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import { BaseArmsParams } from '@api/optimization/base-arms';
import { regenerateEvaluationsWithExamples } from '@api/optimization/utils/evaluations';
import {
generateSeedSystemPromptForSkill,
generateSeedSystemPromptWithContext,
} from '@api/optimization/utils/system-prompt';
import type {
EvaluationMethodConnector,
LogsStorageConnector,
UserDataStorageConnector,
} from '@api/types/connector';
import type { AppContext } from '@api/types/hono';
import type {
SkillOptimizationArmCreateParams,
SkillOptimizationArmParams,
} from '@shared/types/data/skill-optimization-arm';
import type { EvaluationMethodName } from '@shared/types/evaluations';
export async function handleGenerateArms(
c: AppContext,
userStorageConnector: UserDataStorageConnector,
skillId: string,
clusterId?: string, // Optional: if provided, only regenerate arms for this cluster
) {
const skills = await userStorageConnector.getSkills(c, {
id: skillId,
});
if (skills.length === 0) {
return c.json({ error: 'Skill not found' }, 404);
}
const skill = skills[0];
// Get logs storage connector and evaluation connectors from context
const logsStorageConnector = c.get('logs_storage_connector');
const evaluationConnectorsMap = c.get('evaluation_connectors_map');
// Check if we have at least 5 logs with embeddings to use context-aware generation
let hasEnoughLogsForContext = false;
let logs: Awaited<ReturnType<LogsStorageConnector['getLogs']>> = [];
if (logsStorageConnector) {
logs = await logsStorageConnector.getLogs(c, {
skill_id: skill.id,
embedding_not_null: true,
limit: 5,
});
hasEnoughLogsForContext = logs.length >= 5;
}
// If we have enough logs, regenerate evaluations with context before creating arms
// Only do this for skill-wide regeneration (not cluster-specific)
if (hasEnoughLogsForContext && !clusterId) {
const exampleLogs = logs.slice(0, 5);
const examples = generateExampleConversations(exampleLogs);
// Get existing evaluations
const existingEvaluations =
await userStorageConnector.getSkillOptimizationEvaluations(c, {
skill_id: skill.id,
});
if (existingEvaluations.length > 0 && examples.length > 0) {
// Get agent description for context
const agents = await userStorageConnector.getAgents(c, {
id: skill.agent_id,
});
if (agents.length > 0) {
const agent = agents[0];
// Extract existing evaluation methods
const existingMethods = existingEvaluations.map(
(e) => e.evaluation_method,
);
// Regenerate evaluations with context
const regeneratedEvaluationParams =
await regenerateEvaluationsWithExamples(
c,
skill,
agent.description,
examples,
evaluationConnectorsMap as Record<
string,
EvaluationMethodConnector
>,
existingMethods as EvaluationMethodName[],
userStorageConnector,
);
// Delete old evaluations and create new ones
await userStorageConnector.deleteSkillOptimizationEvaluationsForSkill(
c,
skill.id,
);
await userStorageConnector.createSkillOptimizationEvaluations(
c,
regeneratedEvaluationParams,
);
}
}
}
// Get existing arms - either for specific cluster or entire skill
const existingArms = clusterId
? await userStorageConnector.getSkillOptimizationArms(c, {
cluster_id: clusterId,
})
: await userStorageConnector.getSkillOptimizationArms(c, {
skill_id: skill.id,
});
// Reset cluster step count - either specific cluster or all clusters
let clusters: Awaited<
ReturnType<UserDataStorageConnector['getSkillOptimizationClusters']>
>;
if (clusterId) {
clusters = await userStorageConnector.getSkillOptimizationClusters(c, {
id: clusterId,
});
if (clusters.length === 0) {
return c.json({ error: 'Cluster not found' }, 404);
}
// Only reset the specific cluster (already done in caller, but ensure consistency)
await userStorageConnector.updateSkillOptimizationCluster(c, clusterId, {
total_steps: 0,
});
} else {
clusters = await userStorageConnector.getSkillOptimizationClusters(c, {
skill_id: skill.id,
});
if (!clusters) {
return c.json({ error: 'Clusters not found' }, 404);
}
// Reset all clusters
for (const cluster of clusters) {
