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[aw] Repo Assist has no AI credits pricing for model (gpt-5.6-luna-utility)

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Los mantenedores suelen responder en 1 día

Nadie ha tomado este issue todavía.

Evaluación

Dificultad
2/5
Tiempo estimado
1-3 horas
Aptitud para principiantes
48/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
github-actions
Área
ci-cd

Línea de trabajo

Start with the Repo Assist workflow frontmatter and the linked failed run to identify where gpt-5.6-luna-utility is configured and which provider it uses. Check whether the model has a valid pricing entry or alias; done when the workflow can make inference requests without the missing pricing error and the task completes.

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

Descripción

agentic-workflows
Workflow Failure

Workflow: Repo Assist
Branch: main
Run: https://github.com/IntelliTect/EssentialCSharp.Web/actions/runs/39201411885

[!WARNING]
Model has no AI credits pricing: The agent failed because model gpt-5.6-luna-utility is not in the built-in pricing table and no default fallback pricing is configured. The AWF API proxy rejected every inference request with HTTP 400.

This is a configuration issue — retrying will not help. The model must have pricing before the workflow can run.

How to fix this

Option 1 — Add pricing in the workflow frontmatter:

models:
  providers:
    github-copilot:
      models:
        'gpt-5.6-luna-utility':
          cost:
            # Placeholder values — replace with actual pricing for this model
            input: "0e0"      # $0.00 per million input tokens
            output: "0e0"     # $0.00 per million output tokens
            cache_read: "0e0"  # $0.00 per million cache-read tokens
            cache_write: "0e0" # $0.00 per million cache-write tokens

Use the provider key matching your engine: github-copilot (Copilot), anthropic (Claude), openai (Codex), or google (Gemini). Only input and output are required; the rest default to zero (or output for reasoning).

Option 2 — Map the model to a known model using the models field:

If gpt-5.6-luna-utility is an alias for a model already in the built-in pricing table, use the models frontmatter field to provide the mapping:

models:
  'gpt-5.6-luna-utility':
    - claude-sonnet-4-5

Option 3 — Switch to a model already in the built-in pricing table:

Replace gpt-5.6-luna-utility in the workflow frontmatter with a model name that the AWF pricing system recognizes (e.g. claude-sonnet-4-5, gpt-4.1, gemini-2.0-flash).

[!WARNING]
Task Could Not Be Completed: The workflow recorded a report_incomplete signal: the task was not completed or completion could not be confirmed.

Error details: 
Failure classification: request_rejection
Driver exit code: 1. The engine driver exited before a terminal safe output was recorded.
Last tool call status: not recorded
Failed tool calls observed: 0
Token budget state: unknown (no exhaustion signal recorded)
Step budget state (LLM invocations): unknown (no exhaustion signal recorded)
Safe-output tools: available at gateway snapshot (registered 12 tools)
Safe-output CLI calls observed: unknown (not recorded)
Safe-output MCP calls observed: 0
Safe-output persistence: not recorded
Engine error: Model has no AI credits pricing (missing_model_pricing_error)
Agent finished without emitting a terminal safe output; task completion could not be confirmed.
Engine HTTP error codes: 400
Last engine error type: missing_model_pricing_error
Retry attempts observed: 0

A comment or other safe output does not confirm that the requested task was completed. Only inferred runtime status and error codes are reported; agent text is excluded.

Failure Diagnostics

Agent job: agent
Agent job conclusion: failure
Failing step: Execute GitHub Copilot CLI

The runtime did not record a specific cause. Check the linked run for failure details.

Only runtime metadata is shown; agent-generated text is excluded.

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/IntelliTect/EssentialCSharp.Web/actions/runs/39201411885
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 Repo Assist · ◷

Lenguaje dominante
HTML
Estrellas
8
Forks
8
Merge medio
1 d 31 min
PR fusionados (30 d)
87

Preparar el entorno

Abrir en Codespaces

Inicia el contenedor de desarrollo del proyecto en tu navegador, con tu propia cuenta de GitHub.

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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