mirror of
https://github.com/VectifyAI/PageIndex.git
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e94f6d45c8
The server's chat/completions agent identifies documents by doc_name (api.py:3108-3112), not doc_id. The local agent tools used UUID-based doc_id, forcing the LLM to copy opaque strings and making same-name documents indistinguishable. - Agent tools now take doc_name (doc_id accepted as fallback) - _resolve: name→id within scope, ambiguity returns candidates - _sanitize_doc_name: mirrors server sanitize_filename (NFKC, whitespace collapse, 180-byte truncation with md5 suffix) - _dedupe_doc_name: a.pdf → a_1.pdf on collision, matching the server's _find_unique_key suffix scheme - _defang_delimiters: also collapses whitespace to block newline injection in the <docs> prompt block - System prompts and wrap_with_doc_context updated to name-first
456 lines
21 KiB
Python
456 lines
21 KiB
Python
# pageindex/backend/local.py
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import hashlib
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import os
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import re
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import sqlite3
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import unicodedata
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import uuid
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import shutil
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from pathlib import Path
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from ..parser.protocol import DocumentParser, ParsedDocument
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from ..parser.pdf import PdfParser
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from ..parser.markdown import MarkdownParser
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from ..storage.protocol import StorageEngine
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from ..index.pipeline import build_index
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from ..index.utils import parse_pages, get_pdf_page_content, remove_fields
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from ..backend.protocol import AgentTools
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from ..errors import (FileTypeError, DocumentNotFoundError, CollectionNotFoundError,
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IndexingError)
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from .._validation import validate_collection_name
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# Collections created by older SDK versions used their names directly as safe
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# directory names. Preserve that layout for backward compatibility; names newly
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# allowed by the cloud-compatible contract use an opaque directory instead.
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_LEGACY_COLLECTION_DIR_RE = re.compile(r'[a-zA-Z0-9_-]{1,128}')
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class _DocResolveError(Exception):
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"""Agent-tool doc_name resolution failure; str() is the agent-facing error JSON."""
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class LocalBackend:
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def __init__(self, storage: StorageEngine, files_dir: str, model: str = None,
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retrieve_model: str = None, index_config=None):
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self._storage = storage
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self._files_dir = Path(files_dir)
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self._model = model
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self._retrieve_model = retrieve_model or model
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self._index_config = index_config
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self._parsers: list[DocumentParser] = [PdfParser(), MarkdownParser()]
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def register_parser(self, parser: DocumentParser) -> None:
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self._parsers.insert(0, parser) # user parsers checked first
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def get_retrieve_model(self) -> str | None:
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return self._retrieve_model
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def _resolve_parser(self, file_path: str) -> DocumentParser:
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ext = os.path.splitext(file_path)[1].lower()
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for parser in self._parsers:
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if ext in parser.supported_extensions():
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return parser
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raise FileTypeError(f"No parser for extension: {ext}")
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# Collection management
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def _validate_collection_name(self, name: str) -> None:
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validate_collection_name(name)
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def _collection_dir(self, name: str) -> Path:
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"""Return a stable, contained directory for a logical collection name.
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Legacy-safe names retain their historical ``files/{name}`` layout. Any
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other cloud-valid name is hashed so spaces, Unicode, slashes, ``..``, or
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platform-specific path characters can never escape ``files_dir``.
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"""
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if _LEGACY_COLLECTION_DIR_RE.fullmatch(name):
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return self._files_dir / name
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digest = hashlib.sha256(name.encode("utf-8")).hexdigest()
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return self._files_dir / ".collections" / digest
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def create_collection(self, name: str) -> None:
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self._validate_collection_name(name)
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self._storage.create_collection(name)
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def get_or_create_collection(self, name: str) -> None:
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self._validate_collection_name(name)
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self._storage.get_or_create_collection(name)
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def list_collections(self) -> list[str]:
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return self._storage.list_collections()
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def delete_collection(self, name: str) -> None:
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self._validate_collection_name(name)
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self._storage.delete_collection(name)
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col_dir = self._collection_dir(name)
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if col_dir.exists():
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shutil.rmtree(col_dir)
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@staticmethod
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def _file_hash(file_path: str) -> str:
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"""Compute SHA-256 hash of a file."""
