feat(prompts): implement TOML-backed prompt loading and refactor message generation

python/ebook_search/prompts/lib.py

@@ -0,0 +1,44 @@
+"""Load and render TOML-backed LLM prompt templates."""
+
+from __future__ import annotations
+
+import tomllib
+from dataclasses import dataclass
+from functools import cache
+from pathlib import Path
+
+
+@dataclass(frozen=True)
+class Prompt:
+    """A system and user prompt pair loaded from TOML."""
+
+    system: str
+    user: str
+
+    def messages(self, **values: str) -> list[dict[str, str]]:
+        """Render this prompt as OpenAI-style chat messages."""
+        return [
+            {"role": "system", "content": self.system.format(**values)},
+            {"role": "user", "content": self.user.format(**values)},
+        ]
+
+
+@cache
+def _get_prompt_dir() -> Path:
+    """Return the directory containing prompt template files."""
+    return Path(__file__).resolve().parent
+
+
+@cache
+def load_prompt(name: str) -> Prompt:
+    """Load and validate a named system and user prompt pair from TOML."""
+    path = _get_prompt_dir() / f"{name}.toml"
+    with path.open("rb") as file:
+        body = tomllib.load(file)
+
+    system = body.get("system")
+    user = body.get("user")
+    if not isinstance(system, str) or not isinstance(user, str):
+        msg = f"{path} must define string system and user prompts"
+        raise TypeError(msg)
+    return Prompt(system=system, user=user)