[aw] Repo Assist has no AI credits pricing for model (gpt-5.6-luna-utility)
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Nessuno ha ancora preso questa issue.
Valutazione
- Difficoltà
- 2/5
- Tempo stimato
- 1-3 ore
- Idoneità per principianti
- 48/100
- Tipo di issue
- Bug
- Chiarezza
- Abbastanza chiara
- Stato di attività
- Attiva
- Stack tecnologico
- github-actions
- Ambito
- ci-cd
Direzione di ricerca
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.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Descrizione
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 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/39201411885
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/39201411885
[!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 · ◷
- Lingua principale
- HTML
- Stelle
- 8
- Fork
- 8
- Merge medio
- 1g 31m
- PR unite (30g)
- 87
Preparare l'ambiente
Avvia il container di sviluppo del progetto nel browser, con il tuo account GitHub.
- Nessun Dockerfile né file Docker Compose
- Nessun modello di pull request
- Leggi la guida per i contributori
Come iniziare
- Leggi tutta la issue e poi la guida ai contributi del progetto.
- Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
- Fai un fork del repository e lavora su un branch.
- Apri una pull request che faccia riferimento al numero della issue.
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