from typing import Dict, Optional, Set

from helm.benchmark.annotation.model_as_judge import AnnotatorModelInfo, LLMAsJuryAnnotator
from helm.clients.auto_client import AutoClient


PROMPT_TEMPLATE = """You are a medical expert tasked with evaluating the quality of a
generated clinical note given unstructured clinical text.
Your goal is to assess how well the generated response captures the necessary information
and follows provided instructions in terms of accuracy, structure, and clarity.

The user's request will be provided in these tags:
<user_request>
{QUESTION}
</user_request>

The response will be provided in these tags:
<response>
{RESPONSE}
</response>

Carefully analyze the <response>.
For each of the following categories, rate the response on a scale of 1 to 5 (1 = very poor, 5 = excellent),
and provide a short justification for your score.

Evaluation Criteria:
Accuracy (1-5)
- Is all the information in the response factually correct?

Structure (1-5)
- Does the response contain all parts for the provided note generation structure?

Clarity (1-5)
- Is the response easy to understand for a clinician?

Output Format:
Output the evaluation as a single valid JSON object matching the following structure:
{
    "accuracy": {
        "score": 0,
        "explanation": "Explain why this score was given."
    },
    "structure": {
        "score": 0,
        "explanation": "Explain why this score was given."
    },
    "clarity": {
        "score": 0,
        "explanation": "Explain why this score was given."
    }
}

Ensure the output is valid JSON:
- Use **double quotes** (") for all keys and string values.
- When quoting text or sections inside the explanations, use escaped double quotes (\") to
  maintain valid JSON formatting.
- Do not include any additional information in the output.
"""

ANNOTATION_CRITERIA: Dict[str, Set[str]] = {
    "accuracy": {"score", "explanation"},
    "structure": {"score", "explanation"},
    "clarity": {"score", "explanation"},
}


class CHWCarePlanAnnotator(LLMAsJuryAnnotator):
    """The CHWCarePlan autograder."""

    def __init__(
        self,
        auto_client: AutoClient,
        annotator_models: Dict[str, AnnotatorModelInfo],
        template_name: Optional[str] = None,
    ):
        super().__init__(
            name="chw_care_plan",
            auto_client=auto_client,
            prompt_template=PROMPT_TEMPLATE,
            annotation_criteria=ANNOTATION_CRITERIA,
            annotator_models=annotator_models,
        )
