rotalabs-context 1.0.0

Context intelligence for AI agents - Ingest, search, and subscribe to shared context across your AI systems

rotalabs-context

Context intelligence for AI agents — Ingest, search, and subscribe to shared context across your AI systems.

Part of the Rotalabs trust intelligence research ecosystem.

Installation

pip install rotalabs-context

With local embedding support:

pip install rotalabs-context[local]

With Rotascale platform integration:

pip install rotalabs-context[platform]

Quick Start

from rotalabs_context import ContextEngine

# Local mode (zero config, SQLite backend)
ctx = ContextEngine()

# Platform mode (connects to Rotascale)
ctx = ContextEngine(
    api_key="rot_...",
    base_url="https://api.rotascale.com",
)

# Ingest context
result = ctx.ingest(
    records=[
        {"content": "User reported login issue", "title": "Support ticket #1234"},
        {"content": "Auth service latency spike at 2pm UTC", "title": "Incident report"},
    ],
    source="helpdesk",
    tags=["support", "auth"],
    scope="team:support",
)

# Search
results = ctx.search("login issues", top_k=5, mode="semantic")
for hit in results:
    print(f"{hit.score:.2f} — {hit.title}")

# Subscribe to context updates
ctx.on("context.created", filter={"tags": ["support"]}, callback=my_handler)

Features

• Ingest: Push data from any pipeline; we add the "C" (embeddings, entities, relationships)
• Search: Semantic + keyword + hybrid search across all ingested context
• Subscribe: Real-time context propagation via events
• ACLs: Scope-based access control (global, team, agent, project, user)
• Pluggable backends: SQLite (local), PostgreSQL (self-hosted), Rotascale Platform (managed)

Pipeline Adapters

# Airflow
from rotalabs_context.adapters import AirflowContextOperator

# In your DAG
ingest_task = AirflowContextOperator(
    task_id="ingest_to_context",
    source="airflow-etl",
    tags=["daily-batch"],
)

License

AGPL-3.0 — See LICENSE for details.