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.
355 lines
12 KiB
Python
355 lines
12 KiB
Python
"""
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Integration test to verify all three agents' work integrates properly.
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"""
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import sys
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import os
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import tempfile
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from pathlib import Path
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# Fix Windows encoding
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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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from mini_rag.chunker import CodeChunker
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from mini_rag.indexer import ProjectIndexer
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from mini_rag.search import CodeSearcher
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from mini_rag.embeddings import CodeEmbedder
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def test_chunker():
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"""Test that chunker creates chunks with all required metadata."""
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print("1. Testing Chunker...")
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# Create test Python file with more substantial content
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test_code = '''"""Test module for integration testing the chunker."""
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import os
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import sys
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class TestClass:
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"""A test class with multiple methods."""
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def __init__(self):
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"""Initialize the test class."""
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self.value = 42
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self.name = "test"
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def method_one(self):
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"""First method with some logic."""
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result = self.value * 2
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return result
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def method_two(self, x):
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"""Second method that takes a parameter."""
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if x > 0:
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return self.value + x
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else:
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return self.value - x
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def method_three(self):
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"""Third method for testing."""
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data = []
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for i in range(10):
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data.append(i * self.value)
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return data
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class AnotherClass:
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"""Another test class."""
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def __init__(self, name):
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"""Initialize with name."""
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self.name = name
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def process(self):
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"""Process something."""
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return f"Processing {self.name}"
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def standalone_function(arg1, arg2):
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"""A standalone function that does something."""
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result = arg1 + arg2
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return result * 2
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def another_function():
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"""Another standalone function."""
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data = {"key": "value", "number": 123}
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return data
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'''
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chunker = CodeChunker(min_chunk_size=1) # Use small chunk size for testing
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chunks = chunker.chunk_file(Path("test.py"), test_code)
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print(f" Created {len(chunks)} chunks")
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# Debug: Show what chunks were created
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print(" Chunks created:")
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for chunk in chunks:
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print(f" - Type: {chunk.chunk_type}, Name: {chunk.name}, Lines: {chunk.start_line}-{chunk.end_line}")
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# Check metadata
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issues = []
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for i, chunk in enumerate(chunks):
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if chunk.chunk_index is None:
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issues.append(f"Chunk {i} missing chunk_index")
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if chunk.total_chunks is None:
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issues.append(f"Chunk {i} missing total_chunks")
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if chunk.file_lines is None:
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issues.append(f"Chunk {i} missing file_lines")
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# Check links (except first/last)
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if i > 0 and chunk.prev_chunk_id is None:
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issues.append(f"Chunk {i} missing prev_chunk_id")
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if i < len(chunks) - 1 and chunk.next_chunk_id is None:
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issues.append(f"Chunk {i} missing next_chunk_id")
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# Check parent_class for methods
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if chunk.chunk_type == 'method' and chunk.parent_class is None:
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issues.append(f"Method chunk {chunk.name} missing parent_class")
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print(f" - Chunk {i}: {chunk.chunk_type} '{chunk.name}' "
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f"[{chunk.chunk_index}/{chunk.total_chunks}] "
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f"prev={chunk.prev_chunk_id} next={chunk.next_chunk_id}")
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if issues:
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print(" Issues found:")
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for issue in issues:
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print(f" - {issue}")
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else:
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print(" All metadata present")
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return len(issues) == 0
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def test_indexer_storage():
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"""Test that indexer stores the new metadata."""
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print("\n2. Testing Indexer Storage...")
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with tempfile.TemporaryDirectory() as tmpdir:
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project_path = Path(tmpdir)
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# Create test file
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test_file = project_path / "test.py"
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test_file.write_text('''
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class MyClass:
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def my_method(self):
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return 42
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''')
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# Index the project with small chunk size for testing
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from mini_rag.chunker import CodeChunker
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chunker = CodeChunker(min_chunk_size=1)
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indexer = ProjectIndexer(project_path, chunker=chunker)
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stats = indexer.index_project()
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print(f" Indexed {stats['chunks_created']} chunks")
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# Check what was stored
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if indexer.table:
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df = indexer.table.to_pandas()
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columns = df.columns.tolist()
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required_fields = ['chunk_id', 'prev_chunk_id', 'next_chunk_id', 'parent_class']
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missing_fields = [f for f in required_fields if f not in columns]
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if missing_fields:
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print(f" Missing fields in database: {missing_fields}")
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print(f" Current fields: {columns}")
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return False
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else:
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print(" All required fields in database schema")
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# Check if data is actually stored
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sample = df.iloc[0] if len(df) > 0 else None
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if sample is not None:
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print(f" Sample chunk_id: {sample.get('chunk_id', 'MISSING')}")
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print(f" Sample prev_chunk_id: {sample.get('prev_chunk_id', 'MISSING')}")
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print(f" Sample next_chunk_id: {sample.get('next_chunk_id', 'MISSING')}")
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print(f" Sample parent_class: {sample.get('parent_class', 'MISSING')}")
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return len(missing_fields) == 0
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def test_search_integration():
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"""Test that search uses the new metadata."""
