SurfSense/surfsense_backend/app/podcasts/generation/structured.py

49 lines
1.6 KiB
Python

"""Parse a model's reply into a Pydantic shape, tolerating chatty output.
Agent LLMs return JSON wrapped in prose, markdown fences, or reasoning blocks.
This mirrors the legacy podcaster's resilient parsing — strip fences, then fall
back to the outermost ``{...}`` span — so every generation node validates the
reply the same way instead of repeating ad-hoc parsing.
"""
from __future__ import annotations
from typing import TYPE_CHECKING, TypeVar
from pydantic import BaseModel, ValidationError
from app.utils.content_utils import extract_text_content, strip_markdown_fences
if TYPE_CHECKING:
from langchain_core.messages import BaseMessage
T = TypeVar("T", bound=BaseModel)
class StructuredOutputError(RuntimeError):
"""The model reply could not be parsed into the expected shape."""
async def invoke_json(llm, messages: list[BaseMessage], model: type[T]) -> T:
"""Invoke ``llm`` and validate its reply as ``model``."""
response = await llm.ainvoke(messages)
content = strip_markdown_fences(extract_text_content(response.content))
try:
return model.model_validate_json(content)
except (ValidationError, ValueError):
pass
start = content.find("{")
end = content.rfind("}") + 1
if 0 <= start < end:
try:
return model.model_validate_json(content[start:end])
except (ValidationError, ValueError) as exc:
raise StructuredOutputError(
f"could not parse {model.__name__} from model reply"
) from exc
raise StructuredOutputError(
f"no JSON object found for {model.__name__} in model reply"
)