llm-ci-runner 1.3.0

A simple CI/CD utility for running LLM tasks with Semantic Kernel

AI-First Toolkit: LLM-Powered Automation

🚀 The Future of DevOps is AI-First
This toolkit represents a step toward AI-First DevOps - where intelligent automation handles the entire development lifecycle. Built for teams ready to embrace the exponential productivity gains of AI-powered development. Please read the blog post for more details on the motivation.

TLDR: What This Tool Does

Purpose: Zero-friction LLM integration for pipelines with 100% guaranteed schema compliance. This is your foundation for AI-first integration practices.

Perfect For:

• 🤖 AI-Generated Code Reviews: Automated PR analysis with structured findings
• 📝 Intelligent Documentation: Generate changelogs, release notes, and docs automatically
• 🔍 Security Analysis: AI-powered vulnerability detection with structured reports
• 🎯 Quality Gates: Enforce standards through AI-driven validation
• 🚀 Autonomous Development: Enable AI agents to make decisions in your pipelines
• 🎯 JIRA Ticket Updates: Update JIRA tickets based on LLM output
• 🔗 Unlimited Integration Possibilities: Chain it multiple times and use as glue code in your tool stack

---

Simple structured output example

# Install and use immediately
pip install llm-ci-runner
llm-ci-runner --input-file examples/02-devops/pr-description/input.json --schema-file examples/02-devops/pr-description/schema.json

The AI-First Development Revolution

This toolkit embodies the principles outlined in Building AI-First DevOps:

Traditional DevOps	AI-First DevOps (This Tool)
Manual code reviews	🤖 AI-powered reviews with structured findings
Human-written documentation	📝 AI-generated docs with guaranteed consistency
Reactive security scanning	🔍 Proactive AI security analysis
Manual quality gates	🎯 AI-driven validation with schema enforcement
Linear productivity	📈 Exponential gains through intelligent automation

Features

• 🎯 100% Schema Enforcement: Your pipeline never gets invalid data. Token-level schema enforcement with guaranteed compliance
• 🔄 Resilient execution: Retries with exponential back-off and jitter plus a clear exception hierarchy keep transient cloud faults from breaking your CI.
• 🚀 Zero-Friction CLI: Single script, minimal configuration for pipeline integration and automation
• 🔐 Enterprise Security: Azure RBAC via DefaultAzureCredential with fallback to API Key
• 📦 CI-friendly CLI: Stateless command that reads JSON/YAML, writes JSON/YAML, and exits with proper codes
• 🎨 Beautiful Logging: Rich console output with timestamps and colors
• 📁 File-based I/O: CI/CD friendly with JSON/YAML input/output
• 📋 Template-Driven Workflows: Handlebars and Jinja2 templates with YAML variables for dynamic prompt generation
• 📄 YAML Support: Use YAML for schemas, input files, and output files - more readable than JSON
• 🔧 Simple & Extensible: Easy to understand and modify for your specific needs
• 🤖 Semantic Kernel foundation: async, service-oriented design ready for skills, memories, orchestration, and future model upgrades
• 📚 Documentation: Comprehensive documentation for all features and usage examples. Use your semantic kernel skills to extend the functionality.
• 🧑‍⚖️ Acceptance Tests: pytest framework with the LLM-as-Judge pattern for quality gates. Test your scripts before you run them in production.
• 💰 Coming soon: token usage and cost estimation appended to each result for budgeting and optimisation

🚀 The Only Enterprise AI DevOps Tool That Delivers RBAC Security, Robustness and Simplicity

LLM-CI-Runner stands alone in the market as the only tool combining 100% schema enforcement, enterprise RBAC authentication, and robust Semantic Kernel integration with templates in a single CLI solution. No other tool delivers all three critical enterprise requirements together.

Installation

pip install llm-ci-runner

That's it! No complex setup, no dependency management - just install and use. Perfect for CI/CD pipelines and local development.

Quick Start

1. Install from PyPI

pip install llm-ci-runner

2. Set Environment Variables

Azure OpenAI (Priority 1):

export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
export AZURE_OPENAI_MODEL="gpt-4.1-nano"  # or any other GPT deployment name
export AZURE_OPENAI_API_VERSION="2024-12-01-preview"  # Optional

OpenAI (Fallback):

export OPENAI_API_KEY="your-very-secret-api-key"
export OPENAI_CHAT_MODEL_ID="gpt-4.1-nano"  # or any OpenAI model
export OPENAI_ORG_ID="org-your-org-id"  # Optional

Authentication Options:

• Azure RBAC (Recommended): Uses DefaultAzureCredential for Azure RBAC authentication - no API key needed! See Microsoft Docs for setup.
• Azure API Key: Set AZURE_OPENAI_API_KEY environment variable if not using RBAC.
• OpenAI API Key: Required for OpenAI fallback when Azure is not configured.

