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import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from openai import OpenAI
from dotenv import load_dotenv
import os
load_dotenv(Path(__file__).parent.parent.parent.parent.parent / ".env", override=True)
from rag_system import QueryExpander, HybridRetriever, RAGSystem
def test_query_expansion():
print("\n" + "="*60)
print("TEST: Query Expansion")
print("="*60)
try:
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
expander = QueryExpander(client)
query = "What are your programming skills?"
expanded = expander.expand_query(query, num_variations=2)
assert isinstance(expanded, list), "Should return a list"
assert len(expanded) >= 1, "Should have at least original query"
assert query in expanded, "Should include original query"
print(f"✓ Original: {query}")
for i, q in enumerate(expanded[1:], 1):
print(f"✓ Variation {i}: {q}")
print("✅ Query expansion test PASSED")
return True
except Exception as e:
print(f"❌ Query expansion test FAILED: {e}")
return False
def test_retriever_initialization():
print("\n" + "="*60)
print("TEST: Retriever Initialization")
print("="*60)
try:
retriever = HybridRetriever(data_dir="data/test_retriever")
assert retriever.embedder is not None, "Embedder should be initialized"
assert retriever.reranker is not None, "Reranker should be initialized"
assert retriever.chroma_client is not None, "ChromaDB client should be initialized"
print("✓ Embedder loaded")
print("✓ Reranker loaded")
print("✓ ChromaDB client initialized")
print("✅ Retriever initialization test PASSED")
return True
except Exception as e:
print(f"❌ Retriever initialization test FAILED: {e}")
return False
def test_chunking():
print("\n" + "="*60)
print("TEST: Text Chunking")
print("="*60)
try:
retriever = HybridRetriever(data_dir="data/test_chunking")
text = " ".join([f"word{i}" for i in range(100)])
chunks = retriever.chunk_text(text, chunk_size=20, overlap=5)
assert isinstance(chunks, list), "Should return a list"
assert len(chunks) > 0, "Should create at least one chunk"
assert all(isinstance(c, str) for c in chunks), "All chunks should be strings"
print(f"✓ Created {len(chunks)} chunks from {len(text)} character text")
print(f"✓ First chunk: {len(chunks[0].split())} words")
print("✅ Chunking test PASSED")
return True
except Exception as e:
print(f"❌ Chunking test FAILED: {e}")
return False
def test_document_indexing():
print("\n" + "="*60)
print("TEST: Document Indexing")
print("="*60)
try:
retriever = HybridRetriever(data_dir="data/test_indexing")
test_docs = {
"doc1": "Python is a high-level programming language. It is widely used for web development and data science.",
"doc2": "Machine learning involves training models on data. It uses algorithms like neural networks.",
"doc3": "FastAPI is a modern web framework for Python. It is fast and easy to use."
}
retriever.index_documents(test_docs, chunk_size=20, overlap=5)
assert retriever.documents is not None, "Documents should be indexed"
assert len(retriever.documents) > 0, "Should have indexed chunks"
assert retriever.bm25 is not None, "BM25 index should be created"
assert retriever.collection is not None, "ChromaDB collection should be created"
print(f"✓ Indexed {len(test_docs)} documents")
print(f"✓ Created {len(retriever.documents)} chunks")
print("✓ BM25 index created")
print("✓ Semantic index created")
print("✅ Document indexing test PASSED")
return True
except Exception as e:
print(f"❌ Document indexing test FAILED: {e}")
return False
def test_retrieval_methods():
print("\n" + "="*60)
print("TEST: Retrieval Methods")
print("="*60)
try:
retriever = HybridRetriever(data_dir="data/test_methods")
test_docs = {
"doc1": "Python programming language for web development and machine learning applications",
"doc2": "JavaScript is used for frontend development with React and Vue frameworks",
"doc3": "SQL databases like PostgreSQL store structured data efficiently"
}
retriever.index_documents(test_docs, chunk_size=15, overlap=3)
query = "Python programming"
bm25_results = retriever.retrieve_bm25(query, top_k=2)
assert isinstance(bm25_results, list), "BM25 should return a list"
print(f"✓ BM25 retrieval: {len(bm25_results)} results")
semantic_results = retriever.retrieve_semantic(query, top_k=2)
assert isinstance(semantic_results, list), "Semantic should return a list"
print(f"✓ Semantic retrieval: {len(semantic_results)} results")
hybrid_results = retriever.retrieve_hybrid(query, top_k=2)
assert isinstance(hybrid_results, list), "Hybrid should return a list"
print(f"✓ Hybrid retrieval: {len(hybrid_results)} results")
reranked = retriever.rerank(query, hybrid_results, top_k=1)
assert isinstance(reranked, list), "Reranking should return a list"
print(f"✓ Reranking: {len(reranked)} results")
print("✅ Retrieval methods test PASSED")
return True
except Exception as e:
print(f"❌ Retrieval methods test FAILED: {e}")
return False
def test_rag_system():
print("\n" + "="*60)
print("TEST: RAG System End-to-End")
print("="*60)
try:
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
rag_system = RAGSystem(client, data_dir="data/test_rag")
test_docs = {
"summary": "I am an experienced AI engineer with 5 years of Python development",
"projects": "Built RAG systems, multi-agent frameworks, and production ML pipelines",
"stack": "Expert in Python, FastAPI, LangChain, ChromaDB, and OpenAI APIs"
}
rag_system.load_knowledge_base(test_docs, chunk_size=20, overlap=5)
system_prompt = "Answer questions about professional background."
response = rag_system.query(
"What programming languages do you know?",
system_prompt,
method="hybrid",
top_k=3
)
assert "answer" in response, "Response should contain answer"
assert "context" in response, "Response should contain context"
assert "method" in response, "Response should contain method"
assert len(response["context"]) > 0, "Should retrieve some context"
print(f"✓ Retrieved {len(response['context'])} context documents")
print(f"✓ Generated answer: {len(response['answer'])} characters")
print(f"✓ Method used: {response['method']}")
print("✅ RAG system test PASSED")
return True
except Exception as e:
print(f"❌ RAG system test FAILED: {e}")
return False
def run_all_tests():
print("\n" + "="*70)
print("RUNNING RAG SYSTEM TESTS")
print("="*70)
tests = [
test_query_expansion,
test_retriever_initialization,
test_chunking,
test_document_indexing,
test_retrieval_methods,
test_rag_system
]
results = [test() for test in tests]
print("\n" + "="*70)
print(f"RESULTS: {sum(results)}/{len(results)} tests passed")
print("="*70)
return all(results)
if __name__ == "__main__":
success = run_all_tests()
sys.exit(0 if success else 1)
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