Which is more popular, Auto-evaluator or LiteLLM?

LiteLLM has more GitHub stars (60,036 vs 1,104).

Which is more actively developed, Auto-evaluator or LiteLLM?

LiteLLM had more commits in the last 90 days (13,191 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

Auto-evaluator has had no commit in 41 months; LiteLLM is actively maintained (13,191 commits in the last 90 days).
LiteLLM is growing faster: +2,991 GitHub stars in the last 30 days vs +51 for Auto-evaluator.
Pick Auto-evaluator for: evaluation tool for LLM QA chains. Pick LiteLLM for: open-source Python SDK and AI gateway for calling 100+ LLMs through a unified OpenAI-compatible interface.

From GitHub data refreshed daily.

Evaluation tool for LLM QA chains

Open-source Python SDK and AI gateway for calling 100+ LLMs through a unified OpenAI-compatible interface

+Fully automated evaluation pipeline that generates question-answer pairs from documents without manual dataset creation
+Comprehensive configuration testing across multiple parameters including chunk sizes, retrieval methods, and embedding approaches
+User-friendly Streamlit interface with hosted versions available on HuggingFace and langchain.com for easy access

-Requires paid API access to both OpenAI (GPT-4) and Anthropic services for full functionality
-Limited to GPT-3.5-turbo for both question generation and response scoring, which may introduce model-specific biases
-Evaluation quality depends on the automatic question generation, which may not capture all important aspects of document content

•Optimizing RAG system parameters by testing different chunk sizes, overlap settings, and retrieval strategies on domain-specific documents
•Benchmarking multiple embedding methods and language models to find the best combination for specific document types and query patterns
•Conducting systematic performance comparisons when migrating between different QA architectures or upgrading model versions

Which is more popular, Auto-evaluator or LiteLLM?: LiteLLM has more GitHub stars (60,036 vs 1,104).
Which is more actively developed, Auto-evaluator or LiteLLM?: LiteLLM had more commits in the last 90 days (13,191 vs 0).
Should I use Auto-evaluator or LiteLLM?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.