mirror of
https://github.com/catlog22/Claude-Code-Workflow.git
synced 2026-02-10 02:24:35 +08:00
feat: Enhance embedding generation to track current index path and improve metadata retrieval
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catlog22
@@ -1990,12 +1990,6 @@ def embeddings_generate(
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"--chunk-size",
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help="Maximum chunk size in characters.",
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),
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recursive: bool = typer.Option(
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False,
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"--recursive",
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"-r",
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help="Recursively process all _index.db files in directory tree.",
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),
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max_workers: int = typer.Option(
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1,
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"--max-workers",
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@@ -2049,7 +2043,6 @@ def embeddings_generate(
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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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generate_dense_embeddings_centralized,
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scan_for_model_conflicts,
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check_global_model_lock,
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@@ -2070,25 +2063,21 @@ def embeddings_generate(
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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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# Determine index path or root for centralized mode
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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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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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# Directory: Try to find index for this project
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if centralized:
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# Centralized mode uses directory as root
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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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# Single index mode: find the specific index
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registry = RegistryStore()
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try:
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registry.initialize()
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@@ -2099,6 +2088,7 @@ def embeddings_generate(
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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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index_root = index_path.parent
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finally:
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registry.close()
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else:
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@@ -2115,9 +2105,6 @@ def embeddings_generate(
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effective_root = index_root if index_root else (index_path.parent if index_path else target_path)
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console.print(f"Index root: [dim]{effective_root}[/dim]")
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console.print(f"Mode: [green]Centralized[/green]")
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elif 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"Backend: [cyan]{backend}[/cyan]")
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@@ -2154,7 +2141,7 @@ def embeddings_generate(
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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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scan_root = index_root if use_recursive else (index_path.parent if index_path else None)
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scan_root = index_root if index_root else (index_path.parent if index_path else None)
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if scan_root:
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conflict_result = scan_for_model_conflicts(scan_root, backend, model)
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@@ -2208,16 +2195,6 @@ def embeddings_generate(
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progress_callback=progress_update,
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max_workers=max_workers,
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)
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elif use_recursive:
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result = generate_embeddings_recursive(
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index_root,
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embedding_backend=backend,
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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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max_workers=max_workers,
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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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@@ -2257,7 +2234,7 @@ def embeddings_generate(
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if centralized:
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# Centralized mode output
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elapsed = data.get("elapsed_time", 0)
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console.print(f"[green]✓[/green] Centralized embeddings generated successfully!")
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console.print(f"[green]v[/green] Centralized embeddings generated successfully!")
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console.print(f" Model: {data.get('model_name', model)}")
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console.print(f" Chunks created: {data['chunks_created']:,}")
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console.print(f" Files processed: {data['files_processed']}")
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@@ -2265,32 +2242,11 @@ def embeddings_generate(
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console.print(f" [yellow]Files failed: {data['files_failed']}[/yellow]")
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console.print(f" Central index: {data.get('central_index_path', 'N/A')}")
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console.print(f" Time: {elapsed:.1f}s")
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elif use_recursive:
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# Recursive mode output
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console.print(f"[green]✓[/green] Recursive embeddings generation complete!")
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console.print(f" Indexes processed: {data['indexes_processed']}")
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console.print(f" Indexes successful: {data['indexes_successful']}")
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if data['indexes_failed'] > 0:
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console.print(f" [yellow]Indexes failed: {data['indexes_failed']}[/yellow]")
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console.print(f" Total chunks created: {data['total_chunks_created']:,}")
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console.print(f" Total files processed: {data['total_files_processed']}")
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if data['total_files_failed'] > 0:
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console.print(f" [yellow]Total files failed: {data['total_files_failed']}[/yellow]")
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console.print(f" Model profile: {data['model_profile']}")
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# Show details if verbose
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if verbose and data.get('details'):
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console.print("\n[dim]Index details:[/dim]")
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for detail in data['details']:
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status_icon = "[green]✓[/green]" if detail['success'] else "[red]✗[/red]"
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console.print(f" {status_icon} {detail['path']}")
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if not detail['success'] and detail.get('error'):
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console.print(f" [dim]Error: {detail['error']}[/dim]")
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else:
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# Single index mode output
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elapsed = data["elapsed_time"]
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console.print(f"[green]✓[/green] Embeddings generated successfully!")
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console.print(f"[green]v[/green] Embeddings generated successfully!")
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console.print(f" Model: {data['model_name']}")
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console.print(f" Chunks created: {data['chunks_created']:,}")
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console.print(f" Files processed: {data['files_processed']}")
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