LibreChat/api/server/controllers/agents/responses.js
Dustin Healy 5867f1a065
🛡️ feat: Configurable Message PII Filter (#13602)
* 🛡️ feat: Reject chat messages matching configured credential patterns

Adds an opt-in `messagePiiFilter` middleware mounted on the agent
chat route ahead of `moderateText`. When the configured patterns
match the user's input the request is refused with 400, so the
credential never reaches OpenAI moderation, the model, or MongoDB.
Three starter patterns ship by default and operators can subset
them or add their own regex via `customPatterns` in librechat.yaml.

* 🧪 test: Memoize compiled patterns + add middleware spec

Memoize the compiled pattern array via a WeakMap keyed by the
messagePiiFilter config object so repeat requests against the same
config skip the per-request RegExp construction. Cache entries are
released automatically when the config object itself rotates.

Adds packages/api/src/middleware/messagePiiFilter.spec.ts covering
the default-starter rejections, the starterPatterns subset and
empty-array semantics, customPatterns matching layered on top of and
in place of the starters, the no-config and empty-text pass-through
paths, and a memoization regression check.

* 🛡️ fix: Skip invalid customPattern regexes instead of crashing the request

Admin DB overrides for `messagePiiFilter.customPatterns` reach
`req.config` via `mergeConfigOverrides`, which deep-merges raw
override values without re-running `configSchema`. A typo'd regex
like `(` would slip past the YAML-load validation and throw inside
`new RegExp(...)` during `compile()`, returning 500 for every chat
request until the operator rolled the override back.

Wrapped the per-pattern compile in a try/catch that logs the
invalid pattern id + reason and skips it, so other valid patterns
(starters and other custom entries) keep filtering. Added a
regression test alongside the existing spec.

* 🛡️ feat: Extend PII filter to OpenAI-compatible and Responses agent APIs

The chat-route middleware operates on `req.body.text`, but the remote
agent API endpoints (`/api/agents/v1/chat/completions`,
`/api/agents/v1/responses`) accept the same prompt content as a
`messages` array or an `input` field. A caller using their API key
could send a credential-shaped value through either route and bypass
the configured PII filter even though they share the same agent and
model backbone the middleware is meant to guard.

Factored out `findPiiMatchInMessages`, a tolerant walker that handles
both `content: string` and `content: ContentPart[]` user-message
shapes against the same compiled, cached pattern list. Wired it into
the OpenAI-compat controller after agent lookup and into the
Responses controller right after `convertToInternalMessages`. Each
returns the endpoint's native 400 error shape
(`sendErrorResponse` / `sendResponsesErrorResponse`) with the
`message_pii_filter_block` code when a user message matches.

* 🩹 test: Add findPiiMatchInMessages to OpenAI + Responses controller mocks

The OpenAI-compat and Responses controller specs mock `@librechat/api`
with a hand-listed object. The new `findPiiMatchInMessages` export
wired into both controllers in 3ea35af9a was missing from those
mocks, so the production lookup returned undefined and the controllers
threw at request time under jest. Added the missing entries (default
mock: returns null so the handlers fall through to the existing happy
paths). All 278 agents-controller tests pass locally.

* 🧹 refactor: Namespace messagePiiFilter under messageFilter.pii + fix import order

Renames the yaml field `messagePiiFilter` to `messageFilter.pii`, the
module to `messageFilterPii`, the factory to `createMessageFilterPii`,
the type to `MessageFilterPiiConfig`, and the error code to
`message_filter_pii_block`. The wrapper `messageFilter` namespace
gives future safety filters (e.g. `messageFilter.toxicity`) a place
to plug in without restructuring the config later. The
`findPiiMatchInMessages` helper kept its name because it already
describes what it does at the value level.

Also fixes import order Danny flagged on the OpenAI-compatible and
Responses controllers: `findPiiMatchInMessages` was appended at the
bottom of two `require('@librechat/api')` destructures rather than
placed in the length-sorted slot the house style expects.

* 🧹 chore: Length-sort the general require destructure in responses.js

Reorders the general sub-group inside the `require('@librechat/api')`
destructure shortest to longest so the whole block conforms to the
length-sort rule the file's `// Responses API` sub-group already
follows. Pure reorder, no other changes.