Priority: Azure OpenAI takes priority when both Azure and OpenAI environment variables are present.

3a. Basic Usage

# Simple chat example
llm-ci-runner --input-file examples/01-basic/simple-chat/input.json

# With structured output schema
llm-ci-runner \
  --input-file examples/01-basic/sentiment-analysis/input.json \
  --schema-file examples/01-basic/sentiment-analysis/schema.json

# Custom output file
llm-ci-runner \
  --input-file examples/02-devops/pr-description/input.json \
  --schema-file examples/02-devops/pr-description/schema.json \
  --output-file pr-analysis.json

# YAML input files (alternative to JSON)
llm-ci-runner \
  --input-file config.yaml \
  --schema-file schema.yaml \
  --output-file result.yaml

3b. Template-Based Workflows

Dynamic prompt generation with YAML, Handlebars or Jinja2 templates:

# Handlebars template example
llm-ci-runner \
  --template-file examples/05-templates/handlebars-template/template.hbs \
  --template-vars examples/05-templates/handlebars-template/template-vars.yaml \
  --schema-file examples/05-templates/handlebars-template/schema.yaml \
  --output-file handlebars-result.yaml
  
# Or using Jinja2 templates
llm-ci-runner \
  --template-file examples/05-templates/jinja2-template/template.j2 \
  --template-vars examples/05-templates/jinja2-template/template-vars.yaml \
  --schema-file examples/05-templates/jinja2-template/schema.yaml \
  --output-file jinja2-result.yaml

For more examples see the examples directory.

Benefits of Template Approach:

• 🎯 Reusable Templates: Create once, use across multiple scenarios
• 📝 YAML Configuration: More readable than JSON for complex setups
• 🔄 Dynamic Content: Variables and conditional rendering
• 🚀 CI/CD Ready: Perfect for parameterized pipeline workflows

4. Development Setup (Optional)

For contributors or advanced users who want to modify the source:

# Install UV if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and install for development
git clone https://github.com/Nantero1/ai-first-devops-toolkit.git
cd ai-first-devops-toolkit
uv sync

# Run from source
uv run llm-ci-runner --input-file examples/01-basic/simple-chat/input.json

Real-World Examples

You can explore the examples directory for a complete collection of self-contained examples organized by category.

For comprehensive real-world CI/CD scenarios, see examples/uv-usage-example.md. Some possibilities:

