zaza-semantic-engine 3.2.0

Local-first multi-format document ingestion engine with semantic search using sentence-transformers and ChromaDB

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title: Zaza Semantic Engine emoji: 🧠 colorFrom: indigo colorTo: blue sdk: gradio sdk_version: 4.44.0 app_file: app.py pinned: false license: mit short_description: Local-first multilingual semantic search (50+ languages)

Zaza Semantic Engine

Local-first multi-format document ingestion engine with real semantic search.

Why Zaza?

Most document tools fall into two camps: cloud-based SaaS (your docs leave your machine) or dumb keyword search (finds exact word matches, misses the point). Zaza does both locally and semantically.

• Local-first — your documents never leave your machine. No API keys, no data leaks.
• Semantic search — find documents by meaning, not just keywords. Search "budget" and it finds "financial analysis", "quarterly results".
• Multi-format — TXT, PDF, Markdown, DOCX, JSON, YAML, EPUB, CSV, HTML, XML. Ingest anything.
• 50+ languages — built on paraphrase-multilingual-MiniLM-L12-v2. Search in French, English, Arabic, or any supported language.
• Zero config — zaza ingest ./docs/ and you're done.

Installation

# Core package
pip install -e .

# With API support
pip install -e ".[api]"

# With semantic search (embeddings + multilingual model)
pip install -e ".[semantic]"

# Full installation
pip install -e ".[all]"

Quick Start

# Ingest documents
zaza ingest ./my-documents/

# Keyword search (by filename)
zaza search "report"

# Semantic search (by meaning)
zaza search-semantic "financial analysis quarterly results" --top 5

# View stats
zaza stats

# Start API server (V3: either form works)
zaza api
zaza server

Semantic Search in Action

This project uses sentence-transformers (paraphrase-multilingual-MiniLM-L12-v2) to generate embeddings and ChromaDB for vector storage.

Unlike keyword search, semantic search finds documents with related concepts even when the exact words differ:

Query	Keyword Search	Semantic Search
"budget"	Only files named "budget"	Finds "financial report", "quarterly analysis", "cost breakdown"
"rapport financier"	Only French files with exact match	Finds "financial analysis", "balance sheet", "revenue summary"

Demo

Try it live on Hugging Face: Zaza Semantic Search Space

CLI Commands

Command	Description
zaza ingest <path>	Index documents from a directory or file
zaza search <query>	Search documents by filename (keyword)
zaza search-semantic <query>	Semantic search using embeddings
zaza stats	Show indexing statistics
zaza documents	List all indexed documents
zaza report [format]	Generate report (json/csv)
zaza api	Start the REST API server
zaza server	V3 alias — same as zaza api

API Endpoints

Method	Path	Description
GET	/health	Health check
GET	/summary	Engine summary
GET	/documents	List documents
GET	/search?q=	Keyword search
GET	/search-semantic?q=&top=10	Semantic search
GET	/embeddings/status	Check embedding store
POST	/analyze	Analyze raw text
POST	/ingest/file	Upload and ingest a file
POST	/ingest/directory	Ingest all files from directory

Supported Formats

Format	Extension	Method
Plain text	.txt	Direct read
Markdown	.md, .markdown	Syntax stripped
PDF	.pdf	via pypdf
CSV	.csv	Converted to key-value
HTML	.html, .htm	via BeautifulSoup
XML	.xml	Standard library
Word	.docx	via python-docx
JSON	.json	Recursive key-value (V3)
YAML	.yaml, .yml	Recursive key-value (V3)
ePUB	.epub	via ebooklib (V3, requires [semantic])

Model Caching (V3)

The embedding model is cached globally within a single process. zaza ingest + zaza search-semantic doesn't reload the model — it reuses the cached instance. Startup time drops significantly.

Configuration

Edit config.yaml to customize paths, embedding models, and search settings.

semantic:
  enabled: true                    # Set false to disable embeddings
  model_name: "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"
  embed_dir: "./data/embeddings"   # ChromaDB persist directory
  max_search_results: 10

License

MIT