* 🧹 chore: Length-sort the defaultConfig block in AppService

Reorders the `defaultConfig` keys in `packages/data-schemas/src/app/service.ts`
shortest-line to longest-line, with the explicit-value entries
(`mcpConfig`, `fileStrategies`, `cloudfront`) trailing the shorthand
ones. Pure reorder, no behavior change.
2026-06-10 09:03:05 -04:00

1198 lines
38 KiB
JavaScript

const { nanoid } = require('nanoid');
const { v4: uuidv4 } = require('uuid');
const { logger } = require('@librechat/data-schemas');
const { Callback, ToolEndHandler, formatAgentMessages } = require('@librechat/agents');
const {
EModelEndpoint,
ResourceType,
PermissionBits,
hasPermissions,
AgentCapabilities,
} = require('librechat-data-provider');
const {
createRun,
buildToolSet,
createSafeUser,
initializeAgent,
loadSkillStates,
getBalanceConfig,
injectSkillPrimes,
extractManualSkills,
recordCollectedUsage,
getTransactionsConfig,
findPiiMatchInMessages,
discoverConnectedAgents,
createToolExecuteHandler,
getRemoteAgentPermissions,
resolveAgentScopedSkillIds,
// Responses API
writeDone,
buildResponse,
generateResponseId,
isValidationFailure,
emitResponseCreated,
createResponseContext,
createResponseTracker,
setupStreamingResponse,
emitResponseInProgress,
convertInputToMessages,
validateResponseRequest,
buildAggregatedResponse,
createResponseAggregator,
sendResponsesErrorResponse,
createResponsesEventHandlers,
createAggregatorEventHandlers,
} = require('@librechat/api');
const {
createResponsesToolEndCallback,
buildSummarizationHandlers,
markSummarizationUsage,
createToolEndCallback,
agentLogHandlerObj,
} = require('~/server/controllers/agents/callbacks');
const { loadAgentTools, loadToolsForExecution } = require('~/server/services/ToolService');
const {
findAccessibleResources,
getEffectivePermissions,
} = require('~/server/services/PermissionService');
const {
getSkillToolDeps,
getSkillDbMethods,
canAuthorSkillFiles,
withDeploymentSkillIds,
buildAgentToolContext,
enrichLoadedToolsWithAgentContext,
} = require('~/server/services/Endpoints/agents/skillDeps');
const { getModelsConfig } = require('~/server/controllers/ModelController');
const { logViolation } = require('~/cache');
const db = require('~/models');
/**
* Creates a tool loader function for the agent.
* @param {AbortSignal} signal - The abort signal
* @param {boolean} [definitionsOnly=true] - When true, returns only serializable
* tool definitions without creating full tool instances (for event-driven mode)
*/
function createToolLoader(signal, definitionsOnly = true) {
return async function loadTools({
req,
res,
tools,
model,
agentId,
provider,
tool_options,
tool_resources,
}) {
const agent = { id: agentId, tools, provider, model, tool_options };
try {
return await loadAgentTools({
req,
res,
agent,
signal,
tool_resources,
definitionsOnly,
streamId: null,
});
} catch (error) {
logger.error('Error loading tools for agent ' + agentId, error);
}
};
}
/**
* Convert Open Responses input items to internal messages
* @param {import('@librechat/api').InputItem[]} input
* @returns {Array} Internal messages
*/
function convertToInternalMessages(input) {
return convertInputToMessages(input);
}
/**
* Load messages from a previous response/conversation
* @param {string} conversationId - The conversation/response ID
* @param {string} userId - The user ID
* @returns {Promise<Array>} Messages from the conversation
*/
async function loadPreviousMessages(conversationId, userId) {
try {
const messages = await db.getMessages({ conversationId, user: userId });
if (!messages || messages.length === 0) {
return [];
}
// Convert stored messages to internal format
return messages.map((msg) => {
const internalMsg = {
role: msg.isCreatedByUser ? 'user' : 'assistant',
content: '',
messageId: msg.messageId,
};
// Handle content - could be string or array
if (typeof msg.text === 'string') {
internalMsg.content = msg.text;
} else if (Array.isArray(msg.content)) {
// Handle content parts
internalMsg.content = msg.content;
} else if (msg.text) {
internalMsg.content = String(msg.text);
}
return internalMsg;
});
} catch (error) {
logger.error('[Responses API] Error loading previous messages:', error);
return [];
}
}
/**
* Save input messages to database
* @param {import('express').Request} req
* @param {string} conversationId
* @param {Array} inputMessages - Internal format messages
* @param {string} agentId
* @returns {Promise<void>}
*/
async function saveInputMessages(req, conversationId, inputMessages, agentId) {
for (const msg of inputMessages) {
if (msg.role === 'user') {
await db.saveMessage(
req,
{
messageId: msg.messageId || nanoid(),
conversationId,
parentMessageId: null,
