The official Python SDK for Eval Protocol (EP.) EP is an open protocol that standardizes how developers author evals for large language model (LLM) applications.
Project description
Eval Protocol (EP)
The open-source toolkit for building your internal model leaderboard.
When you have multiple AI models to choose from—different versions, providers, or configurations—how do you know which one is best for your use case?
Quick Example
Compare models on a simple formatting task:
from eval_protocol.models import EvaluateResult, EvaluationRow, Message
from eval_protocol.pytest import default_single_turn_rollout_processor, evaluation_test
@evaluation_test(
input_messages=[
[
Message(role="system", content="Use bold text to highlight important information."),
Message(role="user", content="Explain why evaluations matter for AI agents. Make it dramatic!"),
],
],
model=[
"fireworks_ai/accounts/fireworks/models/llama-v3p1-8b-instruct",
"openai/gpt-4",
"anthropic/claude-3-sonnet"
],
rollout_processor=default_single_turn_rollout_processor,
mode="pointwise",
)
def test_bold_format(row: EvaluationRow) -> EvaluationRow:
"""Check if the model's response contains bold text."""
assistant_response = row.messages[-1].content
if assistant_response is None:
row.evaluation_result = EvaluateResult(score=0.0, reason="No response")
return row
has_bold = "**" in str(assistant_response)
score = 1.0 if has_bold else 0.0
reason = "Contains bold text" if has_bold else "No bold text found"
row.evaluation_result = EvaluateResult(score=score, reason=reason)
return row
📚 Resources
- Documentation - Complete guides and API reference
- Discord - Community discussions
Installation
This library requires Python >= 3.10.
Install with pip:
pip install eval-protocol
License
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