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refactor: extract _resolve_model_options() to remove duplicated logic 

Both select_shallow_thinking_agent and select_deep_thinking_agent had
identical Copilot/static model resolution blocks. Extract into a single
helper to improve maintainability.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Jiaxu Liu 2026-03-23 14:47:20 +00:00
parent d6ef3c5d4d
commit 902ad8b932
1 changed files with 47 additions and 20 deletions
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67
cli/utils.py
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@ -134,6 +134,28 @@ def select_research_depth() -> int:
return choice
def _resolve_model_options(
provider: str, static_options: dict
) -> list[tuple[str, str]]:
"""Return model options for the given provider.
For Copilot, fetches the live model list from the API.
For all other providers, looks up the static options dict.
Exits with an error message if no models are available.
"""
if provider.lower() == "copilot":
options = fetch_copilot_models()
if not options:
console.print("[red]No Copilot models available. Exiting...[/red]")
exit(1)
else:
options = static_options.get(provider.lower())
if not options:
console.print(f"[red]No models available for provider '{provider}'. Exiting...[/red]")
exit(1)
return options
def select_shallow_thinking_agent(provider) -> str:
"""Select shallow thinking llm engine using an interactive selection."""
@ -175,16 +197,7 @@ def select_shallow_thinking_agent(provider) -> str:
"copilot": [],
}
if provider.lower() == "copilot":
options = fetch_copilot_models()
if not options:
console.print("[red]No Copilot models available. Exiting...[/red]")
exit(1)
else:
options = SHALLOW_AGENT_OPTIONS.get(provider.lower())
if not options:
console.print(f"[red]No models available for provider '{provider}'. Exiting...[/red]")
exit(1)
options = _resolve_model_options(provider, SHALLOW_AGENT_OPTIONS)
choice = questionary.select(
"Select Your [Quick-Thinking LLM Engine]:",
@ -254,16 +267,7 @@ def select_deep_thinking_agent(provider) -> str:
"copilot": [], # populated dynamically by fetch_copilot_models()
}
if provider.lower() == "copilot":
options = fetch_copilot_models()
if not options:
console.print("[red]No Copilot models available. Exiting...[/red]")
exit(1)
else:
options = DEEP_AGENT_OPTIONS.get(provider.lower())
if not options:
console.print(f"[red]No models available for provider '{provider}'. Exiting...[/red]")
exit(1)
options = _resolve_model_options(provider, DEEP_AGENT_OPTIONS)
choice = questionary.select(
"Select Your [Deep-Thinking LLM Engine]:",
@ -287,6 +291,29 @@ def select_deep_thinking_agent(provider) -> str:
return choice
def _resolve_model_options(
provider: str, static_options: dict
) -> list[tuple[str, str]]:
"""Return the model list for the given provider.
For Copilot, fetches live from the inference API.
For all others, looks up the static options dict.
Exits with an error message if no models are available.
"""
if provider.lower() == "copilot":
options = fetch_copilot_models()
if not options:
console.print("[red]No Copilot models available. Exiting...[/red]")
exit(1)
return options
options = static_options.get(provider.lower())
if not options:
console.print(f"[red]No models available for provider '{provider}'. Exiting...[/red]")
exit(1)
return options
def fetch_copilot_models() -> list[tuple[str, str]]:
"""Fetch models from the GitHub Copilot inference API.