isCreatedByUser: true,
text: typeof msg.content === 'string' ? msg.content : JSON.stringify(msg.content),
sender: 'User',
endpoint: EModelEndpoint.agents,
model: agentId,
},
{ context: 'Responses API - save user input' },
);
}
}
}
/**
* Save response output to database
* @param {import('express').Request} req
* @param {string} conversationId
* @param {string} responseId
* @param {import('@librechat/api').Response} response
* @param {string} agentId
* @returns {Promise<void>}
*/
async function saveResponseOutput(req, conversationId, responseId, response, agentId) {
// Extract text content from output items
let responseText = '';
for (const item of response.output) {
if (item.type === 'message' && item.content) {
for (const part of item.content) {
if (part.type === 'output_text' && part.text) {
responseText += part.text;
}
}
}
}
// Save the assistant message
await db.saveMessage(
req,
{
messageId: responseId,
conversationId,
parentMessageId: null,
isCreatedByUser: false,
text: responseText,
sender: 'Agent',
endpoint: EModelEndpoint.agents,
model: agentId,
finish_reason: response.status === 'completed' ? 'stop' : response.status,
tokenCount: response.usage?.output_tokens,
},
{ context: 'Responses API - save assistant response' },
);
}
/**
* Save or update conversation
* @param {import('express').Request} req
* @param {string} conversationId
* @param {string} agentId
* @param {object} agent
* @returns {Promise<void>}
*/
async function saveConversation(req, conversationId, agentId, agent) {
await db.saveConvo(
{
userId: req?.user?.id,
isTemporary: req?.body?.isTemporary,
interfaceConfig: req?.config?.interfaceConfig,
},
{
conversationId,
endpoint: EModelEndpoint.agents,
agentId,
title: agent?.name || 'Open Responses Conversation',
model: agent?.model,
},
{ context: 'Responses API - save conversation' },
);
}
/**
* Convert stored messages to Open Responses output format
* @param {Array} messages - Stored messages
* @returns {Array} Output items
*/
function convertMessagesToOutputItems(messages) {
const output = [];
for (const msg of messages) {
if (!msg.isCreatedByUser) {
output.push({
type: 'message',
id: msg.messageId,
role: 'assistant',
status: 'completed',
content: [
{
type: 'output_text',
text: msg.text || '',
annotations: [],
},
],
});
}
}
return output;
}
/**
* Create Response - POST /v1/responses
*
* Creates a model response following the Open Responses API specification.
* Supports both streaming and non-streaming responses.
*
* @param {import('express').Request} req
* @param {import('express').Response} res
*/
const createResponse = async (req, res) => {
const appConfig = req.config;
const requestStartTime = Date.now();
// Validate request
const validation = validateResponseRequest(req.body);
if (isValidationFailure(validation)) {
return sendResponsesErrorResponse(res, 400, validation.error);
}
const request = validation.request;
const agentId = request.model;
const isStreaming = request.stream === true;
const summarizationConfig = appConfig?.summarization;
// Look up the agent
const agent = await db.getAgent({ id: agentId });
if (!agent) {
return sendResponsesErrorResponse(
res,
404,
`Agent not found: ${agentId}`,
'not_found',
'model_not_found',
);
}
// Generate IDs
const responseId = generateResponseId();
const context = createResponseContext(request, responseId);
logger.debug(
`[Responses API] Request ${responseId} started for agent ${agentId}, stream: ${isStreaming}`,
);
// Set up abort controller
const abortController = new AbortController();
// Handle client disconnect
req.on('close', () => {
if (!abortController.signal.aborted) {
abortController.abort();
logger.debug('[Responses API] Client disconnected, aborting');
}
});
try {
if (request.previous_response_id != null) {
if (typeof request.previous_response_id !== 'string') {
return sendResponsesErrorResponse(
res,
400,
'previous_response_id must be a string',
'invalid_request',
);
}
if (!(await db.getConvo(req.user?.id, request.previous_response_id))) {
return sendResponsesErrorResponse(res, 404, 'Conversation not found', 'not_found');
}
}
const conversationId = request.previous_response_id ?? uuidv4();
const parentMessageId = null;
// Build allowed providers set
const allowedProviders = new Set(
appConfig?.endpoints?.[EModelEndpoint.agents]?.allowedProviders,
);
// Create tool loader
const loadTools = createToolLoader(abortController.signal);
const skillDbMethods = getSkillDbMethods();
// Initialize the agent first to check for disableStreaming
const endpointOption = {
endpoint: agent.provider,
model_parameters: agent.model_parameters ?? {},
};
// `filterFilesByAgentAccess` is intentionally omitted: it calls
