LibreChat/api/server/services/ToolService.js
Ruben Talstra d99a9db3f6
feat: OAuth for Actions (#5693)
* feat: OAuth for Actions

* WIP: PoC flow state manager

* refactor: Add identifier field to token model from action schema

* chore: fix potential file type issues

* ci: fix type issue with action metadata auth

* fix: ensure FlowManagerOptions has a default ttl value

* WIP: OAUTH actions

* WIP: first pass OAuth Action

* fix: standardize identifier usage in OAuth flow handling

* fix: update token retrieval to include userId in query and use correct identifier

* refacotr: update token retrieval to use userId for OAuth token query

* feat: Tool Call Auth styling

* fix: streamline token creation and add type field to token schema

* refactor: cleanup OAuth flow by encrypting client credentials and ensuring oauth operations only run under condition

* refactor: use encrypted credentials in OAuth callback

* fix: update Token collection indexes to use expiresAt TTL index and not createdAt legacy index

* refactor: enhance Token index cleanup by improving logging and removing redundant index creation logic

* refactor: remove unused OAuth login route and related logic for improved clarity

* refactor: replace fetch with axios for OAuth token exchange and improve error handling

* refactor: better UX after authentication before oauth tool execution

* refactor: implement cleanup handlers for FlowStateManager intervals to enhance resource management

* refactor: encrypt OAuth tokens before storing and decrypt upon retrieval for enhanced security

* refactor: enhance authentication success page with improved styling and countdown feature

* refactor: add response_type parameter to OAuth redirect URI for improved compatibility

* chore: update translation.json new localizations

* chore: remove unused OGDialog import from OGDialogTemplate component

* refactor: Actions Auth using new Dialog styling, use same component with Agents/Assistants

* refactor: update removeNullishValues function to support removal of empty strings and adjust transform usage in schemas

* chore: bump version of librechat-data-provider to 0.7.6991

* refactor: integrate removeNullishValues function to clean metadata before encryption in agent and assistant routes

* refactor: update OAuth input fields to use 'password' type for better security

* refactor: update localization placeholders for sign-in message to use double curly braces

* refactor: add access_type parameter for offline access in createActionTool function

* refactor: implement handleOAuthToken function for token management and encryption

* feat: refresh token support

* refactor: add default expiration for access token and error handling for missing token

* feat: localizations for ActionAuth

* refactor: set refresh token expiration to null to not expire if expiry never given

* fix: prevent crash fromerror within async handleAbortError in AskController, EditController, and AgentController

* feat: Action Callback URL

* 🌍 i18n: Update translation.json with latest translations

* refactor: handle errors in flow state checking to prevent unhandled promise rejections

* fix: improve flow state concurrency to prevent multiple token creation calls

* refactor: RequestExecutor to use separate axios instance

* refactor: improve concurrency flows by keeping completed state until TTL expiry

* refactor: increase TTL for flow state management and adjust monitoring interval

* ci: mock axios instance creation in actions spec

* feat: add Babel and Jest configuration files; implement FlowStateManager tests with concurrency handling

* chore: add disableOAuth prop to ActionsAuth (not implemented for Assistants yet)

---------

Co-authored-by: Danny Avila <danny@librechat.ai>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
2025-02-10 15:56:08 -05:00

