ragzen 0.2.0

Enterprise-grade, local-first RAG for Python

RagZen

RagZen is a local-first, permission-aware RAG framework for Python. It provides durable ingestion, hybrid or graph-assisted retrieval, pluggable providers, grounded generation, a CLI, and an optional FastAPI server.

RagZen 0.2 is an alpha release. Its public API is usable, but production users should pin the exact version and validate their own retrieval and security policies.

Features

• Persistent local mode: SQLite document registry, SQLite vectors, and durable BM25.
• Retrieval modes: dense, sparse, hybrid, graph, and hybrid_graph.
• Vector backends: zero-config SQLite, in-memory development backend, and Qdrant.
• RRF or weighted fusion and optional cross-encoder reranking.
• TXT, Markdown, CSV, JSON, HTML, PDF, DOCX, and XLSX ingestion.
• Tenant, department, role, group, permission, owner, and declared ABAC filtering.
• Idempotent ingestion, content deduplication, document versions, scoped deletion, complete local backup bundles, and restart-safe indexes.
• OpenAI-compatible providers including Ollama, plus a dependency-free extractive mode.
• Native async APIs, provider token streaming, Prometheus text metrics, health probes, API-key principals, audit events, Redis search cache, and plugin entry-point discovery.

Install

pip install ragzen

Optional capabilities:

pip install "ragzen[local]"       # sentence-transformers and cross-encoder reranking
pip install "ragzen[documents]"   # PDF, DOCX and XLSX loaders
pip install "ragzen[qdrant]"      # Qdrant vector backend
pip install "ragzen[redis]"       # distributed search cache
pip install "ragzen[server]"      # FastAPI server
pip install "ragzen[all]"

Zero-config quickstart

from ragzen import RagZen, SecurityContext

with RagZen.local("./data/ragzen") as rag:
    document = rag.add_text(
        "The refund period is 30 days.",
        metadata={"tenant_id": "acme", "department": "support"},
    )

    context = SecurityContext(
        tenant_id="acme",
        user_id="user-1",
        departments=["support"],
    )

    results = rag.search("refund period", security_context=context)
    response = rag.ask("How long is the refund period?", security_context=context)
    print(document.document_id, results[0].content, response.answer)

Local mode uses durable SQLite vectors and a dependency-free extractive generator. The same search results remain available after the process restarts.

Semantic embeddings and Ollama

# ragzen.yaml
embedding:
  provider: sentence_transformers
  model: sentence-transformers/all-MiniLM-L6-v2

llm:
  provider: ollama
  base_url: http://localhost:11434/v1
  model: llama3.2
  timeout_seconds: 60

from ragzen import RagZen

rag = RagZen.from_config("ragzen.yaml")

Qdrant and graph-assisted retrieval

vector_store:
  provider: qdrant
  url: http://localhost:6333
  collection: company_documents

retrieval:
  mode: hybrid_graph
  fusion: rrf

graph:
  enabled: true
  path: .ragzen/graph.json
  max_hops: 2

The built-in graph index is a deterministic entity co-occurrence graph with chunk provenance. Applications needing ontology extraction or a remote graph database can inject a custom graph index or retriever.

Server security

Server principals are configured on the server, not supplied by request bodies:

environment: production
security:
  require_security_context: true
  fail_closed: true
  abac_keys: [region, clearance]

server:
  allowed_ingest_roots: [/srv/ragzen/imports]
  principals:
    - api_key: ${RAGZEN_API_KEY}
      tenant_id: acme
      user_id: service-account
      roles: [reader]
      departments: [support]

Start the server:

ragzen --config ragzen.yaml serve --host 0.0.0.0 --port 8000

Use Authorization: Bearer <api-key>. Production server mode refuses to start without a configured principal. Filesystem ingestion is disabled unless allowed_ingest_roots is configured.

The Docker Compose deployment uses the production config and Qdrant. Set RAGZEN_API_KEY before running docker compose; startup fails if it is absent.

CLI

ragzen init --path .ragzen
ragzen ingest ./documents --tenant acme
ragzen search "refund policy" --tenant acme
ragzen query "Summarize the refund policy" --tenant acme
ragzen stats
ragzen doctor
ragzen backup ./backups/ragzen
ragzen restore ./backups/ragzen.zip

Provider plugins

Third-party packages can expose a class through the ragzen.plugins Python entry-point group. Set plugin_capability to embedding, vector_store, or llm, and plugin_name to the corresponding config provider name. A plugin may implement from_config(config) or a constructor accepting config=.

Quality gates

The repository CI runs Ruff, Mypy, Bandit, dependency auditing, the full pytest suite with branch coverage, package build, Twine metadata validation, and a Python 3.11-3.13 matrix on Linux and Windows. The dependency-free evaluate_retrieval helper provides Recall@K, reciprocal rank and nDCG@K for application-specific evaluation sets.

See documentation, architecture, security model, and contributing guide.

License

Apache-2.0. See LICENSE.