// `checkPermission` with `resourceType: AGENT`, but this route
// authorizes callers through `REMOTE_AGENT` (via
// `getRemoteAgentPermissions`), so including it would silently drop
// owner-attached context files for any remote user who has
// `REMOTE_AGENT_VIEWER` but not direct `AGENT_VIEW`.
const dbMethods = {
getConvoFiles: db.getConvoFiles,
getFiles: db.getFiles,
getUserKey: db.getUserKey,
getMessages: db.getMessages,
updateFilesUsage: db.updateFilesUsage,
getUserKeyValues: db.getUserKeyValues,
getUserCodeFiles: db.getUserCodeFiles,
getToolFilesByIds: db.getToolFilesByIds,
getCodeGeneratedFiles: db.getCodeGeneratedFiles,
listSkillsByAccess: skillDbMethods.listSkillsByAccess,
listAlwaysApplySkills: skillDbMethods.listAlwaysApplySkills,
getSkillByName: skillDbMethods.getSkillByName,
};
const enabledCapabilities = new Set(
appConfig?.endpoints?.[EModelEndpoint.agents]?.capabilities,
);
const skillsCapabilityEnabled = enabledCapabilities.has(AgentCapabilities.skills);
const ephemeralSkillsToggle = req.body?.ephemeralAgent?.skills === true;
const accessibleSkillIds = skillsCapabilityEnabled
? withDeploymentSkillIds(
await findAccessibleResources({
userId: req.user.id,
role: req.user.role,
resourceType: ResourceType.SKILL,
requiredPermissions: PermissionBits.VIEW,
}),
)
: [];
const editableSkillIds = skillsCapabilityEnabled
? await findAccessibleResources({
userId: req.user.id,
role: req.user.role,
resourceType: ResourceType.SKILL,
requiredPermissions: PermissionBits.EDIT,
})
: [];
const skillCreateAllowed = skillsCapabilityEnabled
? await getSkillToolDeps().canCreateSkill({ req })
: false;
const { skillStates, defaultActiveOnShare } = await loadSkillStates({
userId: req.user.id,
appConfig,
getUserById: db.getUserById,
accessibleSkillIds,
});
const manualSkills = extractManualSkills(req.body);
const primaryScopedSkillIds = resolveAgentScopedSkillIds({
agent,
accessibleSkillIds,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
});
const primaryScopedEditableSkillIds = resolveAgentScopedSkillIds({
agent,
accessibleSkillIds: editableSkillIds,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
});
const primaryConfig = await initializeAgent(
{
req,
res,
loadTools,
requestFiles: [],
conversationId,
parentMessageId,
agent,
endpointOption,
allowedProviders,
isInitialAgent: true,
accessibleSkillIds: primaryScopedSkillIds,
skillAuthoringAvailable: canAuthorSkillFiles({
agent,
scopedEditableSkillIds: primaryScopedEditableSkillIds,
skillCreateAllowed,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
}),
codeEnvAvailable: enabledCapabilities.has(AgentCapabilities.execute_code),
skillStates,
defaultActiveOnShare,
manualSkills,
},
dbMethods,
);
/**
* Per-agent tool-execution context map, keyed by agentId. Ensures the
* ON_TOOL_EXECUTE callback routes each sub-agent's tool calls to the
* correct toolRegistry / userMCPAuthMap / tool_resources.
* @type {Map<string, {
* agent: object,
* toolRegistry?: import('@librechat/agents').LCToolRegistry,
* userMCPAuthMap?: Record<string, Record<string, string>>,
* tool_resources?: object,
* actionsEnabled?: boolean,
* }>}
*/
const agentToolContexts = new Map();
agentToolContexts.set(
primaryConfig.id,
buildAgentToolContext({ agent, config: primaryConfig }),
);
// Only run BFS discovery (and pay `getModelsConfig` upfront) when the
// primary has edges to follow — the common API case is single-agent.
let handoffAgentConfigs = new Map();
let discoveredEdges = [];
let discoveredMCPAuthMap;
if (primaryConfig.edges?.length) {
const modelsConfig = await getModelsConfig(req);
({
agentConfigs: handoffAgentConfigs,
edges: discoveredEdges,
userMCPAuthMap: discoveredMCPAuthMap,
} = await discoverConnectedAgents(
{
req,
res,
primaryConfig,
endpointOption,
allowedProviders,
modelsConfig,
loadTools,
requestFiles: [],
conversationId,
parentMessageId,
// The route enforces REMOTE_AGENT on the primary; every discovered
// sub-agent must clear the same sharing boundary, not the looser
// in-app AGENT one.
resourceType: ResourceType.REMOTE_AGENT,
computeAccessibleSkillIds: (handoffAgent) =>
resolveAgentScopedSkillIds({
agent: handoffAgent,
accessibleSkillIds,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
}),
computeSkillAuthoringAvailable: (handoffAgent) =>
canAuthorSkillFiles({
agent: handoffAgent,
scopedEditableSkillIds: resolveAgentScopedSkillIds({
agent: handoffAgent,
accessibleSkillIds: editableSkillIds,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
}),
skillCreateAllowed,
skillsCapabilityEnabled,
ephemeralSkillsToggle,
}),
skillStates,
defaultActiveOnShare,
/** @see DiscoverConnectedAgentsParams.codeEnvAvailable */
