v0.1.5

Added

• Semantic chunking — all-MiniLM-L6-v2 embedding-based boundary detection in HybridChunker (optional via use_semantic_chunking).
• Cross-reference resolution — Highly efficient $O(N)$ resolution for explicit ("Figure 3") and implicit ("the table below") references via spatial proximity.
• Summary chunks — Asynchronous ARQ background worker (enrich_summaries_job) to auto-generate LLM section summaries for hierarchical RAG retrieval.
• Chunk quality scorer — Zero-ML, heuristic-based chunk scoring using block token confidences, Dictionary Word Coverage (/usr/share/dict/words), and fastText Lang-ID validation.
• PII redaction — Hybrid approach using fast Regex+Luhn (Emails, Phones, SSNs, CCs, IPs) and optional spaCy NER (en_core_web_sm) for names, organizations, and locations. Preserves original values in secure block metadata for HITL.

Changed

• Bumped marker-pdf version support in dependencies.
• Added ner optional dependency group (spacy>=3.7.0) in pyproject.toml.
• Expanded ChunkingConfig and ProcessingConfig with new semantic, summary, and PII toggle options.
• Marked Phase 1 as officially complete in Roadmap.

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v0.1.4

Release v0.1.4: Add fast PDF extractor, auto-language detection, AGPL…

v0.1.3

Fixed

• Source code: Added DocumentPipeline as a public alias for PipelineOrchestrator —
  docs, quickstart, and all examples now use this name consistently
• Documentation: Fixed wrong coverage path long_parser → longparser in CONTRIBUTING.md
• Documentation: Replaced stale cleanrag-api reference in Docker deployment docs
• Documentation: Standardized Gemini API key env var to GOOGLE_API_KEY across all docs
• Source code: Updated default LLM model fallback from gpt-4o to gpt-5.3 in
  schemas.py, llm_chain.py, and engine.py
• Source code: Renamed stale cleanrag: Redis key prefix to longparser: in embeddings

Changed

• Python 3.13 added to CI matrix, badges, and installation docs
• SECURITY.md updated with Redis rate-limiting and CORS threat mitigations

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v0.1.2

Changed

• Project logo added to documentation site, README, and PyPI page
• Documentation site header updated — logo replaces text title
• Installation guide restructured for clarity

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v0.1.1

Added

• CPU / GPU install separation — dedicated [cpu] and [gpu] meta-extras for clean one-command installs
• faiss-gpu extra (faiss-gpu>=1.7) as a distinct option from faiss-cpu
• Granular torch-based extras — embeddings-cpu, embeddings-gpu, latex-ocr-cpu, latex-ocr-gpu for fine-grained dependency control

Fixed

• Package metadata: license field updated to SPDX expression format per PEP 639
• Documentation site build reliability improvements

Changed

• [gpu] is now the recommended default install — one command, works on both GPU and CPU machines
• [cpu] documented as the advanced path for size-constrained environments (Docker, edge, CI)
• [all] now resolves to [cpu] as a safe, dependency-minimal default

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v0.1.0

🎉 Initial Public Release

LongParser is the open-source document intelligence engine built by ENDEVSOLS
for production RAG pipelines.

Added

• 5-stage extraction pipeline — Extract → Validate → HITL Review → Chunk → Embed → Index
• Multi-format extraction — PDF, DOCX, PPTX, XLSX, CSV via Docling
• HybridChunker — token-aware, heading-hierarchy-aware, table-aware chunking
• Human-in-the-Loop (HITL) review — approve / edit / reject blocks and chunks
  via LangGraph interrupt() before embedding
• 3-layer memory chat — short-term turns + rolling summary + long-term facts,
  powered by LCEL chains
• Multi-provider LLM support — OpenAI (gpt-4o), Gemini (gemini-2.0-flash),
  Groq (llama-3.3-70b-versatile), OpenRouter
• Multi-backend vector stores — Chroma, FAISS, Qdrant
• Async-first REST API — FastAPI + Motor (MongoDB) + ARQ (Redis job queue)
• LongParserRetriever — drop-in LangChain BaseRetriever adapter
• LongParserLoader — LangChain document loader integration
• LongParserReader — LlamaIndex BaseReader integration
• LongParserCallbackHandler — observability callbacks for LangChain chains
• Built-in citation validation — chunk IDs verified against retrieved set
  before any answer is returned
• Privacy-first — all processing runs locally; no data leaves your infrastructure
• py.typed marker — full PEP 561 typing support
• Unit test suite — test_schemas.py (22 passing), test_llm_chain.py,
  test_chat_utils.py
• GitHub Actions CI — lint (ruff), tests across Python 3.10 / 3.11 / 3.12,
  coverage reporting
• GitHub Actions publish — PyPI trusted publishing triggered on GitHub releases
• pyproject.toml with server, langchain, llamaindex, embeddings,
  chroma, faiss, qdrant optional extras
• Dockerfile and docker-compose.yml for one-command local deployment
• CONTRIBUTING.md, SECURITY.md, .env.example — full OSS scaffolding

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