Better visualization of the evaluation

llm-complete-guide/ZENML_VERSION.txt

@@ -1 +1 @@
-0.74.0
+0.75.0

llm-complete-guide/pipelines/llm_eval.py

@@ -17,7 +17,7 @@
 from typing import Optional
 
 import click
-from steps.create_prompt import create_prompt
+from steps.create_prompt import PROMPT, create_prompt
 from steps.eval_e2e import e2e_evaluation, e2e_evaluation_llm_judged
 from steps.eval_retrieval import (
     retrieval_evaluation_full,
@@ -26,14 +26,14 @@
     retrieval_evaluation_small_with_reranking,
 )
 from steps.eval_visualisation import visualize_evaluation_results
-from zenml import pipeline
+from zenml import pipeline, save_artifact
 
 
 @pipeline(enable_cache=True)
 def llm_eval(after: Optional[str] = None) -> None:
     """Executes the pipeline to evaluate a RAG pipeline."""
     # define prompt
-    prompt = create_prompt()
+    prompt = save_artifact(PROMPT, "prompt")
 
     # Retrieval evals
     failure_rate_retrieval = retrieval_evaluation_small(after=after)

llm-complete-guide/steps/create_prompt.py

@@ -16,6 +16,13 @@
 
 from zenml import log_metadata, step
 
+PROMPT = """
+You are a friendly chatbot. \
+You can answer questions about ZenML, its features and its use cases. \
+You respond in a concise, technically credible tone. \
+You ONLY use the context from the ZenML documentation to provide relevant
+answers. \
+"""
 
 @step
 def create_prompt() -> str: