Eval directory
Evals for LlamaIndex
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for LlamaIndex AI products.
About LlamaIndex
LlamaIndex is a data framework for building RAG and agent applications over private data — documents/nodes, indexes (VectorStoreIndex), retrievers and query engines, the IngestionPipeline, plus LlamaParse and LlamaCloud for managed document parsing and retrieval.
Available eval packs for LlamaIndex
8 packs ready to run.
Agents And Workflows
LlamaIndex evals — Agents & Workflows (relift v3 InfraRed)
Documents Nodes And Ingestion
LlamaIndex evals — Documents, Nodes & Ingestion (relift v3 InfraRed)
Embeddings And Vector Stores
LlamaIndex evals — Embeddings & Vector Stores (relift v3 InfraRed)
Indexes
LlamaIndex evals — Indexes (relift v3 InfraRed)
Llamaparse And Llamacloud
LlamaIndex evals — LlamaParse / LlamaCloud (relift v3 InfraRed)
Observability Settings And Safety
LlamaIndex evals — Observability, Settings & Safety (relift v3 InfraRed)
Retrievers And Query Engines
LlamaIndex evals — Retrievers & Query Engines (relift v3 InfraRed)
Structured Outputs And Extraction
LlamaIndex evals — Structured Outputs & Extraction (relift v3 InfraRed)
Why eval LlamaIndex AI
LlamaIndex's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for LlamaIndex measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against LlamaIndex's public product surface and runnable in Corsac with your own data.