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Zyra

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Zyra Presentation

Zyra is an open-source Python framework for modular, reproducible data workflows — helping you import, process, visualize, and export scientific and environmental data.

Highlights

  • Modular pieces: connectors, processors, visualizers, and utilities.
  • CLI-first & streaming-friendly: compose stages with pipes and configs.
  • Install what you need: keep core small; add extras per stage.

Quickstart

Install

pip install zyra

Try the CLI

zyra --help

Minimal example

# Acquire → Process → Visualize
zyra acquire http https://example.com/sample.grib2 -o sample.grib2
zyra process convert-format sample.grib2 netcdf --stdout > sample.nc
zyra visualize heatmap --input sample.nc --var VAR --output plot.png

More Examples per Module

See module-level READMEs under src/zyra/ for focused examples and options:

  • Connectors/Ingest: src/zyra/connectors/ingest/README.md
  • Processing: src/zyra/processing/README.md
  • API (service): src/zyra/api/README.md
  • MCP Tools: src/zyra/api/mcp_tools/README.md

Learn More (Wiki)

Stage Map

Swarm Orchestration

  • zyra swarm --plan samples/swarm/mock_basic.yaml --dry-run prints the instantiated agents.
  • Remove --dry-run to execute mock simulate→narrate agents; use --memory provenance.db to persist provenance and --guardrails schema.rail to enforce structured outputs.
  • Guardrail validation requires the optional extra: pip install "zyra[guardrails]" (or poetry install --with guardrails) before using --guardrails schema.rail.
  • To exercise the skeleton simulate/decide flow end-to-end, try zyra swarm --plan samples/swarm/simulate_decide.yaml --dry-run (or drop --dry-run to run the mock pipeline).
  • Add --log-events to echo provenance events live, and --dump-memory provenance.db to inspect existing runs without executing new stages.
  • Target specific stages or experiment with partial DAGs using --agents acquire,visualize,narrate; unknown stage names are rejected early so typos do not silently skip work.
  • Control concurrency explicitly with --parallel/--no-parallel (the latter forces max-workers=1) and use --max-workers N when you want a fixed pool size.
  • Override LLM settings for proposal/narrate stages with --provider mock|openai|ollama|gemini|vertex, --model <name>, and --base-url <endpoint> instead of editing .env or wizard config files. Gemini runs with either GOOGLE_API_KEY (Generative Language API) or Vertex credentials (VERTEX_PROJECT, GOOGLE_APPLICATION_CREDENTIALS, etc.).
  • A real-world example lives in samples/swarm/drought_animation.yaml; run it with poetry run zyra swarm --plan samples/swarm/drought_animation.yaml --memory drought.db. Create data/drought/ ahead of time, place earth_vegetation.jpg in your working directory (or adjust the manifest), and ensure Pillow is installed for process pad-missing.
  • Preview planner output (JSON manifest with augmentation suggestions) before running: poetry run zyra plan --intent "mock swarm plan".
  • Plans are YAML/JSON manifests listing agents, dependencies (depends_on), and CLI args; see samples/swarm/ to get started.

Import (acquire/ingest)

Process (transform)

Simulate

Decide (optimize)

Visualize (render)

Narrate

Verify

Export (disseminate; legacy: decimate)

LLM Providers for Wizard/Narrate

Zyra’s Wizard, narrative swarm, and discovery semantic search all share the same provider configuration. Install google-auth when needed with pip install "zyra[llm]" (or poetry install --with llm). Key options:

Provider Configuration
OpenAI OPENAI_API_KEY, optional OPENAI_BASE_URL
Ollama Local server on http://localhost:11434 (override with OLLAMA_BASE_URL)
Gemini (Generative Language API) Set GOOGLE_API_KEY; optional GENLANG_BASE_URL, VERTEX_MODEL (default gemini-2.5-flash)
Gemini (Vertex AI) Provide VERTEX_PROJECT (aliases: GOOGLE_PROJECT_ID, GOOGLE_CLOUD_PROJECT), VERTEX_LOCATION (default us-central1), and Application Default Credentials (GOOGLE_APPLICATION_CREDENTIALS pointing to a service-account JSON). Optional VERTEX_MODEL, VERTEX_ENDPOINT, VERTEX_PUBLISHER.
Mock No credentials needed; deterministic offline responses. Useful for testing.

Example ~/.zyra_wizard.yaml targeting Gemini via Vertex:

provider: gemini
model: gemini-2.5-flash
project: my-vertex-project
location: us-central1

API & Reference Docs

Contributing

License

Apache-2.0 — see LICENSE

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