1. 🤖 AI-generated PR review – automated pull request analysis with structured review findings
2. 📝 Commit summarizer – convert commit logs into concise release notes
3. 🔍 Vulnerability scanner – map code vulnerabilities to OWASP standards with actionable remediation
4. 🎯 Quality gate enforcer – validate build artifacts against schema-defined quality criteria
5. 🏦 Loan application analyzer – transform free-text loan applications into Basel-III risk-model inputs
6. 💼 Consulting report generator – convert meeting notes into itemized Statement of Work deliverables
7. 🏛️ Legal contract parser – extract clauses and compute risk scores from contract documents
8. 📝 Court opinion digest – summarize judicial opinions into structured precedent and citation graphs
9. 🏥 Patient intake processor – build HL7/FHIR-compliant patient records from free-form intake forms
10. 📈 Earnings call analyzer – convert transcripts into KPI dashboards for financial performance review
11. 🔍 Code-review bot – scan commits and PRs to produce OWASP-mapped vulnerability reports
12. 🎯 Incident post-mortem summarizer – generate structured root cause analysis and corrective action plans
13. 📊 Regulatory compliance reporter – synthesize regulatory texts into structured compliance checklists
14. 💼 Financial audit note handler – convert audit commentary into ledger-ready journal entries
15. 🔍 Vulnerability scanner – map code vulnerabilities to OWASP standards with actionable remediation
16. 🎯 Quality gate enforcer – validate build artifacts against schema-defined quality criteria
17. 🏦 Loan application analyzer – transform free-text loan applications into Basel-III risk-model inputs
18. 💼 Consulting report generator – convert meeting notes into itemized Statement of Work deliverables
19. 🏛️ Legal contract parser – extract clauses and compute risk scores from contract documents
20. 📝 Court opinion digest – summarize judicial opinions into structured precedent and citation graphs
21. 🏥 Patient intake processor – build HL7/FHIR-compliant patient records from free-form intake forms
22. 📈 Earnings call analyzer – convert transcripts into KPI dashboards for financial performance review
23. 🔍 Code-review bot – scan commits and PRs to produce OWASP-mapped vulnerability reports
24. 🎯 Incident post-mortem summarizer – generate structured root cause analysis and corrective action plans
25. 📊 Regulatory compliance reporter – synthesize regulatory texts into structured compliance checklists
26. 💼 Financial audit note handler – convert audit commentary into ledger-ready journal entries
27. 🔧 Technical review assistant – output structured code review reports with clear action items
28. 🏥 Doctor dictation converter – transform verbal notes into ICD-10 coded encounter records
29. 🏛️ Legal discovery summarizer – extract key issues and risks from large document sets
30. 📁 Manufacturing defect analyzer – build 8D corrective-action records from production issue notes
31. 💹 Budget variance analyzer – summarize financial reports into detailed KPI and variance analyses
32. 🖥️ Ticket triage assistant – prioritize technical support tickets with automated incident classification
33. 🏦 Compliance transformer – create structured Basel reports from raw regulatory text
34. 📊 Credit risk evaluator – convert customer feedback into quantifiable risk scores
35. 💰 Investor memo summarizer – distill strategic memos into pitch-deck bullet points
36. 🛡️ Cyber threat mapper – translate security alerts into MITRE ATT&CK mapped incident reports
37. 👷 Equipment maintenance scheduler – analyze sensor logs to generate predictive maintenance reports
38. 🫀 Health history compiler – produce structured patient histories from narrative medical notes
39. 🛑 Safety inspection checker – transform inspection narratives into OSHA citation checklists
40. 🏥 Radiology result formatter – convert radiology reports into SNOMED-coded JSON outputs
41. 📝 Insurance claim analyzer – structure claim narratives into automated claim assessments
42. 💼 Contract review summarizer – extract risk factors and key dates from legal contracts
43. 🔍 Fraud detector – transform analyst notes into SAR (Suspicious Activity Report) JSON objects
44. 🏛️ Policy impact assessor – convert policy proposals into stakeholder impact matrices
45. 🏭 Production incident reporter – build actionable recovery plans from factory incident logs
46. 📝 Documentation updater – generate schema-compliant technical documentation automatically
47. 🔄 API diff analyzer – produce backward-compatibility risk reports from API specification changes
48. 📊 Financial forecaster – summarize financial reports into structured cash-flow and projection objects
49. 🔧 Deployment log analyzer – convert rollout logs into performance and downtime metrics
50. 🛒 E-commerce sentiment analyzer – tag customer reviews with sentiment and key product features
51. 🎙️ Meeting minute extractor – transform recorded meetings into action items and follow-up tasks
52. 📝 Sprint retrospective summarizer – generate improvement plans from agile team discussions
53. 🏥 Clinical trial data packager – automatically structure clinical notes for FDA-submission
54. 🏢 Employee feedback analyzer – convert free-text feedback into HR insights and action checklists
55. 🛠️ Process efficiency reporter – output production logs into structured performance metrics
56. 🏛️ Legal bill auditor – transform billing details into itemized expense and compliance reports
