Vectros SDK for Python

The official Python client for the Vectros API — hybrid search, document ingestion, structured records, and grounded inference for your application.

Installation

pip install vectros

Requires Python 3.8+.

Quick start

import os
from vectros import VectrosApi

client = VectrosApi(
    base_url="https://api.vectros.ai",
    token=os.environ["VECTROS_API_KEY"],  # sk_live_... or sk_test_...
)

# Hybrid (keyword + semantic) search over your indexed content
results = client.search.content(
    query="patient intake form diabetes",
)

# Ingest a document — extracted, chunked, and indexed for search + RAG
doc = client.documents.ingest_document(
    title="Patient Intake Form — Jane Doe",
)

# Write a structured record against one of your schemas
record = client.records.create_record(
    type_name="intake_form",
    schema_id="6ba7b810-9dad-11d1-80b4-00c04fd430c8",
    payload={"first_name": "Jane", "email": "jane@example.com"},
)

An AsyncVectrosApi with the same surface is available for asyncio.

Authentication

The SDK sends whatever credential you pass in the Authorization: Bearer <token> header. Two credential types are accepted:

Keep API keys server-side only. For untrusted runtimes, mint a short-lived scoped token on your backend and pass it as token. See the authentication guide for the full pattern.

What you can do

• Hybrid search & RAG — client.search, client.inference — vector + keyword search and grounded document Q&A over your indexed corpus.
• Documents & folders — client.documents, client.folders — ingest, organize, retrieve, and look documents up by field.
• Structured records — client.records — create, read, update (full and partial), delete, and look records up by indexed field.
• Schemas — client.schemas — define and evolve record/document schemas.
• Scripts — client.scripts — push, list, retrieve and delete versioned script object source, and execute a stored script synchronously as one atomic transaction. Each push creates a new immutable version; there is no update surface.
• Triggers — client.triggers — declare, list, retrieve, reconcile, and delete async trigger rules ("when a schema record fires this event, invoke this script version under this grant"), and list the trigger executions that failed. The rule fires: a matching record write runs the script asynchronously under the rule's own grant.
• Identity & access — client.identity, client.auth — manage users and namespaced identity entities (org and client are reserved names, registered the same way as any other namespace); mint and revoke scoped credentials.

Full API reference

Every method, parameter, and type is documented in reference.md.

Rate limits

Requests are rate limited per account on a fixed one-minute window — writes, searches, and inference count against it; reads do not. When you exceed the limit the API returns HTTP 429 with a Retry-After header (seconds until the window resets) plus X-RateLimit-Limit and X-RateLimit-Remaining. Honor Retry-After (or back off exponentially with jitter), and pace bulk work so your steady rate stays under your plan's per-minute budget. See the rate limits guide for the per-plan limits.

Documentation

• Guides & reference: docs.vectros.ai
• Product: vectros.ai

Security & trust

Vectros enforces per-customer, fail-closed isolation and least-privilege scoped keys, with a tamper-evident audit and version history. Customer-facing surfaces are hardened through extensive adversarial security review. For the full trust posture, drawn plainly with its boundaries, see the compliance and trust guide.

License

Apache License 2.0.