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refactor(model): extract shared switch_model() from CLI and gateway handlers
Phase 4 of the /model command overhaul. Both the CLI (cli.py) and gateway (gateway/run.py) /model handlers had ~50 lines of duplicated core logic: parsing, provider detection, credential resolution, and model validation. This extracts that pipeline into hermes_cli/model_switch.py. New module exports: - ModelSwitchResult: dataclass with all fields both handlers need - CustomAutoResult: dataclass for bare '/model custom' results - switch_model(): core pipeline — parse → detect → resolve → validate - switch_to_custom_provider(): resolve endpoint + auto-detect model The shared functions are pure (no I/O side effects). Each caller handles its own platform-specific concerns: - CLI: sets self.model/provider/etc, calls save_config_value(), prints - Gateway: writes config.yaml directly, sets env vars, returns markdown Net result: -244 lines from handlers, +234 lines in shared module. The handlers are now ~80 lines each (down from ~150+) and can't drift apart on core logic.
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3 changed files with 359 additions and 258 deletions
234
hermes_cli/model_switch.py
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234
hermes_cli/model_switch.py
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"""Shared model-switching logic for CLI and gateway /model commands.
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Both the CLI (cli.py) and gateway (gateway/run.py) /model handlers
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share the same core pipeline:
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parse_model_input → is_custom detection → auto-detect provider
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→ credential resolution → validate model → return result
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This module extracts that shared pipeline into pure functions that
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return result objects. The callers handle all platform-specific
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concerns: state mutation, config persistence, output formatting.
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"""
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from __future__ import annotations
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import os
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from dataclasses import dataclass, field
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from typing import Optional
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@dataclass
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class ModelSwitchResult:
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"""Result of a model switch attempt."""
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success: bool
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new_model: str = ""
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target_provider: str = ""
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provider_changed: bool = False
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api_key: str = ""
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base_url: str = ""
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persist: bool = False
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error_message: str = ""
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warning_message: str = ""
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is_custom_target: bool = False
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provider_label: str = ""
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@dataclass
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class CustomAutoResult:
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"""Result of switching to bare 'custom' provider with auto-detect."""
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success: bool
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model: str = ""
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base_url: str = ""
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api_key: str = ""
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error_message: str = ""
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def switch_model(
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raw_input: str,
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current_provider: str,
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current_base_url: str = "",
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current_api_key: str = "",
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) -> ModelSwitchResult:
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"""Core model-switching pipeline shared between CLI and gateway.
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Handles parsing, provider detection, credential resolution, and
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model validation. Does NOT handle config persistence, state
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mutation, or output formatting — those are caller responsibilities.
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Args:
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raw_input: The user's model input (e.g. "claude-sonnet-4",
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"zai:glm-5", "custom:local:qwen").
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current_provider: The currently active provider.
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current_base_url: The currently active base URL (used for
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is_custom detection).
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current_api_key: The currently active API key.
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Returns:
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ModelSwitchResult with all information the caller needs to
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apply the switch and format output.
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"""
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from hermes_cli.models import (
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parse_model_input,
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detect_provider_for_model,
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validate_requested_model,
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_PROVIDER_LABELS,
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)
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from hermes_cli.runtime_provider import resolve_runtime_provider
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# Step 1: Parse provider:model syntax
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target_provider, new_model = parse_model_input(raw_input, current_provider)
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# Step 2: Detect if we're currently on a custom endpoint
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_base = current_base_url or ""
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is_custom = current_provider == "custom" or (
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"localhost" in _base or "127.0.0.1" in _base
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)
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# Step 3: Auto-detect provider when no explicit provider:model syntax
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# was used. Skip for custom providers — the model name might
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# coincidentally match a known provider's catalog.
