FSSCoding
930f53a0fb
- Applied Black formatter and isort across entire codebase for professional consistency - Moved implementation scripts (rag-mini.py, rag-tui.py) to bin/ directory for cleaner root - Updated shell scripts to reference new bin/ locations maintaining user compatibility - Added comprehensive linting configuration (.flake8, pyproject.toml) with dedicated .venv-linting - Removed development artifacts (commit_message.txt, GET_STARTED.md duplicate) from root - Consolidated documentation and fixed script references across all guides - Relocated test_fixes.py to proper tests/ directory - Enhanced project structure following Python packaging standards All user commands work identically while improving code organization and beginner accessibility.
48 lines
1.2 KiB
Python
48 lines
1.2 KiB
Python
#!/usr/bin/env python3
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"""
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Show what files are actually indexed in the RAG system.
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"""
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import os
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import sys
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from collections import Counter
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from pathlib import Path
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from mini_rag.vector_store import VectorStore
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if sys.platform == "win32":
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os.environ["PYTHONUTF8"] = "1"
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sys.stdout.reconfigure(encoding="utf-8")
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sys.path.insert(0, str(Path(__file__).parent))
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project_path = Path.cwd()
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store = VectorStore(project_path)
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store._connect()
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# Get all indexed files
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files = []
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chunks_by_file = Counter()
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chunk_types = Counter()
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for row in store.table.to_pandas().itertuples():
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files.append(row.file_path)
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chunks_by_file[row.file_path] += 1
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chunk_types[row.chunk_type] += 1
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unique_files = sorted(set(files))
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print("\n Indexed Files Summary")
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print(f"Total files: {len(unique_files)}")
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print(f"Total chunks: {len(files)}")
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print(f"\nChunk types: {dict(chunk_types)}")
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print("\n Files with most chunks:")
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for file, count in chunks_by_file.most_common(10):
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print(f" {count:3d} chunks: {file}")
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print("\n Text-to-speech files:")
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tts_files = [f for f in unique_files if "text-to-speech" in f or "speak" in f.lower()]
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for f in tts_files:
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print(f" - {f} ({chunks_by_file[f]} chunks)")
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