57. 📦 Automated inventory trigger – build reordering reports from warehouse inventory logs
58. 🧾 Receipt processor – convert OCR receipts into ledger-ready accounting entries
59. 🏦 Mortgage eligibility assessor – analyze mortgage applications to generate risk and eligibility scores
60. 🚧 Infrastructure incident analyst – summarize log files into detailed RCAs and incident timelines
61. 🏛️ Regulatory update tracker – generate structured compliance action items from updated guidelines
62. 📝 Board meeting summarizer – extract key decisions and action items from meeting transcripts
63. 🔍 Vulnerability risk assessor – create remediation plans by mapping findings to risk frameworks
64. 💼 Legal email analyzer – extract key issues and deadlines from email threads for legal review
65. 🏥 Prescription manager – transform handwritten prescription notes into structured medication lists
66. 🖥️ Git log analyzer – generate detailed changelogs from version control commit histories
67. 📋 SOP generator – create standard operating procedures with checklist items from process descriptions
68. 🎯 PR triage tool – score and tag pull requests by urgency and impact automatically
69. 🏦 Audit finding summarizer – convert audit observations into structured compliance and risk reports
70. 📈 Market trend analyzer – synthesize marketing data into structured trend forecasting objects
71. 🧑‍💼 Proposal evaluator – produce structured scoring and evaluation criteria from project proposals
72. 🏢 Operations dashboard creator – translate facility logs into productivity and efficiency metrics
73. 🏥 Lab result organizer – build structured diagnostic tables from laboratory results
74. 💡 Innovation evaluator – compile ideation logs into cost-benefit structured analyses
75. 🏛️ Judicial ruling summarizer – generate concise, structured digests from court rulings
76. 🔧 Commit changelog generator – extract impactful changes from commit logs for release summaries
77. 🏭 Production yield analyzer – produce reports on output statistics and downtime from factory logs
78. 💳 Fraud alert generator – transform risk signals into automated CVSS-scored alerts
79. 📝 Regulatory filing assistant – structure raw regulatory data for seamless filing and compliance tracking
80. 👩‍⚕️ Clinical observation compiler – convert medical research notes into structured clinical data entries
81. 🚀 Deployment success reporter – summarize production rollouts with performance metrics and KPIs
82. 🏦 Mortgage risk evaluator – process mortgage files into detailed risk scoring and eligibility summaries
83. 💼 Contract amendment monitor – track version changes and compliance updates in amended contracts
84. 🏥 Vital signs monitor – generate alert reports from patient vital signs and anomaly detection
85. 🔐 IT security auditor – convert access logs into structured audit and compliance reports
86. 🚧 Incident ticket classifier – generate detailed RCA reports and automated ticket categorizations
87. 🏛️ Governance mapper – produce structured mappings of internal policies to regulatory frameworks
88. 🏢 Onboarding compliance checker – convert training logs into automated compliance and checklist trackers
89. 📝 Data breach notifier – build structured breach incident reports with remediation plans
90. 🏦 Teller performance analyzer – transform shift logs into performance and error analysis reports
91. 💼 Contract risk assessor – generate automated legal risk memos from detailed contract reviews
92. 🛠️ Bug report classifier – categorize issue reports by severity and produce remediation plans
93. 🏥 Appointment summarizer – convert appointment notes into structured follow-up recommendations
94. 🔄 Data migration manifest – output ETL mapping details into a structured transformation record
95. 🚀 Post-release analyst – synthesize customer feedback into performance improvement metrics
96. 🏭 Equipment efficiency evaluator – analyze production logs to predict maintenance needs and cost analysis
97. 🕵️ Fraud case reporter – compile investigative notes into structured fraud case summaries
98. 🏛️ Compliance checklist generator – map internal controls to GDPR or other frameworks in structured reports
99. 👨‍💻 Diff summarizer – automatically generate summaries of code differences for peer review
100. 📄 Patent claim comparator – produce novelty and prior art comparison tables from patent texts
101. 🔍 Cyber incident analyzer – structure incident narratives into threat intelligence and remediation guides
102. 🛡️ Security audit mapper – create control maps aligned with NIST frameworks from audit notes
103. 🏦 Portfolio risk analyzer – transform investment notes into performance and risk metric summaries
104. 📊 Stress test reporter – compile financial stress test scenarios into structured risk reports
105. 📝 Meeting action tracker – extract decisions and assign tasks from meeting minutes
106. 🛠️ DevOps runbook creator – produce actionable standard operating procedures from runbook logs
107. 🚚 Supply chain optimizer – generate delay forecasts and automated inventory suggestions from logistics notes
108. ⚙️ Process improvement recommender – convert operational logs into structured efficiency recommendations
109. 👮 Compliance reporter – map internal governance policies to GDPR and similar frameworks
110. 🌐 API performance optimizer – analyze API usage logs to generate optimization and performance metrics
111. 🛠️ Legacy system analyzer – assess legacy code bases and produce migration impact reports
112. 🧩 Unstructured anything → your bespoke schema-validated JSON

