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"""
Quick test for RAGAS integration
Run: python -m src.evaluation.ragas_integration.test_ragas
"""
import asyncio
from src.rag import RAGPipeline, RAGConfig
from src.evaluation.ragas_integration import RagasReadyPipeline, RagasEvaluator
async def test_ragas():
print("=" * 50)
print("Testing RAGAS Integration")
print("=" * 50)
# Step 1: Initialize pipeline
print("\n1. Initializing pipeline...")
pipeline = RAGPipeline(RAGConfig())
ragas_pipeline = RagasReadyPipeline(pipeline)
print(" ✓ Pipeline ready")
# Step 2: Initialize evaluator
print("\n2. Initializing RAGAS evaluator...")
evaluator = RagasEvaluator()
print(" ✓ Evaluator ready")
# Step 3: Ingest a test document
print("\n3. Ingesting test document...")
test_text = """
Machine learning is a subset of artificial intelligence that enables
systems to learn from data. Deep learning is a type of machine learning
that uses neural networks with multiple layers. Natural language processing
(NLP) is used to understand human language.
"""
pipeline.ingest("test_doc", test_text)
print(f" ✓ Ingested {pipeline.vector_store.size()} chunks")
# Step 4: Query with full context capture
print("\n4. Querying pipeline...")
response = ragas_pipeline.query_for_evaluation("What is machine learning?")
print(f" Query: {response.query}")
print(f" Answer: {response.answer[:100]}...")
print(f" Contexts captured: {len(response.contexts)}")
print(f" Status: {response.status}")
# Step 5: Evaluate with RAGAS
print("\n5. Running RAGAS evaluation...")
result = await evaluator.evaluate_single(
query=response.query,
answer=response.answer,
contexts=response.contexts
)
print(f"\n{'=' * 50}")
print("RAGAS RESULTS")
print(f"{'=' * 50}")
print(f" Faithfulness: {result.faithfulness:.3f}")
print(f" Answer Relevancy: {result.answer_relevancy:.3f}")
print(f" Context Precision: {result.context_precision:.3f}")
print(f" ─────────────────────────────")
print(f" RAGAS Score: {result.ragas_score:.3f}")
print(f" Eval Time: {result.latency_ms:.0f}ms")
print(f"{'=' * 50}")
return result
if __name__ == "__main__":
asyncio.run(test_ragas()) |