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[aw] Prompt Optimization reported incomplete result

Aperta
  • Qualcosa non va?
#329 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

I maintainer di solito rispondono entro 1 giorno

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
42/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
github-actions, javascript, ollama
Ambito
ai, ci-cd, devops

Direzione di ricerca

Start by reading .github/workflows/prompt-optimization.md and the failed run linked in the issue. Trace the steps that restore the Ollama cache, fetch the GGUF models, and start the server; check whether each step succeeds and makes the CLI available. The issue is resolved when the workflow provides the evaluation server and both models so the optimization script can produce measured scores.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

agentic-workflows
Workflow Failure

Workflow: Prompt Optimization
Branch: main
Run: https://github.com/githubnext/gh-aw-wizard/actions/runs/38176105592

[!WARNING]
Task Could Not Be Completed: The agent reported that the task could not be performed due to an infrastructure or tool failure.

Reasons:

  • Required Ollama eval infrastructure was not available, so the hill-climbing loop could not run.

    The task stated the Ollama cache was restored, GGUF proxies for both browser models were downloaded from Hugging Face, and an OpenAI-compatible server was started on (127.0.0.1/redacted) None of this was true in this run:

  • curl to (127.0.0.1/redacted) and /api/tags returned "Connection refused" (no listener on port 11434; ss/netstat showed nothing bound there).

  • No ollama process was running (ps aux showed only the Copilot CLI harness process).

  • The ollama CLI was not on PATH (which ollama -> not found), though the binary exists at /opt/hostedtoolcache/ollama/0.33.2/x64/ollama.

  • No model weights were cached anywhere on disk: ~/.ollama does not exist, OLLAMA_MODELS env var is unset, and a full filesystem search for *.gguf, qwen2.5*, and smollm2* found nothing related to the required models (hf.co/bartowski/Qwen2.5-1.5B-Instruct-GGUF:Q4_K_M and hf.co/unsloth/SmolLM2-360M-Instruct-GGUF:Q4_K_M).

Pre-optimization guard was checked first and found no open PR titled "Prompt optimization:" (gh pr list --state open returned []), so no review-comment action was applicable either.

Without a running eval server and the two GGUF proxy models, scripts/prompt-optimizer.mjs --evaluate/--score cannot produce real measured scores, so per the task's explicit constraints I did not fabricate scores, did not install/download the ~1-2GB of model weights myself (out of scope for this task and not something the task asked me to set up), and made no changes to src/js/slm.js. Working tree is clean (git status --short is empty); an incidental metadata diff in .github/skills/optimize-scenario-prompt/SKILL.md was reverted with git checkout --.

Recommended fix for the workflow owner: verify the upstream step(s) that are supposed to restore the Ollama cache, download the GGUF model proxies, and start ollama serve actually execute successfully before this job runs, and that ollama is placed on PATH or its full path is used.

This is a structured incompletion signal (report_incomplete), not a real task outcome. Any other safe outputs emitted alongside this signal (e.g., comments) describe the failure state, not a completed review or action.

Action Required

Assign this issue to an agent to debug and fix the issue.

Debug with any coding agent

Use this prompt with any coding agent (GitHub Copilot, Claude, Gemini, etc.):

Debug the agentic workflow failure using https://raw.githubusercontent.com/github/gh-aw/main/debug.md

The failed workflow run is at https://github.com/githubnext/gh-aw-wizard/actions/runs/38176105592
Manually invoke the agent

Debug this workflow failure using your favorite Agent CLI and the agentic-workflows prompt.

[!TIP]

Stop reporting this workflow as a failure

To stop a workflow from creating failure issues, set report-failure-as-issue: false in its frontmatter:

safe-outputs:
  report-failure-as-issue: false

Generated from Prompt Optimization · copilot · 30.5 AIC · ◷

Lingua principale
JavaScript
Stelle
6
Fork
1
Merge medio
1g 4h
PR unite (30g)
19

Preparare l'ambiente

Questo progetto non fornisce container di sviluppo, Dockerfile né guida per i contributori, quindi l'ambiente è a tuo carico: parti dal suo README e consulta la nostra guida al primo contributo per i passaggi generali.

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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