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[aw] Prompt Optimization reported incomplete result

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  • ¿Algo no está bien?
#329 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
42/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github-actions, javascript, ollama
Área
ai, ci-cd, devops

Línea de trabajo

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.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

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 · ◷

Lenguaje dominante
JavaScript
Estrellas
6
Forks
1
Merge medio
1 d 5 h
PR fusionados (30 d)
21

Preparar el entorno

Este proyecto no incluye contenedor de desarrollo, Dockerfile ni guía de contribución, así que la configuración corre por tu cuenta: empieza por su README y consulta nuestra guía para la primera contribución para los pasos generales.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

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