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if target_provider == current_provider and not is_custom:
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detected = detect_provider_for_model(new_model, current_provider)
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if detected:
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target_provider, new_model = detected
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provider_changed = target_provider != current_provider
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# Step 4: Resolve credentials for target provider
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api_key = current_api_key
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base_url = current_base_url
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if provider_changed:
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try:
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runtime = resolve_runtime_provider(requested=target_provider)
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api_key = runtime.get("api_key", "")
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base_url = runtime.get("base_url", "")
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except Exception as e:
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provider_label = _PROVIDER_LABELS.get(target_provider, target_provider)
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if target_provider == "custom":
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return ModelSwitchResult(
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success=False,
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target_provider=target_provider,
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error_message=(
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"No custom endpoint configured. Set model.base_url "
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"in config.yaml, or set OPENAI_BASE_URL in .env, "
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"or run: hermes setup → Custom OpenAI-compatible endpoint"
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),
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)
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return ModelSwitchResult(
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success=False,
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target_provider=target_provider,
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error_message=(
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f"Could not resolve credentials for provider "
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f"'{provider_label}': {e}"
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),
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)
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else:
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# Gateway also resolves for unchanged provider to get accurate
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# base_url for validation probing.
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try:
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runtime = resolve_runtime_provider(requested=current_provider)
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api_key = runtime.get("api_key", "")
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base_url = runtime.get("base_url", "")
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except Exception:
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pass
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# Step 5: Validate the model
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try:
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validation = validate_requested_model(
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new_model,
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target_provider,
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api_key=api_key,
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base_url=base_url,
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)
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except Exception:
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validation = {
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"accepted": True,
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"persist": True,
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"recognized": False,
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"message": None,
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}
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if not validation.get("accepted"):
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msg = validation.get("message", "Invalid model")
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return ModelSwitchResult(
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success=False,
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new_model=new_model,
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target_provider=target_provider,
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error_message=msg,
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)
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# Step 6: Build result
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provider_label = _PROVIDER_LABELS.get(target_provider, target_provider)
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is_custom_target = target_provider == "custom" or (
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base_url
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and "openrouter.ai" not in (base_url or "")
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and ("localhost" in (base_url or "") or "127.0.0.1" in (base_url or ""))
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)
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return ModelSwitchResult(
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success=True,
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new_model=new_model,
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target_provider=target_provider,
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provider_changed=provider_changed,
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api_key=api_key,
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base_url=base_url,
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persist=bool(validation.get("persist")),
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warning_message=validation.get("message") or "",
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is_custom_target=is_custom_target,
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provider_label=provider_label,
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)
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def switch_to_custom_provider() -> CustomAutoResult:
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"""Handle bare '/model custom' — resolve endpoint and auto-detect model.
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Returns a result object; the caller handles persistence and output.
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"""
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from hermes_cli.runtime_provider import (
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resolve_runtime_provider,
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_auto_detect_local_model,
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)
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try:
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runtime = resolve_runtime_provider(requested="custom")
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except Exception as e:
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return CustomAutoResult(
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success=False,
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error_message=f"Could not resolve custom endpoint: {e}",
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)
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cust_base = runtime.get("base_url", "")
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cust_key = runtime.get("api_key", "")
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if not cust_base or "openrouter.ai" in cust_base:
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return CustomAutoResult(
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success=False,
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error_message=(
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"No custom endpoint configured. "
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"Set model.base_url in config.yaml, or set OPENAI_BASE_URL "
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"in .env, or run: hermes setup → Custom OpenAI-compatible endpoint"
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),
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)
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detected_model = _auto_detect_local_model(cust_base)
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if not detected_model:
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return CustomAutoResult(
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success=False,
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base_url=cust_base,
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api_key=cust_key,
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error_message=(
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f"Custom endpoint at {cust_base} is reachable but no single "
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f"model was auto-detected. Specify the model explicitly: "
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f"/model custom:<model-name>"
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),
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)
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return CustomAutoResult(
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success=True,
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model=detected_model,
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base_url=cust_base,
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api_key=cust_key,
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)
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