await userStorageConnector.updateSkillOptimizationCluster(c, cluster.id, {
total_steps: 0,
});
}
}
const skillModels = await userStorageConnector.getSkillModels(c, skill.id);
// Use the clusters we already fetched (either specific one or all)
const skillClusters = clusters;
if (!skillModels || !skillClusters) {
return c.json({ error: 'Skill models or clusters not found' }, 404);
}
// We don't need to create arms if there are no models or clusters
if (skillModels.length === 0 || skillClusters.length === 0) {
// Delete existing arms if any
for (const arm of existingArms) {
await userStorageConnector.deleteSkillOptimizationArmStats(c, {
arm_id: arm.id,
});
}
return c.json({ updatedArms: [] }, 200);
}
// Generate system prompt based on whether we have enough context
let systemPrompt: string;
if (hasEnoughLogsForContext) {
const exampleLogs = logs.slice(0, 5);
const examples = generateExampleConversations(exampleLogs);
// Get agent description for context
const agents = await userStorageConnector.getAgents(c, {
id: skill.agent_id,
});
if (agents.length > 0 && examples.length > 0) {
const agent = agents[0];
systemPrompt = await generateSeedSystemPromptWithContext(
c,
agent.description,
skill.description,
examples,
userStorageConnector,
);
} else {
// Fallback to no-context generation
systemPrompt = await generateSeedSystemPromptForSkill(
c,
skill,
userStorageConnector,
);
}
} else {
// Use no-context generation for initial setup
systemPrompt = await generateSeedSystemPromptForSkill(
c,
skill,
userStorageConnector,
);
}
// Build a map of existing arms by cluster_id -> list of arms (not just IDs)
const existingArmsByCluster = new Map<string, (typeof existingArms)[0][]>();
for (const arm of existingArms) {
if (!existingArmsByCluster.has(arm.cluster_id)) {
existingArmsByCluster.set(arm.cluster_id, []);
}
existingArmsByCluster.get(arm.cluster_id)!.push(arm);
}
// Process each cluster independently to ensure arms are named 1-n per cluster
const updatedArms: string[] = [];
const armsToCreate: SkillOptimizationArmCreateParams[] = [];
const matchedArmIds = new Set<string>();
for (const cluster of skillClusters) {
const availableArms = existingArmsByCluster.get(cluster.id) || [];
// Track used names in this cluster to avoid conflicts
const usedNames = new Set<string>();
// Track next available name counter for new arms
let nextNameCounter = 1;
for (const model of skillModels) {
for (const baseArm of BaseArmsParams) {
const armParams: SkillOptimizationArmParams = {
...baseArm,
model_id: model.id,
system_prompt: systemPrompt,
};
// Try to reuse an existing arm for this cluster
const existingArm = availableArms.shift();
if (existingArm) {
// Update existing arm in-place, keeping its original name
await userStorageConnector.updateSkillOptimizationArm(
c,
existingArm.id,
{
params: armParams,
},
);
// Delete arm stats to reset performance history
await userStorageConnector.deleteSkillOptimizationArmStats(c, {
arm_id: existingArm.id,
});
updatedArms.push(existingArm.id);
matchedArmIds.add(existingArm.id);
usedNames.add(existingArm.name);
} else {
// Find next available name that doesn't conflict with existing arms
while (usedNames.has(`${nextNameCounter}`)) {
nextNameCounter++;
}
const newName = `${nextNameCounter}`;
usedNames.add(newName);
nextNameCounter++;
// Need to create new arm
armsToCreate.push({
agent_id: skill.agent_id,
skill_id: skill.id,
cluster_id: cluster.id,
name: newName,
params: armParams,
});
}
}
}
}
// Create any new arms needed
if (armsToCreate.length > 0) {
const createdArms = await userStorageConnector.createSkillOptimizationArms(
c,
armsToCreate,
);
updatedArms.push(...createdArms.map((a) => a.id));
}
// Delete any orphaned arms that don't match expected structure
for (const arm of existingArms) {
if (!matchedArmIds.has(arm.id)) {
await userStorageConnector.deleteSkillOptimizationArmStats(c, {
arm_id: arm.id,
});
await userStorageConnector.deleteSkillOptimizationArm(c, arm.id);
}
}
return c.json({ updatedArms }, 200);
}
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