mirror of
https://github.com/danny-avila/LibreChat.git
synced 2026-08-04 14:57:42 +00:00
7e74f8eb8c
Unresolved {{LIBRECHAT_USER_*}} header templates leaked literally to
upstream providers when user context was missing at resolution time
(e.g. async title generation racing client disposal), letting a gateway
trust LibreChat's own template syntax as an account identity.
resolveHeaders now takes an opt-in stripUnresolved flag that blanks any
resolvable-but-unresolved LIBRECHAT_USER/BODY/OPENID placeholder, enabled
at every final resolution boundary (resolveConfigHeaders, model fetches,
Google init, summarization overrides, azureAssistants init). Staged
passes that resolve again later with more context are left untouched, as
is the async-resolved {{LIBRECHAT_GRAPH_ACCESS_TOKEN}} and unknown names.
titleConvo now resolves headers from the req captured at entry instead of
re-reading this.options.req, which disposeClient nulls concurrently.
Fixes #14580
3386 lines
136 KiB
JavaScript
3386 lines
136 KiB
JavaScript
require('events').EventEmitter.defaultMaxListeners = 100;
|
|
const { logger } = require('@librechat/data-schemas');
|
|
const { getBufferString, HumanMessage } = require('@librechat/agents/langchain/messages');
|
|
const {
|
|
createRun,
|
|
isEnabled,
|
|
checkAccess,
|
|
buildToolSet,
|
|
logToolError,
|
|
sanitizeTitle,
|
|
payloadParser,
|
|
createSafeUser,
|
|
initializeAgent,
|
|
resolveConfigHeaders,
|
|
countTokens,
|
|
getBalanceConfig,
|
|
omitTitleOptions,
|
|
getProviderConfig,
|
|
memoryInstructions,
|
|
createTokenCounter,
|
|
applyContextToAgent,
|
|
isMemoryAgentEnabled,
|
|
recordCollectedUsage,
|
|
sendEvent,
|
|
computeUsageCostUSD,
|
|
aggregateEmittedUsage,
|
|
resolveAgentTokenConfig,
|
|
buildPersistedContextUsage,
|
|
computeSummaryUsedTokens,
|
|
priorRunOutputTokens,
|
|
createSubagentUsageSink,
|
|
anyAgentReplaysReasoningContent,
|
|
GenerationJobManager,
|
|
getTransactionsConfig,
|
|
resolveRecursionLimit,
|
|
buildPendingAction,
|
|
toClientPendingAction,
|
|
computeAgentRequestFingerprint,
|
|
getRunDiscoveredTools,
|
|
captureResumeModelParameters,
|
|
pickResumeContext,
|
|
getApprovalTtlMs,
|
|
isHITLEnabled,
|
|
captureAgentCheckpointGeneration,
|
|
deleteAgentCheckpoint,
|
|
LIBRECHAT_CHECKPOINT_NAMESPACE_KEY,
|
|
agentRequestsAskUserQuestion,
|
|
attachAskUserQuestionArgs,
|
|
hydrateResumeRunSteps,
|
|
createContentIndexOffsetHandlers,
|
|
createSteerIndexOffsetHandlers,
|
|
createSteerDrainHook,
|
|
createSteerPreemptBoundaryHook,
|
|
createSteerPreemptPoll,
|
|
isSteeringSupported,
|
|
isSteerPreemptSupported,
|
|
buildSteerMedia,
|
|
stampSteerPartMedia,
|
|
createActivityLabelWiring,
|
|
resolveActivityConfig,
|
|
getCustomEndpointConfig,
|
|
mapCollectedMetadataToUsage,
|
|
resolveActivityLabelModel,
|
|
settlePendingLabelFills,
|
|
stripActivityLabelParts,
|
|
getRequestMemories,
|
|
getMemoryAgentId,
|
|
createMemoryProcessor,
|
|
agentHasInlineMemoryTools,
|
|
loadAgent: loadAgentFn,
|
|
createMultiAgentMapper,
|
|
filterMalformedContentParts,
|
|
countFormattedMessageTokens,
|
|
prependFileContext,
|
|
prependQuotes,
|
|
hydrateMissingIndexTokenCounts,
|
|
injectSkillPrimes,
|
|
collectFreshSkillPrimeNames,
|
|
isSkillPrimeMessage,
|
|
collectFileIds,
|
|
processTextWithTokenLimit,
|
|
buildAgentScopedContext,
|
|
buildSkillPrimeContentParts,
|
|
buildInitialToolSessions,
|
|
hasUrlContextTool,
|
|
hasYouTubeVideoParts,
|
|
appendYouTubeVideoParts,
|
|
resolveGoogleVideoError,
|
|
resolveYouTubeInjectionConfig,
|
|
decrementPendingRequest,
|
|
maybePrewarmCodeSandbox,
|
|
} = require('@librechat/api');
|
|
const {
|
|
Run,
|
|
Callback,
|
|
Providers,
|
|
TitleMethod,
|
|
formatMessage,
|
|
formatAgentMessages,
|
|
createMetadataAggregator,
|
|
} = require('@librechat/agents');
|
|
const {
|
|
Constants,
|
|
SteerEvents,
|
|
ActivityLabelEvents,
|
|
UsageEvents,
|
|
Permissions,
|
|
VisionModes,
|
|
ContentTypes,
|
|
ApprovalEvents,
|
|
EModelEndpoint,
|
|
PermissionTypes,
|
|
AgentCapabilities,
|
|
isAgentsEndpoint,
|
|
isEphemeralAgentId,
|
|
removeNullishValues,
|
|
DEFAULT_MEMORY_MAX_INPUT_TOKENS,
|
|
} = require('librechat-data-provider');
|
|
const { filterFilesByAgentAccess } = require('~/server/services/Files/permissions');
|
|
const { encodeAndFormat } = require('~/server/services/Files/images/encode');
|
|
const { createContextHandlers } = require('~/app/clients/prompts');
|
|
const { resolveConfigServers, getAccessibleMcpServerNames } = require('~/server/services/MCP');
|
|
const { getMCPServerTools } = require('~/server/services/Config');
|
|
const BaseClient = require('~/app/clients/BaseClient');
|
|
const { getMCPManager } = require('~/config');
|
|
const db = require('~/models');
|
|
|
|
const loadAgent = (params) => loadAgentFn(params, { getAgent: db.getAgent, getMCPServerTools });
|
|
|
|
const MEMORY_INPUT_CHARS_PER_TOKEN = 8;
|
|
|
|
class AgentClient extends BaseClient {
|
|
constructor(options = {}) {
|
|
super(null, options);
|
|
/** The current client class
|
|
* @type {string} */
|
|
this.clientName = EModelEndpoint.agents;
|
|
|
|
/** @deprecated @type {true} - Is a Chat Completion Request */
|
|
this.isChatCompletion = true;
|
|
/** @type {number | undefined} */
|
|
this.jobCreatedAt = options.jobCreatedAt;
|
|
/** Generation-scoped LangGraph checkpoint namespace. Legacy paused jobs
|
|
* intentionally use the historical empty namespace. @type {string} */
|
|
this.checkpointNamespace = options.checkpointNamespace ?? '';
|
|
|
|
/** @type {AgentRun} */
|
|
this.run;
|
|
|
|
/** Resolves with the agent run once `chatCompletion` initializes it (or
|
|
* `null` if initialization fails), letting immediate-mode title generation
|
|
* await the run instead of throwing when fired before the run exists.
|
|
* @type {Promise<AgentRun | null> | null} */
|
|
this._runReady = null;
|
|
/** @type {((run: AgentRun | null) => void) | null} */
|
|
this._resolveRun = null;
|
|
|
|
const {
|
|
agentConfigs,
|
|
contentParts,
|
|
stepMap,
|
|
collectedUsage,
|
|
collectedThoughtSignatures,
|
|
artifactPromises,
|
|
maxContextTokens,
|
|
subagentAggregatorsByToolCallId,
|
|
contextUsageSink,
|
|
usageEmitSink,
|
|
toolInputValidationErrors,
|
|
...clientOptions
|
|
} = options;
|
|
|
|
this.agentConfigs = agentConfigs;
|
|
this.maxContextTokens = maxContextTokens;
|
|
/** Latest visible context snapshot for this response, captured live by the
|
|
* ON_CONTEXT_USAGE handler; persisted on `metadata.contextUsage`.
|
|
* @type {{ latest: import('librechat-data-provider').TContextUsageEvent | null } | undefined} */
|
|
this.contextUsageSink = contextUsageSink;
|
|
/** Every emitted `on_token_usage` payload for this response (primary,
|
|
* summarization, sequential, and subagent); aggregated into the rollup
|
|
* persisted on `metadata.usage`.
|
|
* @type {Array<import('librechat-data-provider').TTokenUsageEvent> | undefined} */
|
|
this.usageEmitSink = usageEmitSink;
|
|
/** Schema-validation exceptions keyed by tool-call ID. The completion
|
|
* handler consumes these to distinguish execution failures from tool
|
|
* output that merely contains similar text.
|
|
* @type {Map<string, import('@librechat/api').ToolInputValidationError> | undefined} */
|
|
this.toolInputValidationErrors = toolInputValidationErrors;
|
|
/** @type {MessageContentComplex[]} */
|
|
this.contentParts = contentParts;
|
|
/** Original run-step identity used by the content aggregator to attach
|
|
* completion events to their rendered content indices.
|
|
* @type {Map<string, import('@librechat/agents').RunStep | undefined> | undefined} */
|
|
this.stepMap = stepMap;
|
|
/** @type {Array<UsageMetadata>} */
|
|
this.collectedUsage = collectedUsage;
|
|
/** Vertex Gemini 3 thought signatures captured during the run, keyed by
|
|
* `tool_call_id`. Persisted on `responseMessage.metadata.thoughtSignatures`
|
|
* and restored as `additional_kwargs.signatures` on subsequent turns to
|
|
* keep tool round-trips valid across DB reconstruction.
|
|
* @type {Record<string, string> | undefined} */
|
|
this.collectedThoughtSignatures = collectedThoughtSignatures;
|
|
/** @type {ArtifactPromises} */
|
|
this.artifactPromises = artifactPromises;
|
|
/** Per-request map of `createContentAggregator` instances keyed by
|
|
* the parent's `tool_call_id`. `ON_SUBAGENT_UPDATE` events stream
|
|
* into each aggregator as they arrive; `finalizeSubagentContent`
|
|
* harvests `contentParts` onto the matching `subagent` tool_call
|
|
* so the child's full activity survives a page refresh. */
|
|
this.subagentAggregatorsByToolCallId = subagentAggregatorsByToolCallId ?? new Map();
|
|
/** In-flight `on_token_usage` emits from subagent child runs. The sink
|
|
* fires the emitter without awaiting, so chatCompletion's finally flushes
|
|
* these before returning — otherwise job cleanup can race the persist.
|
|
* @type {Promise<void>[]} */
|
|
this.pendingSubagentEmits = [];
|
|
/** @type {AgentClientOptions} */
|
|
this.options = Object.assign({ endpoint: options.endpoint }, clientOptions);
|
|
/** @type {string} */
|
|
this.model = this.options.agent.model_parameters.model;
|
|
/** The key for the usage object's input tokens
|
|
* @type {string} */
|
|
this.inputTokensKey = 'input_tokens';
|
|
/** The key for the usage object's output tokens
|
|
* @type {string} */
|
|
this.outputTokensKey = 'output_tokens';
|
|
/** @type {UsageMetadata} */
|
|
this.usage;
|
|
/** @type {Record<string, number>} */
|
|
this.indexTokenCountMap = {};
|
|
/** @type {Array<Record<string, unknown>> | null} */
|
|
this.memoryPayload = null;
|
|
/** Mutable content-index shift shared with the steer offset handlers.
|
|
* Incremented each time a steer part is spliced into `contentParts`, so
|
|
* SDK-emitted indices that arrive after an injection land past it.
|
|
* @type {import('@librechat/api').SteerOffsetState} */
|
|
this.steerOffsetState = { offset: 0 };
|
|
/** @type {(messages: BaseMessage[]) => Promise<void>} */
|
|
this.processMemory;
|
|
}
|
|
|
|
/**
|
|
* Returns the aggregated content parts for the current run.
|
|
* @returns {MessageContentComplex[]} */
|
|
getContentParts() {
|
|
return this.contentParts;
|
|
}
|
|
|
|
/**
|
|
* Harvest the `contentParts` from each per-subagent `createContentAggregator`
|
|
* instance and attach them onto the matching parent `subagent` tool_call
|
|
* as `subagent_content`. Runs once per message save (from
|
|
* `sendCompletion`'s `finally`) so the child's full reasoning / tool
|
|
* calls / final text survive a page refresh — the client-side Recoil
|
|
* atom is session-only. Aggregators keyed by a tool_call_id that never
|
|
* appeared in `contentParts` are discarded (no home to attach to).
|
|
*/
|
|
finalizeSubagentContent() {
|
|
const buffer = this.subagentAggregatorsByToolCallId;
|
|
if (!buffer || buffer.size === 0 || !Array.isArray(this.contentParts)) {
|
|
return;
|
|
}
|
|
for (const part of this.contentParts) {
|
|
if (part?.type !== ContentTypes.TOOL_CALL) continue;
|
|
const toolCall = part[ContentTypes.TOOL_CALL];
|
|
if (!toolCall || toolCall.name !== Constants.SUBAGENT || !toolCall.id) continue;
|
|
const aggregator = buffer.get(toolCall.id);
|
|
if (!aggregator) continue;
|
|
try {
|
|
/** `createContentAggregator` returns a sparse array (undefined
|
|
* slots for indices that never received content). Strip those
|
|
* so the persisted shape is a clean `TMessageContentParts[]`. */
|
|
const parts = Array.isArray(aggregator.contentParts)
|
|
? aggregator.contentParts.filter((p) => p != null)
|
|
: [];
|
|
if (parts.length > 0) {
|
|
toolCall.subagent_content = parts;
|
|
}
|
|
} catch (err) {
|
|
logger.warn(
|
|
`[AgentClient] Failed to attach subagent content for tool_call ${toolCall.id}: ${err?.message ?? err}`,
|
|
);
|
|
}
|
|
}
|
|
buffer.clear();
|
|
}
|
|
|
|
/**
|
|
* Apply one drained steer to host state: append the steer content part at
|
|
* the live content index, bump the shared index offset so subsequent SDK
|
|
* step indices land past it, and emit `on_steer_applied` so the live client
|
|
* replaces its pending chip with the inline part (the emitted chunk also
|
|
* reaches the Redis chunk log for reconnect reconstruction).
|
|
*
|
|
* Runs BEFORE the drain hook's media encode so an abort during the encode
|
|
* cannot lose the steer. File refs persist from the queue item (sanitized at
|
|
* enqueue); replay/token accounting re-fetch owner-scoped and re-encode per
|
|
* turn (stampSteerPartMedia), so unauthorized ids drop out there.
|
|
*
|
|
* @param {string} streamId
|
|
* @param {import('@librechat/api').SteerQueueItem} item
|
|
*/
|
|
async applySteerPart(streamId, item) {
|
|
const index = this.contentParts.length;
|
|
const part = {
|
|
type: ContentTypes.STEER,
|
|
[ContentTypes.STEER]: item.text,
|
|
steerId: item.steerId,
|
|
...(item.clientSteerId && { clientSteerId: item.clientSteerId }),
|
|
createdAt: item.createdAt,
|
|
...(item.files?.length && { files: item.files }),
|
|
};
|
|
this.contentParts.push(part);
|
|
this.steerOffsetState.offset += 1;
|
|
// durable: the chunk-log XADD is this event's recovery record — it must
|
|
// commit before the publish or a cross-replica reconnect that missed the
|
|
// pub/sub delivery reconstructs content without the steer part.
|
|
try {
|
|
await GenerationJobManager.emitChunk(
|
|
streamId,
|
|
{
|
|
event: SteerEvents.ON_STEER_APPLIED,
|
|
data: {
|
|
steerId: item.steerId,
|
|
...(item.clientSteerId && { clientSteerId: item.clientSteerId }),
|
|
index,
|
|
part,
|
|
responseMessageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
},
|
|
},
|
|
{
|
|
durable: true,
|
|
expectedCreatedAt: this.jobCreatedAt,
|
|
deliveredSteer: item,
|
|
},
|
|
);
|
|
} catch (error) {
|
|
/** The part and its receipt commit as one durable unit. Roll the local
|
|
* projection back when that commit fails so the drain can restore the
|
|
* claimed item instead of injecting an instruction absent from replay. */
|
|
if (this.contentParts[index] === part) {
|
|
this.contentParts.splice(index, 1);
|
|
this.steerOffsetState.offset -= 1;
|
|
}
|
|
throw error;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* The `steering` fragment for `createRun`: the run-scoped PostToolBatch
|
|
* drain hook — plus, when the SDK can seal mid-stream, the PreemptBoundary
|
|
* twin and the preempt poll built from the SAME drain closures, so both
|
|
* boundaries inject byte-identical shapes. `undefined` when there is no
|
|
* resumable job surface or the installed SDK cannot inject hook messages
|
|
* (draining would drop them).
|
|
*
|
|
* @param {string | undefined} streamId
|
|
*/
|
|
buildSteerWiring(streamId) {
|
|
if (!streamId || !isSteeringSupported()) {
|
|
return undefined;
|
|
}
|
|
const drainOptions = {
|
|
streamId,
|
|
jobCreatedAt: this.jobCreatedAt,
|
|
applySteer: (item) => this.applySteerPart(streamId, item),
|
|
buildMedia: (item) =>
|
|
buildSteerMedia({
|
|
client: this,
|
|
user: this.options.req?.user,
|
|
item,
|
|
getFiles: db.getFiles,
|
|
}),
|
|
};
|
|
return {
|
|
hook: createSteerDrainHook(drainOptions),
|
|
...(isSteerPreemptSupported() && {
|
|
preemptHook: createSteerPreemptBoundaryHook(drainOptions),
|
|
preemption: createSteerPreemptPoll(streamId),
|
|
}),
|
|
};
|
|
}
|
|
|
|
setOptions(_options) {}
|
|
|
|
/**
|
|
* Resolve provider + client options for the
|
|
* tool-batch summary model. Same resolution path as titleConvo minus the
|
|
* title-specific branches. Model precedence: the endpoint's
|
|
* `activityModel` > its `titleModel` > the agent's own model, on the
|
|
* endpoint named by `activityEndpoint` (default: the agent's).
|
|
*/
|
|
async resolveActivityLabelLLM() {
|
|
/** Memoized per response: resolution reads provider config and can hit the
|
|
* database for user keys, and nothing it depends on changes between
|
|
* batches of the same run — so re-resolving on every batch (twice, with
|
|
* usage accounting) is repeated credential work for an identical result.
|
|
* The promise is cached rather than the value so concurrent batches share
|
|
* one in-flight resolution. */
|
|
this.activityLabelLLMPromise =
|
|
this.activityLabelLLMPromise ??
