" Files with embeddings: {data['files_with_chunks']:,}/{data['total_files']}")
console.print(f" Total files indexed: {data['total_files']:,}") console.print(f" Coverage: {data['coverage_percent']:.1f}%")
console.print("\n[dim]Generate embeddings with:[/dim]")
console.print(f" [cyan]codexlens embeddings-generate {index_path}[/cyan]") if data["files_without_chunks"] > 0:
console.print(f"\n[yellow]Warning:[/yellow] {data['files_without_chunks']} files missing embeddings")
if data["missing_files_sample"]:
console.print(" Sample missing files:")
for file in data["missing_files_sample"]:
console.print(f" [dim]{file}[/dim]")
else:
console.print(f"[yellow]—[/yellow] No embeddings found")
console.print(f" Total files indexed: {data['total_files']:,}")
console.print("\n[dim]Generate embeddings with:[/dim]")
console.print(f" [cyan]codexlens embeddings-generate {index_path}[/cyan]")
@app.command(name="embeddings-generate") @app.command(name="embeddings-generate")
@@ -1788,133 +1785,132 @@ def embeddings_generate(
""" """
_configure_logging(verbose) _configure_logging(verbose)
try: from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive
from codexlens.cli.embedding_manager import generate_embeddings, generate_embeddings_recursive
# Resolve path # Resolve path
target_path = path.expanduser().resolve() target_path = path.expanduser().resolve()
# Determine if we should use recursive mode # Determine if we should use recursive mode
use_recursive = False use_recursive = False
index_path = None index_path = None
index_root = None index_root = None
if target_path.is_file() and target_path.name == "_index.db": if target_path.is_file() and target_path.name == "_index.db":
# Direct index file # Direct index file
index_path = target_path index_path = target_path
if recursive: if recursive:
# Use parent directory for recursive processing # Use parent directory for recursive processing
use_recursive = True use_recursive = True
index_root = target_path.parent index_root = target_path.parent
elif target_path.is_dir(): elif target_path.is_dir():
if recursive: if recursive:
# Recursive mode: process all _index.db files in directory tree # Recursive mode: process all _index.db files in directory tree
use_recursive = True use_recursive = True
index_root = target_path index_root = target_path
else:
# Non-recursive: Try to find index for this project
registry = RegistryStore()
try:
registry.initialize()
mapper = PathMapper()
index_path = mapper.source_to_index_db(target_path)
if not index_path.exists():
console.print(f"[red]Error:[/red] No index found for {target_path}")
console.print("Run 'codexlens init' first to create an index")
raise typer.Exit(code=1)
finally:
registry.close()
else: else:
console.print(f"[red]Error:[/red] Path must be _index.db file or directory") # Non-recursive: Try to find index for this project
registry = RegistryStore()
try:
registry.initialize()
mapper = PathMapper()
index_path = mapper.source_to_index_db(target_path)
if not index_path.exists():
console.print(f"[red]Error:[/red] No index found for {target_path}")
console.print("Run 'codexlens init' first to create an index")
raise typer.Exit(code=1)
finally:
registry.close()
else:
console.print(f"[red]Error:[/red] Path must be _index.db file or directory")
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")
if use_recursive:
result = generate_embeddings_recursive(
index_root,
model_profile=model,
force=force,
chunk_size=chunk_size,
progress_callback=progress_update,
)
else:
result = generate_embeddings(
index_path,
model_profile=model,
force=force,
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) raise typer.Exit(code=1)
# Progress callback data = result["result"]
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")
if use_recursive: if use_recursive:
result = generate_embeddings_recursive( # Recursive mode output
index_root, console.print(f"[green]✓[/green] Recursive embeddings generation complete!")
model_profile=model, console.print(f" Indexes processed: {data['indexes_processed']}")
force=force, console.print(f" Indexes successful: {data['indexes_successful']}")
chunk_size=chunk_size, if data['indexes_failed'] > 0:
progress_callback=progress_update, 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: else:
result = generate_embeddings( # Single index mode output
index_path, elapsed = data["elapsed_time"]
model_profile=model,
force=force,
chunk_size=chunk_size,
progress_callback=progress_update,
)
if json_mode: console.print(f"[green]✓[/green] Embeddings generated successfully!")
print_json(**result) console.print(f" Model: {data['model_name']}")
else: console.print(f" Chunks created: {data['chunks_created']:,}")
if not result["success"]: console.print(f" Files processed: {data['files_processed']}")
error_msg = result.get("error", "Unknown error")
console.print(f"[red]Error:[/red] {error_msg}")
# Provide helpful hints if data["files_failed"] > 0:
if "already has" in error_msg: console.print(f" [yellow]Files failed: {data['files_failed']}[/yellow]")
console.print("\n[dim]Use --force to regenerate existing embeddings[/dim]") if data["failed_files"]:
elif "Semantic search not available" in error_msg: console.print(" [dim]First failures:[/dim]")
console.print("\n[dim]Install semantic dependencies:[/dim]") for file_path, error in data["failed_files"]:
console.print(" [cyan]pip install codexlens[semantic][/cyan]") console.print(f" [dim]{file_path}: {error}[/dim]")
raise typer.Exit(code=1) console.print(f" Time: {elapsed:.1f}s")
data = result["result"] console.print("\n[dim]Use vector search with:[/dim]")
console.print(" [cyan]codexlens search 'your query' --mode pure-vector[/cyan]")
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]")