codeEnvAvailable: enabledCapabilities.has(AgentCapabilities.execute_code),
},
{
getAgent: db.getAgent,
// Use `getRemoteAgentPermissions` so sub-agent authorization
// matches what the route's `createCheckRemoteAgentAccess`
// middleware does for the primary: AGENT owners with the SHARE
// bit are treated as remotely authorized even without an
// explicit REMOTE_AGENT grant.
checkPermission: async ({ userId, role, resourceId, requiredPermission }) => {
const permissions = await getRemoteAgentPermissions(
{ getEffectivePermissions },
userId,
role,
resourceId,
);
return hasPermissions(permissions, requiredPermission);
},
logViolation,
db: dbMethods,
onAgentInitialized: (agentId, handoffAgent, config) => {
agentToolContexts.set(agentId, buildAgentToolContext({ agent: handoffAgent, config }));
},
initializeAgent,
},
));
}
primaryConfig.edges = discoveredEdges;
const runAgents = [primaryConfig, ...handoffAgentConfigs.values()];
const mergedMCPAuthMap = discoveredMCPAuthMap ?? primaryConfig.userMCPAuthMap;
// Determine if streaming is enabled (check both request and agent config)
const streamingDisabled = !!primaryConfig.model_parameters?.disableStreaming;
const actuallyStreaming = isStreaming && !streamingDisabled;
// Load previous messages if previous_response_id is provided
let previousMessages = [];
if (request.previous_response_id) {
const userId = req.user?.id ?? 'api-user';
previousMessages = await loadPreviousMessages(request.previous_response_id, userId);
}
// Convert input to internal messages
const inputMessages = convertToInternalMessages(
typeof request.input === 'string' ? request.input : request.input,
);
const piiHit = findPiiMatchInMessages(inputMessages, appConfig?.messageFilter?.pii);
if (piiHit != null) {
return sendResponsesErrorResponse(
res,
400,
`Message contains a ${piiHit.label}. Remove it and try again.`,
'invalid_request',
'message_filter_pii_block',
);
}
// Merge previous messages with new input
const allMessages = [...previousMessages, ...inputMessages];
const toolSet = buildToolSet(primaryConfig);
const formatted = formatAgentMessages(allMessages, {}, toolSet);
const formattedMessages = formatted.messages;
const initialSummary = formatted.summary;
let indexTokenCountMap = formatted.indexTokenCountMap;
/**
* Inject manual + always-apply skill primes so the model sees SKILL.md
* bodies for this turn — parity with AgentClient's chat path. The
* Responses API uses its own response-builder shape, so LibreChat-
* style card SSE events don't apply; only the message-context part
* carries over.
*/
const manualSkillPrimes = primaryConfig.manualSkillPrimes;
const alwaysApplySkillPrimes = primaryConfig.alwaysApplySkillPrimes;
if (
(manualSkillPrimes && manualSkillPrimes.length > 0) ||
(alwaysApplySkillPrimes && alwaysApplySkillPrimes.length > 0)
) {
const primeResult = injectSkillPrimes({
initialMessages: formattedMessages,
indexTokenCountMap,
manualSkillPrimes,
alwaysApplySkillPrimes,
});
indexTokenCountMap = primeResult.indexTokenCountMap;
/* Surface the cap-driven always-apply truncation at the controller
layer too — `injectSkillPrimes` already logs internally, but the
controller-level warn includes endpoint context so operators can
tell at a glance which path hit the cap. Mirrors AgentClient's
warn in `client.js`. */
if (primeResult.alwaysApplyDropped > 0) {
logger.warn(
`[Responses API] Dropped ${primeResult.alwaysApplyDropped} always-apply prime(s) to stay within MAX_PRIMED_SKILLS_PER_TURN.`,
);
}
}
/* Stable for the turn: the primary prime list is fixed once
`initializeAgent` resolves and is used as the fallback when a
specific agent context is unavailable. `codeEnvAvailable` is read
per-agent from the stored tool context (admin cap AND that
agent's `tools` list includes `execute_code`) — a skills-only
agent never gains sandbox access even if the admin enabled the
capability globally. */
// Create tracker for streaming or aggregator for non-streaming
const tracker = actuallyStreaming ? createResponseTracker() : null;
const aggregator = actuallyStreaming ? null : createResponseAggregator();
// Set up response for streaming
if (actuallyStreaming) {
setupStreamingResponse(res);
// Create handler config
const handlerConfig = {
res,
context,
tracker,
};
// Emit response.created then response.in_progress per Open Responses spec
emitResponseCreated(handlerConfig);
emitResponseInProgress(handlerConfig);
// Create event handlers
const { handlers: responsesHandlers, finalizeStream } =
createResponsesEventHandlers(handlerConfig);
// Collect usage for balance tracking
const collectedUsage = [];
// Artifact promises for processing tool outputs