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h = hashlib.sha256()
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with open(file_path, "rb") as f:
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for chunk in iter(lambda: f.read(65536), b""):
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h.update(chunk)
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return h.hexdigest()
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@staticmethod
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def _sanitize_doc_name(doc_name: str, max_bytes: int = 180) -> str:
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"""Match the cloud upload pipeline's sanitize_filename: NFKC-normalize
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and collapse whitespace so names are reproducible by the agent (and a
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newline in a filename can't forge extra entries in the <docs> prompt
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block), then truncate over-long names with a stable hash suffix."""
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name = re.sub(r"\s+", " ", unicodedata.normalize("NFKC", doc_name)).strip()
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if len(name.encode("utf-8")) <= max_bytes:
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return name
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stem, ext = os.path.splitext(name)
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suffix = "_" + hashlib.md5(name.encode("utf-8")).hexdigest()[:8]
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max_stem = max_bytes - len(ext.encode("utf-8")) - len(suffix.encode("utf-8"))
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while len(stem.encode("utf-8")) > max_stem and stem:
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stem = stem[:-1]
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return stem + suffix + ext
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def _dedupe_doc_name(self, collection: str, doc_name: str) -> str:
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"""Uniquify a colliding doc_name with a numeric suffix (a.pdf ->
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a_1.pdf), matching the cloud upload contract — names stay unique per
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collection so the name-based agent tools resolve unambiguously."""
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existing = {d["doc_name"] for d in self._storage.list_documents(collection)}
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if doc_name not in existing:
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return doc_name
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stem, ext = os.path.splitext(doc_name)
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num = 1
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while f"{stem}_{num}{ext}" in existing:
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num += 1
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return f"{stem}_{num}{ext}"
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# Document management
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def add_document(self, collection: str, file_path: str) -> str:
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file_path = os.path.realpath(file_path)
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if not os.path.isfile(file_path):
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# Missing path is a file-not-found error, not an unsupported-type one.
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raise FileNotFoundError(f"No such file: {file_path}")
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# Fail fast before the expensive parse + LLM indexing if the collection
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# doesn't exist — otherwise the FK constraint only trips at save time,
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# after the LLM work (and its cost) is already spent.
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if collection not in self._storage.list_collections():
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raise CollectionNotFoundError(
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f"Collection '{collection}' does not exist; "
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f"create it first (e.g. client.collection('{collection}'))."
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)
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parser = self._resolve_parser(file_path)
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# Dedup is content-only — same file is reused regardless of IndexConfig
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# changes. If you've changed IndexConfig and need a fresh tree, delete
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# the existing doc first or use a new collection.
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file_hash = self._file_hash(file_path)
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existing_id = self._storage.find_document_by_hash(collection, file_hash)
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if existing_id:
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return existing_id
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doc_id = str(uuid.uuid4())
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# Copy file to managed directory
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ext = os.path.splitext(file_path)[1]
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col_dir = self._collection_dir(collection)
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col_dir.mkdir(parents=True, exist_ok=True)
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managed_path = col_dir / f"{doc_id}{ext}"
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shutil.copy2(file_path, managed_path)
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try:
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# Store images alongside the managed document directory.
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images_dir = str(col_dir / doc_id / "images")
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parsed = parser.parse(file_path, model=self._model, images_dir=images_dir)
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result = build_index(parsed, model=self._model, opt=self._index_config)
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# Cache page text for fast retrieval (avoids re-reading files) and to
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# reconstruct node text on demand (get_document(include_text=True),
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# get_page_content fallback) independent of whether IndexConfig kept
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# text in the stored structure. build_index() already applies
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# if_add_node_text to result["structure"] for every strategy, so no
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# extra stripping is needed here.