586 lines
18 KiB
JavaScript

const fs = require('fs');
const path = require('path');
const { zodToJsonSchema } = require('zod-to-json-schema');
const { tool: toolFn, Tool, DynamicStructuredTool } = require('@langchain/core/tools');
const { Calculator } = require('@langchain/community/tools/calculator');
const {
Tools,
ErrorTypes,
ContentTypes,
imageGenTools,
EModelEndpoint,
actionDelimiter,
ImageVisionTool,
openapiToFunction,
AgentCapabilities,
validateAndParseOpenAPISpec,
} = require('librechat-data-provider');
const { processFileURL, uploadImageBuffer } = require('~/server/services/Files/process');
const { createYouTubeTools, manifestToolMap, toolkits } = require('~/app/clients/tools');
const { loadActionSets, createActionTool, domainParser } = require('./ActionService');
const { getEndpointsConfig } = require('~/server/services/Config');
const { recordUsage } = require('~/server/services/Threads');
const { loadTools } = require('~/app/clients/tools/util');
const { redactMessage } = require('~/config/parsers');
const { sleep } = require('~/server/utils');
const { logger } = require('~/config');
/**
* Loads and formats tools from the specified tool directory.
*
* The directory is scanned for JavaScript files, excluding any files in the filter set.
* For each file, it attempts to load the file as a module and instantiate a class, if it's a subclass of `StructuredTool`.
* Each tool instance is then formatted to be compatible with the OpenAI Assistant.
* Additionally, instances of LangChain Tools are included in the result.
*
* @param {object} params - The parameters for the function.
* @param {string} params.directory - The directory path where the tools are located.
* @param {Array<string>} [params.adminFilter=[]] - Array of admin-defined tool keys to exclude from loading.
* @param {Array<string>} [params.adminIncluded=[]] - Array of admin-defined tool keys to include from loading.
* @returns {Record<string, FunctionTool>} An object mapping each tool's plugin key to its instance.
*/
function loadAndFormatTools({ directory, adminFilter = [], adminIncluded = [] }) {
const filter = new Set([...adminFilter]);
const included = new Set(adminIncluded);
const tools = [];
/* Structured Tools Directory */
const files = fs.readdirSync(directory);
if (included.size > 0 && adminFilter.length > 0) {
logger.warn(
'Both `includedTools` and `filteredTools` are defined; `filteredTools` will be ignored.',
);
}
for (const file of files) {
const filePath = path.join(directory, file);
if (!file.endsWith('.js') || (filter.has(file) && included.size === 0)) {
continue;
}
let ToolClass = null;
try {
ToolClass = require(filePath);
} catch (error) {
logger.error(`[loadAndFormatTools] Error loading tool from ${filePath}:`, error);
continue;
}
if (!ToolClass || !(ToolClass.prototype instanceof Tool)) {
continue;
}
let toolInstance = null;
try {
toolInstance = new ToolClass({ override: true });
} catch (error) {
logger.error(
`[loadAndFormatTools] Error initializing \`${file}\` tool; if it requires authentication, is the \`override\` field configured?`,
error,
);
continue;
}
if (!toolInstance) {
continue;
}
if (filter.has(toolInstance.name) && included.size === 0) {
continue;
}
if (included.size > 0 && !included.has(file) && !included.has(toolInstance.name)) {
continue;
}
const formattedTool = formatToOpenAIAssistantTool(toolInstance);
tools.push(formattedTool);
}
/** Basic Tools; schema: { input: string } */
const basicToolInstances = [new Calculator(), ...createYouTubeTools({ override: true })];
for (const toolInstance of basicToolInstances) {
const formattedTool = formatToOpenAIAssistantTool(toolInstance);
let toolName = formattedTool[Tools.function].name;
toolName = toolkits.some((toolkit) => toolName.startsWith(toolkit.pluginKey))
? toolName.split('_')[0]
: toolName;
if (filter.has(toolName) && included.size === 0) {
continue;
}
if (included.size > 0 && !included.has(toolName)) {
continue;
}
tools.push(formattedTool);
}
tools.push(ImageVisionTool);
return tools.reduce((map, tool) => {
map[tool.function.name] = tool;
return map;
}, {});
}
/**
* Formats a `StructuredTool` instance into a format that is compatible
* with OpenAI's ChatCompletionFunctions. It uses the `zodToJsonSchema`
* function to convert the schema of the `StructuredTool` into a JSON
* schema, which is then used as the parameters for the OpenAI function.
*
* @param {StructuredTool} tool - The StructuredTool to format.
* @returns {FunctionTool} The OpenAI Assistant Tool.
*/
function formatToOpenAIAssistantTool(tool) {
return {
type: Tools.function,
[Tools.function]: {
name: tool.name,
description: tool.description,
parameters: zodToJsonSchema(tool.schema),
},
};
}
/**
* Processes the required actions by calling the appropriate tools and returning the outputs.
* @param {OpenAIClient} client - OpenAI or StreamRunManager Client.
* @param {RequiredAction} requiredActions - The current required action.
