LibreChat/api/server/controllers/agents/responses.js
Dustin Healy 3f0a1ec8d9
🛡️ fix: Run message-filter PII patterns on a linear-time regex engine (ReDoS) (#14554)
* 🛡️ fix: Run message-filter PII patterns on a linear-time regex engine

The messageFilter.pii middleware compiled admin-configured customPatterns with the native RegExp engine and ran them synchronously against every message on the shared event loop, so a catastrophic-backtracking pattern such as (a+)+$ could stall the entire process (native RegExp takes tens of seconds at roughly 32 characters) and take the instance down for every user.

Compile these patterns with RE2JS, a linear-time RE2 port with no native addon, so catastrophic backtracking is impossible regardless of the pattern rather than something the code tries to detect. Patterns using features RE2 does not support, such as backreferences, fail to compile and are dropped and logged exactly as an invalid pattern already is. The filter only tests for a match, so this is a drop-in engine swap with no behavior change for valid patterns.

* 🛡️ fix: Reject RE2-incompatible messageFilter patterns at config load

The customPatterns regex was validated with native RegExp at config load, but the runtime now compiles it with a linear-time engine (RE2) that does not support backreferences or lookaround. Such a pattern passed validation, then failed to compile and was silently dropped at request time, quietly removing PII protection after upgrade.

Reject backreferences and lookaround during config validation with an explicit message, and document RE2 syntax in the example config instead of "JavaScript-flavor". The runtime engine remains the authoritative boundary and still drops-and-logs anything this load-time check misses.

* 🧹 test: Use direct MessageFilterPiiConfig annotations in the PII specs

The added ReDoS cases satisfy the exported MessageFilterPiiConfig type directly, so the `as unknown as` assertions were unnecessary. Annotate the config objects directly, matching the repo's type-safety guidance.

* 🧹 fix: Reject named backreferences in messageFilter patterns at config load

Extend the config-load check to also reject named backreferences (\k<name>), which are valid JavaScript regex but unsupported by the linear-time runtime engine, so they surface at load rather than being dropped at request time. Together with the existing numeric-backreference and lookaround checks this covers the RE2-incompatible construct set; the runtime engine remains authoritative.

* 🛡️ fix: Preserve Unicode whitespace matching in messageFilter starter patterns

RE2's \s is ASCII-only, so after the engine swap the built-in api-key and Bearer starters no
longer matched a secret separated by non-ASCII whitespace (e.g. a non-breaking space), which
native RegExp did match. Broaden the whitespace classes to [\s\p{Zs}] so those patterns keep
their original coverage, and add a regression test for a non-breaking-space separator.

* 🛡️ fix: Validate messageFilter patterns with the RE2 engine at config load

Replace the syntax blacklist (numeric/named backreferences, lookaround) with authoritative
validation: config load now compiles each custom pattern with the same linear-time engine the
runtime uses, so any RE2-incompatible construct (including control escapes like \cA) is rejected
at load with a clear error instead of being silently dropped at request time.

The validator is swappable and defaults to native RegExp so browser builds add no engine; the
server wires the RE2-backed check at startup via configureMessageFilterRegexValidator in both
entry points.

* 🛡️ fix: Match the full whitespace set in messageFilter starter patterns

RE2's `\s` omits the vertical tab and `\p{Zs}` omits U+2028, U+2029, and
U+FEFF, so a separator built from one of those characters slipped past the
`api-key` and `Bearer` starter patterns and reached the model. Broaden the
starter whitespace class to the full JavaScript whitespace set so those
separators are covered again.

* fix: fail closed when messageFilter.pii compiles to zero patterns

DB and admin config overrides bypass the RE2 schema validation (it only
runs at YAML load), so an override whose only pattern is RE2-incompatible
was dropped at compile time, left zero patterns, and let the request
through. compile() now returns a failClosed flag when a config declared
patterns but every one failed to compile; the middleware returns 400 and
findPiiMatchInMessages returns a distinct misconfigured match that the
OpenAI and Responses controllers surface with an admin-facing message.

* 🛡️ fix: Fail closed when any messageFilter.pii custom pattern drops

compile() previously set failClosed only when every pattern dropped (patterns.length === 0 && dropped > 0). With the default starters present, a single RE2-incompatible custom override incremented dropped but left patterns.length > 0, so the filter silently enforced only the surviving subset and text matching only the dropped rule passed.

failClosed now keys off dropped > 0, so any dropped custom pattern blocks with the misconfigured 400. YAML patterns are RE2-validated at load, so dropped stays 0 for valid configs and only unvalidated DB or admin overrides can trip it. Reframed the two keeps-others-active specs to assert fail-closed and added a default-starters partial-drop regression.

