"""Compact, citation-friendly formatting for LightRAG retrieval results.""" from __future__ import annotations from collections.abc import Mapping from typing import Any def _truncate(value: str, max_chars: int, *, marker: str = "…") -> str: if len(value) <= max_chars: return value if max_chars <= len(marker): return marker[:max_chars] return f"{value[: max_chars - len(marker)].rstrip()}{marker}" def _chunks(value: object) -> list[Mapping[str, Any]]: if not isinstance(value, list): return [] return [chunk for chunk in value if isinstance(chunk, Mapping)] def _reference_file_paths(value: object) -> dict[str, str]: if not isinstance(value, list): return {} file_paths: dict[str, str] = {} for reference in value: if not isinstance(reference, Mapping): continue reference_id = reference.get("reference_id") file_path = reference.get("file_path") if isinstance(reference_id, str) and isinstance(file_path, str) and file_path.strip(): file_paths.setdefault(reference_id, file_path.strip()) return file_paths def format_retrieval_result( result: Mapping[str, Any], *, max_chars_per_chunk: int = 800, max_total_chars: int = 8000, ) -> str: """Format one LightRAG ``/query/data`` payload into compact cited text. The consumed field names (``chunks[].content/file_path/chunk_id/reference_id`` and ``references[].reference_id/file_path``) are cross-checked against the LightRAG v1.5.7 source tree; the endpoint shipped in v1.4.8 but only v1.4.9 introduced the status/data envelope and these citation fields. Opaque internal identifiers (``chunk_id`` and the response-local ``reference_id``) are never emitted; the operator-readable ``file_path`` labels each citation instead. Entities and relationships are deliberately dropped: the chunks are the document text the selected query mode already ranked as relevant, and keeping the output compact preserves the citation shape shared with the RAGFlow provider. """ raw_chunks = _chunks(result.get("chunks")) if not raw_chunks: return "No relevant content found." file_paths_by_reference = _reference_file_paths(result.get("references")) entries: list[str] = [] matched_documents: list[str] = [] counts_by_document: dict[str, int] = {} for index, chunk in enumerate(raw_chunks, start=1): file_path = chunk.get("file_path") if not isinstance(file_path, str) or not file_path.strip(): reference_id = chunk.get("reference_id") file_path = file_paths_by_reference.get(str(reference_id)) if reference_id is not None else None document_name = str(file_path).strip() if file_path and str(file_path).strip() else "Unknown document" counts_by_document[document_name] = counts_by_document.get(document_name, 0) + 1 content = str(chunk.get("content") or "").strip() content = _truncate(content, max_chars_per_chunk) entries.append(f"[{index}] {document_name}\n{content}") for document_name, count in counts_by_document.items(): unit = "chunk" if count == 1 else "chunks" matched_documents.append(f"{document_name} ({count} {unit})") entries.append(f"Matched documents: {', '.join(matched_documents)}") formatted = "\n\n".join(entries) truncation_marker = "… (response truncated)" if len(formatted) <= max_total_chars: return formatted if max_total_chars <= len(truncation_marker): return truncation_marker[:max_total_chars] prefix_length = max_total_chars - len(truncation_marker) return f"{formatted[:prefix_length].rstrip()}{truncation_marker}"