Input Formats

Traditional JSON Input

{
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user", 
      "content": "Your task description here"
    }
  ],
  "context": {
    "session_id": "optional-session-id",
    "metadata": {
      "any": "additional context"
    }
  }
}

YAML Input

messages:
  - role: system
    content: "You are a helpful assistant."
  - role: user
    content: "Your task description here"
context:
  session_id: "optional-session-id"
  metadata:
    any: "additional context"

Template-Based Input

Handlebars Template (template.hbs):

<message role="system">
You are an expert {{expertise.domain}} engineer.
Focus on {{expertise.focus_areas}}.
</message>

<message role="user">
Analyze this {{task.type}}:

{{#each task.items}}
- {{this}}
{{/each}}

Requirements: {{task.requirements}}
</message>

Jinja2 Template (template.j2):

<message role="system">
You are an expert {{expertise.domain}} engineer.
Focus on {{expertise.focus_areas}}.
</message>

<message role="user">
Analyze this {{task.type}}:

{% for item in task.items %}
- {{item}}
{% endfor %}

Requirements: {{task.requirements}}
</message>

Template Variables (vars.yaml):

expertise:
  domain: "DevOps"
  focus_areas: "security, performance, maintainability"
task:
  type: "pull request"
  items:
    - "Changed authentication logic"
    - "Updated database queries"
    - "Added input validation"
  requirements: "Focus on security vulnerabilities"

Structured Outputs with 100% Schema Enforcement

When you provide a --schema-file, the runner guarantees perfect schema compliance:

llm-ci-runner \
  --input-file examples/01-basic/sentiment-analysis/input.json \
  --schema-file examples/01-basic/sentiment-analysis/schema.json

Note: Output defaults to result.json. Use --output-file custom-name.json for custom output files.

Supported Schema Features: ✅ String constraints (enum, minLength, maxLength, pattern)
✅ Numeric constraints (minimum, maximum, multipleOf)
✅ Array constraints (minItems, maxItems, items type)
✅ Required fields enforced at generation time
✅ Type validation (string, number, integer, boolean, array)

CI/CD Integration

GitHub Actions Example

- name: Setup Python
  uses: actions/setup-python@v5
  with:
    python-version: '3.12'

- name: Install LLM CI Runner
  run: pip install llm-ci-runner

- name: Generate PR Review with Templates
  run: |
    llm-ci-runner \
      --template-file .github/templates/pr-review.j2 \
      --template-vars pr-context.yaml \
      --schema-file .github/schemas/pr-review.yaml \
      --output-file pr-analysis.yaml
  env:
    AZURE_OPENAI_ENDPOINT: ${{ secrets.AZURE_OPENAI_ENDPOINT }}
    AZURE_OPENAI_MODEL: ${{ secrets.AZURE_OPENAI_MODEL }}

For complete CI/CD examples, see examples/uv-usage-example.md.

Authentication

Azure OpenAI: Uses Azure's DefaultAzureCredential supporting:

• Environment variables (local development)
• Managed Identity (recommended for Azure CI/CD)
• Azure CLI (local development)
• Service Principal (non-Azure CI/CD)

OpenAI: Uses API key authentication with optional organization ID.

Testing

We maintain comprehensive test coverage with 100% success rate:

# For package users - install test dependencies
pip install llm-ci-runner[dev]

# For development - install from source with test dependencies
uv sync --group dev

# Run specific test categories
pytest tests/unit/ -v          # 70 unit tests
pytest tests/integration/ -v   # End-to-end examples
pytest acceptance/ -v          # LLM-as-judge evaluation

# Or with uv for development
uv run pytest tests/unit/ -v
uv run pytest tests/integration/ -v
uv run pytest acceptance/ -v

Architecture

Built on Microsoft Semantic Kernel for:

• Enterprise-ready Azure OpenAI and OpenAI integration
• Future-proof model compatibility
• 100% Schema Enforcement: KernelBaseModel integration with token-level constraints
• Dynamic Model Creation: Runtime JSON schema → Pydantic model conversion
• Azure RBAC: Azure RBAC via DefaultAzureCredential
• Automatic Fallback: Azure-first priority with OpenAI fallback

The AI-First Development Journey

This toolkit is your first step toward AI-First DevOps. As you integrate AI into your development workflows, you'll experience:

1. 🚀 Exponential Productivity: AI handles routine tasks while you focus on architecture
2. 🎯 Guaranteed Quality: Schema enforcement eliminates validation errors
3. 🤖 Autonomous Operations: AI agents make decisions in your pipelines
4. 📈 Continuous Improvement: Every interaction improves your AI system

The future belongs to teams that master AI-first principles. This toolkit gives you the foundation to start that journey today.

License

MIT License - See LICENSE file for details. Copyright (c) 2025, Benjamin Linnik.

Support

🐛 Found a bug? 💡 Have a question? 📚 Need help?

GitHub is your primary destination for all support:

• 📋 Issues & Bug Reports: Create an issue
• 📖 Documentation: Browse examples
• 🔧 Source Code: View source

Before opening an issue, please:

1. ✅ Check the examples directory for solutions
2. ✅ Review the error logs (beautiful output with Rich!)
3. ✅ Validate your Azure authentication and permissions
4. ✅ Ensure your input JSON follows the required format
5. ✅ Search existing issues for similar problems

Quick Links:

• 🚀 Getting Started Guide
• 📚 Complete Examples
• 🔧 CI/CD Integration
• 🎯 Use Cases

---

Ready to embrace the AI-First future? Start with this toolkit and build your path to exponential productivity. Learn more about the AI-First DevOps revolution in Building AI-First DevOps.