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pages = [{"page": n.index, "content": n.content,
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**({"images": n.images} if n.images else {})}
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for n in parsed.nodes if n.content]
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doc_name = self._dedupe_doc_name(
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collection, self._sanitize_doc_name(parsed.doc_name))
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self._storage.save_document(collection, doc_id, {
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"doc_name": doc_name,
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"doc_description": result.get("doc_description", ""),
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"file_path": str(managed_path),
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"file_hash": file_hash,
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"doc_type": ext.lstrip("."),
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"status": "completed",
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**(parsed.metadata or {}), # parser-reported, e.g. page_count / line_count
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"structure": result["structure"],
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"pages": pages,
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})
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except sqlite3.IntegrityError as e:
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# Lost a concurrent add of the same content (UNIQUE collection+hash).
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# Discard our managed files and return the winner's doc_id.
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managed_path.unlink(missing_ok=True)
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doc_dir = col_dir / doc_id
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if doc_dir.exists():
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shutil.rmtree(doc_dir)
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existing_id = self._storage.find_document_by_hash(collection, file_hash)
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if existing_id:
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return existing_id
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# No winner — likely an FK violation from a concurrent collection delete.
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if collection not in self._storage.list_collections():
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raise CollectionNotFoundError(
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f"Collection '{collection}' was deleted while indexing {file_path}"
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) from e
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raise IndexingError(f"Failed to index {file_path}: {e}") from e
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except Exception as e:
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managed_path.unlink(missing_ok=True)
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doc_dir = col_dir / doc_id
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if doc_dir.exists():
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shutil.rmtree(doc_dir)
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raise IndexingError(f"Failed to index {file_path}: {e}") from e
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return doc_id
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def _require_document(self, collection: str, doc_id: str) -> dict:
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"""Return the document's storage row, or raise DocumentNotFoundError.
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Single source of truth for "does this doc exist" — every public method
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and agent tool below goes through this, so a missing doc always
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surfaces the same way instead of each caller re-implementing its own
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(and potentially inconsistent) existence check.
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"""
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doc = self._storage.get_document(collection, doc_id)
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if not doc:
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raise DocumentNotFoundError(f"Document {doc_id} not found")
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return doc
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def get_document(self, collection: str, doc_id: str, include_text: bool = False) -> dict:
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"""Get document metadata with structure.
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Args:
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include_text: If True, populate each structure node's 'text' field
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from cached page content. WARNING: may be very large — do NOT
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use in agent/LLM contexts as it can exhaust the context window.
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"""
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doc = self._require_document(collection, doc_id)
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doc["structure"] = self._storage.get_document_structure(collection, doc_id)
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if include_text:
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pages = self._storage.get_pages(collection, doc_id) or []
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page_map = {p["page"]: p["content"] for p in pages}
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self._fill_node_text(doc["structure"], page_map)
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return doc
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@staticmethod
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def _fill_node_text(nodes: list, page_map: dict) -> None:
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"""Recursively fill 'text' on structure nodes from cached page content.
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Two node conventions, one per indexing strategy: content_based (PDF)
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nodes span a start_index..end_index page range; level_based (Markdown)
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nodes map 1:1 to a single page keyed by line_num. Handling only the
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first would silently leave Markdown nodes with no text.
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"""
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for node in nodes:
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start = node.get("start_index")
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end = node.get("end_index")
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if start is not None and end is not None:
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node["text"] = "\n".join(
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page_map.get(p, "") for p in range(start, end + 1)
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)
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elif "line_num" in node:
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node["text"] = page_map.get(node["line_num"], "")
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if "nodes" in node:
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LocalBackend._fill_node_text(node["nodes"], page_map)
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def get_document_structure(self, collection: str, doc_id: str) -> list:
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self._require_document(collection, doc_id)
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return self._storage.get_document_structure(collection, doc_id)
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def get_page_content(self, collection: str, doc_id: str, pages: str) -> list:
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doc = self._require_document(collection, doc_id)
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page_nums = parse_pages(pages)
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# Try cached pages first (fast, no file I/O)
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cached_pages = self._storage.get_pages(collection, doc_id)
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if cached_pages:
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return [p for p in cached_pages if p["page"] in page_nums]
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# Fallback: re-derive from the source file, same as the PDF path below
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# — never from the stored structure, whose 'text' field may have been
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# stripped (if_add_node_text=False, the default). Reachable only for a
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# custom StorageEngine that doesn't cache pages (the built-in
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# SQLiteStorage always does).
