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import type { LLMJudgeModelConfig } from '@api/evaluations/llm-judge';
import type { UserDataStorageConnector } from '@api/types/connector';
import type { AppContext } from '@api/types/hono';
import { warn } from '@shared/console-logging';
import type { AIProvider } from '@shared/types/constants';
import type { Model, SkillOptimizationEvaluation } from '@shared/types/data';
/**
* Model configuration resolved from system settings or evaluation.
*/
export interface ResolvedModelConfig {
model: string;
provider: AIProvider;
/**
* The provider's API key, where it has one. Self-hosted providers such as
* Ollama are configured without a key and are called without one.
*/
apiKey?: string;
/**
* The provider's configured base URL, where it has one.
*
* Internal skills call back through the gateway with a target naming only a
* provider and a model, so without this a self-hosted provider is sent to its
* vendor default -- Ollama to `http://localhost:11434` -- no matter what the
* user configured. The failure is quiet: the call cannot connect, the error
* is logged, and optimization simply stops happening.
*/
customHost?: string;
}
/**
* System settings model type for lookup.
*/
export type SystemSettingsModelType =
| 'judge'
| 'embedding'
| 'system_prompt_reflection'
| 'evaluation_generation';
/**
* Resolves a model configuration from a model ID.
*
* @param modelId - The model ID to resolve
* @param connector - The storage connector to look up models
* @param logPrefix - Prefix for log messages
* @returns The model configuration or null if not found
*/
async function resolveModelById(
c: AppContext,
modelId: string,
connector: UserDataStorageConnector,
logPrefix: string,
): Promise<ResolvedModelConfig | null> {
// Look up the model
const models = await connector.getModels(c, { id: modelId });
if (models.length === 0) {
warn(`[${logPrefix}] Model not found: ${modelId}`);
return null;
}
const model = models[0];
// Look up the provider to get the API key
const providers = await connector.getAIProviderAPIKeys(c, {
id: model.ai_provider_id,
});
if (providers.length === 0) {
warn(
`[${logPrefix}] Provider not found for model: ${model.ai_provider_id}`,
);
return null;
}
const providerConfig = providers[0];
// Ensure we have an API key, for the providers that need one
if (
!providerConfig.api_key &&
isAPIKeyRequiredForProvider(providerConfig.ai_provider)
) {
warn(
`[${logPrefix}] No API key configured for provider: ${model.ai_provider_id}`,
);
return null;
}
return {
model: model.model_name,
provider: providerConfig.ai_provider as AIProvider,
apiKey: providerConfig.api_key ?? undefined,
customHost: providerConfig.custom_fields?.custom_host as string | undefined,
};
}
/**
* Resolves a model configuration from system settings.
*
* @param modelType - The type of model to resolve from system settings
* @param connector - The storage connector to look up models and settings
* @returns The model configuration or null if not configured
*/
export async function resolveSystemSettingsModel(
c: AppContext,
modelType: SystemSettingsModelType,
connector: UserDataStorageConnector,
): Promise<ResolvedModelConfig | null> {
const logPrefix = `MODEL_RESOLVER_${modelType.toUpperCase()}`;
const systemSettings = await connector.getSystemSettings(c);
let modelId: string | null = null;
switch (modelType) {
case 'judge':
modelId = systemSettings.judge_model_id;
break;
case 'embedding':
modelId = systemSettings.embedding_model_id;
break;
case 'system_prompt_reflection':
modelId = systemSettings.system_prompt_reflection_model_id;
break;
case 'evaluation_generation':
modelId = systemSettings.evaluation_generation_model_id;
break;
}
if (!modelId) {
warn(
`[${logPrefix}] No ${modelType}_model_id configured in system settings`,
);
return null;
}
return resolveModelById(c, modelId, connector, logPrefix);
}
/**
* Resolves the model configuration for an evaluation.
*
* Resolution order:
* 1. If evaluation.model_id is set, use that model
* 2. Otherwise, use the judge_model_id from system settings
*
* @param evaluation - The evaluation to resolve model for
* @param connector - The storage connector to look up models and settings
* @returns The model configuration or null if no model could be resolved
*/
export async function resolveEvaluationModelConfig(
c: AppContext,
evaluation: SkillOptimizationEvaluation,
connector: UserDataStorageConnector,
): Promise<LLMJudgeModelConfig | null> {
const logPrefix = 'EVAL_MODEL_RESOLVER';
// If evaluation has a model_id, use it
if (evaluation.model_id) {
return await resolveModelById(c, evaluation.model_id, connector, logPrefix);
}
// Fall back to system settings judge_model_id
return await resolveSystemSettingsModel(c, 'judge', connector);
}
/**
* Embedding model configuration with dimensions.
*/
export interface EmbeddingModelConfig {
modelId: string;
model: Model;
dimensions: number;
}
/**
* Resolves the embedding model configuration from system settings.
*
* @param connector - The storage connector to look up models and settings
* @returns The embedding model config or null if not configured
*/
export async function resolveEmbeddingModelConfig(
c: AppContext,
connector: UserDataStorageConnector,
): Promise<EmbeddingModelConfig | null> {
const logPrefix = 'EMBEDDING_MODEL_RESOLVER';
const systemSettings = await connector.getSystemSettings(c);
if (!systemSettings.embedding_model_id) {
warn(`[${logPrefix}] No embedding_model_id configured in system settings`);
return null;
}
const models = await connector.getModels(c, {
id: systemSettings.embedding_model_id,
});
if (models.length === 0) {
warn(
`[${logPrefix}] Embedding model not found: ${systemSettings.embedding_model_id}`,
);
return null;
}
const model = models[0];
if (!model.embedding_dimensions) {
warn(
`[${logPrefix}] Embedding model ${model.model_name} has no dimensions configured`,
);
return null;
}
return {
modelId: model.id,
model,
dimensions: model.embedding_dimensions,
};
}
|