mirror of
https://github.com/VectifyAI/PageIndex.git
synced 2026-07-18 21:21:05 +02:00
Verified 12 findings from an xhigh-effort review of the prior review-fix
batch; all confirmed real. Most trace back to one root cause: the
build_index() text-stripping fix (8f536cb) correctly stopped Markdown from
leaking full text by default, but broke every path that assumed text could
be re-read later.
Correctness:
- LocalBackend._fill_node_text (get_document(include_text=True)) only handled
PDF's start_index/end_index convention; Markdown nodes use line_num and got
silently empty text. Now handles both.
- get_page_content's Markdown fallback (triggered when a StorageEngine
legitimately returns None from get_pages()) read from the now-text-stripped
structure. It now re-derives from the source file, mirroring the PDF
fallback, so it no longer depends on structure text at all.
- add_document's PDF-only text-stripping branch (with the stale "markdown
needs text in structure for fallback retrieval" comment) is now dead/wrong
since build_index() already applies if_add_node_text uniformly — removed.
- _validate_llm_provider's keyless-provider allowlist was missing several
local LiteLLM providers (xinference, llamafile, triton, oobabooga,
openai_like, docker_model_runner, custom, custom_openai, petals) that need
no API key just like ollama/lm_studio; expanded.
- The three agent-tool closures (get_document, get_document_structure,
get_page_content) had three different not-found patterns; two bypassed the
backend's DocumentNotFoundError entirely. Extracted LocalBackend.
_require_document as the single existence check every method/tool now uses.
- examples/agentic_vectorless_rag_demo.py's hand-rolled Agent() didn't apply
the litellm/ prefix normalization the SDK does internally, so its own
documented "any LiteLLM provider" claim broke for non-openai models.
- cloud delete_collection's cache eviction removed the "folders unavailable"
None sentinel too, forcing a wasted re-fetch; now only pops on a real id.
Cleanup / altitude:
- build_index() skips the remove_structure_text walk entirely when text was
never added (content_based + if_add_node_summary=False + if_add_node_text=
False) instead of a guaranteed no-op tree walk.
- page_index()'s locals()-capture-as-kwargs (fragile by construction) replaced
with an explicit dict of the named parameters.
- run_pageindex.py's _cli_bool and the page_index_md.py legacy shim's
_coerce_bool were duplicate, diverging implementations; both now bind
directly to the canonical pageindex.index.page_index_md._coerce_bool.
- retrieve.py's _get_md_page_content delegated its own traversal instead of
calling the canonical get_md_page_content; now a one-line delegation.
- FileTypeError's docstring now calls out the except-ordering gotcha from
also subclassing ValueError.
17 new regression tests (tests/test_review_fixes_2.py) plus 2 updated in
tests/test_legacy_shims.py for the simplified md_to_tree shim. Full suite:
210 passed, 2 skipped.
Claude-Session: https://claude.ai/code/session_01Kx5DgKbhK1N8autqXH8SmS
146 lines
5.7 KiB
Python
146 lines
5.7 KiB
Python
# pageindex/index/pipeline.py
|
|
from __future__ import annotations
|
|
from ..parser.protocol import ContentNode, ParsedDocument
|
|
|
|
|
|
def detect_strategy(nodes: list[ContentNode]) -> str:
|
|
"""Determine which indexing strategy to use based on node data."""
|
|
if any(n.level is not None for n in nodes):
|
|
return "level_based"
|
|
return "content_based"
|
|
|
|
|
|
def build_tree_from_levels(nodes: list[ContentNode]) -> list[dict]:
|
|
"""Strategy 0: Build tree from explicit level information.
|
|
Adapted from pageindex/page_index_md.py:build_tree_from_nodes."""
|
|
stack = []
|
|
root_nodes = []
|
|
|
|
for node in nodes:
|
|
tree_node = {
|
|
"title": node.title or "",
|
|
"text": node.content,
|
|
"line_num": node.index,
|
|
"nodes": [],
|
|
}
|
|
current_level = node.level or 1
|
|
|
|
while stack and stack[-1][1] >= current_level:
|
|
stack.pop()
|
|
|
|
if not stack:
|
|
root_nodes.append(tree_node)
|
|
else:
|
|
parent_node, _ = stack[-1]
|
|
parent_node["nodes"].append(tree_node)
|
|
|
|
stack.append((tree_node, current_level))
|
|
|
|
return root_nodes
|
|
|
|
|
|
def _run_async(coro):
|
|
"""Run an async coroutine, handling the case where an event loop is already running."""
