How to Submit RAG Relevancy Evaluations Back to Phoenix

from phoenix.evals import (
    RAG_RELEVANCY_PROMPT_RAILS_MAP,
    RAG_RELEVANCY_PROMPT_TEMPLATE,
    OpenAIModel,
    download_benchmark_dataset,
    llm_classify,
)
from phoenix.session.evaluation import get_retrieved_documents

retrieved_documents = get_retrieved_documents(px_client, project_name=PROJECT_NAME)
model = OpenAIModel(
    model="gpt-4-turbo-preview",
    temperature=0.0,
)

#The rails is used to hold the output to specific values based on the template
#It will remove text such as ",,," or "..."
#Will ensure the binary value expected from the template is returned
rails = list(RAG_RELEVANCY_PROMPT_RAILS_MAP.values())
relevance_classifications = llm_classify(
    dataframe=retrieved_documents,
    template=RAG_RELEVANCY_PROMPT_TEMPLATE,
    model=model,
    rails=rails,
    provide_explanation=True, #optional to generate explanations for the value produced by the eval LLM
)