UnifyOps Python SDK (unifyops)
UnifyOps is an enterprise-grade AI Industrial Knowledge Intelligence Platform Python SDK for industrial plant operations. It unifies plant manuals, SOPs, work orders, incident logs, and regulatory standard specifications into a continuously-updating Knowledge Graph, exposing callable Python interfaces for:
- Expert Knowledge Copilot (RAG Engine) - Hybrid graph-proximity & vector retrieval with citation grounding and confidence scoring.
- Maintenance Intelligence & RCA Agent - Automated Root Cause Analysis, failure mode prediction, and maintenance timelines.
- Quality & Regulatory Compliance Layer - Automated SOP gap scanning against OISD, API, PNGRB, and ISO standards.
- Lessons Learned Engine - Operational failure intelligence and incident knowledge capture.
📦 Installation
pip install unifyops
🚀 Quickstart Guide
1. Initialize Client & Ingest Plant SOP Document
from unifyops import UnifyOpsClient, DocumentType
# Initialize UnifyOps Client for your plant organization
client = UnifyOpsClient(org_id="refinery_unit_2")
# Ingest an SOP document into the Knowledge Graph
doc_text = """
SOP-204: Emergency Shutdown and Trip Protocol for Pump P-204.
When bearing temperature exceeds 95°C or vibration exceeds 6.5 mm/s,
execute immediate trip sequence. Refer to OISD-STD-154 for safety clearance.
"""
doc = client.ingest_document(
text=doc_text,
filename="SOP_Pump_P204.txt",
document_type=DocumentType.SOP,
plant_id="Unit-2"
)
print(f"Ingested Document ID: {doc.id} with {doc.chunk_count} chunk(s).")
2. Query Expert Knowledge Copilot
from unifyops import CopilotQuery
# Ask a technical question to the RAG engine
query = CopilotQuery(
query="What are the trip thresholds for Pump P-204?",
user_role="maintenance_engineer"
)
response = client.copilot.query(query, org_id="refinery_unit_2")
print(f"Answer: {response.answer}")
print(f"Confidence Score: {response.confidence_score}%")
for citation in response.citations:
print(f"Citation: {citation.citation_id} -> {citation.document_name}")
3. Execute Automated Root Cause Analysis (RCA)
from unifyops import RCARequest
rca_request = RCARequest(
equipment_tag="P-204",
incident_description="Centrifugal pump tripped unexpectedly with high vibration and seal leak."
)
rca = client.maintenance.analyze_root_cause(rca_request, org_id="refinery_unit_2")
print(f"Equipment: {rca.equipment_tag}")
print(f"Root Cause: {rca.root_cause}")
print("Recommended Actions:")
for action in rca.recommended_actions:
print(f" - {action}")
4. Scan Regulatory Compliance Gaps
from unifyops import ComplianceScanRequest
scan_req = ComplianceScanRequest(
standard="OISD-STD-154",
plant_unit="Unit-2"
)
report = client.compliance.scan_gaps(scan_req, org_id="refinery_unit_2")
print(f"Standard: {report.standard}")
print(f"Compliance Score: {report.compliance_percentage}%")
for gap in report.gaps:
print(f"Gap [{gap.severity}]: {gap.description}")
print(f"Recommendation: {gap.recommendation}")
🛠️ API Reference Summary
| Module | Core Class / Method | Description |
|---|---|---|
unifyops.client |
UnifyOpsClient |
Main SDK orchestrator |
unifyops.store |
KnowledgeStore |
Knowledge Graph & Document Chunk Registry |
unifyops.copilot |
CopilotEngine |
Hybrid RAG Q&A with Grounded Citations |
unifyops.maintenance |
MaintenanceEngine |
Root Cause Analysis & Maintenance Intelligence |
unifyops.compliance |
ComplianceEngine |
SOP vs Regulatory Standard Gap Analysis |
unifyops.lessons |
LessonsEngine |
Lessons Learned & Failure Intelligence |
📄 License
MIT License. Copyright (c) 2026 UnifyOps Team.
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