|
|
import asyncio
|
|
import concurrent.futures
|
|
import contextvars
|
|
# Only the detection is guarded — NOT the run. If the coroutine's own work
|
|
# raises RuntimeError, letting it fall into `except RuntimeError` here would
|
|
# misfire the "no running loop" branch and mask the real error behind a
|
|
# bogus "asyncio.run() cannot be called from a running event loop".
|
|
try:
|
|
asyncio.get_running_loop()
|
|
except RuntimeError:
|
|
# No running loop -- drive the coroutine directly.
|
|
return asyncio.run(coro)
|
|
# Already inside an event loop -- run in a separate thread so we don't nest
|
|
# asyncio.run. Copy the current context so ContextVar-based settings (e.g.
|
|
# the max_concurrency_scope override set by build_index) propagate into the
|
|
# worker thread; .result() re-raises the worker's real exception unchanged.
|
|
ctx = contextvars.copy_context()
|
|
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
|
|
return pool.submit(ctx.run, asyncio.run, coro).result()
|
|
|
|
|
|
def build_index(parsed: ParsedDocument, model: str = None, opt=None) -> dict:
|
|
"""Main entry point: ParsedDocument -> tree structure dict.
|
|
Routes to the appropriate strategy and runs enhancement."""
|
|
from .utils import (write_node_id, add_node_text, remove_structure_text,
|
|
generate_summaries_for_structure, generate_doc_description,
|
|
create_clean_structure_for_description)
|
|
from ..config import IndexConfig, max_concurrency_scope
|
|
|
|
if opt is None:
|
|
opt = IndexConfig(model=model) if model else IndexConfig()
|
|
|
|
# Scope the per-index concurrency cap to THIS call only (per thread/async
|
|
# context), so concurrent indexing of other documents isn't affected and a
|
|
# one-off value never sticks as the process default.
|
|
with max_concurrency_scope(getattr(opt, "max_concurrency", None)):
|
|
nodes = parsed.nodes
|
|
strategy = detect_strategy(nodes)
|
|
|
|
if strategy == "level_based":
|
|
structure = build_tree_from_levels(nodes)
|
|
# For level-based, text is already in the tree nodes
|
|
else:
|
|
# Strategies 1-3: convert ContentNode list to page_list format for existing pipeline
|
|
page_list = [(n.content, n.tokens) for n in nodes]
|
|
structure = _run_async(_content_based_pipeline(page_list, opt))
|
|
|
|
# Unified enhancement
|
|
if opt.if_add_node_id:
|
|
write_node_id(structure)
|
|
|
|
if strategy != "level_based":
|
|
if opt.if_add_node_text or opt.if_add_node_summary:
|
|
add_node_text(structure, page_list)
|
|
|
|
if opt.if_add_node_summary:
|
|
_run_async(generate_summaries_for_structure(structure, model=opt.model))
|
|
|
|
result = {
|
|
"doc_name": parsed.doc_name,
|
|
"structure": structure,
|
|
}
|
|
|
|
if opt.if_add_doc_description:
|
|
clean_structure = create_clean_structure_for_description(structure)
|
|
result["doc_description"] = generate_doc_description(
|
|
clean_structure, model=opt.model
|
|
)
|
|
|
|
# 'text' is populated for level_based (Markdown, always) or for
|
|
# content_based when if_add_node_text/if_add_node_summary requested it.
|
|
# Strip it LAST, for BOTH strategies, unless explicitly requested —
|
|
# otherwise a default index leaks each node's full text into
|
|
# get_document_structure / storage, inconsistent with
|
|
# if_add_node_text=False, the README, and the legacy md_to_tree. Skip
|
|
# the walk entirely when text was never added in the first place
|
|
# (content_based with if_add_node_text=if_add_node_summary=False) —
|
|
# there's nothing to strip.
|
|
text_present = strategy == "level_based" or opt.if_add_node_text or opt.if_add_node_summary
|
|
if text_present and not opt.if_add_node_text:
|
|
remove_structure_text(structure)
|
|
|
|
return result
|
|
|
|
|
|
class _NullLogger:
|
|
"""Minimal logger that satisfies the tree_parser interface without writing files."""
|
|
def info(self, message, **kwargs): pass
|
|
def error(self, message, **kwargs): pass
|
|
def debug(self, message, **kwargs): pass
|
|
|
|
|
|
async def _content_based_pipeline(page_list, opt):
|
|
"""Strategies 1-3: delegates to the existing PDF pipeline from pageindex/page_index.py.
|
|
|
|
The page_list is already in the format expected by tree_parser:
|
|
[(page_text, token_count), ...]
|
|
"""
|
|
from .page_index import tree_parser
|
|
|
|
logger = _NullLogger()
|
|
structure = await tree_parser(page_list, opt, doc=None, logger=logger)
|
|
return structure
|