PageIndex/pageindex/index/pipeline.py
mountain cf7f5ce9bf fix: address PR #272 review findings (directly-fixable items)
Verified against current dev; the compat/behavior decisions (#7 api_key
semantics, #10 CLI flags, #11 doc-description default) are deferred.

Crashes:
- page_index(): snapshot args before importing IndexConfig — locals() was
  capturing the imported class and IndexConfig(extra='forbid') made every call
  raise ValidationError.
- process_none_page_numbers: pop('page', None) instead of del (a TOC item
  without 'page' raised KeyError mid-pipeline).
- pipeline._run_async: guard only the loop detection, not the run, so a real
  RuntimeError from the coroutine isn't masked as "asyncio.run() cannot be
  called from a running event loop".

Silent-wrong / robustness:
- LocalBackend.get_document_structure and the agent get_document /
  get_document_structure tools now surface a missing doc (raise / error-JSON)
  instead of returning empty, matching get_page_content and the cloud backend.
- cloud delete_collection drops the cached folder_id.
- cloud query raises on an empty collection instead of POSTing doc_id:[].
- LocalClient skips the API-key check for keyless providers (ollama, lm_studio,
  …) so keyless LiteLLM models aren't rejected at construction.

Compat / cleanup:
- md_to_tree coerces legacy 'yes'/'no' string flags (a bare 'no' was truthy).
- FileTypeError also subclasses ValueError (0.2.x raised ValueError).
- _validate_llm_provider no longer mutates global litellm.model_cost_map_url.
- __all__ re-includes legacy exports (page_index, md_to_tree, get_*).
- Rewrite examples/agentic_vectorless_rag_demo.py to the Collection API and use
  the in-repo attention.pdf (the old workspace=/client.index/client.documents
  API no longer exists).

Adds tests/test_review_fixes.py (10 regressions). Full suite: 189 passed.

Claude-Session: https://claude.ai/code/session_01Kx5DgKbhK1N8autqXH8SmS
2026-07-08 18:56:51 +08:00

136 lines
5.1 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))
if not opt.if_add_node_text and strategy != "level_based":
remove_structure_text(structure)
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
)
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