|
|
resolveActivityLabelModel({
|
|
req: this.options.req,
|
|
agent: this.options.agent,
|
|
/** Same public-endpoint-first field resolution as the wiring gate. */
|
|
publicEndpoint: this.options.endpoint,
|
|
ids: {
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
parentMessageId: this.parentMessageId,
|
|
},
|
|
db: { getUserKey: db.getUserKey, getUserKeyValues: db.getUserKeyValues },
|
|
}).catch((error) => {
|
|
/** Never cache a rejection: a transient credential read failure would
|
|
* otherwise disable labels for the rest of the response. */
|
|
this.activityLabelLLMPromise = null;
|
|
throw error;
|
|
});
|
|
return this.activityLabelLLMPromise;
|
|
}
|
|
|
|
/**
|
|
* Bills the label call and folds its usage into the response rollup with
|
|
* an `activity-label` tag (subagent precedent) so `metadata.usage` and the
|
|
* live cost gauge reflect it. Tagged, so it is not a PRIMARY usage event
|
|
* and cannot disturb the context-snapshot pairing in buildResponseMetadata.
|
|
*/
|
|
async recordActivityLabelUsage(
|
|
collectedMetadata,
|
|
model,
|
|
endpointTokenConfig,
|
|
sameEndpoint,
|
|
/** Optional suppression gate, defaulting open. The hook-driven paths
|
|
* deliberately pass nothing: they invoke accounting ONLY for a
|
|
* COMMITTED fill, and a committed (visible) label must bill even when
|
|
* its scope closed during the durable emit — the commit flag, not the
|
|
* scope, is the billing authority. */
|
|
scopeOpen = () => true,
|
|
/** The LABEL endpoint's provider — cost math needs it to know whether
|
|
* cache tokens are folded into `input_tokens` (additive providers like
|
|
* Bedrock keep them separate). */
|
|
provider = undefined,
|
|
/** Lazy `() => ({ promptText, completionText })` fallback. When the
|
|
* provider omits usage metadata entirely, labels bill by ESTIMATE —
|
|
* the title convention — from locally counted text rather than going
|
|
* unbilled. Invoked only when no entry carries a real token count. */
|
|
estimate = undefined,
|
|
) {
|
|
const appConfig = this.options.req?.config;
|
|
/** Provider ON EVERY ENTRY, not just the streamed event: `splitUsage`
|
|
* keys additive-vs-subset cache math on `usage.provider`, and an
|
|
* unknown provider takes the additive branch — for Anthropic/OpenAI
|
|
* (cache already inside `input_tokens`) that re-adds cache_read and
|
|
* cache_creation on top, double-charging the balance while the
|
|
* streamed cost (which carries the provider) disagrees. */
|
|
let collectedUsage = mapCollectedMetadataToUsage(collectedMetadata).map((usage) =>
|
|
provider != null ? { ...usage, provider } : usage,
|
|
);
|
|
const hasRealUsage = collectedUsage.some(
|
|
(usage) => usage.input_tokens != null || usage.output_tokens != null,
|
|
);
|
|
if (!hasRealUsage && typeof estimate === 'function') {
|
|
try {
|
|
const { promptText = '', completionText = '' } = estimate() ?? {};
|
|
const [input_tokens, output_tokens] = await Promise.all([
|
|
countTokens(promptText),
|
|
countTokens(completionText),
|
|
]);
|
|
collectedUsage = [
|
|
provider != null
|
|
? { input_tokens, output_tokens, provider }
|
|
: { input_tokens, output_tokens },
|
|
];
|
|
} catch (err) {
|
|
logger.warn(
|
|
`[AgentClient] Failed to estimate activity-label usage: ${err?.message ?? err}`,
|
|
);
|
|
}
|
|
}
|
|
if (
|
|
collectedUsage.length === 0 ||
|
|
!collectedUsage.some((usage) => usage.input_tokens != null || usage.output_tokens != null)
|
|
) {
|
|
return;
|
|
}
|
|
if (!scopeOpen()) {
|
|
return;
|
|
}
|
|
const streamId = this.options.req?._resumableStreamId || null;
|
|
const includeCost = this.options.req?.config?.interfaceConfig?.contextCost === true;
|
|
/** Cross-endpoint labels (`activityEndpoint`) price with THEIR endpoint's
|
|
* rates. `undefined` is a MEANINGFUL result for a built-in label endpoint
|
|
* (built-ins price from the shared table, not a per-endpoint map), so it
|
|
* must not fall through to the agent's custom rates — a custom primary
|
|
* pointing `activityEndpoint` at a built-in would bill the label at its
|
|
* own rates. Only inherit when the label actually runs on the agent's
|
|
* endpoint. */
|
|
const labelTokenConfig = sameEndpoint
|
|
? (endpointTokenConfig ?? this.options.endpointTokenConfig)
|
|
: endpointTokenConfig;
|
|
for (const usage of collectedUsage) {
|
|
/** `seq` is normally a position in `collectedUsage` (each emitter
|
|
* pushes, then emits with the new length). Label usage is billed
|
|
* separately and never appended there, so it has no position: any
|
|
* positive value eventually collides with a real one, and the client
|
|
* dedupes on `runId:seq`. Labels therefore occupy a NEGATIVE seq
|
|
* namespace that positional sequences can never reach. The key is
|
|
* only used for Set membership, so the sign is inert. */
|
|
this.activityLabelUsageSeq = (this.activityLabelUsageSeq ?? 0) + 1;
|
|
const data = {
|
|
input_tokens: usage.input_tokens,
|
|
output_tokens: usage.output_tokens,
|
|
/** Cache tokens ride along (subagent-event shape) so display and
|
|
* aggregation price cached label calls at cache rates. */
|
|
...(usage.input_token_details != null && {
|
|
input_token_details: usage.input_token_details,
|
|
}),
|
|
...(provider != null && { provider }),
|
|
model,
|
|
usage_type: 'activity-label',
|
|
/**
|
|
* Scoped to the GENERATION, not just the response. Editing one
|
|
* assistant response reuses its `responseMessageId` while each fresh
|
|
* server generation restarts `activityLabelUsageSeq`, so a second
|
|
* edit re-emitted `<responseId>:-1` and the client — which dedupes on
|
|
* exactly `runId:seq` — discarded the newer usage even though its
|
|
* balance transaction was still written. `jobCreatedAt` is the run's
|
|
* own epoch: stable across reconnects and HITL resumes of one
|
|
* generation, distinct between generations.
|
|
*/
|
|
runId:
|
|
this.jobCreatedAt != null
|
|
? `${this.responseMessageId}:${this.jobCreatedAt}`
|
|
: this.responseMessageId,
|
|
seq: -this.activityLabelUsageSeq,
|
|
/** Cost coverage is all-or-nothing in `aggregateEmittedUsage`: an
|
|
* event without `cost` suppresses the whole response's cost when
|
|
* `interface.contextCost` is on. */
|
|
cost: includeCost
|
|
? computeUsageCostUSD(
|
|
{ ...usage, model, provider },
|
|
{ getMultiplier: db.getMultiplier, getCacheMultiplier: db.getCacheMultiplier },
|
|
labelTokenConfig,
|
|
)
|
|
: undefined,
|
|
};
|
|
/** Fold into the response rollup synchronously, then stream it like
|
|
* primary/subagent usage so the live session gauge stays honest.
|
|
* Retained and flushed with the subagent emits so job cleanup cannot
|
|
* race the persist. */
|
|
this.usageEmitSink?.push(data);
|
|
if (streamId) {
|
|
const emit = GenerationJobManager.emitChunk(
|
|
streamId,
|
|
{
|
|
event: UsageEvents.ON_TOKEN_USAGE,
|
|
data,
|
|
},
|
|
/** Same epoch scoping as the label event: this usage is recorded
|
|
* from a detached generation and must not bill against whichever
|
|
* generation replaced it. */
|
|
{ expectedCreatedAt: this.jobCreatedAt },
|
|
).catch((err) => {
|
|
logger.warn(`[AgentClient] Failed to emit activity-label usage: ${err?.message ?? err}`);
|
|
});
|
|
this.pendingSubagentEmits.push(emit);
|
|
}
|
|
}
|
|
await this.recordCollectedUsage({
|
|
collectedUsage,
|
|
context: 'activity-label',
|
|
model,
|
|
endpointTokenConfig: labelTokenConfig,
|
|
/** The label ran elsewhere, so its config governs even when undefined. */
|
|
crossEndpoint: sameEndpoint === false,
|
|
balance: getBalanceConfig(appConfig),
|
|
transactions: getTransactionsConfig(appConfig),
|
|
messageId: this.responseMessageId,
|
|
/** Billed, but NOT the response's stream usage — see the parameter. */
|
|
updateStreamUsage: false,
|
|
}).catch((err) => {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #recordActivityLabelUsage] Error recording usage',
|
|
err,
|
|
);
|
|
});
|
|
}
|
|
|
|
/**
|
|
* Bridges label generation to the SDK's `run.generateActivityLabel()` so
|
|
* the fast-model call is Langfuse-traced under the conversation's session
|
|
* (thread_id) with its own tags — never as an orphan trace. Returns null
|
|
* when the label could not be generated.
|
|
*/
|
|
async generateActivityLabelViaRun({
|
|
entries,
|
|
context,
|
|
previousLabels,
|
|
traceSeed,
|
|
signal,
|
|
charLimit,
|
|
prompt,
|
|
executingAgentId,
|
|
deferUsage,
|
|
}) {
|
|
/** Version gating happens at wiring time via the `sdkCapable` prototype
|
|
* probe, so this only catches a run that is missing or not yet built.
|
|
* Resolve `undefined` (not `null`) so the hook reads it as "this path
|
|
* cannot serve the request" and falls back to the direct model call;
|
|
* `null` would mean "ran, produced no label" and would leave the slot
|
|
* permanently empty. */
|
|
if (typeof this.run?.generateActivityLabel !== 'function') {
|
|
return undefined;
|
|
}
|
|
const { provider, clientOptions, endpointTokenConfig, sameEndpoint } =
|
|
await this.resolveActivityLabelLLM();
|
|
const { handleLLMEnd, collected: collectedMetadata } = createMetadataAggregator();
|
|
/**
|
|
* NO scope gate here: the hook invokes this ONLY for a COMMITTED fill,
|
|
* and the commit flag is the single billing authority. A scope that
|
|
* closes while the fill's durable emit is in flight does not un-commit
|
|
* the label — it is persisted and visible — so gating on the scope here
|
|
* turned that race into a completed provider call escaping both the
|
|
* label charge and the primary abort accounting. The reverse direction
|
|
* (billed but never shown) is enforced by the commit gate itself: a
|
|
* dropped fill never reaches this callback.
|
|
*/
|
|
/**
|
|
* The PROMPT THE SDK ACTUALLY SENT, captured at chain start. The hook's
|
|
* estimate thunk carries this module's locally built prompt — same
|
|
* entries and instruction but different framing — so estimated billing
|
|
* on this path would count a prompt that was never sent. When capture
|
|
* succeeded, it replaces the thunk's promptText.
|
|
*/
|
|
let sdkPromptText;
|
|
const capturePrompt = {
|
|
handleLLMStart: (_llm, prompts) => {
|
|
sdkPromptText = Array.isArray(prompts) ? prompts.join('\n') : undefined;
|
|
},
|
|
handleChatModelStart: (_llm, messages) => {
|
|
try {
|
|
sdkPromptText = (messages ?? [])
|
|
.flat()
|
|
.map((message) =>
|
|
typeof message?.content === 'string'
|
|
? message.content
|
|
: JSON.stringify(message?.content ?? ''),
|
|
)
|
|
.join('\n');
|
|
} catch {
|
|
/** Estimation falls back to the local approximation. */
|
|
}
|
|
},
|
|
};
|
|
const recordUsage = async (estimate) => {
|
|
const refined =
|
|
typeof estimate === 'function'
|
|
? () => {
|
|
const base = estimate() ?? {};
|
|
return sdkPromptText != null && sdkPromptText.length > 0
|
|
? { ...base, promptText: sdkPromptText }
|
|
: base;
|
|
}
|
|
: estimate;
|
|
await this.recordActivityLabelUsage(
|
|
collectedMetadata,
|
|
clientOptions.model,
|
|
endpointTokenConfig,
|
|
sameEndpoint,
|
|
undefined,
|
|
provider,
|
|
refined,
|
|
);
|
|
};
|
|
/**
|
|
* Accounting is DEFERRED to the hook, which runs it only after the slot
|
|
* commit settles. Awaiting it here (pre-fill) let the settlement window
|
|
* expire during the balance write: the charge landed, then the fill was
|
|
* dropped as out-of-scope — billed, never shown. Registered before the
|
|
* call so a mid-call throw still bills whatever metadata the provider
|
|
* returned, exactly like the old `finally` did.
|
|
*/
|
|
let usageDeferred = false;
|
|
if (typeof deferUsage === 'function') {
|
|
usageDeferred = true;
|
|
deferUsage(recordUsage);
|
|
}
|
|
try {
|
|
const { label } = await this.run.generateActivityLabel({
|
|
provider,
|
|
clientOptions,
|
|
entries: entries.map(({ toolName, toolInput, toolOutput, error, status }) => ({
|
|
toolName,
|
|
toolInput,
|
|
toolOutput,
|
|
error,
|
|
status,
|
|
})),
|
|
thinkingExcerpts: context.thinkingExcerpts,
|
|
lastAssistantText: context.lastAssistantText,
|
|
...(previousLabels != null && { previousLabels }),
|
|
traceSeed,
|
|
charLimit,
|
|
/** Selects the EXECUTING agent's Langfuse metadata and, more
|
|
* importantly, its tool-output redaction policy. Omitting it lets a
|
|
* handoff's activity be traced and redacted under the default
|
|
* agent's configuration, bypassing a stricter per-agent policy. */
|
|
...(executingAgentId != null && { agentId: executingAgentId }),
|
|
/** The wiring always supplies one (the yaml `activityPrompt` when
|
|
* set, else this repo's instruction). Falling through to the SDK's
|
|
* built-in prompt would silently use a different register. */
|
|
...((prompt ?? this.activityLabelPrompt) != null && {
|
|
prompt: prompt ?? this.activityLabelPrompt,
|
|
}),
|
|
chainOptions: {
|
|
signal,
|
|
callbacks: [{ handleLLMEnd, ...capturePrompt }],
|
|
configurable: {
|
|
thread_id: this.conversationId,
|
|
user_id: this.user ?? this.options.req?.user?.id,
|
|
},
|
|
},
|
|
});
|
|
return label ?? null;
|
|
} finally {
|
|
/** Safety net for a caller that did not defer (none in-tree): the old
|
|
* inline accounting, still scope-gated. */
|
|
if (!usageDeferred) {
|
|
await recordUsage();
|
|
}
|
|
}
|
|
}
|
|
|
|
/** Bounded settle for in-flight label fills before finalization. On
|
|
* timeout the label scope is closed and its abort controller fired, so a
|
|
* straggler cannot mutate the saved response or emit into a dead job. */
|
|
async settleActivityLabels(timeoutMs = 3000) {
|
|
/** Detached even when nothing settled: the wiring attaches its abort
|
|
* listener at BUILD time, and a segment can end without a single claim
|
|
* (text-only, or handoff batches, which skip labels) — the early
|
|
* return below would otherwise leave that listener accumulating across
|
|
* HITL approval cycles on the shared job signal. Idempotent. */
|
|
const detachScopeListeners = () => {
|
|
for (const scope of this.activityLabelScopes ?? []) {
|
|
scope.detach?.();
|
|
}
|
|
};
|
|
const pending = this.pendingActivityLabelFills;
|
|
if (!pending || pending.length === 0) {
|
|
detachScopeListeners();
|
|
return;
|
|
}
|
|
this.pendingActivityLabelFills = [];
|
|
await settlePendingLabelFills(pending, timeoutMs, () => {
|
|
/** Close EVERY generation's scope: a pre-pause wiring's straggler must
|
|
* stay closed even though a resume built a newer one. */
|
|
for (const scope of this.activityLabelScopes ?? []) {
|
|
scope.closed = true;
|
|
scope.abort.abort();
|
|
}
|
|
});
|
|
detachScopeListeners();
|
|
}
|
|
|
|
/**
|
|
* Activity-label wiring. At each batch boundary the hook synchronously
|
|
* claims a live content slot (steering's index-offset pattern: push
|
|
* placeholder with deterministic counts, bump the shared offset so
|
|
* subsequent SDK indices land past it) and fills it when the fast-model
|
|
* label resolves. Both states reach the live client via the dedicated
|
|
* `on_activity_label` event; failures leave the counts-only part.
|
|
* @param {string | undefined} streamId
|
|
*/
|
|
buildActivityLabelWiring(streamId, abortSignal) {
|
|
if (!streamId) {
|
|
return undefined;
|
|
}
|
|
/** Per-endpoint opt-in via `activityLabel: true` in librechat.yaml,
|
|
* resolved the same way the title options are (endpoints.all > named
|
|
* endpoint > custom endpoint config). Custom endpoints live in the
|
|
* `endpoints.custom` ARRAY, so their settings are only visible through
|
|
* the matched entry — without it every custom endpoint reads as
|
|
* disabled. */
|
|
const agentEndpoint = this.options.agent?.endpoint ?? '';
|
|
const appConfigForActivity = this.options.req?.config;
|
|
let customEndpointConfig;
|
|
try {
|
|
customEndpointConfig = getCustomEndpointConfig({
|
|
endpoint: agentEndpoint,
|
|
appConfig: appConfigForActivity,
|
|
});
|
|
} catch {
|
|
customEndpointConfig = undefined;
|
|
}
|
|
const activityConfig = resolveActivityConfig(
|
|
appConfigForActivity,
|
|
agentEndpoint,
|
|
customEndpointConfig,
|
|
/** The PUBLIC endpoint (`agents`): `initializeAgent` rewrites
|
|
* `agent.endpoint` to the backing provider, so without this an
|
|
* admin's `endpoints.agents.activityLabel: true` reads the
|
|
* provider's block instead and the feature stays off. */
|
|
this.options.endpoint,
|
|
);
|
|
if (!activityConfig.enabled) {
|
|
return undefined;
|
|
}
|
|
this.activityLabelPrompt = activityConfig.prompt;
|
|
/**
|
|
* Mark the job so a resume can reconcile label gaps without probing
|
|
* content. Retried rather than fire-and-forget: this flag GATES that
|
|
* reconciliation, and it is a separate write from the durable label
|
|
* append — so a single lost write silently drops a label that the label
|
|
* content itself recorded perfectly well. One retry costs nothing at run
|
|
* setup and removes the only realistic way the gate goes stale.
|
|
*/
|
|
/** Retained (not fire-and-forget): the RUN START awaits this persist
|
|
* (chatCompletion/resumeCompletion, before processStream/resume), so
|
|
* the flag is durable before any batch can claim a label — closing the
|
|
* immediate-reconnect race WITHOUT delaying the claim-time reservation
|
|
* emit, whose ordering against shifted SDK indices is load-bearing.
