Configure ragas RAG evaluation to use AINative's free LLMs + embeddings — no OpenAI key needed.
Project description
ragas-ainative
Configure ragas to use AINative's free LLMs + embeddings for RAG evaluation. No OpenAI key needed.
Zero setup. Evaluate faithfulness, answer relevancy, and more with Llama 3.3 70B — completely free.
Install
pip install ragas-ainative
Quick Start
from ragas_ainative import configure_ragas
from ragas.metrics import faithfulness, answer_relevancy
from ragas import evaluate
configure_ragas() # Auto-provisions free API key
results = evaluate(dataset, metrics=[faithfulness, answer_relevancy])
print(results)
How It Works
ragas-ainative is a companion package (NOT a fork) that configures ragas to use AINative's free, OpenAI-compatible API. It sets OPENAI_API_KEY and OPENAI_API_BASE so ragas routes all LLM judge calls and embeddings through AINative.
On first use, the package auto-provisions a free API key (72-hour TTL). Claim your account at ainative.studio/signup for permanent access.
Available Models
from ragas_ainative import configure_ragas
configure_ragas(model="llama") # meta-llama/Llama-3.3-70B-Instruct (default)
configure_ragas(model="qwen") # qwen3-coder-flash
configure_ragas(model="deepseek") # deepseek-4-flash
configure_ragas(model="kimi") # kimi-k2
Store Results to ZeroDB
Track evaluation scores over time:
from ragas_ainative import configure_ragas, store_results
configure_ragas()
# After evaluation
results = {"faithfulness": 0.85, "answer_relevancy": 0.92}
store_results(results, dataset_name="my-rag-pipeline")
# Stored to ZeroDB — searchable and trackable
Explicit API Key
configure_ragas(api_key="your-key-here")
Or set the environment variable:
export AINATIVE_API_KEY=your-key-here
API Key Resolution Order
- Explicit
api_keyparameter AINATIVE_API_KEYenvironment variableZERODB_API_KEYenvironment variable~/.zerodb/credentials.json(shared with zerodb ecosystem)- Auto-provision via instant-db
Requirements
- Python >= 3.9
- ragas >= 0.1.0
License
MIT
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