componentsv1.2.0 (Latest Release)
Enterprise Document Intelligence & RAG Pipeline
Private document vectorization, semantic chunking, and streaming LLM chat agent.
An enterprise-ready Retrieval-Augmented Generation (RAG) platform. Ingests complex PDFs, invoices, spreadsheets, and technical manuals, computes multi-dimensional vector embeddings with pgvector, and streams precise answers with exact document citations.
Choose accessReady after payment
USD 199.00one-time payment
Standard License
Single enterprise document repository
Full TypeScript UI & FastAPI vector ingestion source
Pre-built chat widget ready to embed
1 year of model compatibility patches
✓ 100% Source Code•✓ Secure Token•✓ Zero Lock-In
Key Architectural Capabilities
Document ingestion with OCR for scanned receipts and complex PDF tables
Hybrid dense-sparse vector search combining pgvector and full-text ranking
Streaming markdown answers with verifiable page-number citations
Private self-hosted LLM compatibility (Ollama, vLLM, DeepSeek)
Runtime & System Requirements
Python 3.11+
Node.js 20+
PostgreSQL 15+ with pgvector
OpenAI API or local Ollama
Release History & Changelogs
v1.2.0Latest Stable
Released 10/1/2026Added hybrid semantic-keyword ranking, table extraction parser, and DeepSeek model connector.
SHA256: 3e23e8160039594a…5.4 MB archive
Technology Stack
Next.jsPython / FastAPIPostgreSQL pgvectorOpenAI / Claude APILangChain
What's In The Package
Complete unminified TypeScript source code
PostgreSQL migration scripts & schema definitions
Docker Compose multi-container production configuration
OpenAPI / Swagger API specification files
Step-by-step local setup and cloud deployment guide
Automated test suites (Vitest, integration tests)
Need Us To Customize & Deploy This?
Our engineering team can tailor this architecture to your exact business requirements or deploy it directly into your AWS/GCP cloud environment.
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