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30 Minutes to Local Compute

Use this path when you want SpectraSherpa running on your own machine. You will install the app, add optional extras only if you need them, run a starter PCA workflow, and then point that workflow at your own data.

Install

pip install spectra-sherpa
spectra-sherpa

Open the local URL printed in the terminal, usually http://localhost:8000. Local OSS needs no account and no cloud connection for normal analysis.

Add Optional Extras Only If Needed

The base install reads .csv, JCAMP-DX (.jdx, .dx), NumPy (.npy, .npz), and .mat. To read vendor and spectroscopy-native files, add the SpectroChemPy extra:

pip install "spectra-sherpa[scp]"
spectra-sherpa

This unlocks SpectroChemPy-backed readers for Thermo OMNIC/OMNICxi .spa, .spg, .srs, Bruker .opus, Galactic .spc, Renishaw WiRE .wdf, and vendor .txt/.dat. Newer Thermo containers such as .srsx, .session, .map, and .mapx are not read directly today; export them to .spa, .spg, or legacy .srs first.

For HITRAN line-by-line synthesis, add the HITRAN/HAPI extra:

pip install "spectra-sherpa[hitran]"
spectra-sherpa

You still need a HITRAN API key and egress enabled in application settings. For exact versions and format notes, use Supported File Types.

For Eigenvector Research example datasets, enable the local runtime downloader:

export SPECTRASHERPA_EIGENVECTOR_DOWNLOADS=true
spectra-sherpa

These datasets are highly recommended for learning NIR/OES chemometrics in SpectraSherpa. They include corn instrument-transfer data, diesel NIR calibration data, IDRC shootout data, CGL NIR data, and metal-etch OES/process examples. SpectraSherpa catalogs them but does not redistribute the raw files; downloads come from Eigenvector Research and are cached on your machine.

Optional: Add a Chat Endpoint for Advisor

Local Advisor is optional. Scientific workflows still run without AI. To enable Advisor, configure a bring-your-own-provider endpoint before launching. The local transport supports OpenAI-compatible /chat/completions APIs, Anthropic's native Messages API, and Ollama. For OpenAI:

export CHAT_ENDPOINT_PROVIDER="openai_compatible"
export CHAT_ENDPOINT_URL="https://api.openai.com/v1"
export CHAT_ENDPOINT_KEY="sk-..."          # your OpenAI key
export CHAT_ENDPOINT_MODEL="gpt-4o-mini"   # any OpenAI chat model
spectra-sherpa

CHAT_ENDPOINT_PROVIDER selects the transport, CHAT_ENDPOINT_URL is its base URL, and CHAT_ENDPOINT_MODEL selects the model. CHAT_ENDPOINT_KEY is required for OpenAI-compatible and Anthropic providers but not Ollama. For an Ollama loopback URL, set CHAT_ENDPOINT_ALLOW_PRIVATE=true explicitly. Some builds also expose local BYO Chat settings in the app. Review AI Use and BYOK before relying on AI-assisted text.

Run an Example PCA with New Analysis

Open New Analysis and choose a PCA starter. If you choose an Eigenvector-backed starter, keep SPECTRASHERPA_EIGENVECTOR_DOWNLOADS=true enabled for the first run so the upstream example files can be cached locally. Review the scores, loadings, explained variance, and Node Detail view.

Ask Advisor along the way

With a chat endpoint configured, Advisor can answer questions at any step: "What does this score plot suggest?", "Which preprocessing should I try next?", "Are these samples outliers?". Use it as an interpretation aid, not a replacement for scientific judgment.

Import Your Data into My Dataset

Open Data > Upload and add a small representative file. Confirm Files, Metadata, and Data Matrix: file names, extensions, spectral axis, sample count, and target metadata. Then save it into My Dataset so a workflow can use it. See Import Your First Dataset for the checklist.

Build a PCA for Your Own Data

Duplicate the example PCA sheet, open its data node, and select your My Dataset entry as the input. Run it. You now have the same PCA workflow pointed at your data. Adjust preprocessing and components as needed, and use the Node Detail view to review the result.

Report or Extend

Open Report for a shareable record of the run, or export figures, tables, workflows, and generated Python where available. Developers can continue with Developer Setup, Writing a Plugin Node, or Export Design.