BobAi
dc866e6ce3
Complete rebrand for v1.0-simple-search branch: Directory Changes: - claude_rag/ → mini_rag/ (preserving git history) Content Changes: - Updated all imports: from claude_rag → from mini_rag - Updated all file paths: .claude-rag → .mini-rag - Updated documentation and comments - Updated configuration files and examples - Updated all tests to use mini_rag imports This ensures complete independence from Claude/Anthropic branding while maintaining all functionality and git history. Simple branch contains the basic RAG system without LLM features.
47 lines
1.2 KiB
Python
47 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 sys
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import os
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from pathlib import Path
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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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from mini_rag.vector_store import VectorStore
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from collections import Counter
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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(f"\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(f"\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(f"\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)") |