/** @type {Promise<import('librechat-data-provider').TAttachment | null>[]} */
const artifactPromises = [];
// Use Responses API-specific callback that emits librechat:attachment events
const toolEndCallback = createResponsesToolEndCallback({
req,
res,
tracker,
artifactPromises,
});
// Create tool execute options for event-driven tool execution
const toolExecuteOptions = {
loadTools: async (toolNames, agentId) => {
const ctx =
agentToolContexts.get(agentId) ?? agentToolContexts.get(primaryConfig.id) ?? {};
const result = await loadToolsForExecution({
req,
res,
toolNames,
agent: ctx.agent ?? agent,
signal: abortController.signal,
toolRegistry: ctx.toolRegistry,
userMCPAuthMap: ctx.userMCPAuthMap,
tool_resources: ctx.tool_resources,
actionsEnabled: ctx.actionsEnabled,
});
return enrichLoadedToolsWithAgentContext({
result,
req,
ctx,
});
},
toolEndCallback,
...getSkillToolDeps(),
};
// Combine handlers
const handlers = {
on_message_delta: responsesHandlers.on_message_delta,
on_reasoning_delta: responsesHandlers.on_reasoning_delta,
on_run_step: responsesHandlers.on_run_step,
on_run_step_delta: responsesHandlers.on_run_step_delta,
on_chat_model_end: {
handle: (event, data, metadata) => {
responsesHandlers.on_chat_model_end.handle(event, data);
const usage = data?.output?.usage_metadata;
if (usage) {
const taggedUsage = markSummarizationUsage(usage, metadata);
collectedUsage.push(taggedUsage);
}
},
},
on_tool_end: new ToolEndHandler(toolEndCallback, logger),
on_run_step_completed: { handle: () => {} },
on_chain_stream: { handle: () => {} },
on_chain_end: { handle: () => {} },
on_agent_update: { handle: () => {} },
on_custom_event: { handle: () => {} },
on_tool_execute: createToolExecuteHandler(toolExecuteOptions),
on_agent_log: agentLogHandlerObj,
...(summarizationConfig?.enabled !== false
? buildSummarizationHandlers({ isStreaming: actuallyStreaming, res })
: {}),
};
// Create and run the agent
const userId = req.user?.id ?? 'api-user';
const userMCPAuthMap = mergedMCPAuthMap;
const run = await createRun({
agents: runAgents,
messages: formattedMessages,
indexTokenCountMap,
initialSummary,
runId: responseId,
summarizationConfig,
appConfig,
signal: abortController.signal,
customHandlers: handlers,
requestBody: {
messageId: responseId,
conversationId,
},
user: { id: userId },
});
if (!run) {
throw new Error('Failed to create agent run');
}
// Process the stream
const config = {
runName: 'AgentRun',
configurable: {
thread_id: conversationId,
user_id: userId,
user: createSafeUser(req.user),
requestBody: {
messageId: responseId,
conversationId,
},
...(userMCPAuthMap != null && { userMCPAuthMap }),
},
signal: abortController.signal,
streamMode: 'values',
version: 'v2',
};
await run.processStream({ messages: formattedMessages }, config, {
callbacks: {
[Callback.TOOL_ERROR]: (graph, error, toolId) => {
logger.error(`[Responses API] Tool Error "${toolId}"`, error);
},
},
});
// Record token usage against balance
const balanceConfig = getBalanceConfig(appConfig);
const transactionsConfig = getTransactionsConfig(appConfig);
recordCollectedUsage(
{
spendTokens: db.spendTokens,
spendStructuredTokens: db.spendStructuredTokens,
pricing: { getMultiplier: db.getMultiplier, getCacheMultiplier: db.getCacheMultiplier },
bulkWriteOps: { insertMany: db.bulkInsertTransactions, updateBalance: db.updateBalance },
},
{
user: userId,
conversationId,
collectedUsage,
context: 'message',
messageId: responseId,
balance: balanceConfig,
transactions: transactionsConfig,
model: primaryConfig.model || agent.model_parameters?.model,
},
).catch((err) => {
logger.error('[Responses API] Error recording usage:', err);
});
// Finalize the stream
finalizeStream();
res.end();
const duration = Date.now() - requestStartTime;
logger.debug(`[Responses API] Request ${responseId} completed in ${duration}ms (streaming)`);
// Save to database if store: true
if (request.store === true) {
try {
// Save conversation
await saveConversation(req, conversationId, agentId, agent);
// Save input messages
await saveInputMessages(req, conversationId, inputMessages, agentId);
// Build response for saving (use tracker with buildResponse for streaming)
const finalResponse = buildResponse(context, tracker, 'completed');
await saveResponseOutput(req, conversationId, responseId, finalResponse, agentId);
logger.debug(
`[Responses API] Stored response ${responseId} in conversation ${conversationId}`,
);
} catch (saveError) {
logger.error('[Responses API] Error saving response:', saveError);
// Don't fail the request if saving fails
}
}
// Wait for artifact processing after response ends (non-blocking)
if (artifactPromises.length > 0) {
Promise.all(artifactPromises).catch((artifactError) => {
