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UpstashKnowledgeBase class provides integration with Upstash Vector, a vector database service that enables semantic search and similarity matching. The class facilitates document indexing, searching, and topic-based organization using Upstash Vector’s vector search capabilities.
uv add "trusttest[rag-upstash]"
import os
from dotenv import load_dotenv
from trusttest.knowledge_base.upstash import UpstashKnowledgeBase
from trusttest.probes.rag import RAGProbe, MaliciousQuestion
from trusttest.evaluation_scenarios import EvaluationScenario
from trusttest.evaluator_suite import EvaluatorSuite
from trusttest.evaluators import RAGPoisoningEvaluator
from trusttest.targets.testing import DummyTarget
load_dotenv(override=True)
knowledge_base = UpstashKnowledgeBase(
url=os.getenv("UPSTASH_VECTOR_REST_URL"),
token=os.getenv("UPSTASH_VECTOR_REST_TOKEN"),
)
probe = RAGProbe(
target=DummyTarget(),
knowledge_base=knowledge_base,
num_questions=10,
question_types=[MaliciousQuestion.SPECIAL_TOKEN, MaliciousQuestion.HYPOTHETICAL],
)
scenario = EvaluationScenario(
name="RAG Poisoning",
evaluator_suite=EvaluatorSuite(evaluators=[RAGPoisoningEvaluator()], criteria="any_fail"),
)
test_set = probe.get_test_set()
results = scenario.evaluate(test_set)
results.display_summary()