testcontainers initial setup #95
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RAG Module Integration Tests: Missing Required SecretsRAG Module Integration tests cannot run because the following GitHub secrets are not configured:
How to Fix
Azure OpenAI Configuration:
Additional LLM APIs:
NoteTests will not run until all required secrets are configured. Workflow: RAG Module Integration Tests | Run: #1 |
RAG System Security Assessment ReportRed Team Testing with DeepTeam Framework Executive SummarySystem Security Status: VULNERABLE Overall Pass Rate: 0.0% Risk Level: HIGH Attack Vector Analysis
Only tested attack categories are shown above. Vulnerability Assessment
Multilingual Security Analysis
Failed Security Tests Analysis
(2 additional failures not shown) Security RecommendationsPriority Actions RequiredCritical Vulnerabilities (Immediate Action Required):
Attack Vector Improvements:
Specific Technical Recommendations:
General Security Enhancements:
Testing MethodologyThis security assessment used DeepTeam, an advanced AI red teaming framework that simulates real-world adversarial attacks. Test Execution Process
Attack Categories TestedSingle-Turn Attacks:
Multi-Turn Attacks:
Vulnerabilities Assessed
Language SupportTests were conducted across multiple languages:
Pass/Fail Criteria
Report generated on 2025-12-03 12:12:38 by DeepTeam automated red teaming pipeline |
RAG System Evaluation ReportDeepEval Test Results Summary
Total Tests: 20 | Passed: 0 | Failed: 20 Detailed Test Results| Test | Language | Category | CP | CR | CRel | AR | Faith | Status | Legend: CP = Contextual Precision, CR = Contextual Recall, CRel = Contextual Relevancy, AR = Answer Relevancy, Faith = Faithfulness Failed Test Analysis
(90 additional failures not shown) RecommendationsContextual Precision (Score: 0.000): Consider improving your reranking model or adjusting reranking parameters to better prioritize relevant documents. Contextual Recall (Score: 0.000): Review your embedding model choice and vector search parameters. Consider domain-specific embeddings. Contextual Relevancy (Score: 0.000): Optimize chunk size and top-K retrieval parameters to reduce noise in retrieved contexts. Answer Relevancy (Score: 0.000): Review your prompt template and LLM parameters to improve response relevance to the input query. Faithfulness (Score: 0.000): Strengthen hallucination detection and ensure the LLM stays grounded in the provided context. Report generated on 2025-12-03 12:12:48 by DeepEval automated testing pipeline |
RAG Module Integration Tests: Missing Required SecretsRAG Module Integration tests cannot run because the following GitHub secrets are not configured:
How to Fix
Azure OpenAI Configuration:
Additional LLM APIs:
NoteTests will not run until all required secrets are configured. Workflow: RAG Module Integration Tests | Run: #2 |
fixed issue gitleaks solve test1
RAG Module Integration Tests: Missing Required SecretsRAG Module Integration tests cannot run because the following GitHub secrets are not configured:
How to Fix
Azure OpenAI Configuration:
Additional LLM APIs:
NoteTests will not run until all required secrets are configured. Workflow: RAG Module Integration Tests | Run: #3 |
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