|
|
* The chain settles on failure (warned retry), so a lost write can
|
|
* never wedge run startup. */
|
|
this.activityLabelsMarkedPromise = GenerationJobManager.markActivityLabels(
|
|
streamId,
|
|
this.jobCreatedAt,
|
|
).catch(() =>
|
|
GenerationJobManager.markActivityLabels(streamId, this.jobCreatedAt).catch(() => {
|
|
logger.warn(
|
|
`[AgentClient] Could not flag activity labels for ${streamId}; a label resolving during a resume gap may not be reconciled.`,
|
|
);
|
|
}),
|
|
);
|
|
/** SDK support probe (steering-style): the Run method and the formatter
|
|
* replay skip ship together, so method presence is the capability. */
|
|
const sdkCapable = typeof Run?.prototype?.generateActivityLabel === 'function';
|
|
/** Label-scoped abort: fired when settle times out so a straggling
|
|
* generation stops burning provider time for a finalized response.
|
|
* Chained to the run signal so a user abort still cancels labels. */
|
|
/** Close state is PER WIRING, not per client: a HITL resume rebuilds the
|
|
* wiring, and resetting a shared instance flag would re-open closures
|
|
* from the pre-pause segment whose provider call ignored the abort.
|
|
* Scopes are retained so settle closes every generation, past included. */
|
|
const labelScope = { closed: false, abort: new AbortController() };
|
|
this.activityLabelScopes = this.activityLabelScopes ?? [];
|
|
this.activityLabelScopes.push(labelScope);
|
|
/** Seed the usage sequence past the labels already on this response.
|
|
* `runId` is the response message id, so a HITL resume — which builds a
|
|
* NEW client for the SAME response — would otherwise restart at -1 and
|
|
* the client's `runId:seq` deduper would discard the post-approval
|
|
* label's usage as already counted. Each label generation is a single
|
|
* non-streaming invoke, so one existing label part == one consumed seq. */
|
|
this.activityLabelUsageSeq =
|
|
this.activityLabelUsageSeq ??
|
|
(this.contentParts ?? []).filter((part) => part?.type === ContentTypes.ACTIVITY_LABEL).length;
|
|
this.activityLabelAbort = labelScope.abort;
|
|
/** An abort CLOSES the scope, not just cancels the call. The rejected
|
|
* generation still runs its catch and calls `fill(null)`; with the scope
|
|
* merely aborted that fill would emit — and by then the next generation
|
|
* may already own the stream, so the event would land an index from the
|
|
* abandoned response onto the new one. */
|
|
const closeOnAbort = () => {
|
|
labelScope.closed = true;
|
|
labelScope.abort.abort();
|
|
};
|
|
if (abortSignal != null) {
|
|
if (abortSignal.aborted) {
|
|
closeOnAbort();
|
|
} else {
|
|
abortSignal.addEventListener('abort', closeOnAbort, { once: true });
|
|
/** Detached once this segment settles: HITL runs rebuild a wiring
|
|
* per approval cycle on the SAME job signal, and `once` only
|
|
* removes the listener if an abort actually fires — long
|
|
* multi-approval runs would otherwise accumulate obsolete
|
|
* closures toward the listener-limit warning. */
|
|
labelScope.detach = () => abortSignal.removeEventListener('abort', closeOnAbort);
|
|
}
|
|
}
|
|
/** Thin wrapper: slot claiming, lane stamping, emit ordering, and settle
|
|
* tracking live in `createActivityLabelWiring` (packages/api, TS). */
|
|
return createActivityLabelWiring({
|
|
maxPerRun: activityConfig.maxPerRun,
|
|
charLimit: activityConfig.charLimit,
|
|
prompt: activityConfig.prompt,
|
|
abortSignal: labelScope.abort.signal,
|
|
isClosed: () => labelScope.closed,
|
|
getContentParts: () => this.contentParts,
|
|
bumpIndexOffset: () => {
|
|
this.steerOffsetState.offset += 1;
|
|
},
|
|
/** Emits IMMEDIATELY — never sequenced behind the flag persist. The
|
|
* claim has already bumped the shared index offset, so delaying the
|
|
* reservation while shifted SDK chunks persist would let a
|
|
* cross-instance reconnect reconstruct a hole, compact it, and have
|
|
* the late label event overwrite the part that moved into its index.
|
|
* Flag ordering is guaranteed upstream instead: run start awaits the
|
|
* persist, so the flag is durable before any batch can claim. */
|
|
emitLabelEvent: (index, part) =>
|
|
GenerationJobManager.emitChunk(
|
|
streamId,
|
|
{
|
|
event: ActivityLabelEvents.ON_ACTIVITY_LABEL,
|
|
data: {
|
|
index,
|
|
part,
|
|
responseMessageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
},
|
|
},
|
|
/** Label generation is detached and can outlive its generation, so
|
|
* the emit is scoped to the epoch that claimed the index. Without
|
|
* it a straggler from a replaced generation lands its old index on
|
|
* the new response — invisibly, since an empty label renders
|
|
* nothing — overwriting whatever occupies that slot. */
|
|
{ durable: true, expectedCreatedAt: this.jobCreatedAt },
|
|
),
|
|
trackPendingFill: (fillDone) => {
|
|
this.pendingActivityLabelFills = this.pendingActivityLabelFills ?? [];
|
|
this.pendingActivityLabelFills.push(fillDone);
|
|
},
|
|
resolveLLM: () => this.resolveActivityLabelLLM(),
|
|
/** Per-generation usage accounting for the direct fallback path;
|
|
* the SDK bridge records its own via chainOptions callbacks. */
|
|
getInvokeCallbacks: () => {
|
|
const { handleLLMEnd, collected } = createMetadataAggregator();
|
|
return {
|
|
callbacks: [{ handleLLMEnd }],
|
|
collect: async (estimate) => {
|
|
const { provider, clientOptions, endpointTokenConfig, sameEndpoint } =
|
|
await this.resolveActivityLabelLLM();
|
|
await this.recordActivityLabelUsage(
|
|
collected,
|
|
clientOptions.model,
|
|
endpointTokenConfig,
|
|
sameEndpoint,
|
|
/** No scope gate — the hook invokes collect ONLY for a
|
|
* COMMITTED fill (the billing authority), and a scope that
|
|
* closes during the fill's durable emit must not let a
|
|
* visible label escape its charge. Dropped fills never
|
|
* reach this callback. */
|
|
undefined,
|
|
provider,
|
|
estimate,
|
|
);
|
|
},
|
|
};
|
|
},
|
|
...(sdkCapable && {
|
|
generateLabel: (payload) => this.generateActivityLabelViaRun(payload),
|
|
}),
|
|
});
|
|
}
|
|
|
|
/**
|
|
* `AgentClient` is not opinionated about vision requests, so we don't do anything here
|
|
* @param {MongoFile[]} attachments
|
|
*/
|
|
checkVisionRequest() {}
|
|
|
|
getSaveOptions() {
|
|
let runOptions = {};
|
|
try {
|
|
runOptions = payloadParser(this.options) ?? {};
|
|
} catch (error) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #getSaveOptions] Error parsing options',
|
|
error,
|
|
);
|
|
}
|
|
|
|
return removeNullishValues(
|
|
Object.assign(
|
|
{
|
|
spec: this.options.spec,
|
|
iconURL: this.options.iconURL,
|
|
chatProjectId: this.options.chatProjectId,
|
|
endpoint: this.options.endpoint,
|
|
agent_id: this.options.agent.id,
|
|
modelLabel: this.options.modelLabel,
|
|
resendFiles: this.options.resendFiles,
|
|
imageDetail: this.options.imageDetail,
|
|
maxContextTokens: this.maxContextTokens,
|
|
},
|
|
// TODO: PARSE OPTIONS BY PROVIDER, MAY CONTAIN SENSITIVE DATA
|
|
runOptions,
|
|
),
|
|
);
|
|
}
|
|
|
|
/**
|
|
* Returns build message options. For AgentClient, agent-specific instructions
|
|
* are retrieved directly from agent objects in buildMessages, so this returns empty.
|
|
* @returns {Object} Empty options object
|
|
*/
|
|
getBuildMessagesOptions() {
|
|
return {};
|
|
}
|
|
|
|
/**
|
|
*
|
|
* @param {TMessage} message
|
|
* @param {Array<MongoFile>} attachments
|
|
* @returns {Promise<Array<Partial<MongoFile>>>}
|
|
*/
|
|
async addImageURLs(message, attachments) {
|
|
const { files, image_urls } = await encodeAndFormat(
|
|
this.options.req,
|
|
attachments,
|
|
{
|
|
provider: this.options.agent.provider,
|
|
endpoint: this.options.endpoint,
|
|
},
|
|
VisionModes.agents,
|
|
);
|
|
message.image_urls = image_urls.length ? image_urls : undefined;
|
|
return files;
|
|
}
|
|
|
|
async buildMessages(messages, parentMessageId, _buildOptions, opts) {
|
|
/** Always pass mapMethod; getMessagesForConversation applies it only to messages with addedConvo flag */
|
|
const orderedMessages = this.constructor.getMessagesForConversation({
|
|
messages,
|
|
parentMessageId,
|
|
summary: this.shouldSummarize,
|
|
mapMethod: createMultiAgentMapper(this.options.agent, this.agentConfigs),
|
|
mapCondition: (message) => message.addedConvo === true,
|
|
});
|
|
|
|
let payload;
|
|
/** @type {number | undefined} */
|
|
let promptTokens;
|
|
|
|
/** Normalize instruction fields before applying per-run context. */
|
|
const normalizeInstructions = (agent) => {
|
|
agent.instructions = agent.instructions?.trim() || undefined;
|
|
agent.additional_instructions = agent.additional_instructions?.trim() || undefined;
|
|
return agent;
|
|
};
|
|
|
|
/** Collect all agents for unified processing while preserving stable/dynamic instruction fields. */
|
|
const allAgents = [
|
|
{ agent: normalizeInstructions(this.options.agent), agentId: this.options.agent.id },
|
|
...(this.agentConfigs?.size > 0
|
|
? Array.from(this.agentConfigs.entries()).map(([agentId, agent]) => ({
|
|
agent: normalizeInstructions(agent),
|
|
agentId,
|
|
}))
|
|
: []),
|
|
];
|
|
|
|
/**
|
|
* Memory authorization/loading and MCP config resolution do not depend on
|
|
* attachment hydration or prompt formatting. Start them before that work,
|
|
* but keep the existing context-application barrier below.
|
|
*
|
|
* Attach a rejection observer immediately because these operations may
|
|
* settle while request attachments are still being prepared. Awaiting the
|
|
* original promise later still propagates either error.
|
|
*/
|
|
const earlySharedContextPromise = Promise.all([
|
|
this.useMemory(),
|
|
resolveConfigServers(this.options.req),
|
|
]);
|
|
void earlySharedContextPromise.catch(() => {});
|
|
|
|
const sharedRunAttachmentIds = new Set();
|
|
/** @type {ReturnType<typeof buildAgentScopedContext>} */
|
|
let agentScopedContextPromise;
|
|
const startAgentScopedContext = () => {
|
|
const contextPromise = buildAgentScopedContext({
|
|
agentIds: allAgents.map(({ agentId }) => agentId),
|
|
attachmentsByAgentId: this.options.agentContextAttachmentsByAgentId,
|
|
sharedRunAttachmentIds,
|
|
req: this.options.req,
|
|
tokenCountFn: (text) => countTokens(text),
|
|
});
|
|
void contextPromise.catch(() => {});
|
|
return contextPromise;
|
|
};
|
|
|
|
if (this.options.attachments) {
|
|
const attachments = await this.options.attachments;
|
|
const latestMessage = orderedMessages[orderedMessages.length - 1];
|
|
|
|
for (const fileId of collectFileIds(attachments)) {
|
|
sharedRunAttachmentIds.add(fileId);
|
|
}
|
|
|
|
/** Agent-scoped extraction only depends on the shared attachment IDs. */
|
|
agentScopedContextPromise = startAgentScopedContext();
|
|
|
|
if (this.message_file_map) {
|
|
this.message_file_map[latestMessage.messageId] = attachments;
|
|
} else {
|
|
this.message_file_map = {
|
|
[latestMessage.messageId]: attachments,
|
|
};
|
|
}
|
|
|
|
const [, files] = await Promise.all([
|
|
this.addFileContextToMessage(latestMessage, attachments),
|
|
this.processAttachments(latestMessage, attachments),
|
|
]);
|
|
|
|
this.options.attachments = files;
|
|
} else {
|
|
agentScopedContextPromise = startAgentScopedContext();
|
|
}
|
|
|
|
/** Note: Bedrock uses legacy RAG API handling */
|
|
if (this.message_file_map && !isAgentsEndpoint(this.options.endpoint)) {
|
|
this.contextHandlers = createContextHandlers(
|
|
this.options.req,
|
|
orderedMessages[orderedMessages.length - 1].text,
|
|
);
|
|
}
|
|
|
|
/** @type {Record<number, number>} */
|
|
const indexTokenCountMap = {};
|
|
/** @type {Record<string, number>} */
|
|
const tokenCountMap = {};
|
|
const memoryPayload = [];
|
|
let hasFileContext = false;
|
|
let promptTokenTotal = 0;
|
|
const encoding = this.getEncoding();
|
|
const formattedMessages = orderedMessages.map((message, i) => {
|
|
const formattedMessage = formatMessage({
|
|
message,
|
|
userName: this.options?.name,
|
|
assistantName: this.options?.modelLabel,
|
|
});
|
|
const memoryFormattedMessage = formatMessage({
|
|
message,
|
|
userName: this.options?.name,
|
|
assistantName: this.options?.modelLabel,
|
|
});
|
|
|
|
/**
|
|
* Bind file context to the message it belongs to. Historical attachments
|
|
* are resent inline, so the current turn's text attachment must be inline
|
|
* too instead of living only in the dynamic system tail.
|
|
*/
|
|
if (message.fileContext) {
|
|
hasFileContext = true;
|
|
prependFileContext(formattedMessage, message.fileContext);
|
|
}
|
|
|
|
/**
|
|
* Durably re-merge quoted excerpts into every user turn that carries them
|
|
* (current and historical) so the model receives the referenced context on
|
|
* every prompt and the token count matches what was persisted. Applied to
|
|
* the memory copy too so the canonical per-message count includes them.
|
|
*/
|
|
if (Array.isArray(message.quotes) && message.quotes.length > 0) {
|
|
prependQuotes(formattedMessage, message.quotes);
|
|
prependQuotes(memoryFormattedMessage, message.quotes);
|
|
}
|
|
|
|
memoryPayload.push(memoryFormattedMessage);
|
|
|
|
const dbTokenCount = Number(orderedMessages[i].tokenCount);
|
|
const hasDbTokenCount = Number.isFinite(dbTokenCount) && dbTokenCount > 0;
|
|
/**
|
|
* Force a recount when the message carries quotes: a plain text-only
|
|
* "Save" edit recomputes `tokenCount` from `text` alone while leaving
|
|
* `message.quotes` persisted, so the stored count would undercount the
|
|
* quote block this turn prepends. Recounting from the quote-merged memory
|
|
* copy keeps context accounting accurate (and self-heals stale counts).
|
|
*/
|
|
const needsCanonicalTokenCount =
|
|
!hasDbTokenCount ||
|
|
(this.isVisionModel && (message.image_urls || message.files)) ||
|
|
(Array.isArray(message.quotes) && message.quotes.length > 0);
|
|
|
|
let canonicalTokenCount = hasDbTokenCount ? dbTokenCount : 0;
|
|
if (needsCanonicalTokenCount) {
|
|
canonicalTokenCount = countFormattedMessageTokens(memoryFormattedMessage, encoding);
|
|
}
|
|
|
|
const promptMessageTokenCount = message.fileContext
|
|
? countFormattedMessageTokens(formattedMessage, encoding)
|
|
: canonicalTokenCount;
|
|
|
|
/* If message has files, calculate image token cost */
|
|
if (this.message_file_map && this.message_file_map[message.messageId]) {
|
|
const attachments = this.message_file_map[message.messageId];
|
|
for (const file of attachments) {
|
|
if (file.embedded) {
|
|
this.contextHandlers?.processFile(file);
|
|
continue;
|
|
}
|
|
if (file.metadata?.codeEnvRef) {
|
|
continue;
|
|
}
|
|
}
|
|
}
|
|
|
|
const normalizedCanonicalTokenCount =
|
|
Number.isFinite(canonicalTokenCount) && canonicalTokenCount > 0 ? canonicalTokenCount : 0;
|
|
const normalizedPromptTokenCount =
|
|
Number.isFinite(promptMessageTokenCount) && promptMessageTokenCount > 0
|
|
? promptMessageTokenCount
|
|
: 0;
|
|
|
|
orderedMessages[i].tokenCount = normalizedCanonicalTokenCount;
|
|
indexTokenCountMap[i] = normalizedPromptTokenCount;
|
|
promptTokenTotal += normalizedPromptTokenCount;
|
|
|
|
if (message.messageId) {
|
|
tokenCountMap[message.messageId] = normalizedCanonicalTokenCount;
|
|
}
|
|
|
|
if (isEnabled(process.env.AGENT_DEBUG_LOGGING)) {
|
|
const role = message.isCreatedByUser ? 'user' : 'assistant';
|
|
const hasSummary =
|
|
Array.isArray(message.content) && message.content.some((p) => p && p.type === 'summary');
|
|
const suffix = hasSummary ? '[S]' : '';
|
|
const id = (message.messageId ?? message.id ?? '').slice(-8);
|
|
const recalced = needsCanonicalTokenCount ? normalizedCanonicalTokenCount : null;
|
|
const promptRecalced = message.fileContext ? normalizedPromptTokenCount : null;
|
|
logger.debug(
|
|
`[AgentClient] msg[${i}] ${role}${suffix} id=…${id} db=${dbTokenCount} needsRecount=${needsCanonicalTokenCount} recalced=${recalced} promptRecalced=${promptRecalced} tokens=${normalizedPromptTokenCount}`,
|
|
);
|
|
}
|
|
|
|
return formattedMessage;
|
|
});
|
|
|
|
/**
|
|
* Native YouTube -> video understanding: when Google `url_context` is enabled
|
|
* (resolved to the native `urlContext` provider tool), inject any YouTube URLs
|
|
* from the latest user turn as Gemini `fileData` video parts. The URL Context
|
|
* tool cannot read YouTube, so this routes those links through the video path
|
|
* while other URLs still flow through `urlContext`. Done after token counting
|
|
* (video tokens are reported by the provider) and only on the LLM payload, so
|
|
* the memory copy and persisted message are untouched.