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print("\n3. Testing Search Integration...")
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with tempfile.TemporaryDirectory() as tmpdir:
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project_path = Path(tmpdir)
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# Create test files with proper content that will create multiple chunks
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(project_path / "math_utils.py").write_text('''"""Math utilities module."""
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import math
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class Calculator:
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"""A simple calculator class."""
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def __init__(self):
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"""Initialize calculator."""
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self.result = 0
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def add(self, a, b):
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"""Add two numbers."""
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self.result = a + b
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return self.result
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def multiply(self, a, b):
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"""Multiply two numbers."""
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self.result = a * b
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return self.result
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def divide(self, a, b):
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"""Divide two numbers."""
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if b == 0:
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raise ValueError("Cannot divide by zero")
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self.result = a / b
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return self.result
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class AdvancedCalculator(Calculator):
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"""Advanced calculator with more operations."""
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def power(self, a, b):
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"""Raise a to power b."""
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self.result = a ** b
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return self.result
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def sqrt(self, a):
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"""Calculate square root."""
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self.result = math.sqrt(a)
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return self.result
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def compute_average(numbers):
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"""Compute average of a list."""
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if not numbers:
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return 0
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return sum(numbers) / len(numbers)
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def compute_median(numbers):
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"""Compute median of a list."""
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if not numbers:
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return 0
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sorted_nums = sorted(numbers)
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n = len(sorted_nums)
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if n % 2 == 0:
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return (sorted_nums[n//2-1] + sorted_nums[n//2]) / 2
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return sorted_nums[n//2]
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''')
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# Index with small chunk size for testing
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chunker = CodeChunker(min_chunk_size=1)
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indexer = ProjectIndexer(project_path, chunker=chunker)
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indexer.index_project()
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# Search
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searcher = CodeSearcher(project_path)
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# Test BM25 integration
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results = searcher.search("multiply numbers", limit=5,
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semantic_weight=0.3, bm25_weight=0.7)
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if results:
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print(f" BM25 + semantic search returned {len(results)} results")
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for r in results[:2]:
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print(f" - {r.chunk_type} '{r.name}' score={r.score:.3f}")
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else:
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print(" No search results returned")
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return False
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# Test context retrieval
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print("\n Testing context retrieval...")
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if searcher.table:
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df = searcher.table.to_pandas()
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print(f" Total chunks in DB: {len(df)}")
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# Find a method chunk to test parent context
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method_chunks = df[df['chunk_type'] == 'method']
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if len(method_chunks) > 0:
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method_chunk_id = method_chunks.iloc[0]['chunk_id']
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context = searcher.get_chunk_context(method_chunk_id)
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if context['chunk']:
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print(f" Got main chunk: {context['chunk'].name}")
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if context['prev']:
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print(f" Got previous chunk: {context['prev'].name}")
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else:
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print(f" - No previous chunk (might be first)")
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if context['next']:
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print(f" Got next chunk: {context['next'].name}")
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else:
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print(f" - No next chunk (might be last)")
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if context['parent']:
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print(f" Got parent chunk: {context['parent'].name}")
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else:
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print(f" - No parent chunk")
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# Test include_context in search
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results_with_context = searcher.search("add", include_context=True, limit=2)
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if results_with_context:
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print(f" Found {len(results_with_context)} results with context")
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for r in results_with_context:
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has_context = bool(r.context_before or r.context_after or r.parent_chunk)
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print(f" - {r.name}: context_before={bool(r.context_before)}, "
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f"context_after={bool(r.context_after)}, parent={bool(r.parent_chunk)}")
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# Check if at least one result has some context
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if any(r.context_before or r.context_after or r.parent_chunk for r in results_with_context):
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print(" Search with context working")
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return True
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else:
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print(" Search returned results but no context attached")
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return False
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else:
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print(" No search results returned")
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return False
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else:
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print(" No method chunks found in database")
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return False
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return True
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def test_server():
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"""Test that server still works."""
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print("\n4. Testing Server...")
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# Just check if we can import and create server instance
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try:
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from mini_rag.server import RAGServer
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server = RAGServer(Path("."), port=7778)
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print(" Server can be instantiated")
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return True
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except Exception as e:
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print(f" Server error: {e}")
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return False
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def main():
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"""Run all integration tests."""
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print("=" * 50)
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print("RAG System Integration Check")
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print("=" * 50)
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results = {
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"Chunker": test_chunker(),
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"Indexer": test_indexer_storage(),
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"Search": test_search_integration(),
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"Server": test_server()
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}
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print("\n" + "=" * 50)
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print("SUMMARY:")
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print("=" * 50)
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all_passed = True
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for component, passed in results.items():
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status = " PASS" if passed else " FAIL"
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print(f"{component}: {status}")
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if not passed:
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all_passed = False
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if all_passed:
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print("\n All integration tests passed!")
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else:
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print("\n️ Some tests failed - fixes needed!")
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return all_passed
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if __name__ == "__main__":
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success = main()
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sys.exit(0 if success else 1) |