logger.warn('[Responses API] Error processing artifacts:', artifactError);
});
}
} else {
const aggregatorHandlers = createAggregatorEventHandlers(aggregator);
// Collect usage for balance tracking
const collectedUsage = [];
/** @type {Promise<import('librechat-data-provider').TAttachment | null>[]} */
const artifactPromises = [];
const toolEndCallback = createToolEndCallback({ req, res, artifactPromises, streamId: null });
const toolExecuteOptions = {
loadTools: async (toolNames, agentId) => {
const ctx =
agentToolContexts.get(agentId) ?? agentToolContexts.get(primaryConfig.id) ?? {};
const result = await loadToolsForExecution({
req,
res,
toolNames,
agent: ctx.agent ?? agent,
signal: abortController.signal,
toolRegistry: ctx.toolRegistry,
userMCPAuthMap: ctx.userMCPAuthMap,
tool_resources: ctx.tool_resources,
actionsEnabled: ctx.actionsEnabled,
});
return enrichLoadedToolsWithAgentContext({
result,
req,
ctx,
});
},
toolEndCallback,
...getSkillToolDeps(),
};
const handlers = {
on_message_delta: aggregatorHandlers.on_message_delta,
on_reasoning_delta: aggregatorHandlers.on_reasoning_delta,
on_run_step: aggregatorHandlers.on_run_step,
on_run_step_delta: aggregatorHandlers.on_run_step_delta,
on_chat_model_end: {
handle: (event, data, metadata) => {
aggregatorHandlers.on_chat_model_end.handle(event, data);
const usage = data?.output?.usage_metadata;
if (usage) {
const taggedUsage = markSummarizationUsage(usage, metadata);
collectedUsage.push(taggedUsage);
}
},
},
on_tool_end: new ToolEndHandler(toolEndCallback, logger),
on_run_step_completed: { handle: () => {} },
on_chain_stream: { handle: () => {} },
on_chain_end: { handle: () => {} },
on_agent_update: { handle: () => {} },
on_custom_event: { handle: () => {} },
on_tool_execute: createToolExecuteHandler(toolExecuteOptions),
on_agent_log: agentLogHandlerObj,
...(summarizationConfig?.enabled !== false
? buildSummarizationHandlers({ isStreaming: false, res })
: {}),
};
const userId = req.user?.id ?? 'api-user';
const userMCPAuthMap = mergedMCPAuthMap;
const run = await createRun({
agents: runAgents,
messages: formattedMessages,
indexTokenCountMap,
initialSummary,
runId: responseId,
summarizationConfig,
appConfig,
signal: abortController.signal,
customHandlers: handlers,
requestBody: {
messageId: responseId,
conversationId,
},
user: { id: userId },
});
if (!run) {
throw new Error('Failed to create agent run');
}
const config = {
runName: 'AgentRun',
configurable: {
thread_id: conversationId,
user_id: userId,
user: createSafeUser(req.user),
requestBody: {
messageId: responseId,
conversationId,
},
...(userMCPAuthMap != null && { userMCPAuthMap }),
},
signal: abortController.signal,
streamMode: 'values',
version: 'v2',
};
await run.processStream({ messages: formattedMessages }, config, {
callbacks: {
[Callback.TOOL_ERROR]: (graph, error, toolId) => {
logger.error(`[Responses API] Tool Error "${toolId}"`, error);
},
},
});
// Record token usage against balance
const balanceConfig = getBalanceConfig(appConfig);
const transactionsConfig = getTransactionsConfig(appConfig);
recordCollectedUsage(
{
spendTokens: db.spendTokens,
spendStructuredTokens: db.spendStructuredTokens,
pricing: { getMultiplier: db.getMultiplier, getCacheMultiplier: db.getCacheMultiplier },
bulkWriteOps: { insertMany: db.bulkInsertTransactions, updateBalance: db.updateBalance },
},
{
user: userId,
conversationId,
collectedUsage,
context: 'message',
messageId: responseId,
balance: balanceConfig,
transactions: transactionsConfig,
model: primaryConfig.model || agent.model_parameters?.model,
},
).catch((err) => {
logger.error('[Responses API] Error recording usage:', err);
});
if (artifactPromises.length > 0) {
try {
await Promise.all(artifactPromises);
} catch (artifactError) {
logger.warn('[Responses API] Error processing artifacts:', artifactError);
}
}
const response = buildAggregatedResponse(context, aggregator);
if (request.store === true) {
try {
await saveConversation(req, conversationId, agentId, agent);
await saveInputMessages(req, conversationId, inputMessages, agentId);
await saveResponseOutput(req, conversationId, responseId, response, agentId);
logger.debug(
`[Responses API] Stored response ${responseId} in conversation ${conversationId}`,
);
} catch (saveError) {
logger.error('[Responses API] Error saving response:', saveError);
// Don't fail the request if saving fails
}
}
res.json(response);
const duration = Date.now() - requestStartTime;
logger.debug(
`[Responses API] Request ${responseId} completed in ${duration}ms (non-streaming)`,
);
}
} catch (error) {
const errorMessage = error instanceof Error ? error.message : 'An error occurred';