* 🧹 fix: Correct the misconfigured JSDoc and drop redundant casts in the PII specs

The misconfigured flag now means any configured custom pattern failed to compile, not that every pattern failed, so its JSDoc on PiiMatch is updated to match. The partial-drop regressions now use direct MessageFilterPiiConfig annotations instead of as-unknown-as casts, keeping the specs type-checked, consistent with the rest of the suite.
2026-08-05 13:42:18 -04:00

1296 lines
42 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,
applyContextToAgent,
buildToolSet,
AgentRunEnvelopeError,
createAgentRunEnvelope,
buildAgentScopedContext,
buildAgentContextAttachmentsByAgentId,
createSafeUser,
initializeAgent,
loadSkillStates,
getBalanceConfig,
injectSkillPrimes,
extractManualSkills,
recordCollectedUsage,
createSubagentUsageSink,
getTransactionsConfig,
findPiiMatchInMessages,
discoverConnectedAgents,
createToolExecuteHandler,
getRemoteAgentPermissions,
resolveAgentScopedSkillIds,
// Responses API
writeDone,
buildResponse,
generateResponseId,
isValidationFailure,
emitResponseCreated,
createResponseContext,
createResponseTracker,
setupStreamingResponse,
emitResponseInProgress,
convertInputToMessages,
validateResponseRequest,
buildAggregatedResponse,
createResponseAggregator,
sendResponsesErrorResponse,
createResponsesEventHandlers,
createAggregatorEventHandlers,
stripActivityLabelParts,
} = 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 { filterFilesByAgentAccess } = require('~/server/services/Files/permissions');
const { resolveConfigServers, getAccessibleMcpServerNames } = require('~/server/services/MCP');
const { getMCPManager } = require('~/config');
const { logViolation } = require('~/cache');
const db = require('~/models');
const filterFilesByRemoteAgentAccess = (params) =>
filterFilesByAgentAccess({ ...params, resourceType: ResourceType.REMOTE_AGENT });
/**
* 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,
accessibleMcpServerNames,
}) {
const agent = { id: agentId, tools, provider, model, tool_options };
try {
return await loadAgentTools({
req,
res,
agent,
signal,
tool_resources,
agentResourceType: ResourceType.REMOTE_AGENT,
definitionsOnly,
accessibleMcpServerNames,
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;
}
/**
* Runs a validated Responses envelope in the current process.
* Express remains runtime-only state while the envelope is the portable run input.
*
* @param {import('@librechat/api').ResponsesRunEnvelope} envelope
* @param {{req: import('express').Request, res: import('express').Response}} runtime
*/
const executeResponse = async (envelope, { req, res }) => {
const appConfig = req.config;
const requestStartTime = envelope.receivedAt;
const request = envelope.payload;
const { principal } = envelope;
// The local executor keeps the current Express-dependent initialization path,
// but all request-body reads now observe the detached envelope payload.
req.body = 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(principal.userId, 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 ?? {},
};
const dbMethods = {
getConvoFiles: db.getConvoFiles,
getFiles: db.getFiles,
filterFilesByAgentAccess: filterFilesByRemoteAgentAccess,
getUserKey: db.getUserKey,
getMessages: db.getMessages,
getAccessibleMcpServerNames,
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 = request.ephemeralAgent?.skills === true;
const accessibleSkillIds = skillsCapabilityEnabled
? withDeploymentSkillIds(
await findAccessibleResources({
userId: principal.userId,
role: principal.role,
resourceType: ResourceType.SKILL,
requiredPermissions: PermissionBits.VIEW,
}),
)
: [];
const editableSkillIds = skillsCapabilityEnabled
? await findAccessibleResources({
userId: principal.userId,
role: principal.role,
resourceType: ResourceType.SKILL,
requiredPermissions: PermissionBits.EDIT,
})
: [];
const skillCreateAllowed = skillsCapabilityEnabled
? await getSkillToolDeps().canCreateSkill({ req })
: false;
const { skillStates, defaultActiveOnShare } = await loadSkillStates({
userId: principal.userId,
appConfig,
getUserById: db.getUserById,
accessibleSkillIds,
});
const manualSkills = extractManualSkills(request);
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),
backgroundToolsAvailable: enabledCapabilities.has(AgentCapabilities.run_in_background),
toolIntentsAvailable: enabledCapabilities.has(AgentCapabilities.tool_intents),
statefulSessionsAvailable: enabledCapabilities.has(
AgentCapabilities.stateful_code_sessions,
),
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,
* requestScopedConnections?: import('@librechat/api').RequestScopedMCPConnectionStore,
* 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),
