Spaces:
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File size: 2,073 Bytes
62065d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | """
Load LLM documentation for form generation. Direct only — no URL reading.
Uses embedded built-in docs (fast) or optional local JSON file. No network calls.
"""
import json
import logging
import os
import time
from pathlib import Path
from typing import Any, Dict, Optional
from .builtin_docs import BUILTIN_DOCS
logger = logging.getLogger(__name__)
_DOCS_CACHE: Optional[Dict[str, Any]] = None
_CACHE_TIME: float = 0
_DOCS_TTL_SECONDS = 3600 # 1 hour for file; built-in is effectively permanent
def _get_docs_json_path() -> Optional[Path]:
path = os.getenv("DOCS_JSON_PATH")
if path:
p = Path(path)
return p if p.is_absolute() else Path(__file__).resolve().parent.parent / path
default = Path(__file__).resolve().parent / "llm_docs.json"
return default if default.exists() else None
def fetch_docs(
include_examples: bool = True,
include_conditional_logic: bool = True,
include_ai_fields: bool = True,
force_refresh: bool = False,
) -> Dict[str, Any]:
"""
Return LLM documentation. No URL fetch — uses local file if present, else built-in docs.
Always returns a dict (built-in docs at minimum) so context packs are always available.
"""
global _DOCS_CACHE, _CACHE_TIME
now = time.time()
if not force_refresh and _DOCS_CACHE is not None and (now - _CACHE_TIME) < _DOCS_TTL_SECONDS:
return _DOCS_CACHE
docs_path = _get_docs_json_path()
if docs_path:
try:
with open(docs_path, "r", encoding="utf-8") as f:
docs = json.load(f)
if isinstance(docs, dict):
_DOCS_CACHE = docs
_CACHE_TIME = now
logger.info("Loaded docs from file %s (version=%s)", docs_path, docs.get("version"))
return docs
except Exception as e:
logger.warning("Failed to load docs from %s: %s", docs_path, e)
_DOCS_CACHE = BUILTIN_DOCS
_CACHE_TIME = now
logger.debug("Using built-in docs (version=%s)", BUILTIN_DOCS.get("version"))
return BUILTIN_DOCS
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