logger.error('[Responses API] Error:', error);
// Check if we already started streaming (headers sent)
if (res.headersSent) {
// Headers already sent, write error event and close
writeDone(res);
res.end();
} else {
// Forward upstream provider status codes (e.g., Anthropic 400s) instead of masking as 500
const statusCode =
typeof error?.status === 'number' && error.status >= 400 && error.status < 600
? error.status
: 500;
const errorType = statusCode >= 400 && statusCode < 500 ? 'invalid_request' : 'server_error';
sendResponsesErrorResponse(res, statusCode, errorMessage, errorType);
}
}
};
/**
* List available agents as models - GET /v1/models (also works with /v1/responses/models)
*
* Returns a list of available agents the user has remote access to.
*
* @param {import('express').Request} req
* @param {import('express').Response} res
*/
const listModels = async (req, res) => {
try {
const userId = req.user?.id;
const userRole = req.user?.role;
if (!userId) {
return sendResponsesErrorResponse(res, 401, 'Authentication required', 'auth_error');
}
// Find agents the user has remote access to (VIEW permission on REMOTE_AGENT)
const accessibleAgentIds = await findAccessibleResources({
userId,
role: userRole,
resourceType: ResourceType.REMOTE_AGENT,
requiredPermissions: PermissionBits.VIEW,
});
// Get the accessible agents
let agents = [];
if (accessibleAgentIds.length > 0) {
agents = await db.getAgents({ _id: { $in: accessibleAgentIds } });
}
// Convert to models format
const models = agents.map((agent) => ({
id: agent.id,
object: 'model',
created: Math.floor(new Date(agent.createdAt).getTime() / 1000),
owned_by: agent.author ?? 'librechat',
// Additional metadata
name: agent.name,
description: agent.description,
provider: agent.provider,
}));
res.json({
object: 'list',
data: models,
});
} catch (error) {
logger.error('[Responses API] Error listing models:', error);
sendResponsesErrorResponse(
res,
500,
error instanceof Error ? error.message : 'Failed to list models',
'server_error',
);
}
};
/**
* Get Response - GET /v1/responses/:id
*
* Retrieves a stored response by its ID.
* The response ID maps to a conversationId in LibreChat's storage.
*
* @param {import('express').Request} req
* @param {import('express').Response} res
*/
const getResponse = async (req, res) => {
try {
const responseId = req.params.id;
const userId = req.user?.id;
if (!responseId) {
return sendResponsesErrorResponse(res, 400, 'Response ID is required');
}
// The responseId could be either the response ID or the conversation ID
// Try to find a conversation with this ID
const conversation = await db.getConvo(userId, responseId);
if (!conversation) {
return sendResponsesErrorResponse(
res,
404,
`Response not found: ${responseId}`,
'not_found',
'response_not_found',
);
}
// Load messages for this conversation
const messages = await db.getMessages({ conversationId: responseId, user: userId });
if (!messages || messages.length === 0) {
return sendResponsesErrorResponse(
res,
404,
`No messages found for response: ${responseId}`,
'not_found',
'response_not_found',
);
}
// Convert messages to Open Responses output format
const output = convertMessagesToOutputItems(messages);
// Find the last assistant message for usage info
const lastAssistantMessage = messages.filter((m) => !m.isCreatedByUser).pop();
// Build the response object
const response = {
id: responseId,
object: 'response',
created_at: Math.floor(new Date(conversation.createdAt || Date.now()).getTime() / 1000),
completed_at: Math.floor(new Date(conversation.updatedAt || Date.now()).getTime() / 1000),
status: 'completed',
incomplete_details: null,
model: conversation.agentId || conversation.model || 'unknown',
previous_response_id: null,
instructions: null,
output,
error: null,
tools: [],
tool_choice: 'auto',
truncation: 'disabled',
parallel_tool_calls: true,
text: { format: { type: 'text' } },
temperature: 1,
top_p: 1,
presence_penalty: 0,
frequency_penalty: 0,
top_logprobs: null,
reasoning: null,
user: userId,
usage: lastAssistantMessage?.tokenCount
? {
input_tokens: 0,
output_tokens: lastAssistantMessage.tokenCount,
total_tokens: lastAssistantMessage.tokenCount,
}
: null,
max_output_tokens: null,
max_tool_calls: null,
store: true,
background: false,
service_tier: 'default',
metadata: {},
safety_identifier: null,
prompt_cache_key: null,
};
res.json(response);
} catch (error) {
logger.error('[Responses API] Error getting response:', error);
sendResponsesErrorResponse(
res,
500,
error instanceof Error ? error.message : 'Failed to get response',
'server_error',
);
}
};
module.exports = {
createResponse,
getResponse,
listModels,
};