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if doc["doc_type"].lower() == "pdf":
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return get_pdf_page_content(doc["file_path"], page_nums)
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else:
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parser = self._resolve_parser(doc["file_path"])
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parsed = parser.parse(doc["file_path"], model=self._model)
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page_map = {n.index: n.content for n in parsed.nodes}
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return [{"page": p, "content": page_map[p]} for p in page_nums if p in page_map]
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def list_documents(self, collection: str) -> list[dict]:
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return self._storage.list_documents(collection)
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def delete_document(self, collection: str, doc_id: str) -> None:
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doc = self._require_document(collection, doc_id)
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self._storage.delete_document(collection, doc_id)
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if doc.get("file_path"):
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Path(doc["file_path"]).unlink(missing_ok=True)
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doc_dir = self._collection_dir(collection) / doc_id
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if doc_dir.exists():
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shutil.rmtree(doc_dir)
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def get_agent_tools(self, collection: str, doc_ids: list[str] | None = None) -> AgentTools:
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"""Build agent tools.
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- doc_ids=None (open mode): includes ``list_documents``; agent picks docs itself.
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- doc_ids=[...] (scoped mode): no ``list_documents``; the other tools
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hard-enforce the whitelist and reject out-of-scope references.
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Tools identify documents by ``doc_name``, matching the cloud
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chat/completions agent contract (names are far more reliable for an
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LLM to pass than UUIDs). A ``doc_id`` is accepted in the same
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parameter as the tie-breaker when several documents share a name.
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Note ``is not None``: an empty list is a scope of *nothing* (reject every
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doc), NOT open mode. Using truthiness would let ``doc_ids=[]`` collapse to
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``None`` and silently grant access to the whole collection.
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"""
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from agents import function_tool
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import json
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storage = self._storage
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col_name = collection
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backend = self
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scope = set(doc_ids) if doc_ids is not None else None
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def _resolve(doc_name: str) -> str:
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"""Resolve a doc_name (or doc_id) to a doc_id within scope.
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Raises _DocResolveError carrying an agent-facing error JSON on failure."""
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rows = storage.list_documents(col_name)
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if scope is not None:
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rows = [r for r in rows if r["doc_id"] in scope]
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for row in rows:
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if row["doc_id"] == doc_name:
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return doc_name
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matches = [r for r in rows if r["doc_name"] == doc_name]
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if len(matches) == 1:
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return matches[0]["doc_id"]
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if len(matches) > 1:
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raise _DocResolveError(json.dumps({
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"error": f"Multiple documents are named {doc_name!r} — "
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"retry with one of these doc_ids.",
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"candidates": [{"doc_id": r["doc_id"],
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"doc_description": r["doc_description"]}
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for r in matches],
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}, ensure_ascii=False))
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if scope is not None:
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raise _DocResolveError(json.dumps({
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"error": f"{doc_name!r} is not in scope.",
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"allowed_documents": [{"doc_id": r["doc_id"],
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"doc_name": r["doc_name"]}
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for r in rows],
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}, ensure_ascii=False))
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raise _DocResolveError(json.dumps({
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"error": f"Document {doc_name!r} not found.",
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"available_doc_names": list(dict.fromkeys(r["doc_name"] for r in rows)),
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}, ensure_ascii=False))
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@function_tool
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def get_document(doc_name: str) -> str:
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"""Get document metadata. Pass the document's doc_name (a doc_id also works)."""
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try:
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# _require_document (not backend.get_document) deliberately:
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# the metadata-only row, no 'structure' — keeps this tool's
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# output small for the agent's context window.
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doc = backend._require_document(col_name, _resolve(doc_name))
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except _DocResolveError as e:
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return str(e)
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except DocumentNotFoundError:
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return json.dumps({"error": f"Document {doc_name!r} not found."})
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return json.dumps(doc)
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@function_tool
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def get_document_structure(doc_name: str) -> str:
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"""Get document tree structure (without text). Pass the document's doc_name (a doc_id also works)."""