|
|
*/
|
|
const latestOrdered = orderedMessages[orderedMessages.length - 1];
|
|
const provider = this.options.agent?.provider;
|
|
if (
|
|
latestOrdered?.isCreatedByUser === true &&
|
|
(provider === Providers.GOOGLE || provider === Providers.VERTEXAI) &&
|
|
hasUrlContextTool(this.options.agent?.tools)
|
|
) {
|
|
const latestFormatted = formattedMessages[formattedMessages.length - 1];
|
|
/** Use the resolved run model (model_parameters override) rather than the saved base model. */
|
|
const resolvedModel =
|
|
this.options.agent?.model_parameters?.model ?? this.options.agent?.model;
|
|
const { max, mimeType } = resolveYouTubeInjectionConfig({
|
|
provider,
|
|
model: resolvedModel,
|
|
});
|
|
latestFormatted.content = appendYouTubeVideoParts({
|
|
enabled: true,
|
|
text: latestOrdered.text,
|
|
content: latestFormatted.content,
|
|
max,
|
|
mimeType,
|
|
});
|
|
/** Google rejects an unusable video with a generic `INVALID_ARGUMENT` that names no cause,
|
|
* so `#sendCompletion` can only attribute one by knowing this turn carried a video. */
|
|
this.injectedYouTubeVideo = hasYouTubeVideoParts(latestFormatted.content);
|
|
}
|
|
|
|
payload = formattedMessages;
|
|
if (this.options.resendFiles) {
|
|
/** Persisted steer parts of past turns replay with their attachments:
|
|
* one batched owner-scoped fetch, re-encoded per turn and stamped as a
|
|
* transient `media` array (same resend semantics as message files).
|
|
* The stamp lands after the loop above finalized its counts, so the
|
|
* re-encoded media (minus the text part the steer part already counted)
|
|
* is folded into the budget here — large steered attachments must
|
|
* shrink the window like any other resent media. */
|
|
const stamped = await stampSteerPartMedia({
|
|
client: this,
|
|
user: this.options.req?.user,
|
|
payload,
|
|
// addPreviousAttachments already fetched steer-part refs in its single
|
|
// per-turn historical-files query — no second round trip.
|
|
docsById: this.authorizedHistoricalFiles,
|
|
getFiles: db.getFiles,
|
|
});
|
|
for (const { index, media, steerText } of stamped) {
|
|
/** Count the FULL stamped content and subtract only the steer body
|
|
* (already counted inside the assistant message): extracted file
|
|
* context prepended into the text part must hit the budget too, or
|
|
* large steered documents bypass pruning. */
|
|
const fullTokens = countFormattedMessageTokens({ role: 'user', content: media }, encoding);
|
|
const bodyTokens = steerText
|
|
? countFormattedMessageTokens(
|
|
{ role: 'user', content: [{ type: ContentTypes.TEXT, text: steerText }] },
|
|
encoding,
|
|
)
|
|
: 0;
|
|
const mediaTokens = Math.max(0, (fullTokens ?? 0) - (bodyTokens ?? 0));
|
|
if (Number.isFinite(mediaTokens) && mediaTokens > 0) {
|
|
indexTokenCountMap[index] = (indexTokenCountMap[index] ?? 0) + mediaTokens;
|
|
promptTokenTotal += mediaTokens;
|
|
}
|
|
}
|
|
}
|
|
this.memoryPayload = hasFileContext ? memoryPayload : null;
|
|
messages = orderedMessages;
|
|
promptTokens = promptTokenTotal;
|
|
|
|
/**
|
|
* Build shared run context - applies to ALL agents in the run.
|
|
* Request attachment file context is already bound inline to the latest
|
|
* user message above; only side-channel context belongs here.
|
|
* Memory context is handled separately and applied per-agent based on config.
|
|
*/
|
|
const sharedRunContextParts = [];
|
|
const [augmentedPrompt, [memories, configServers], agentScopedContext] = await Promise.all([
|
|
this.contextHandlers?.createContext(),
|
|
earlySharedContextPromise,
|
|
agentScopedContextPromise,
|
|
]);
|
|
|
|
/** Augmented prompt from RAG/context handlers */
|
|
this.augmentedPrompt = augmentedPrompt;
|
|
if (this.augmentedPrompt) {
|
|
sharedRunContextParts.push(this.augmentedPrompt);
|
|
}
|
|
|
|
/** Memory context (user preferences/memories). Keyed context (with memory
|
|
* keys + token metadata) is reserved for agents that can call
|
|
* `delete_memory`; everyone else gets the unkeyed values only. */
|
|
/** Partition the loaded memories belong to (the primary agent's). */
|
|
const loadedMemoryAgentId = getMemoryAgentId(this.options.agent);
|
|
const buildMemoryContext = (text) =>
|
|
text ? `${memoryInstructions}\n\n# Existing memory about the user:\n${text}` : undefined;
|
|
/** Resolves formatted memories for an agent's own partition. A defined
|
|
* `memories` means the run-level gates (permission, opt-out, config)
|
|
* passed; agents on other partitions fetch through the request-scoped
|
|
* cache so repeated partitions share one query. */
|
|
const getAgentPartitionMemories = async (agent) => {
|
|
if (!memories) {
|
|
return undefined;
|
|
}
|
|
const agentPartition = getMemoryAgentId(agent);
|
|
if (agentPartition === loadedMemoryAgentId) {
|
|
return memories;
|
|
}
|
|
try {
|
|
return await getRequestMemories({
|
|
req: this.options.req,
|
|
userId: this.options.req.user.id + '',
|
|
agentId: agentPartition,
|
|
getFormattedMemories: db.getFormattedMemories,
|
|
});
|
|
} catch (error) {
|
|
logger.error('[AgentClient] Error loading partition memories', error);
|
|
return undefined;
|
|
}
|
|
};
|
|
|
|
const sharedRunContext = sharedRunContextParts.join('\n\n');
|
|
const memoryAgentEnabled = isMemoryAgentEnabled(this.options.req.config?.memory);
|
|
|
|
/** Preserve prompt token counts for graph formatting and pruning. */
|
|
this.indexTokenCountMap = indexTokenCountMap;
|
|
|
|
/** Extract contextMeta from the parent response (second-to-last in ordered chain;
|
|
* last is the current user message). Seeds the pruner's calibration EMA for this run. */
|
|
const parentResponse =
|
|
orderedMessages.length >= 2 ? orderedMessages[orderedMessages.length - 2] : undefined;
|
|
if (parentResponse?.contextMeta && !parentResponse.isCreatedByUser) {
|
|
this.contextMeta = parentResponse.contextMeta;
|
|
}
|
|
|
|
const result = {
|
|
prompt: payload,
|
|
tokenCountMap,
|
|
promptTokens,
|
|
messages,
|
|
};
|
|
|
|
if (promptTokens >= 0 && typeof opts?.getReqData === 'function') {
|
|
opts.getReqData({ promptTokens });
|
|
}
|
|
|
|
/**
|
|
* Apply context to all agents.
|
|
* Stable agent/MCP instructions stay on `instructions`; shared runtime context
|
|
* is appended to `additional_instructions` as the dynamic system tail.
|
|
*
|
|
* NOTE: This intentionally mutates agent objects in place. The agentConfigs Map
|
|
* holds references to config objects that will be passed to the graph runtime.
|
|
*/
|
|
const ephemeralAgent = this.options.req.body.ephemeralAgent;
|
|
const mcpManager = getMCPManager();
|
|
|
|
await Promise.all(
|
|
allAgents.map(async ({ agent, agentId }) => {
|
|
const agentRunContextParts = [sharedRunContext];
|
|
const agentHasMemory = agentHasInlineMemoryTools(agent);
|
|
if (agentId === this.options.agent.id || memoryAgentEnabled || agentHasMemory) {
|
|
const partitionMemories = await getAgentPartitionMemories(agent);
|
|
const agentMemoryContext = buildMemoryContext(
|
|
agentHasMemory ? partitionMemories?.withKeys : partitionMemories?.withoutKeys,
|
|
);
|
|
if (agentMemoryContext) {
|
|
agentRunContextParts.push(agentMemoryContext);
|
|
}
|
|
}
|
|
const scopedContext = agentScopedContext.get(agentId);
|
|
if (scopedContext) {
|
|
agentRunContextParts.push(scopedContext);
|
|
}
|
|
|
|
return applyContextToAgent({
|
|
agent,
|
|
agentId,
|
|
logger,
|
|
mcpManager,
|
|
configServers,
|
|
sharedRunContext: agentRunContextParts.filter(Boolean).join('\n\n'),
|
|
ephemeralAgent: agentId === this.options.agent.id ? ephemeralAgent : undefined,
|
|
});
|
|
}),
|
|
);
|
|
|
|
return result;
|
|
}
|
|
|
|
/**
|
|
* Creates a promise that resolves with the memory promise result or undefined after a timeout
|
|
* @param {Promise<(TAttachment | null)[] | undefined>} memoryPromise - The memory promise to await
|
|
* @param {number} timeoutMs - Timeout in milliseconds (default: 3000)
|
|
* @returns {Promise<(TAttachment | null)[] | undefined>}
|
|
*/
|
|
async awaitMemoryWithTimeout(memoryPromise, timeoutMs = 3000) {
|
|
if (!memoryPromise) {
|
|
return;
|
|
}
|
|
|
|
try {
|
|
const timeoutPromise = new Promise((_, reject) =>
|
|
setTimeout(() => reject(new Error('Memory processing timeout')), timeoutMs),
|
|
);
|
|
|
|
const attachments = await Promise.race([memoryPromise, timeoutPromise]);
|
|
return attachments;
|
|
} catch (error) {
|
|
if (error.message === 'Memory processing timeout') {
|
|
logger.warn('[AgentClient] Memory processing timed out after 3 seconds');
|
|
} else {
|
|
logger.error('[AgentClient] Error processing memory:', error);
|
|
}
|
|
return;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* @returns {Promise<{ withKeys?: string; withoutKeys?: string } | undefined>}
|
|
*/
|
|
async useMemory() {
|
|
const user = this.options.req.user;
|
|
if (user.personalization?.memories === false) {
|
|
return;
|
|
}
|
|
const hasAccess = await checkAccess({
|
|
user,
|
|
permissionType: PermissionTypes.MEMORIES,
|
|
permissions: [Permissions.USE],
|
|
getRoleByName: db.getRoleByName,
|
|
});
|
|
|
|
if (!hasAccess) {
|
|
logger.debug(
|
|
`[api/server/controllers/agents/client.js #useMemory] User ${user.id} does not have USE permission for memories`,
|
|
);
|
|
return;
|
|
}
|
|
const appConfig = this.options.req.config;
|
|
const memoryConfig = appConfig.memory;
|
|
if (!memoryConfig || memoryConfig.disabled === true) {
|
|
return;
|
|
}
|
|
|
|
const userId = this.options.req.user.id + '';
|
|
/** Memory partition of the primary agent; undefined = shared personal pool */
|
|
const memoryAgentId = getMemoryAgentId(this.options.agent);
|
|
this.processMemory = undefined;
|
|
|
|
if (!isMemoryAgentEnabled(memoryConfig)) {
|
|
try {
|
|
const { withKeys, withoutKeys } = await getRequestMemories({
|
|
req: this.options.req,
|
|
userId,
|
|
agentId: memoryAgentId,
|
|
getFormattedMemories: db.getFormattedMemories,
|
|
});
|
|
return { withKeys, withoutKeys };
|
|
} catch (error) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #useMemory] Error loading memories',
|
|
error,
|
|
);
|
|
return;
|
|
}
|
|
}
|
|
|
|
/** @type {Agent} */
|
|
let prelimAgent;
|
|
const allowedProviders = new Set(
|
|
appConfig?.endpoints?.[EModelEndpoint.agents]?.allowedProviders,
|
|
);
|
|
try {
|
|
if (memoryConfig.agent?.id != null && memoryConfig.agent.id !== this.options.agent.id) {
|
|
prelimAgent = await loadAgent({
|
|
req: this.options.req,
|
|
agent_id: memoryConfig.agent.id,
|
|
endpoint: EModelEndpoint.agents,
|
|
});
|
|
} else if (memoryConfig.agent?.id != null) {
|
|
prelimAgent = this.options.agent;
|
|
} else if (
|
|
memoryConfig.agent?.id == null &&
|
|
memoryConfig.agent?.model != null &&
|
|
memoryConfig.agent?.provider != null
|
|
) {
|
|
prelimAgent = { id: Constants.EPHEMERAL_AGENT_ID, ...memoryConfig.agent };
|
|
}
|
|
} catch (error) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #useMemory] Error loading agent for memory',
|
|
error,
|
|
);
|
|
}
|
|
|
|
if (!prelimAgent) {
|
|
return;
|
|
}
|
|
|
|
/** Forward the same `execute_code` capability gate the chat flow uses —
|
|
* memory agents are unlikely to list `execute_code`, but if one does,
|
|
* Phase 8 relies on this flag to expand the string into
|
|
* `bash_tool` + `read_file` (pre-Phase 8 the legacy `execute_code`
|
|
* tool registered unconditionally; without this passthrough the
|
|
* memory path would silently lose code-execution tooling). */
|
|
const memoryCapabilities = new Set(appConfig?.endpoints?.[EModelEndpoint.agents]?.capabilities);
|
|
const agent = await initializeAgent(
|
|
{
|
|
req: this.options.req,
|
|
res: this.options.res,
|
|
agent: prelimAgent,
|
|
allowedProviders,
|
|
endpointOption: {
|
|
endpoint: !isEphemeralAgentId(prelimAgent.id)
|
|
? EModelEndpoint.agents
|
|
: memoryConfig.agent?.provider,
|
|
},
|
|
codeEnvAvailable: memoryCapabilities.has(AgentCapabilities.execute_code),
|
|
statefulSessionsAvailable: memoryCapabilities.has(AgentCapabilities.stateful_code_sessions),
|
|
},
|
|
{
|
|
getFiles: db.getFiles,
|
|
getUserKey: db.getUserKey,
|
|
getConvoFiles: db.getConvoFiles,
|
|
getAccessibleMcpServerNames,
|
|
updateFilesUsage: db.updateFilesUsage,
|
|
getUserKeyValues: db.getUserKeyValues,
|
|
getToolFilesByIds: db.getToolFilesByIds,
|
|
getCodeGeneratedFiles: db.getCodeGeneratedFiles,
|
|
filterFilesByAgentAccess,
|
|
},
|
|
);
|
|
|
|
if (!agent) {
|
|
logger.warn(
|
|
'[api/server/controllers/agents/client.js #useMemory] No agent found for memory',
|
|
memoryConfig,
|
|
);
|
|
return;
|
|
}
|
|
|
|
const llmConfig = Object.assign(
|
|
{
|
|
provider: agent.provider,
|
|
model: agent.model,
|
|
},
|
|
agent.model_parameters,
|
|
);
|
|
|
|
/** @type {import('@librechat/api').MemoryConfig} */
|
|
const config = {
|
|
validKeys: memoryConfig.validKeys,
|
|
instructions: agent.instructions,
|
|
llmConfig,
|
|
tokenLimit: memoryConfig.tokenLimit,
|
|
};
|
|
|
|
const messageId = this.responseMessageId + '';
|
|
const conversationId = this.conversationId + '';
|
|
const streamId = this.options.req?._resumableStreamId || null;
|
|
const [withoutKeys, processMemory] = await createMemoryProcessor({
|
|
userId,
|
|
agentId: memoryAgentId,
|
|
config,
|
|
messageId,
|
|
streamId,
|
|
jobCreatedAt: this.jobCreatedAt,
|
|
conversationId,
|
|
memoryMethods: {
|
|
setMemory: db.setMemory,
|
|
deleteMemory: db.deleteMemory,
|
|
getFormattedMemories: db.getFormattedMemories,
|
|
},
|
|
res: this.options.res,
|
|
user: createSafeUser(this.options.req.user),
|
|
});
|
|
|
|
this.processMemory = processMemory;
|
|
let withKeys = withoutKeys;
|
|
try {
|
|
({ withKeys } = await getRequestMemories({
|
|
req: this.options.req,
|
|
userId,
|
|
agentId: memoryAgentId,
|
|
getFormattedMemories: db.getFormattedMemories,
|
|
}));
|
|
} catch (error) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #useMemory] Error loading keyed memories',
|
|
error,
|
|
);
|
|
}
|
|
return { withKeys, withoutKeys };
|
|
}
|
|
|
|
/**
|
|
* Filters out image URLs from message content
|
|
* @param {BaseMessage} message - The message to filter
|
|
* @returns {BaseMessage} - A new message with image URLs removed
|
|
*/
|
|
filterImageUrls(message) {
|
|
if (!message.content || typeof message.content === 'string') {
|
|
return message;
|
|
}
|
|
|
|
if (Array.isArray(message.content)) {
|
|
const filteredContent = message.content.filter(
|
|
(part) => part.type !== ContentTypes.IMAGE_URL,
|
|
);
|
|
|
|
if (filteredContent.length === 1 && filteredContent[0].type === ContentTypes.TEXT) {
|
|
const MessageClass = message.constructor;
|
|
return new MessageClass({
|
|
content: filteredContent[0].text,
|
|
additional_kwargs: message.additional_kwargs,
|
|
});
|
|
}
|
|
|
|
const MessageClass = message.constructor;
|
|
return new MessageClass({
|
|
content: filteredContent,
|
|
additional_kwargs: message.additional_kwargs,
|
|
});
|
|
}
|
|
|
|
return message;
|
|
}
|
|
|
|
/**
|
|
* @param {BaseMessage[]} messages
|
|
* @returns {Promise<void | (TAttachment | null)[]>}
|
|
*/
|
|
async runMemory(messages) {
|
|
try {
|
|
if (this.processMemory == null) {
|
|
return;
|
|
}
|
|
const appConfig = this.options.req.config;
|
|
const memoryConfig = appConfig.memory;
|
|
const messageWindowSize = memoryConfig?.messageWindowSize ?? 5;
|
|
|
|
/**
|
|
* Strip skill-primed meta messages before memory extraction. The primes
|
|
* sit next to the latest user message and carry large SKILL.md bodies,
|
|
* so letting them into the window would crowd out real chat turns and
|
|
* pollute extracted memories with synthetic instruction content the
|
|
* user never typed.
