"""Shared helpers for building prompts and (for MockLLMProvider) recovering
the structured evidence a prompt was built from, without a real model call.
Every analysis task embeds its evidence as a fenced JSON block via
`build_user_prompt`, so this stays consistent across all six tasks and lets
the mock provider parse it back out deterministically.
"""

from __future__ import annotations

import json
from typing import Any

_EVIDENCE_FENCE_START = "```json evidence"
_EVIDENCE_FENCE_END = "```"


def build_user_prompt(instructions: str, evidence: dict[str, Any]) -> str:
    evidence_json = json.dumps(evidence, indent=2, default=str)
    return (
        f"{instructions}\n\n"
        "Evidence (only use what is provided here - never invent facts not present):\n"
        f"{_EVIDENCE_FENCE_START}\n{evidence_json}\n{_EVIDENCE_FENCE_END}"
    )


def extract_evidence_block(user_prompt: str) -> dict[str, Any]:
    """Recovers the evidence dict embedded by `build_user_prompt`. Used only
    by MockLLMProvider, which has no model to actually read the prompt."""
    start = user_prompt.find(_EVIDENCE_FENCE_START)
    if start == -1:
        return {}
    start += len(_EVIDENCE_FENCE_START)
    end = user_prompt.find(_EVIDENCE_FENCE_END, start)
    if end == -1:
        return {}
    try:
        return json.loads(user_prompt[start:end].strip())
    except json.JSONDecodeError:
        return {}