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Fiverr Pro
English
$
USD
I will integrate local ollama ai pipelines into your github actions
Rogue Sailor
About this gig
Are soaring cloud API bills holding back your automated testing workflows? Want to integrate smart AI diagnostics into your codebase without exposing your intellectual property to external networks?
As an experienced AI Engineer, I build secure, zero-dependency local AI agents using Ollama and Python's standard library to automate code reviews and parsing pipelines natively inside your CI/CD environment.
What I deliver:
- Custom local Ollama pipeline integration (Llama 3, Mistral, etc.)
- Automated GitHub Actions log analysis and VM error diagnostics
- Zero-dependency Python parsing architectures (no framework bloat)
- Security-first process execution (strictly avoiding shell vulnerabilities)
- Historical log-comparison filters to isolate and trap flaky system tests
- Structured Markdown verdicts outputted directly to your Pull Requests
Stop wasting thousands of dollars on cloud API calls for programmatic code reviews. I engineer fast, secure, local LLM architectures designed to handle large log files effortlessly.
Please reach out with your stack details before ordering so we can align on project scopes!
Get to know Rogue Sailor
Rogue Sailor
AI Engineer and Systems Automator
- FromPakistan
- Member sinceJan 2024
- Avg. response time5 hours
Languages
Urdu, English
Systems & automation engineer with 3 years building production Python backends and AI pipelines. I specialize in three things: cutting AI operating costs (local/offline LLM deployment via Ollama, token-efficient RAG pipelines), hardening automation and DevOps tooling (secure CI/CD, log parsing, API integration), and precision hardware tuning (Klipper firmware, CoreXY/Voron/RatRig calibration). No bloated frameworks — lean, production-ready code. I can also debug and fix AI-generated code that's gone sideways. Let's talk about what you need built.
FAQ
What infrastructure is required to run this local AI setup?
The pipeline runs on standard self-hosted runner machines or local development systems capable of hosting Ollama natively. I optimize the code to utilize lightweight models (like Llama 3 8B or Mistral) to ensure high-velocity execution profiles on basic GPU/CPU configurations.
Is my source code or log data secure with this implementation?
Yes, absolutely. By leveraging a local Ollama integration, all code strings, stack traces, and environment logs are processed entirely on your own computing hardware. No data ever leaves your system or gets sent to external cloud APIs.
How does the agent catch flaky tests?
In the Premium package, I implement multi-run log compilation. The script automatically aggregates and scans data across separate pipeline failures, allowing the local LLM to isolate timing variations, container socket drops, or localized network latency bottlenecks.