|
|
*/
|
|
const chatMessages = messages.filter((m) => !isSkillPrimeMessage(m));
|
|
|
|
let messagesToProcess = [...chatMessages];
|
|
if (chatMessages.length > messageWindowSize) {
|
|
for (let i = chatMessages.length - messageWindowSize; i >= 0; i--) {
|
|
const potentialWindow = chatMessages.slice(i, i + messageWindowSize);
|
|
if (potentialWindow[0]?.role === 'user') {
|
|
messagesToProcess = [...potentialWindow];
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (messagesToProcess.length === chatMessages.length) {
|
|
messagesToProcess = [...chatMessages.slice(-messageWindowSize)];
|
|
}
|
|
}
|
|
|
|
const filteredMessages = messagesToProcess.map((msg) => this.filterImageUrls(msg));
|
|
const bufferString = getBufferString(filteredMessages);
|
|
const configuredMaxInputTokens = Number.isFinite(memoryConfig?.maxInputTokens)
|
|
? Math.floor(memoryConfig.maxInputTokens)
|
|
: undefined;
|
|
const maxInputTokens =
|
|
configuredMaxInputTokens != null && configuredMaxInputTokens > 0
|
|
? configuredMaxInputTokens
|
|
: DEFAULT_MEMORY_MAX_INPUT_TOKENS;
|
|
const maxInputChars = maxInputTokens * MEMORY_INPUT_CHARS_PER_TOKEN;
|
|
const isCharTruncated = bufferString.length > maxInputChars;
|
|
const memoryInput = `# Current Chat:\n\n${
|
|
isCharTruncated
|
|
? `[Earlier chat content omitted due to memory input limit]\n\n${bufferString.slice(
|
|
-maxInputChars,
|
|
)}`
|
|
: bufferString
|
|
}`;
|
|
const {
|
|
text: limitedMemoryInput,
|
|
tokenCount,
|
|
wasTruncated,
|
|
} = await processTextWithTokenLimit({
|
|
text: memoryInput,
|
|
tokenLimit: maxInputTokens,
|
|
tokenCountFn: (text) => countTokens(text),
|
|
preserve: 'end',
|
|
});
|
|
if (isCharTruncated || wasTruncated) {
|
|
logger.warn('[MemoryAgent] Memory input truncated before processing', {
|
|
tokenCount,
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
maxInputTokens,
|
|
wasTruncated,
|
|
maxInputChars,
|
|
originalLength: bufferString.length,
|
|
});
|
|
}
|
|
const bufferMessage = new HumanMessage(limitedMemoryInput);
|
|
return await this.processMemory([bufferMessage]);
|
|
} catch (error) {
|
|
logger.error('Memory Agent failed to process memory', error);
|
|
}
|
|
}
|
|
|
|
/** @type {sendCompletion} */
|
|
async sendCompletion(payload, opts = {}) {
|
|
await this.chatCompletion({
|
|
payload,
|
|
onProgress: opts.onProgress,
|
|
userMCPAuthMap: opts.userMCPAuthMap,
|
|
abortController: opts.abortController,
|
|
});
|
|
|
|
const completion = filterMalformedContentParts(this.contentParts);
|
|
const metadata = this.buildResponseMetadata();
|
|
return metadata ? { completion, metadata } : { completion };
|
|
}
|
|
|
|
/**
|
|
* Assembles the response message `metadata`: Vertex thought signatures plus
|
|
* the persisted context breakdown (Part A) and the usage/cost rollup (Part B),
|
|
* which rebuild the gauge breakdown and branch/total cost across reloads.
|
|
* Returns undefined when nothing was captured.
|
|
* @returns {{
|
|
* thoughtSignatures?: Record<string, string>,
|
|
* contextUsage?: import('librechat-data-provider').TContextUsageEvent,
|
|
* usage?: import('librechat-data-provider').TResponseUsage,
|
|
* } | undefined}
|
|
*/
|
|
buildResponseMetadata() {
|
|
/** @type {{
|
|
* thoughtSignatures?: Record<string, string>,
|
|
* contextUsage?: import('librechat-data-provider').TContextUsageEvent,
|
|
* usage?: import('librechat-data-provider').TResponseUsage,
|
|
* }} */
|
|
const metadata = {};
|
|
const signatures = this.collectedThoughtSignatures;
|
|
if (signatures && Object.keys(signatures).length > 0) {
|
|
metadata.thoughtSignatures = signatures;
|
|
}
|
|
const usageEvents = this.usageEmitSink ?? [];
|
|
/** Persist the breakdown only when the latest snapshot's OWN run completed —
|
|
* i.e. a PRIMARY usage event (usage_type == null) from that run's id arrived
|
|
* AFTER the snapshot. Matching by run id keeps `completedOutputTokens` a real
|
|
* post-snapshot delta even when parallel/direct runs interleave (A snapshot →
|
|
* B snapshot → A usage must NOT persist B's snapshot with A's output); an
|
|
* interrupted final call that emits no usage falls back to the per-message
|
|
* estimate. It still keeps the post-summary snapshot: the summarization detour
|
|
* emits an extra snapshot whose following primary usage shares that run's id,
|
|
* which the old snapshot-count guard miscounted and wrongly dropped. Events
|
|
* without a run id (older lib / resume) match any snapshot for back-compat. */
|
|
const latestSnapshot = this.contextUsageSink?.latest;
|
|
const latestSnapshotUsageIndex = this.contextUsageSink?.latestUsageIndex ?? 0;
|
|
const latestSnapshotRunId = latestSnapshot?.runId;
|
|
const hasPrimaryAfterSnapshot = usageEvents
|
|
.slice(latestSnapshotUsageIndex)
|
|
.some(
|
|
(event) =>
|
|
event.usage_type == null &&
|
|
(latestSnapshotRunId == null ||
|
|
event.runId == null ||
|
|
event.runId === latestSnapshotRunId),
|
|
);
|
|
if (latestSnapshot && hasPrimaryAfterSnapshot) {
|
|
metadata.contextUsage = buildPersistedContextUsage(latestSnapshot, usageEvents);
|
|
}
|
|
/** Lightweight summarization marker — persisted whenever this turn compacted
|
|
* the context, INDEPENDENT of the snapshot guard above. When the client has
|
|
* no usable snapshot on the branch and falls back to the per-message
|
|
* estimate, it caps the discarded pre-summary history at this baseline
|
|
* instead of re-summing it (the gauge otherwise reads 100% forever). Shared
|
|
* with the abort save path via `computeSummaryUsedTokens`. Subtract the
|
|
* response's earlier tool-loop outputs (the primaries that preceded the
|
|
* latest snapshot, same run): those tokens are inside the snapshot baseline
|
|
* AND in the response `tokenCount` the client estimate adds on top, so
|
|
* leaving them in the marker double-counts them on a multi-call turn. */
|
|
const priorOutputTokens = priorRunOutputTokens(
|
|
usageEvents,
|
|
latestSnapshotUsageIndex,
|
|
latestSnapshotRunId,
|
|
);
|
|
const summaryUsedTokens = computeSummaryUsedTokens(latestSnapshot, priorOutputTokens);
|
|
if (summaryUsedTokens != null) {
|
|
metadata.summaryUsedTokens = summaryUsedTokens;
|
|
}
|
|
const usage = aggregateEmittedUsage(usageEvents);
|
|
if (usage) {
|
|
metadata.usage = usage;
|
|
}
|
|
return Object.keys(metadata).length > 0 ? metadata : undefined;
|
|
}
|
|
|
|
/**
|
|
* Resolves the endpoint token config for a usage item by its producing agent
|
|
* (multi-endpoint graphs: connected agents + subagents). A known agent's
|
|
* config is authoritative — including `undefined`, which prices with built-in
|
|
* rates (e.g. a non-custom agent in a custom-primary graph). Only an
|
|
* untagged/unknown agent falls back to the primary config, so single-endpoint
|
|
* graphs are unchanged.
|
|
* @param {UsageMetadata} usage
|
|
* @returns {import('@librechat/api').EndpointTokenConfig | undefined}
|
|
*/
|
|
resolveAgentEndpointTokenConfig(usage) {
|
|
return resolveAgentTokenConfig({
|
|
agentId: usage?.agentId,
|
|
byAgentId: this.options.endpointTokenConfigByAgentId,
|
|
fallback: this.options.endpointTokenConfig,
|
|
});
|
|
}
|
|
|
|
/**
|
|
* @param {Object} params
|
|
* @param {string} [params.model]
|
|
* @param {string} [params.context='message']
|
|
* @param {AppConfig['balance']} [params.balance]
|
|
* @param {AppConfig['transactions']} [params.transactions]
|
|
* @param {UsageMetadata[]} [params.collectedUsage=this.collectedUsage]
|
|
*/
|
|
async recordCollectedUsage({
|
|
model,
|
|
balance,
|
|
transactions,
|
|
context = 'message',
|
|
collectedUsage = this.collectedUsage,
|
|
/**
|
|
* Rates for usage that did NOT run on the agent's endpoint — currently
|
|
* activity labels pointed at a different `activityEndpoint`. Without it
|
|
* the caller's config was dropped here and the balance transaction was
|
|
* written at the primary agent's rates while the UI cost was computed at
|
|
* the label's, so the two disagreed. `undefined` keeps the agent default.
|
|
*/
|
|
endpointTokenConfig,
|
|
/**
|
|
* True when this usage ran on a DIFFERENT endpoint than the agent, making
|
|
* `endpointTokenConfig` authoritative even when it is `undefined` (a
|
|
* built-in endpoint prices from the shared table). Presence of the value
|
|
* cannot express that, which is why the caller states it outright.
|
|
*/
|
|
crossEndpoint = false,
|
|
/**
|
|
* Whether this recording owns `getStreamUsage()`. Only the PRIMARY
|
|
* generation does. Secondary usage (activity labels) must still be
|
|
* billed, but writing it here would hand `BaseClient` the label's token
|
|
* counts as the assistant response's authoritative total — and because
|
|
* the primary call returns early when it collected nothing, the wrong
|
|
* value would never be replaced, suppressing the text-based token
|
|
* fallback and leaving the real generation unbilled.
|
|
*/
|
|
updateStreamUsage = true,
|
|
}) {
|
|
/** Per-agent resolution keys off the AGENT's config map, which cannot
|
|
* describe a label running on a different endpoint — so an explicit
|
|
* config wins outright rather than being second-guessed per usage row.
|
|
*
|
|
* Keyed on the caller's discriminator, NOT on `endpointTokenConfig !==
|
|
* undefined`: a built-in label endpoint prices from the shared table, so
|
|
* `undefined` is its meaningful value. Reading that as "no override" is
|
|
* what silently restored the primary's custom rates. */
|
|
const overrideTokenConfig = crossEndpoint === true;
|
|
const result = await recordCollectedUsage(
|
|
{
|
|
spendTokens: db.spendTokens,
|
|
spendStructuredTokens: db.spendStructuredTokens,
|
|
pricing: { getMultiplier: db.getMultiplier, getCacheMultiplier: db.getCacheMultiplier },
|
|
bulkWriteOps: { insertMany: db.bulkInsertTransactions, updateBalance: db.updateBalance },
|
|
},
|
|
{
|
|
user: this.user ?? this.options.req.user?.id,
|
|
conversationId: this.conversationId,
|
|
collectedUsage,
|
|
model: model ?? this.model ?? this.options.agent.model_parameters.model,
|
|
context,
|
|
messageId: this.responseMessageId,
|
|
balance,
|
|
transactions,
|
|
endpointTokenConfig: overrideTokenConfig
|
|
? endpointTokenConfig
|
|
: this.options.endpointTokenConfig,
|
|
...(overrideTokenConfig
|
|
? {}
|
|
: { resolveEndpointTokenConfig: (usage) => this.resolveAgentEndpointTokenConfig(usage) }),
|
|
},
|
|
);
|
|
|
|
if (result && updateStreamUsage) {
|
|
this.usage = result;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Get stream usage as returned by this client's API response.
|
|
* @returns {UsageMetadata} The stream usage object.
|
|
*/
|
|
getStreamUsage() {
|
|
return this.usage;
|
|
}
|
|
|
|
/**
|
|
* Builds the subagent usage emitter for {@link createSubagentUsageSink}.
|
|
* Streams each billed child-run usage to the client as an `on_token_usage`
|
|
* event tagged `subagent` (folds into session cost/totals, not the live
|
|
* gauge), with the authoritative cost when `interface.contextCost` is on.
|
|
* Returns undefined when there's no stream to write to.
|
|
* @param {AppConfig} [appConfig]
|
|
* @returns {((usage: UsageMetadata) => void) | undefined}
|
|
*/
|
|
buildSubagentUsageEmitter(appConfig) {
|
|
const res = this.options.res;
|
|
const streamId = this.options.req?._resumableStreamId || null;
|
|
if (!res && !streamId) {
|
|
return undefined;
|
|
}
|
|
const includeCost = appConfig?.interfaceConfig?.contextCost === true;
|
|
return (usage) => {
|
|
const data = {
|
|
input_tokens: usage.input_tokens,
|
|
output_tokens: usage.output_tokens,
|
|
total_tokens: usage.total_tokens,
|
|
input_token_details: this.subagentCacheDetails(usage),
|
|
model: usage.model,
|
|
provider: usage.provider,
|
|
usage_type: 'subagent',
|
|
runId: this.responseMessageId,
|
|
/** Unique per collected entry (post-push length) for resume dedupe */
|
|
seq: this.collectedUsage.length,
|
|
/** Price with the SUBAGENT's own endpoint token config (its endpoint may
|
|
* differ from the parent's); `usage.agentId` is tagged by the sink. */
|
|
cost: includeCost
|
|
? computeUsageCostUSD(
|
|
usage,
|
|
{ getMultiplier: db.getMultiplier, getCacheMultiplier: db.getCacheMultiplier },
|
|
this.resolveAgentEndpointTokenConfig(usage),
|
|
)
|
|
: undefined,
|
|
};
|
|
/** Fold into the response's usage rollup (synchronously, regardless of
|
|
* emit success) so the persisted total matches the live session, which
|
|
* also folds subagent usage into its cost/totals. */
|
|
if (this.usageEmitSink) {
|
|
this.usageEmitSink.push(data);
|
|
}
|
|
/** The sink fires this without awaiting, so retain the promise and flush
|
|
* it in chatCompletion's finally — emitChunk persists (HSET) before
|
|
* publishing, and job cleanup must not race that persist or resumed
|
|
* clients miss billed subagent usage. */
|
|
const emit = (async () => {
|
|
try {
|
|
if (streamId) {
|
|
await GenerationJobManager.emitChunk(
|
|
streamId,
|
|
{
|
|
event: UsageEvents.ON_TOKEN_USAGE,
|
|
data,
|
|
},
|
|
{ expectedCreatedAt: this.jobCreatedAt },
|
|
);
|
|
} else {
|
|
sendEvent(res, { event: UsageEvents.ON_TOKEN_USAGE, data });
|
|
}
|
|
} catch (err) {
|
|
logger.warn('[AgentClient] Failed to emit subagent usage', err);
|
|
}
|
|
})();
|
|
this.pendingSubagentEmits.push(emit);
|
|
return emit;
|
|
};
|
|
}
|
|
|
|
/** Normalizes a subagent usage event's cache token details for emission. */
|
|
subagentCacheDetails(usage) {
|
|
const cache_creation =
|
|
usage.input_token_details?.cache_creation ?? usage.cache_creation_input_tokens;
|
|
const cache_read = usage.input_token_details?.cache_read ?? usage.cache_read_input_tokens;
|
|
if (cache_creation == null && cache_read == null) {
|
|
return undefined;
|
|
}
|
|
return { cache_creation, cache_read };
|
|
}
|
|
|
|
/**
|
|
* @param {TMessage} responseMessage
|
|
* @returns {number}
|
|
*/
|
|
getTokenCountForResponse({ content }) {
|
|
return countFormattedMessageTokens({ role: 'assistant', content }, this.getEncoding());
|
|
}
|
|
|
|
/**
|
|
* @param {object} params
|
|
* @param {string | ChatCompletionMessageParam[]} params.payload
|
|
* @param {Record<string, Record<string, string>>} [params.userMCPAuthMap]
|
|
* @param {AbortController} [params.abortController]
|
|
*/
|
|
/**
|
|
* @deprecated Agent Chain — strip hidden intermediate sequential-agent content
|
|
* before persistence, keeping only the last part + tool_call parts. Mirrors the
|
|
* chat path so a HITL resume doesn't persist/emit intermediate outputs the
|
|
* agent's `hide_sequential_outputs` setting is meant to hide.
|
|
*/
|
|
applyHideSequentialOutputsFilter() {
|
|
if (!this.options.agent?.hide_sequential_outputs || !Array.isArray(this.contentParts)) {
|
|
return;
|
|
}
|
|
this.contentParts = this.contentParts.filter(
|
|
(part, index) =>
|
|
index >= this.contentParts.length - 1 ||
|
|
part.type === ContentTypes.TOOL_CALL ||
|
|
// Steer parts are user speech, not intermediate agent output — dropping
|
|
// one would erase the user's words from the persisted turn.
|
|
part.type === ContentTypes.STEER ||
|
|
// Activity labels summarize the hidden intermediate outputs — exactly
|
|
// the affordance hide_sequential_outputs wants to keep visible.
|
|
part.type === ContentTypes.ACTIVITY_LABEL ||
|
|
part.tool_call_ids,
|
|
);
|
|
}
|
|
|
|
/**
|
|
* Surface any human-in-the-loop interrupt the SDK captured during the most
|
|
* recent `processStream` / `resume`. When the run paused for tool approval (or
|
|
* an ask-user question), mark the job `requires_action`, persist the pending
|
|
* review record, and emit it to live clients — then set `this.pendingApproval`
|
|
* so the controller leaves the turn unfinalized for the resume route to continue.
|
|
*
|
|
* No-op when the run completed without an interrupt, or when the job was aborted
|
|
* between the interrupt firing and this mark (a late interrupt must not pause a
|
|
* dead job — the atomic `pause` transition returns false and we drop it).
|
|
*
|
|
* @param {AgentRun} run
|
|
* @param {string} [streamId]
|
|
*/
|
|
async handleRunInterrupt(run, streamId) {
|
|
if (!streamId || typeof run?.getInterrupt !== 'function') {
|
|
return;
|
|
}
|
|
const interrupt = run.getInterrupt();
|
|
if (!interrupt?.payload) {
|
|
return;
|
|
}
|
|
|
|
const appConfig = this.options.req?.config;
|
|
const checkpointerCfg = appConfig?.endpoints?.[EModelEndpoint.agents]?.checkpointer;
|
|
// Persist the generation params (temperature, max tokens, custom endpoint params, …)
|
|
// so an ephemeral-agent resume continues with the SAME settings the run paused on.
|
|
// The resume payload omits them and they aren't part of the fingerprint, so without
|
|
// this the rebuilt ephemeral run falls back to defaults. The paused request body is
|
|
// the primary source (UI-form, round-trips the compact-convo schema by construction);
|
|
// the resolved llmConfig fills gaps and is sanitized — it carries provider secrets
|
|
// (apiKey, credentials) and gateway config — resume re-resolves those server-side.
|
|
// (Saved agents source params from the DB record, so this is belt-and-suspenders.)
|
|
const resumeContext = pickResumeContext(this.options.req?.body);
|
|
const resumeModelParameters = captureResumeModelParameters(
|
|
this.options.req?.body,
|
|
this.options.agent?.model_parameters,
|
|
);
|
|
if (resumeModelParameters) {
|
|
resumeContext.model_parameters = resumeModelParameters;
|
|
}
|
|
// Persist the question onto the paused ask tool_call's args NOW: an
|
|
// abandoned/expired/stopped pause never reaches the answer-resume stamp,
|
|
// and the streamed args were dropped (name-less chunks) — without this the
|
|
// unfinished turn saves an empty ask part the record card can't render.
