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[aw] Prompt Optimization reported incomplete result

Abierto
  • ¿Algo no está bien?
#300 0 comentarios 0 reacciones 0 asignados Ver en GitHub

Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
48/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github-actions, javascript
Área
ci-cd, devops

Línea de trabajo

Start with .github/workflows/prompt-optimization.md and the failed run, then inspect scripts/prompt-optimizer.mjs and the referenced debug guidance. Reproduce the unreachable Ollama condition and verify that the workflow can reach its evaluation server, run the --evaluate or --score command, and complete without reporting an incomplete result.

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/36351370853

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

Reasons:

  • Ollama eval server unreachable from the agent sandbox

    The prompt-optimization task requires an OpenAI-compatible Ollama server at (127.0.0.1/redacted) with hf.co/bartowski/Qwen2.5-1.5B-Instruct-GGUF:Q4_K_M and hf.co/unsloth/SmolLM2-360M-Instruct-GGUF:Q4_K_M loaded. From inside the sandboxed agent container, curl to (127.0.0.1/redacted) gets Connection refused, and the squid firewall access log shows the proxied request to host.docker.internal:11434 (resolving to 172.17.0.1:11434, the host gateway) returning a 503 TCP_MISS_ABORTED, i.e. nothing is listening on port 11434 on the host side reachable from this container. No local ollama binary/process/model cache is present under this container image either (checked /opt/hostedtoolcache/ollama/0.33.2/x64/ollama -- installed but its own ollama serve was never started in this container, and it cannot reach the host Ollama instance through the firewall). This means the earlier workflow steps that were supposed to restore the Ollama cache, download the GGUF proxies, and start the OpenAI-compatible server did not leave a reachable server for this task. I could not run any --evaluate or --score command from scripts/prompt-optimizer.mjs, so no hill-climbing, no candidate scoring, and no DEFAULT_SCENARIO_INSTRUCTIONS change was attempted. No PR guard search found an existing open Prompt optimization PR to review either, so no review comment was needed. No repository files were modified; nothing to revert.

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/36351370853
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 · 69.1 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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