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try:
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structure = storage.get_document_structure(col_name, _resolve(doc_name))
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except _DocResolveError as e:
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return str(e)
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return json.dumps(remove_fields(structure, fields=["text"]), ensure_ascii=False)
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@function_tool
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def get_page_content(doc_name: str, pages: str) -> str:
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"""Get page content. Pass the document's doc_name (a doc_id also works). Use tight ranges: '5-7', '3,8', '12'."""
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try:
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result = backend.get_page_content(col_name, _resolve(doc_name), pages)
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except _DocResolveError as e:
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return str(e)
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except DocumentNotFoundError:
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return json.dumps({"error": f"Document {doc_name!r} not found."})
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except (ValueError, AttributeError) as e:
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# A malformed page spec ("all", "5-") is a recoverable bad tool
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# argument: hand the model an actionable error it can correct
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# (mirroring the legacy retrieval tool) rather than letting the
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# ValueError surface as the agent SDK's generic tool-failure text.
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return json.dumps({
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"error": f"Invalid pages format: {pages!r}. Use '5-7', '3,8', or '12'. Error: {e}"
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})
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return json.dumps(result, ensure_ascii=False)
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tools = [get_document, get_document_structure, get_page_content]
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if scope is None:
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@function_tool
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def list_documents() -> str:
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"""List all documents in the collection."""
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return json.dumps(storage.list_documents(col_name))
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tools.insert(0, list_documents)
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return AgentTools(function_tools=tools)
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def _scoped_docs(self, collection: str, doc_ids: list[str]) -> list[dict]:
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"""Fetch metadata for the docs in scope; raise if any are missing."""
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by_id = {d["doc_id"]: d for d in self._storage.list_documents(collection)}
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missing = [did for did in doc_ids if did not in by_id]
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if missing:
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raise DocumentNotFoundError(
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f"doc_ids not found in collection '{collection}': {missing}"
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)
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return [by_id[did] for did in doc_ids]
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@staticmethod
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def _normalize_doc_ids(doc_ids: str | list[str] | None) -> list[str] | None:
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if isinstance(doc_ids, str):
|
|
return [doc_ids]
|
|
if doc_ids == []:
|
|
raise ValueError(
|
|
"doc_ids cannot be empty; pass None to query the whole collection"
|
|
)
|
|
return doc_ids
|
|
|
|
def query(self, collection: str, question: str,
|
|
doc_ids: str | list[str] | None = None) -> str:
|
|
from ..agent import AgentRunner, SCOPED_SYSTEM_PROMPT, wrap_with_doc_context
|
|
doc_ids = self._normalize_doc_ids(doc_ids)
|
|
tools = self.get_agent_tools(collection, doc_ids)
|
|
instructions = None
|
|
if doc_ids:
|
|
docs = self._scoped_docs(collection, doc_ids)
|
|
question = wrap_with_doc_context(docs, question)
|
|
instructions = SCOPED_SYSTEM_PROMPT
|
|
return AgentRunner(tools=tools, model=self._retrieve_model,
|
|
instructions=instructions).run(question)
|
|
|
|
async def query_stream(self, collection: str, question: str,
|
|
doc_ids: str | list[str] | None = None):
|
|
from ..agent import QueryStream, SCOPED_SYSTEM_PROMPT, wrap_with_doc_context
|
|
doc_ids = self._normalize_doc_ids(doc_ids)
|
|
tools = self.get_agent_tools(collection, doc_ids)
|
|
instructions = None
|
|
if doc_ids:
|
|
docs = self._scoped_docs(collection, doc_ids)
|
|
question = wrap_with_doc_context(docs, question)
|
|
instructions = SCOPED_SYSTEM_PROMPT
|
|
stream = QueryStream(tools=tools, question=question,
|
|
model=self._retrieve_model, instructions=instructions)
|
|
async for event in stream:
|
|
yield event
|