|
|
if (interrupt.payload?.type === 'ask_user_question' && Array.isArray(this.contentParts)) {
|
|
const stamped = attachAskUserQuestionArgs(
|
|
this.contentParts,
|
|
interrupt.payload.question,
|
|
interrupt.payload.tool_call_id,
|
|
);
|
|
if (stamped !== this.contentParts) {
|
|
this.contentParts.length = 0;
|
|
this.contentParts.push(...stamped);
|
|
}
|
|
}
|
|
const pendingAction = buildPendingAction(interrupt.payload, {
|
|
streamId,
|
|
conversationId: this.conversationId,
|
|
// runId mirrors the LangGraph checkpoint namespace when the SDK provides it
|
|
// (its documented meaning), falling back to the response message id.
|
|
runId: interrupt.checkpointNs ?? this.responseMessageId,
|
|
responseMessageId: this.responseMessageId,
|
|
interruptId: interrupt.interruptId,
|
|
// thread_id was bound to conversationId at run config (config.configurable);
|
|
// fall back to it when the SDK doesn't echo threadId on the interrupt.
|
|
threadId: interrupt.threadId ?? this.conversationId,
|
|
ttlMs: getApprovalTtlMs(checkpointerCfg),
|
|
// Pin the graph-determining request fields so resume can't rebuild this paused
|
|
// run on a different agent/tool set (esp. ephemeral agents, whose agent_id is
|
|
// undefined so the id guard can't tell two configs apart).
|
|
requestFingerprint: computeAgentRequestFingerprint(this.options.req?.body ?? {}),
|
|
// Persist those same fields verbatim so the resume route can REPLAY them — a
|
|
// reload/cross-replica resume can't reconstruct the ephemeral config client-side,
|
|
// so the server restores it and rebuilds the same graph (and the fingerprint matches).
|
|
resumeContext,
|
|
});
|
|
|
|
// Job-replacement guard: streamId == conversationId is reused per conversation, so a
|
|
// newer request can replace this run's job. If this (older) run hits an interrupt
|
|
// after a replacement, pausing would flip the NEWER job to requires_action with this
|
|
// stale run's pending action, blocking fresh work behind the wrong approval. Only
|
|
// pause when the live job is still the one THIS run created (mirrors request.js).
|
|
if (this.jobCreatedAt != null) {
|
|
const liveJob = await GenerationJobManager.getJobStore().getJob(streamId);
|
|
if (!liveJob || liveJob.createdAt !== this.jobCreatedAt) {
|
|
logger.debug(`[AgentClient] Interrupt fired but job ${streamId} was replaced; not pausing`);
|
|
return;
|
|
}
|
|
}
|
|
|
|
// Snapshot deferred-tool discovery before exposing the pause. Tool-search results
|
|
// may live only in the interrupted SDK graph, so they must be committed atomically
|
|
// with requires_action for an immediate/cross-replica resume to retain the schemas.
|
|
let discoveredTools = [];
|
|
try {
|
|
discoveredTools = getRunDiscoveredTools(run);
|
|
} catch (err) {
|
|
logger.warn(
|
|
`[AgentClient] Failed to capture discovered tools for resume on ${streamId}`,
|
|
err?.message ?? err,
|
|
);
|
|
}
|
|
|
|
const paused = await GenerationJobManager.approvals.pause(streamId, pendingAction, {
|
|
expectedCreatedAt: this.jobCreatedAt,
|
|
...(discoveredTools.length > 0 ? { discoveredTools } : {}),
|
|
persistencePending: true,
|
|
});
|
|
if (!paused) {
|
|
logger.debug(
|
|
`[AgentClient] Interrupt fired but job ${streamId} was not running; not pausing`,
|
|
);
|
|
return;
|
|
}
|
|
|
|
this.pendingApproval = pendingAction;
|
|
// Release the concurrency slot this request held the MOMENT the turn is durably
|
|
// paused — before the approval card is emitted — so the user's `/resume` can
|
|
// re-acquire one immediately. Otherwise a fast Approve races the HTTP-driver
|
|
// teardown (request.js pause branch / resume.js finally) that would otherwise
|
|
// release it, and `/resume` 429s under LIMIT_CONCURRENT_MESSAGES. Idempotent via
|
|
// the flag; if it fails here, the teardown still releases (it checks the flag).
|
|
if (!this.pendingRequestReleased) {
|
|
try {
|
|
await decrementPendingRequest(this.options.req?.user?.id);
|
|
this.pendingRequestReleased = true;
|
|
} catch (err) {
|
|
logger.error(`[AgentClient] Failed to release request slot on pause ${streamId}`, err);
|
|
}
|
|
}
|
|
await GenerationJobManager.emitChunk(
|
|
streamId,
|
|
{
|
|
event: ApprovalEvents.ON_PENDING_ACTION,
|
|
data: toClientPendingAction(pendingAction),
|
|
},
|
|
{ expectedCreatedAt: this.jobCreatedAt },
|
|
);
|
|
// Steers queued before this pause stay IN the store for the whole approval
|
|
// window: `resumeState.pendingSteers` re-seeds the client's chips on
|
|
// reload, and the resumed run drains them at its first tool boundary.
|
|
// Draining here would leave the only copy in ephemeral client state — a
|
|
// reload during the pause would silently lose the user's message. New
|
|
// steers are rejected while paused (enqueue is status-guarded), and the
|
|
// requires_action TTL extension keeps the queue key alive.
|
|
logger.debug(
|
|
`[AgentClient] Paused ${streamId} for ${interrupt.payload.type} (action ${pendingAction.actionId})`,
|
|
);
|
|
}
|
|
|
|
async chatCompletion({ payload, userMCPAuthMap, abortController = null }) {
|
|
/** @type {Partial<GraphRunnableConfig>} */
|
|
let config;
|
|
/** @type {ReturnType<createRun>} */
|
|
let run;
|
|
/** @type {Promise<(TAttachment | null)[] | undefined>} */
|
|
let memoryPromise;
|
|
const appConfig = this.options.req.config;
|
|
const balanceConfig = getBalanceConfig(appConfig);
|
|
const transactionsConfig = getTransactionsConfig(appConfig);
|
|
try {
|
|
if (!abortController) {
|
|
abortController = new AbortController();
|
|
}
|
|
|
|
/** Fire-and-forget: boot the per-conversation stateful sandbox in
|
|
* parallel with generation so the first execute_code/bash call lands
|
|
* on a warm VM. No-op unless a reachable agent resolved
|
|
* `statefulCodeSessions`. */
|
|
maybePrewarmCodeSandbox({
|
|
req: this.options.req,
|
|
conversationId: this.conversationId,
|
|
agents: [this.options.agent, ...(this.agentConfigs?.values() ?? [])],
|
|
});
|
|
|
|
/** @type {AppConfig['endpoints']['agents']} */
|
|
const agentsEConfig = appConfig.endpoints?.[EModelEndpoint.agents];
|
|
|
|
config = {
|
|
runName: 'AgentRun',
|
|
configurable: {
|
|
thread_id: this.conversationId,
|
|
// LangGraph owns `checkpoint_ns` and resets it to '' at every root
|
|
// invocation. The saver maps this private immutable generation key
|
|
// into its physical namespace while tools keep the conversation id.
|
|
checkpoint_ns: '',
|
|
[LIBRECHAT_CHECKPOINT_NAMESPACE_KEY]: this.checkpointNamespace,
|
|
last_agent_index: this.agentConfigs?.size ?? 0,
|
|
user_id: this.user ?? this.options.req.user?.id,
|
|
hide_sequential_outputs: this.options.agent.hide_sequential_outputs,
|
|
requestBody: {
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
parentMessageId: this.parentMessageId,
|
|
},
|
|
user: createSafeUser(this.options.req.user),
|
|
},
|
|
recursionLimit: resolveRecursionLimit(agentsEConfig, this.options.agent),
|
|
signal: abortController.signal,
|
|
streamMode: 'values',
|
|
version: 'v2',
|
|
};
|
|
|
|
const toolSet = buildToolSet(this.options.agent);
|
|
const tokenCounter = createTokenCounter(this.getEncoding());
|
|
|
|
/** Pre-resolve invoked skill bodies + re-prime files before formatting messages */
|
|
const skillPrimeResult = this.options.primeInvokedSkills
|
|
? await this.options.primeInvokedSkills(payload)
|
|
: undefined;
|
|
|
|
/**
|
|
* Seed `Graph.sessions` with code-env files primed across every
|
|
* reachable agent (primary, handoff/addedConvo, and nested
|
|
* subagents) plus skill-priming output. The merge logic and its
|
|
* run-wide semantics live in `buildInitialToolSessions`; see that
|
|
* helper's doc for why this is intentionally NOT per-agent.
|
|
*/
|
|
const initialSessions = buildInitialToolSessions({
|
|
skillSessions: skillPrimeResult?.initialSessions,
|
|
agents: [this.options.agent, ...(this.agentConfigs ? this.agentConfigs.values() : [])],
|
|
});
|
|
|
|
/**
|
|
* Reconstruct `reasoning_content` on prior tool-call turns: DeepSeek
|
|
* thinking-mode (#13366) or custom endpoints opting in via
|
|
* `customParams.includeReasoningHistory` (e.g. Xiaomi MiMo, Kimi).
|
|
* Walks subagents too — the opted-in endpoint may appear only as a
|
|
* nested subagent, not the primary or a top-level handoff agent.
|
|
*/
|
|
const needsReasoningContentFormat = anyAgentReplaysReasoningContent([
|
|
this.options.agent,
|
|
...(this.agentConfigs ? Array.from(this.agentConfigs.values()) : []),
|
|
]);
|
|
/**
|
|
* Skills primed fresh this turn — manual ($ popover) and always-apply
|
|
* (frontmatter). `injectSkillPrimes` (below) splices their SKILL.md
|
|
* bodies in, so `formatAgentMessages` must NOT also reconstruct the
|
|
* same names from a historical `skill` tool_call — otherwise the body
|
|
* lands twice and a prompt-cache marker can pin to the duplicated
|
|
* synthetic prefix. Names NOT primed this turn still reconstruct from
|
|
* history, preserving sticky manual re-priming across turns.
|
|
*/
|
|
const manualSkillPrimes = this.options.agent?.manualSkillPrimes;
|
|
const alwaysApplySkillPrimes = this.options.agent?.alwaysApplySkillPrimes;
|
|
const freshSkillPrimeNames = collectFreshSkillPrimeNames({
|
|
manualSkillPrimes,
|
|
alwaysApplySkillPrimes,
|
|
});
|
|
const formatOptions =
|
|
needsReasoningContentFormat || freshSkillPrimeNames.size > 0
|
|
? {
|
|
...(needsReasoningContentFormat ? { preserveReasoningContent: true } : {}),
|
|
...(freshSkillPrimeNames.size > 0
|
|
? { skipSkillBodyNames: freshSkillPrimeNames }
|
|
: {}),
|
|
}
|
|
: undefined;
|
|
let {
|
|
messages: initialMessages,
|
|
indexTokenCountMap,
|
|
summary: initialSummary,
|
|
boundaryTokenAdjustment,
|
|
} = formatAgentMessages(
|
|
stripActivityLabelParts(payload),
|
|
this.indexTokenCountMap,
|
|
toolSet,
|
|
skillPrimeResult?.skills,
|
|
formatOptions,
|
|
);
|
|
if (boundaryTokenAdjustment) {
|
|
logger.debug(
|
|
`[AgentClient] Boundary token adjustment: ${boundaryTokenAdjustment.original} → ${boundaryTokenAdjustment.adjusted} (${boundaryTokenAdjustment.remainingChars}/${boundaryTokenAdjustment.totalChars} chars)`,
|
|
);
|
|
}
|
|
|
|
/**
|
|
* Skill priming — both manual ($ popover) and always-apply (frontmatter).
|
|
*
|
|
* Splice + index-shift logic lives in `injectSkillPrimes`
|
|
* (packages/api/src/agents/skills.ts) so the delicate position math
|
|
* can be unit-tested in TS without standing up AgentClient. The
|
|
* resolver enforces a combined ceiling (manual-first, always-apply
|
|
* truncated first when over cap) before reaching here; the splice
|
|
* re-applies the cap as defense-in-depth. Runs for both single-
|
|
* agent and multi-agent runs; how primes interact with handoff /
|
|
* added-convo agents' per-agent state is an agents-SDK concern,
|
|
* not this layer's to gate.
|
|
*
|
|
* `manualSkillPrimes` / `alwaysApplySkillPrimes` are resolved above
|
|
* (used to build `freshSkillPrimeNames` for dedupe against historical
|
|
* skill reconstruction).
|
|
*/
|
|
if (
|
|
(manualSkillPrimes && manualSkillPrimes.length > 0) ||
|
|
(alwaysApplySkillPrimes && alwaysApplySkillPrimes.length > 0)
|
|
) {
|
|
const primeResult = injectSkillPrimes({
|
|
initialMessages,
|
|
indexTokenCountMap,
|
|
manualSkillPrimes,
|
|
alwaysApplySkillPrimes,
|
|
});
|
|
indexTokenCountMap = primeResult.indexTokenCountMap;
|
|
if (primeResult.inserted > 0) {
|
|
const manualNames = (manualSkillPrimes ?? []).map((p) => p.name);
|
|
const alwaysApplyNames = (alwaysApplySkillPrimes ?? []).map((p) => p.name);
|
|
logger.debug(
|
|
`[AgentClient] Primed ${primeResult.inserted} skill(s) at message index ${primeResult.insertIdx} — manual: [${manualNames.join(', ')}], always-apply: [${alwaysApplyNames.join(', ')}]`,
|
|
);
|
|
}
|
|
if (primeResult.alwaysApplyDropped > 0) {
|
|
logger.warn(
|
|
`[AgentClient] Dropped ${primeResult.alwaysApplyDropped} always-apply prime(s) to stay within MAX_PRIMED_SKILLS_PER_TURN.`,
|
|
);
|
|
}
|
|
}
|
|
|
|
if (indexTokenCountMap && isEnabled(process.env.AGENT_DEBUG_LOGGING)) {
|
|
const entries = Object.entries(indexTokenCountMap);
|
|
const perMsg = entries.map(([idx, count]) => {
|
|
const msg = initialMessages[Number(idx)];
|
|
const type = msg ? msg._getType() : '?';
|
|
return `${idx}:${type}=${count}`;
|
|
});
|
|
logger.debug(
|
|
`[AgentClient] Token map after format: [${perMsg.join(', ')}] (payload=${payload.length}, formatted=${initialMessages.length})`,
|
|
);
|
|
}
|
|
indexTokenCountMap = hydrateMissingIndexTokenCounts({
|
|
messages: initialMessages,
|
|
indexTokenCountMap,
|
|
tokenCounter,
|
|
});
|
|
|
|
const memoryMessages =
|
|
this.processMemory && this.memoryPayload
|
|
? formatAgentMessages(
|
|
stripActivityLabelParts(this.memoryPayload),
|
|
undefined,
|
|
toolSet,
|
|
skillPrimeResult?.skills,
|
|
formatOptions,
|
|
).messages
|
|
: initialMessages;
|
|
|
|
/**
|
|
* @param {BaseMessage[]} messages
|
|
*/
|
|
const runAgents = async (messages) => {
|
|
const agents = [this.options.agent];
|
|
// Include additional agents when:
|
|
// - agentConfigs has agents (from addedConvo parallel execution or agent handoffs)
|
|
// - Agents without incoming edges become start nodes and run in parallel automatically
|
|
if (this.agentConfigs && this.agentConfigs.size > 0) {
|
|
agents.push(...this.agentConfigs.values());
|
|
}
|
|
|
|
// TODO: needs to be added as part of AgentContext initialization
|
|
// const noSystemModelRegex = [/\b(o1-preview|o1-mini|amazon\.titan-text)\b/gi];
|
|
// const noSystemMessages = noSystemModelRegex.some((regex) =>
|
|
// agent.model_parameters.model.match(regex),
|
|
// );
|
|
// if (noSystemMessages === true && systemContent?.length) {
|
|
// const latestMessageContent = _messages.pop().content;
|
|
// if (typeof latestMessageContent !== 'string') {
|
|
// latestMessageContent[0].text = [systemContent, latestMessageContent[0].text].join('\n');
|
|
// _messages.push(new HumanMessage({ content: latestMessageContent }));
|
|
// } else {
|
|
// const text = [systemContent, latestMessageContent].join('\n');
|
|
// _messages.push(new HumanMessage(text));
|
|
// }
|
|
// }
|
|
// let messages = _messages;
|
|
// if (agent.useLegacyContent === true) {
|
|
// messages = formatContentStrings(messages);
|
|
// }
|
|
// if (
|
|
// agent.model_parameters?.clientOptions?.defaultHeaders?.['anthropic-beta']?.includes(
|
|
// 'prompt-caching',
|
|
// )
|
|
// ) {
|
|
// messages = addCacheControl(messages);
|
|
// }
|
|
|
|
if (this.processMemory) {
|
|
memoryPromise = this.runMemory(memoryMessages);
|
|
}
|
|
|
|
/** Seed calibration state from previous run if encoding matches */
|
|
const currentEncoding = this.getEncoding();
|
|
const prevMeta = this.contextMeta;
|
|
const encodingMatch = prevMeta?.encoding === currentEncoding;
|
|
const calibrationRatio =
|
|
encodingMatch && prevMeta?.calibrationRatio > 0 ? prevMeta.calibrationRatio : undefined;
|
|
|
|
if (prevMeta) {
|
|
logger.debug(
|
|
`[AgentClient] contextMeta from parent: ratio=${prevMeta.calibrationRatio}, encoding=${prevMeta.encoding}, current=${currentEncoding}, seeded=${calibrationRatio ?? 'none'}`,
|
|
);
|
|
}
|
|
|
|
const streamId = this.options.req?._resumableStreamId;
|
|
// HITL: establish an empty checkpoint barrier for THIS immutable generation
|
|
// before exposing its graph. A retried/recovered initialization may have left
|
|
// partial state in the same saver scope; a predecessor uses a different scope,
|
|
// so even a late remote write cannot be rehydrated or deleted here. No-op when
|
|
// HITL is off or the generation has no remnants. Deliberately unconditional
|
|
// per HITL turn: any cheaper Redis flag can go stale across replicas/restarts,
|
|
// while these are two indexed, usually-empty deleteMany operations.
|
|
// The gate mirrors createRun's checkpointer condition: the approval policy
|
|
// OR an ask_user_question-capable agent (which attaches a checkpointer
|
|
// WITHOUT the approval policy).
|
|
//
|
|
// Start the prune alongside graph construction. The all-settled barrier
|
|
// below still guarantees it completes before the graph is exposed or run.