backgroundToolsAvailable: enabledCapabilities.has(AgentCapabilities.run_in_background),
toolIntentsAvailable: enabledCapabilities.has(AgentCapabilities.tool_intents),
statefulSessionsAvailable: enabledCapabilities.has(
AgentCapabilities.stateful_code_sessions,
),
},
{
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;
const agentContextAttachmentsByAgentId = buildAgentContextAttachmentsByAgentId(runAgents);
const agentScopedContext = await buildAgentScopedContext({
agentIds: runAgents.map(({ id }) => id),
attachmentsByAgentId: agentContextAttachmentsByAgentId,
req,
});
const mcpManager = getMCPManager();
const configServers = await resolveConfigServers(req);
await Promise.all(
runAgents.map((runAgent) =>
applyContextToAgent({
agent: runAgent,
agentId: runAgent.id,
logger,
mcpManager,
configServers,
sharedRunContext: agentScopedContext.get(runAgent.id) ?? '',
}),
),
);
// 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 = principal.userId;
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,
piiHit.misconfigured
? 'Message filtering is misconfigured; contact your administrator.'
: `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(stripActivityLabelParts(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,
agentResourceType: ResourceType.REMOTE_AGENT,
toolNames,
agent: ctx.agent ?? agent,
signal: abortController.signal,
toolRegistry: ctx.toolRegistry,
backgroundToolNames: ctx.backgroundToolNames,
intentToolNames: ctx.intentToolNames,
mcpAvailableTools: ctx.mcpAvailableTools,
requestScopedConnections: ctx.requestScopedConnections,
userMCPAuthMap: ctx.userMCPAuthMap,
tool_resources: ctx.tool_resources,
actionsEnabled: ctx.actionsEnabled,
accessibleMcpServerNames: ctx.accessibleMcpServerNames,
});
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 = principal.userId;
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 },
tenantId: principal.tenantId,
/** Bills subagent child-run model calls (reported outside the
* streamEvents loop) into the same collectedUsage array. */
subagentUsageSink: createSubagentUsageSink(collectedUsage),
});
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,
agentResourceType: ResourceType.REMOTE_AGENT,
toolNames,
agent: ctx.agent ?? agent,
signal: abortController.signal,
toolRegistry: ctx.toolRegistry,
backgroundToolNames: ctx.backgroundToolNames,
intentToolNames: ctx.intentToolNames,
mcpAvailableTools: ctx.mcpAvailableTools,
requestScopedConnections: ctx.requestScopedConnections,
userMCPAuthMap: ctx.userMCPAuthMap,
tool_resources: ctx.tool_resources,
actionsEnabled: ctx.actionsEnabled,
accessibleMcpServerNames: ctx.accessibleMcpServerNames,
});
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 = principal.userId;
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 },
tenantId: principal.tenantId,
/** Bills subagent child-run model calls (reported outside the
* streamEvents loop) into the same collectedUsage array. */
subagentUsageSink: createSubagentUsageSink(collectedUsage),
});
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 ${duration}ms (non-streaming)`,
);
}
} catch (error) {
const errorMessage = error instanceof Error ? error.message : 'An error occurred';
logger.error('[Responses API] Error:', error);
// Check if we already started streaming (headers sent)
if (res.headersSent) {
// Headers already sent, write error event and close
writeDone(res);
res.end();
} else {
// Forward upstream provider status codes (e.g., Anthropic 400s) instead of masking as 500
const statusCode =
typeof error?.status === 'number' && error.status >= 400 && error.status < 600
? error.status
: 500;
const errorType = statusCode >= 400 && statusCode < 500 ? 'invalid_request' : 'server_error';
sendResponsesErrorResponse(res, statusCode, errorMessage, errorType);
}
}
};
/**
* Open Responses ingress adapter for agents.
* Authentication and remote-agent authorization have already run in route middleware.
*
* POST /v1/responses
*
* @param {import('express').Request} req
* @param {import('express').Response} res
*/
const createResponse = async (req, res) => {
const receivedAt = Date.now();
const validation = validateResponseRequest(req.body);
if (isValidationFailure(validation)) {
return sendResponsesErrorResponse(res, 400, validation.error);
}
let envelope;
try {
envelope = createAgentRunEnvelope({
protocol: 'responses',
requestId: req.requestId ?? req.id ?? `agent-run-${nanoid()}`,
receivedAt,
principal: req.user,
payload: validation.request,
});
} catch (error) {
if (error instanceof AgentRunEnvelopeError) {
return sendResponsesErrorResponse(res, 400, error.message, 'invalid_request');
}
throw error;
}
return executeResponse(envelope, { req, res });
};
/**
* 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,
};