[aw] Repo Assist has no AI credits pricing for model (gpt-5.6-luna-utility)
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Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 45/100
Línea de trabajo
Start by reviewing the linked workflow run and the repo-assist.md workflow frontmatter to confirm which model and provider are configured. Then read the model-pricing guidance in the issue and determine whether this model needs explicit pricing, a mapping, or replacement. Done means the configuration supports the model and a rerun completes successfully.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Workflow Failure
Workflow: Repo Assist
Branch: main
Run: https://github.com/IntelliTect/EssentialCSharp.Web/actions/runs/41011173303
[!WARNING]
Model has no AI credits pricing: The agent failed because modelgpt-5.6-luna-utilityis 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 areport_incompletesignal: 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/41011173303
Manually invoke the agent
Debug this workflow failure using your favorite Agent CLI and the agentic-workflows prompt.
- Start your agent
- Load the
agentic-workflowsskill from.github/skills/agentic-workflows/SKILL.mdor https://github.com/github/gh-aw/blob/main/.github/skills/agentic-workflows/SKILL.md - Type
debug the agentic workflow repo-assist failure in https://github.com/IntelliTect/EssentialCSharp.Web/actions/runs/41011173303
[!TIP]
Stop reporting this workflow as a failure
To stop a workflow from creating failure issues, set
report-failure-as-issue: falsein its frontmatter:safe-outputs: report-failure-as-issue: false
Generated from Repo Assist · ◷
- Lenguaje dominante
- HTML
- Estrellas
- 8
- Forks
- 8
- Merge medio
- 7 h 57 min
- PR fusionados (30 d)
- 87
Preparar el entorno
Inicia el contenedor de desarrollo del proyecto en tu navegador, con tu propia cuenta de GitHub.
- Sin Dockerfile ni archivo de Docker Compose
- Sin plantilla de pull request
- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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