|
|
const shouldPruneCheckpoint =
|
|
streamId &&
|
|
(isHITLEnabled(agentsEConfig?.toolApproval) || agents.some(agentRequestsAskUserQuestion));
|
|
let checkpointPrunePromise = Promise.resolve();
|
|
if (shouldPruneCheckpoint && this.checkpointNamespace !== '') {
|
|
checkpointPrunePromise = deleteAgentCheckpoint(
|
|
this.conversationId,
|
|
agentsEConfig?.checkpointer,
|
|
undefined,
|
|
{
|
|
throwOnError: true,
|
|
checkpointNamespace: this.checkpointNamespace,
|
|
},
|
|
);
|
|
} else if (shouldPruneCheckpoint) {
|
|
checkpointPrunePromise = captureAgentCheckpointGeneration(
|
|
this.conversationId,
|
|
agentsEConfig?.checkpointer,
|
|
{ throwOnError: true },
|
|
).then(async (checkpointGeneration) => {
|
|
/** Legacy jobs share LangGraph's root/nested namespaces. Capture
|
|
* their immutable ids first, then prove this client still owns
|
|
* the exact job epoch before deleting that set. If a replacement
|
|
* arrived before/during capture the check fails; if it arrives
|
|
* after the check, its newly-written checkpoint ids are outside
|
|
* the snapshot and therefore cannot be deleted. */
|
|
const liveJob = await GenerationJobManager.getJobStore().getJob(streamId);
|
|
if (
|
|
!liveJob ||
|
|
liveJob.createdAt !== this.jobCreatedAt ||
|
|
liveJob.status !== 'running'
|
|
) {
|
|
throw new Error('Generation replaced before legacy checkpoint cleanup');
|
|
}
|
|
await deleteAgentCheckpoint(
|
|
this.conversationId,
|
|
agentsEConfig?.checkpointer,
|
|
checkpointGeneration,
|
|
{ throwOnError: true },
|
|
);
|
|
});
|
|
}
|
|
|
|
const createRunPromise = createRun({
|
|
agents,
|
|
messages,
|
|
// This controller implements the full HITL pause/resume lifecycle (handleRunInterrupt
|
|
// persists the pending action; the /resume route rebuilds + continues the run), so it
|
|
// opts into the tool-approval wiring. Non-resumable callers (OpenAI-compat, Responses)
|
|
// leave this off so an approval-gated tool can't pause where there's no resume path.
|
|
hitlCapable: true,
|
|
toolInputValidationErrors: this.toolInputValidationErrors,
|
|
// Mid-run steering: drain queued user messages at each tool-batch
|
|
// boundary and inject them into graph state. The offset wrapper
|
|
// shifts SDK content indices past any spliced steer parts.
|
|
steering: this.buildSteerWiring(streamId),
|
|
activityLabel: this.buildActivityLabelWiring(streamId, abortController.signal),
|
|
indexTokenCountMap,
|
|
initialSummary,
|
|
initialSessions,
|
|
calibrationRatio,
|
|
runId: this.responseMessageId,
|
|
signal: abortController.signal,
|
|
customHandlers: createSteerIndexOffsetHandlers(
|
|
this.options.eventHandlers,
|
|
this.steerOffsetState,
|
|
),
|
|
requestBody: config.configurable.requestBody,
|
|
user: createSafeUser(this.options.req?.user),
|
|
tenantId: this.options.req?.user?.tenantId,
|
|
summarizationConfig: appConfig?.summarization,
|
|
appConfig,
|
|
tokenCounter,
|
|
/** Bills subagent child-run model calls — child graphs execute
|
|
* outside the streamEvents loop, so ModelEndHandler never sees
|
|
* them. Entries land in collectedUsage tagged
|
|
* `usage_type: 'subagent'` and are spent by recordCollectedUsage.
|
|
* The sink also streams each as an `on_token_usage` event so the
|
|
* gauge's session cost/totals include billed subagent usage (the
|
|
* `subagent` tag keeps it out of the live context meter). */
|
|
subagentUsageSink: createSubagentUsageSink(
|
|
this.collectedUsage,
|
|
this.buildSubagentUsageEmitter(appConfig),
|
|
),
|
|
}).then((createdRun) => {
|
|
if (!createdRun) {
|
|
throw new Error('Failed to create run');
|
|
}
|
|
this.options.startupTelemetry?.mark('run_created');
|
|
return createdRun;
|
|
});
|
|
|
|
const [createRunResult, checkpointPruneResult] = await Promise.allSettled([
|
|
createRunPromise,
|
|
checkpointPrunePromise,
|
|
]);
|
|
if (createRunResult.status === 'rejected') {
|
|
throw createRunResult.reason;
|
|
}
|
|
if (checkpointPruneResult.status === 'rejected') {
|
|
throw checkpointPruneResult.reason;
|
|
}
|
|
run = createRunResult.value;
|
|
|
|
this.run = run;
|
|
if (this._resolveRun) {
|
|
this._resolveRun(run);
|
|
this._resolveRun = null;
|
|
}
|
|
|
|
if (streamId && run.Graph) {
|
|
GenerationJobManager.setGraph(streamId, run.Graph, this.jobCreatedAt);
|
|
}
|
|
|
|
if (userMCPAuthMap != null) {
|
|
config.configurable.userMCPAuthMap = userMCPAuthMap;
|
|
}
|
|
|
|
/** @deprecated Agent Chain */
|
|
config.configurable.last_agent_id = agents[agents.length - 1].id;
|
|
|
|
this.options.startupTelemetry?.mark('stream_processing_started');
|
|
/** Flag durable BEFORE the run can claim a label: gap reconciliation
|
|
* is gated on it, and ordering it here (one settled-on-failure
|
|
* await) keeps the claim-time reservation emit immediate — see
|
|
* `emitLabelEvent` in buildActivityLabelWiring. */
|
|
if (this.activityLabelsMarkedPromise != null) {
|
|
await this.activityLabelsMarkedPromise;
|
|
}
|
|
await run.processStream({ messages }, config, {
|
|
callbacks: {
|
|
[Callback.TOOL_ERROR]: logToolError,
|
|
},
|
|
});
|
|
|
|
// HITL: if the run paused for tool approval, mark the job
|
|
// `requires_action` + emit the prompt and leave the turn unfinalized
|
|
// (the resume route continues it). No-op when the run completed.
|
|
await this.handleRunInterrupt(run, streamId);
|
|
|
|
config.signal = null;
|
|
};
|
|
|
|
this.options.startupTelemetry?.mark('run_input_prepared');
|
|
await runAgents(initialMessages);
|
|
|
|
/**
|
|
* Surface a completed `skill` tool_call content part per *manually*-
|
|
* primed skill so the existing `SkillCall` frontend renderer shows
|
|
* a "Skill X loaded" card on the assistant response. Applied after
|
|
* the graph finishes to avoid clashing with the aggregator's own
|
|
* per-step content indexing. Prepended (not appended) so cards sit
|
|
* above the model's output — priming ran before the turn, the
|
|
* reply follows.
|
|
*
|
|
* Always-apply primes intentionally do NOT emit assistant-side
|
|
* cards. `extractInvokedSkillsFromPayload` scans history for
|
|
* `skill` tool_calls and feeds `primeInvokedSkills`, which is
|
|
* Phase 3's sticky-re-prime path — that's the right behavior for
|
|
* manual (user picked `$skill` once; re-prime on every subsequent
|
|
* turn from history). For always-apply, `resolveAlwaysApplySkills`
|
|
* already re-primes every turn from fresh DB state, so persisting
|
|
* the card would cause the skill body to get primed twice per
|
|
* turn starting on turn 2. The user-facing acknowledgement for
|
|
* always-apply lives on the user bubble as the pinned
|
|
* `SkillPills` row (`message.alwaysAppliedSkills`), which
|
|
* is the durable signal the user wants: "this skill auto-primes".
|
|
*
|
|
* Live streaming display of manual user-bubble pills is handled
|
|
* by `SkillPills` reading `message.manualSkills`. No
|
|
* separate SSE emit is needed here; trying to stream a mid-run
|
|
* tool_call at index 0 collided with the LLM's first text
|
|
* content, while emitting at a sparse offset pushed the card
|
|
* below the reply on finalize. Post-run unshift keeps the final
|
|
* responseMessage.content in the right order.
|
|
*/
|
|
/**
|
|
* Settle in-flight label fills BEFORE the content is reshaped below.
|
|
* A fill emits its claim-time index; the skill-card unshift and the
|
|
* hide-sequential filter both shift positions, so a fill landing after
|
|
* either would emit a stale index — and a client that already synced
|
|
* the reshaped array applies it onto the wrong part. A paused turn
|
|
* never gets a final event to repair that. Costs nothing extra: these
|
|
* are the same promises the finalization settle would wait on, and
|
|
* that later call then sees an empty pending list.
|
|
*/
|
|
await this.settleActivityLabels();
|
|
|
|
const manualPrimed = this.options.agent?.manualSkillPrimes ?? [];
|
|
if (manualPrimed.length > 0) {
|
|
const runId = this.responseMessageId ?? 'skill-prime';
|
|
const manualParts = buildSkillPrimeContentParts(manualPrimed, { runId });
|
|
this.contentParts.unshift(...manualParts);
|
|
}
|
|
|
|
this.applyHideSequentialOutputsFilter();
|
|
} catch (err) {
|
|
if (abortController.signal.aborted) {
|
|
logger.debug(
|
|
'[api/server/controllers/agents/client.js #sendCompletion] Operation aborted by user',
|
|
{ conversationId: this.conversationId, name: err?.name, code: err?.code },
|
|
);
|
|
} else {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #sendCompletion] Unhandled error type',
|
|
err,
|
|
);
|
|
const videoError = resolveGoogleVideoError({
|
|
error: err,
|
|
provider: this.options.agent?.provider,
|
|
hasYouTubeVideo: this.injectedYouTubeVideo,
|
|
});
|
|
this.contentParts.push({
|
|
type: ContentTypes.ERROR,
|
|
[ContentTypes.ERROR]:
|
|
videoError ??
|
|
`An error occurred while processing the request${err?.message ? `: ${err.message}` : ''}`,
|
|
});
|
|
}
|
|
} finally {
|
|
/** Capture calibration state from the run for persistence on the response message.
|
|
* Runs in finally so values are captured even on abort. */
|
|
const ratio = this.run?.getCalibrationRatio() ?? 0;
|
|
if (ratio > 0 && ratio !== 1) {
|
|
this.contextMeta = {
|
|
calibrationRatio: Math.round(ratio * 1000) / 1000,
|
|
encoding: this.getEncoding(),
|
|
};
|
|
} else {
|
|
this.contextMeta = undefined;
|
|
}
|
|
|
|
this.finalizeSubagentContent();
|
|
await this.settleActivityLabels();
|
|
|
|
/** Flush subagent usage emits the sink fired without awaiting, so their
|
|
* persist/publish completes before we return and the job is cleaned up
|
|
* (resumed clients read this persisted usage). */
|
|
if (this.pendingSubagentEmits.length > 0) {
|
|
await Promise.allSettled(this.pendingSubagentEmits);
|
|
this.pendingSubagentEmits = [];
|
|
}
|
|
|
|
try {
|
|
const attachments = await this.awaitMemoryWithTimeout(memoryPromise);
|
|
if (attachments && attachments.length > 0) {
|
|
this.artifactPromises.push(...attachments);
|
|
}
|
|
|
|
/** Skip token spending if aborted - the abort handler (abortMiddleware.js) handles it
|
|
This prevents double-spending when user aborts via `/api/agents/chat/abort` */
|
|
const wasAborted = abortController?.signal?.aborted;
|
|
if (!wasAborted) {
|
|
await this.recordCollectedUsage({
|
|
context: 'message',
|
|
balance: balanceConfig,
|
|
transactions: transactionsConfig,
|
|
});
|
|
} else {
|
|
logger.debug(
|
|
'[api/server/controllers/agents/client.js #chatCompletion] Skipping token spending - handled by abort middleware',
|
|
);
|
|
}
|
|
} catch (err) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #chatCompletion] Error in cleanup phase',
|
|
err,
|
|
);
|
|
}
|
|
if (this._resolveRun) {
|
|
this._resolveRun(this.run ?? null);
|
|
this._resolveRun = null;
|
|
}
|
|
|
|
// HITL: a non-paused turn deliberately prunes nothing here. The lazy checkpointer
|
|
// (LazyMongoSaver) never persists a clean-exit checkpoint, so there is
|
|
// nothing this turn left to delete. Terminal HITL owners eagerly delete their exact
|
|
// saver scope, with the Mongo TTL as the backstop for a crashed owner. Dropping a
|
|
// generic post-completion prune also removes its
|
|
// job-replacement race: an older run's late finally can no longer delete a newer
|
|
// paused run's checkpoint, because there is no longer a clean-path prune to race.
|
|
|
|
run = null;
|
|
config = null;
|
|
memoryPromise = null;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Resume a run that paused for human-in-the-loop review.
|
|
*
|
|
* The original run lives in a detached background task that exits when the run
|
|
* pauses, so resume REBUILDS the run on a fresh graph bound to the same
|
|
* `thread_id` (= conversationId), immutable saver scope, and durable checkpointer.
|
|
* LangGraph rehydrates the paused graph state from that scoped checkpoint;
|
|
* `run.resume(value)` re-enters the interrupted node with the user's decision.
|
|
* State comes from the checkpoint, so no message history is rebuilt here —
|
|
* `createRun` only needs the agent(s) to reconstruct the graph structure.
|
|
*
|
|
* `seedContent` is the content streamed before the pause (the assistant message +
|
|
* its tool call). In Redis mode the job store's append log already spans the pause,
|
|
* so the finalized message is complete regardless; seeding keeps the in-memory store
|
|
* complete too. The run drives events through the same `streamId`, so the client's
|
|
* open SSE receives the continuation live.
|
|
*
|
|
* Unlike `chatCompletion`, this does NOT prune the checkpoint in its `finally` — the
|
|
* resume controller owns checkpoint lifecycle (it must also clean up on failures that
|
|
* happen before this method runs, and keep the checkpoint on a re-pause).
|
|
*
|
|
* @param {object} params
|
|
* @param {Agents.ToolApprovalDecisionMap | { answer: string }} params.resumeValue
|
|
* @param {Array} [params.seedContent] - content aggregated before the pause
|
|
* @param {Array<import('@librechat/agents').RunStep>} [params.runSteps] - run steps emitted before the pause
|
|
* @param {AbortController} [params.abortController]
|
|
* @param {Pick<import('@langchain/langgraph').Command, 'update' | 'goto'>} [params.commandOptions]
|
|
*/
|
|
async resumeCompletion({
|
|
resumeValue,
|
|
seedContent = [],
|
|
runSteps = [],
|
|
abortController = null,
|
|
commandOptions,
|
|
userMCPAuthMap,
|
|
discoveredToolNames,
|
|
}) {
|
|
/** @type {Partial<GraphRunnableConfig>} */
|
|
let config;
|
|
/** @type {ReturnType<createRun>} */
|
|
let run;
|
|
const appConfig = this.options.req.config;
|
|
const balanceConfig = getBalanceConfig(appConfig);
|
|
const transactionsConfig = getTransactionsConfig(appConfig);
|
|
try {
|
|
if (!abortController) {
|
|
abortController = new AbortController();
|
|
}
|
|
|
|
/** @type {AppConfig['endpoints']['agents']} */
|
|
const agentsEConfig = appConfig.endpoints?.[EModelEndpoint.agents];
|
|
|
|
config = {
|
|
runName: 'AgentRun',
|
|
configurable: {
|
|
thread_id: this.conversationId,
|
|
checkpoint_ns: '',
|
|
[LIBRECHAT_CHECKPOINT_NAMESPACE_KEY]: this.checkpointNamespace,
|
|
last_agent_index: this.agentConfigs?.size ?? 0,
|
|
user_id: this.user ?? this.options.req.user?.id,
|
|
hide_sequential_outputs: this.options.agent.hide_sequential_outputs,
|
|
requestBody: {
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
parentMessageId: this.parentMessageId,
|
|
},
|
|
user: createSafeUser(this.options.req.user),
|
|
},
|
|
recursionLimit: resolveRecursionLimit(agentsEConfig, this.options.agent),
|
|
signal: abortController.signal,
|
|
streamMode: 'values',
|
|
version: 'v2',
|
|
};
|
|
|
|
// Seed pre-pause content so the in-memory job store reports the complete turn
|
|
// (Redis aggregates across the pause via its append log; this covers in-memory).
|
|
if (Array.isArray(seedContent) && seedContent.length > 0) {
|
|
this.contentParts.push(...seedContent);
|
|
}
|
|
|
|
const tokenCounter = createTokenCounter(this.getEncoding());
|
|
const agents = [this.options.agent];
|
|
if (this.agentConfigs && this.agentConfigs.size > 0) {
|
|
agents.push(...this.agentConfigs.values());
|
|
}
|
|
|
|
// Re-prime skill files invoked in the pre-pause segment (mirrors the normal path's
|
|
// `primeInvokedSkills(payload)`), so an approved code/file-backed tool keeps the
|
|
// injected skill-file session refs instead of running without them. The pre-pause
|
|
// content carries the `skill` tool_calls, so it stands in for the message payload.
|
|
let skillSessions;
|
|
if (
|
|
typeof this.options.primeInvokedSkills === 'function' &&
|
|
Array.isArray(seedContent) &&
|
|
seedContent.length > 0
|
|
) {
|
|
try {
|
|
const primed = await this.options.primeInvokedSkills([
|
|
{ role: 'assistant', content: seedContent },
|
|
]);
|
|
skillSessions = primed?.initialSessions;
|
|
} catch (err) {
|
|
logger.warn(
|
|
'[api/server/controllers/agents/client.js #resumeCompletion] Failed to re-prime skill sessions',
|
|
err?.message ?? err,
|
|
);
|
|
}
|
|
}
|
|
|
|
// Seed code-env / skill tool sessions so an approved code/file/skill-backed tool
|
|
// runs with the same uploaded-file context the pre-pause run had — the rebuilt
|
|
// graph otherwise has no `Graph.sessions` entries (especially cross-replica).
|
|
const initialSessions = buildInitialToolSessions({ skillSessions, agents });
|
|
|
|
const streamId = this.options.req?._resumableStreamId;
|
|
run = await createRun({
|
|
agents,
|
|
// State (messages, tool calls) is rehydrated from the checkpoint by
|
|
// run.resume; createRun only needs the agents to rebuild the graph.
|
|
messages: [],
|
|
// The resumed run can pause AGAIN (another tool, a follow-up question), and this
|
|
// controller owns that lifecycle, so it must keep the HITL wiring on the rebuilt run.
|
|
hitlCapable: true,
|
|
toolInputValidationErrors: this.toolInputValidationErrors,
|
|
// Steering stays live across a pause/resume cycle: steers queued while
|
|
// the resumed segment runs drain at its tool-batch boundaries.
|
|
steering: this.buildSteerWiring(streamId),
|
|
// Activity labels likewise survive pause/resume: post-resume tool
|
|
// batches keep claiming slots and generating group headers.
