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RUNLOCALAI · v38
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  6. /Ch. 14
Troubleshooting Local AI

14. Community Resources

Chapter 14 of 15 · 15 min
KEY INSIGHT

Well-documented bugs get fixed. Poorly documented bugs get closed as "cannot reproduce" or "needs more information." Spend 10 minutes writing a complete bug report to save waiting days for a response.

Where to Find Answers

GitHub Issues: Before posting, search closed issues. Most common problems have been solved. Include your system specs, exact error message, and steps to reproduce.

Hugging Face Discord: Active community with channels for specific model families. Use the search function before asking.

Stack Overflow: Tag questions with hugging-face or llama-cpp or vllm. High-quality questions with minimal code get answers. "It doesn't work" gets closed.

Local AI Discord servers: Serve specific deployment technologies (Ollama Discord, LocalAI Discord, text-generation-webui Discord).

Filing Effective Bug Reports

A useful bug report contains:

  1. Environment: OS, GPU model, driver version, CUDA version, Python version, library versions
  2. Reproduction: Exact commands to reproduce the issue
  3. Expected behavior: What should happen
  4. Actual behavior: What happens instead
  5. Full error traceback: Not a screenshot of the error, the actual text
# Generate environment report
echo "=== System ===" > bug_report.txt
uname -a >> bug_report.txt
echo "=== GPU ===" >> bug_report.txt
nvidia-smi >> bug_report.txt
echo "=== CUDA ===" >> bug_report.txt
nvcc --version >> bug_report.txt
echo "=== Python ===" >> bug_report.txt
python --version >> bug_report.txt
pip freeze >> bug_report.txt

Local verification checkpoint

Run the smallest example from this chapter in a local workspace and record the package version, runtime, data path, and observed output. If the result depends on model size, vector count, CPU/GPU backend, or available memory, note that constraint beside the exercise so the lesson remains reproducible.

Local verification checkpoint

Run the smallest example from this chapter in a local workspace and record the package version, runtime, data path, and observed output. If the result depends on model size, vector count, CPU/GPU backend, or available memory, note that constraint beside the exercise so the lesson remains reproducible.

EXERCISE

Write a bug report for a problem you've encountered. Include all sections listed above. Then search for that issue on GitHub. If you find an existing report, compare it to yours.

← Chapter 13
Log Analysis
Chapter 15 →
Troubleshooting Runbook Project