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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