|
|
activityLabel: this.buildActivityLabelWiring(streamId, abortController.signal),
|
|
// Replay deferred tools discovered before the pause. With `messages: []` the
|
|
// discovery scan finds nothing, so these names restore the schemas to the
|
|
// rebuilt model binding. Undefined/empty for non-deferred turns is a no-op.
|
|
discoveredToolNames,
|
|
initialSessions,
|
|
runId: this.responseMessageId,
|
|
signal: abortController.signal,
|
|
// The rebuilt graph numbers content indices from 0, but the aggregator was
|
|
// just seeded with the pre-pause parts at those same indices — shift every
|
|
// resumed step index past the seed, or the new output merges into (or, on a
|
|
// type mismatch, is silently dropped against) the pre-pause content. The
|
|
// steer wrapper composes on top: resumed indices shift by seed + any
|
|
// steer parts spliced in while the resumed segment streams.
|
|
customHandlers: createSteerIndexOffsetHandlers(
|
|
createContentIndexOffsetHandlers(
|
|
this.options.eventHandlers,
|
|
Array.isArray(seedContent) ? seedContent : [],
|
|
),
|
|
this.steerOffsetState,
|
|
),
|
|
requestBody: config.configurable.requestBody,
|
|
user: createSafeUser(this.options.req?.user),
|
|
tenantId: this.options.req?.user?.tenantId,
|
|
summarizationConfig: appConfig?.summarization,
|
|
appConfig,
|
|
tokenCounter,
|
|
subagentUsageSink: createSubagentUsageSink(
|
|
this.collectedUsage,
|
|
this.buildSubagentUsageEmitter(appConfig),
|
|
),
|
|
});
|
|
|
|
if (!run) {
|
|
throw new Error('Failed to create run for resume');
|
|
}
|
|
|
|
hydrateResumeRunSteps(runSteps, this.stepMap, run.Graph, seedContent);
|
|
|
|
this.run = run;
|
|
if (this._resolveRun) {
|
|
this._resolveRun(run);
|
|
this._resolveRun = null;
|
|
}
|
|
|
|
// Do NOT cache the rebuilt graph on resume: it was created with `messages: []`, so
|
|
// RedisJobStore.getContentParts() (which prefers a cached graph over reconstructing
|
|
// from the chunk log) would return only the resumed segment and drop the pre-pause
|
|
// assistant/tool-call content on a same-replica reload/status poll. Skipping it makes
|
|
// introspection fall back to the durable chunk reconstruction, which is complete.
|
|
// `setContentParts` still points the in-memory store at the seeded client content.
|
|
if (streamId && this.contentParts) {
|
|
GenerationJobManager.setContentParts(streamId, this.contentParts, this.jobCreatedAt);
|
|
}
|
|
|
|
// Carry the user's MCP auth into the rebuilt run so an approved MCP tool executes
|
|
// with the same OAuth/user credentials it had before the pause.
|
|
if (userMCPAuthMap != null) {
|
|
config.configurable.userMCPAuthMap = userMCPAuthMap;
|
|
}
|
|
|
|
/** @deprecated Agent Chain */
|
|
config.configurable.last_agent_id = agents[agents.length - 1].id;
|
|
|
|
/** Same flag-before-run ordering as chatCompletion's processStream. */
|
|
if (this.activityLabelsMarkedPromise != null) {
|
|
await this.activityLabelsMarkedPromise;
|
|
}
|
|
await run.resume(
|
|
resumeValue,
|
|
config,
|
|
{ callbacks: { [Callback.TOOL_ERROR]: logToolError } },
|
|
commandOptions,
|
|
);
|
|
|
|
config.signal = null;
|
|
|
|
// The model may pause AGAIN (another tool needs approval, or a follow-up
|
|
// question). Re-arm the same interrupt gate so the cycle can repeat.
|
|
await this.handleRunInterrupt(run, streamId);
|
|
|
|
// Mirror chatCompletion: settle label fills before the filter below can
|
|
// shift part positions out from under an in-flight fill's claimed index.
|
|
await this.settleActivityLabels();
|
|
|
|
// Strip hidden intermediate sequential-agent content
|
|
// before resume finalize/re-pause persistence reads `this.contentParts`, so a
|
|
// resumed sequential chain doesn't persist/emit outputs hide_sequential_outputs
|
|
// is meant to hide.
|
|
this.applyHideSequentialOutputsFilter();
|
|
} catch (err) {
|
|
if (abortController.signal.aborted) {
|
|
logger.debug(
|
|
'[api/server/controllers/agents/client.js #resumeCompletion] Aborted by user',
|
|
{
|
|
conversationId: this.conversationId,
|
|
name: err?.name,
|
|
code: err?.code,
|
|
},
|
|
);
|
|
} else {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #resumeCompletion] Unhandled error',
|
|
err,
|
|
);
|
|
this.contentParts.push({
|
|
type: ContentTypes.ERROR,
|
|
[ContentTypes.ERROR]: `An error occurred while resuming the request${err?.message ? `: ${err.message}` : ''}`,
|
|
});
|
|
}
|
|
} finally {
|
|
const ratio = this.run?.getCalibrationRatio() ?? 0;
|
|
if (ratio > 0 && ratio !== 1) {
|
|
this.contextMeta = {
|
|
calibrationRatio: Math.round(ratio * 1000) / 1000,
|
|
encoding: this.getEncoding(),
|
|
};
|
|
} else {
|
|
this.contextMeta = undefined;
|
|
}
|
|
|
|
this.finalizeSubagentContent();
|
|
await this.settleActivityLabels();
|
|
|
|
if (this.pendingSubagentEmits.length > 0) {
|
|
await Promise.allSettled(this.pendingSubagentEmits);
|
|
this.pendingSubagentEmits = [];
|
|
}
|
|
|
|
try {
|
|
const wasAborted = abortController?.signal?.aborted;
|
|
if (!wasAborted) {
|
|
await this.recordCollectedUsage({
|
|
context: 'message',
|
|
balance: balanceConfig,
|
|
transactions: transactionsConfig,
|
|
});
|
|
}
|
|
} catch (err) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #resumeCompletion] Error in cleanup phase',
|
|
err,
|
|
);
|
|
}
|
|
if (this._resolveRun) {
|
|
this._resolveRun(this.run ?? null);
|
|
this._resolveRun = null;
|
|
}
|
|
run = null;
|
|
config = null;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Resolves with the agent run once it is initialized, or `null` if
|
|
* initialization fails. Lets immediate-mode title generation await the run
|
|
* instead of throwing when fired before `chatCompletion` assigns `this.run`.
|
|
* Rejects promptly if the provided signal aborts before the run is ready.
|
|
* @param {AbortSignal} [signal]
|
|
* @returns {Promise<AgentRun | null>}
|
|
*/
|
|
_waitForRun(signal) {
|
|
if (this.run) {
|
|
return Promise.resolve(this.run);
|
|
}
|
|
if (!this._runReady) {
|
|
this._runReady = new Promise((resolve) => {
|
|
this._resolveRun = resolve;
|
|
});
|
|
}
|
|
if (!signal) {
|
|
return this._runReady;
|
|
}
|
|
if (signal.aborted) {
|
|
return Promise.reject(new Error('Aborted before run initialization'));
|
|
}
|
|
return new Promise((resolve, reject) => {
|
|
const onAbort = () => reject(new Error('Aborted before run initialization'));
|
|
signal.addEventListener('abort', onAbort, { once: true });
|
|
this._runReady.then((run) => {
|
|
signal.removeEventListener('abort', onAbort);
|
|
resolve(run);
|
|
});
|
|
});
|
|
}
|
|
|
|
/**
|
|
* @param {Object} params
|
|
* @param {string} params.text
|
|
* @param {AbortController} params.abortController
|
|
* @param {boolean} [params.immediate] When true, the title is generated as soon
|
|
* as the request is made — the run is awaited (instead of throwing) and the
|
|
* title derives from the user's input only (`contentParts` is empty).
|
|
*/
|
|
async titleConvo({ text, abortController, immediate = false }) {
|
|
if (!this.run) {
|
|
if (!immediate) {
|
|
throw new Error('Run not initialized');
|
|
}
|
|
await this._waitForRun(abortController?.signal);
|
|
if (!this.run) {
|
|
logger.debug(
|
|
'[api/server/controllers/agents/client.js #titleConvo] Run unavailable for immediate title generation',
|
|
);
|
|
return;
|
|
}
|
|
}
|
|
const { handleLLMEnd, collected: collectedMetadata } = createMetadataAggregator();
|
|
const { req, agent } = this.options;
|
|
|
|
if (req?.body?.isTemporary) {
|
|
logger.debug(
|
|
`[api/server/controllers/agents/client.js #titleConvo] Skipping title generation for temporary conversation`,
|
|
);
|
|
return;
|
|
}
|
|
|
|
const appConfig = req.config;
|
|
let endpoint = agent.endpoint;
|
|
|
|
/** @type {import('@librechat/agents').ClientOptions} */
|
|
let clientOptions = {
|
|
model: agent.model || agent.model_parameters.model,
|
|
};
|
|
|
|
let titleProviderConfig = getProviderConfig({ provider: endpoint, appConfig });
|
|
|
|
/** @type {TEndpoint | undefined} */
|
|
const endpointConfig =
|
|
appConfig.endpoints?.all ??
|
|
appConfig.endpoints?.[endpoint] ??
|
|
titleProviderConfig.customEndpointConfig;
|
|
if (!endpointConfig) {
|
|
logger.debug(
|
|
`[api/server/controllers/agents/client.js #titleConvo] No endpoint config for "${endpoint}"`,
|
|
);
|
|
}
|
|
|
|
if (endpointConfig?.titleConvo === false) {
|
|
logger.debug(
|
|
`[api/server/controllers/agents/client.js #titleConvo] Title generation disabled for endpoint "${endpoint}"`,
|
|
);
|
|
return;
|
|
}
|
|
|
|
if (endpointConfig?.titleEndpoint && endpointConfig.titleEndpoint !== endpoint) {
|
|
try {
|
|
titleProviderConfig = getProviderConfig({
|
|
provider: endpointConfig.titleEndpoint,
|
|
appConfig,
|
|
});
|
|
endpoint = endpointConfig.titleEndpoint;
|
|
} catch (error) {
|
|
logger.warn(
|
|
`[api/server/controllers/agents/client.js #titleConvo] Error getting title endpoint config for "${endpointConfig.titleEndpoint}", falling back to default`,
|
|
error,
|
|
);
|
|
// Fall back to original provider config
|
|
endpoint = agent.endpoint;
|
|
titleProviderConfig = getProviderConfig({ provider: endpoint, appConfig });
|
|
}
|
|
}
|
|
|
|
if (
|
|
endpointConfig &&
|
|
endpointConfig.titleModel &&
|
|
endpointConfig.titleModel !== Constants.CURRENT_MODEL
|
|
) {
|
|
clientOptions.model = endpointConfig.titleModel;
|
|
}
|
|
|
|
const options = await titleProviderConfig.getOptions({
|
|
req,
|
|
endpoint,
|
|
model_parameters: clientOptions,
|
|
db: {
|
|
getUserKey: db.getUserKey,
|
|
getUserKeyValues: db.getUserKeyValues,
|
|
},
|
|
});
|
|
|
|
let provider = options.provider ?? titleProviderConfig.overrideProvider ?? agent.provider;
|
|
if (
|
|
endpoint === EModelEndpoint.azureOpenAI &&
|
|
options.llmConfig?.azureOpenAIApiInstanceName == null
|
|
) {
|
|
provider = Providers.OPENAI;
|
|
} else if (
|
|
endpoint === EModelEndpoint.azureOpenAI &&
|
|
options.llmConfig?.azureOpenAIApiInstanceName != null &&
|
|
provider !== Providers.AZURE
|
|
) {
|
|
provider = Providers.AZURE;
|
|
}
|
|
|
|
/** @type {import('@librechat/agents').ClientOptions} */
|
|
clientOptions = { ...options.llmConfig };
|
|
if (options.configOptions) {
|
|
clientOptions.configuration = options.configOptions;
|
|
}
|
|
|
|
if (clientOptions.maxTokens != null) {
|
|
delete clientOptions.maxTokens;
|
|
}
|
|
if (clientOptions?.modelKwargs?.max_completion_tokens != null) {
|
|
delete clientOptions.modelKwargs.max_completion_tokens;
|
|
}
|
|
if (clientOptions?.modelKwargs?.max_output_tokens != null) {
|
|
delete clientOptions.modelKwargs.max_output_tokens;
|
|
}
|
|
|
|
/** `omitTitleOptions` drops the Anthropic `clientOptions` carrier (thinking,
|
|
* streaming, etc.), which would also drop its `defaultHeaders` — preserve the
|
|
* original `clientOptions` object so gateway/reverse-proxy metadata still
|
|
* reaches title requests (the proxy may require it for auth/routing). Restore
|
|
* the SAME object reference, not a copy: the Vertex `createClient` closure from
|
|
* `getLLMConfig` closes over this object, so `resolveConfigHeaders` must mutate
|
|
* the very object the client is built from. */
|
|
const anthropicClientOptions = clientOptions?.clientOptions;
|
|
|
|
clientOptions = Object.assign(
|
|
Object.fromEntries(
|
|
Object.entries(clientOptions).filter(([key]) => !omitTitleOptions.has(key)),
|
|
),
|
|
);
|
|
|
|
if (anthropicClientOptions?.defaultHeaders != null && clientOptions.clientOptions == null) {
|
|
clientOptions.clientOptions = anthropicClientOptions;
|
|
}
|
|
|
|
if (
|
|
provider === Providers.GOOGLE &&
|
|
(endpointConfig?.titleMethod === TitleMethod.FUNCTIONS ||
|
|
endpointConfig?.titleMethod === TitleMethod.STRUCTURED)
|
|
) {
|
|
clientOptions.json = true;
|
|
}
|
|
|
|
/** Resolve request-based headers across provider-specific header locations:
|
|
* OpenAI `configuration.defaultHeaders`, Anthropic `clientOptions.defaultHeaders`
|
|
* (preserved above), and Google `customHeaders`. Uses the `req` captured at
|
|
* entry — `disposeClient` nulls `this.options.req` and can race this async
|
|
* title flow, which would blank the user context mid-generation.
|
|
*/
|
|
resolveConfigHeaders({
|
|
llmConfig: clientOptions,
|
|
user: createSafeUser(req?.user),
|
|
body: {
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
parentMessageId: this.parentMessageId,
|
|
},
|
|
});
|
|
|
|
try {
|
|
const titleResult = await this.run.generateTitle({
|
|
provider,
|
|
clientOptions,
|
|
inputText: text,
|
|
contentParts: immediate ? [] : this.contentParts,
|
|
titleMethod: endpointConfig?.titleMethod,
|
|
titlePrompt: endpointConfig?.titlePrompt,
|
|
titlePromptTemplate: endpointConfig?.titlePromptTemplate,
|
|
chainOptions: {
|
|
runName: 'TitleRun',
|
|
signal: abortController.signal,
|
|
callbacks: [
|
|
{
|
|
handleLLMEnd,
|
|
},
|
|
],
|
|
configurable: {
|
|
thread_id: this.conversationId,
|
|
user_id: this.user ?? this.options.req.user?.id,
|
|
},
|
|
},
|
|
});
|
|
|
|
const collectedUsage = collectedMetadata.map((item) => {
|
|
let input_tokens, output_tokens;
|
|
|
|
if (item.usage) {
|
|
input_tokens =
|
|
item.usage.prompt_tokens || item.usage.input_tokens || item.usage.inputTokens;
|
|
output_tokens =
|
|
item.usage.completion_tokens || item.usage.output_tokens || item.usage.outputTokens;
|
|
} else if (item.tokenUsage) {
|
|
input_tokens = item.tokenUsage.promptTokens;
|
|
output_tokens = item.tokenUsage.completionTokens;
|
|
} else if (item.usage_metadata) {
|
|
input_tokens = item.usage_metadata.input_tokens;
|
|
output_tokens = item.usage_metadata.output_tokens;
|
|
}
|
|
|
|
return {
|
|
input_tokens: input_tokens,
|
|
output_tokens: output_tokens,
|
|
};
|
|
});
|
|
|
|
const balanceConfig = getBalanceConfig(appConfig);
|
|
const transactionsConfig = getTransactionsConfig(appConfig);
|
|
await this.recordCollectedUsage({
|
|
collectedUsage,
|
|
context: 'title',
|
|
model: clientOptions.model,
|
|
balance: balanceConfig,
|
|
transactions: transactionsConfig,
|
|
messageId: this.responseMessageId,
|
|
}).catch((err) => {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #titleConvo] Error recording collected usage',
|
|
err,
|
|
);
|
|
});
|
|
|
|
return sanitizeTitle(titleResult.title);
|
|
} catch (err) {
|
|
logger.error('[api/server/controllers/agents/client.js #titleConvo] Error', err);
|
|
return;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* @param {object} params
|
|
* @param {number} params.promptTokens
|
|
* @param {number} params.completionTokens
|
|
* @param {string} [params.model]
|
|
* @param {OpenAIUsageMetadata} [params.usage]
|
|
* @param {AppConfig['balance']} [params.balance]
|
|
* @param {string} [params.context='message']
|
|
* @returns {Promise<void>}
|
|
*/
|
|
async recordTokenUsage({
|
|
model,
|
|
usage,
|
|
balance,
|
|
promptTokens,
|
|
completionTokens,
|
|
context = 'message',
|
|
}) {
|
|
try {
|
|
await db.spendTokens(
|
|
{
|
|
model,
|
|
context,
|
|
balance,
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
user: this.user ?? this.options.req.user?.id,
|
|
endpointTokenConfig: this.options.endpointTokenConfig,
|
|
},
|
|
{ promptTokens, completionTokens },
|
|
);
|
|
|
|
if (
|
|
usage &&
|
|
typeof usage === 'object' &&
|
|
'reasoning_tokens' in usage &&
|
|
typeof usage.reasoning_tokens === 'number'
|
|
) {
|
|
await db.spendTokens(
|
|
{
|
|
model,
|
|
balance,
|
|
context: 'reasoning',
|
|
messageId: this.responseMessageId,
|
|
conversationId: this.conversationId,
|
|
user: this.user ?? this.options.req.user?.id,
|
|
endpointTokenConfig: this.options.endpointTokenConfig,
|
|
},
|
|
{ completionTokens: usage.reasoning_tokens },
|
|
);
|
|
}
|
|
} catch (error) {
|
|
logger.error(
|
|
'[api/server/controllers/agents/client.js #recordTokenUsage] Error recording token usage',
|
|
error,
|
|
);
|
|
}
|
|
}
|
|
|
|
/** Anthropic Claude models use a distinct BPE tokenizer; all others default to o200k_base. */
|
|
getEncoding() {
|
|
if (this.model && this.model.toLowerCase().includes('claude')) {
|
|
return 'claude';
|
|
}
|
|
return 'o200k_base';
|
|
}
|
|
}
|
|
|
|
module.exports = AgentClient;
|