* @returns {Promise<ToolOutput>} The outputs of the tools.
*/
const processVisionRequest = async (client, currentAction) => {
if (!client.visionPromise) {
return {
tool_call_id: currentAction.toolCallId,
output: 'No image details found.',
};
}
/** @type {ChatCompletion | undefined} */
const completion = await client.visionPromise;
if (completion && completion.usage) {
recordUsage({
user: client.req.user.id,
model: client.req.body.model,
conversationId: (client.responseMessage ?? client.finalMessage).conversationId,
...completion.usage,
});
}
const output = completion?.choices?.[0]?.message?.content ?? 'No image details found.';
return {
tool_call_id: currentAction.toolCallId,
output,
};
};
/**
* Processes return required actions from run.
* @param {OpenAIClient | StreamRunManager} client - OpenAI (legacy) or StreamRunManager Client.
* @param {RequiredAction[]} requiredActions - The required actions to submit outputs for.
* @returns {Promise<ToolOutputs>} The outputs of the tools.
*/
async function processRequiredActions(client, requiredActions) {
logger.debug(
`[required actions] user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id}`,
requiredActions,
);
const toolDefinitions = client.req.app.locals.availableTools;
const seenToolkits = new Set();
const tools = requiredActions
.map((action) => {
const toolName = action.tool;
const toolDef = toolDefinitions[toolName];
if (toolDef && !manifestToolMap[toolName]) {
for (const toolkit of toolkits) {
if (seenToolkits.has(toolkit.pluginKey)) {
return;
} else if (toolName.startsWith(`${toolkit.pluginKey}_`)) {
seenToolkits.add(toolkit.pluginKey);
return toolkit.pluginKey;
}
}
}
return toolName;
})
.filter((toolName) => !!toolName);
const { loadedTools } = await loadTools({
user: client.req.user.id,
model: client.req.body.model ?? 'gpt-4o-mini',
tools,
functions: true,
endpoint: client.req.body.endpoint,
options: {
processFileURL,
req: client.req,
uploadImageBuffer,
openAIApiKey: client.apiKey,
fileStrategy: client.req.app.locals.fileStrategy,
returnMetadata: true,
},
});
const ToolMap = loadedTools.reduce((map, tool) => {
map[tool.name] = tool;
return map;
}, {});
const promises = [];
/** @type {Action[]} */
let actionSets = [];
let isActionTool = false;
const ActionToolMap = {};
const ActionBuildersMap = {};
for (let i = 0; i < requiredActions.length; i++) {
const currentAction = requiredActions[i];
if (currentAction.tool === ImageVisionTool.function.name) {
promises.push(processVisionRequest(client, currentAction));
continue;
}
let tool = ToolMap[currentAction.tool] ?? ActionToolMap[currentAction.tool];
const handleToolOutput = async (output) => {
requiredActions[i].output = output;
/** @type {FunctionToolCall & PartMetadata} */
const toolCall = {
function: {
name: currentAction.tool,
arguments: JSON.stringify(currentAction.toolInput),
output,
},
id: currentAction.toolCallId,
type: 'function',
progress: 1,
action: isActionTool,
};
const toolCallIndex = client.mappedOrder.get(toolCall.id);
if (imageGenTools.has(currentAction.tool)) {
const imageOutput = output;
toolCall.function.output = `${currentAction.tool} displayed an image. All generated images are already plainly visible, so don't repeat the descriptions in detail. Do not list download links as they are available in the UI already. The user may download the images by clicking on them, but do not mention anything about downloading to the user.`;
// Streams the "Finished" state of the tool call in the UI
client.addContentData({
[ContentTypes.TOOL_CALL]: toolCall,
index: toolCallIndex,
type: ContentTypes.TOOL_CALL,
});
await sleep(500);
/** @type {ImageFile} */
const imageDetails = {
...imageOutput,
...currentAction.toolInput,
};
const image_file = {
[ContentTypes.IMAGE_FILE]: imageDetails,
type: ContentTypes.IMAGE_FILE,
// Replace the tool call output with Image file
index: toolCallIndex,
};
client.addContentData(image_file);
// Update the stored tool call
client.seenToolCalls && client.seenToolCalls.set(toolCall.id, toolCall);
return {
tool_call_id: currentAction.toolCallId,
output: toolCall.function.output,
};
}
client.seenToolCalls && client.seenToolCalls.set(toolCall.id, toolCall);
client.addContentData({
[ContentTypes.TOOL_CALL]: toolCall,
index: toolCallIndex,
type: ContentTypes.TOOL_CALL,
// TODO: to append tool properties to stream, pass metadata rest to addContentData
// result: tool.result,
});
return {
tool_call_id: currentAction.toolCallId,
output,
};
};
if (!tool) {
// throw new Error(`Tool ${currentAction.tool} not found.`);
if (!actionSets.length) {
actionSets =
(await loadActionSets({
assistant_id: client.req.body.assistant_id,
})) ?? [];
}
let actionSet = null;
let currentDomain = '';
for (let action of actionSets) {
const domain = await domainParser(client.req, action.metadata.domain, true);
if (currentAction.tool.includes(domain)) {
currentDomain = domain;
actionSet = action;
break;
}
}
if (!actionSet) {
// TODO: try `function` if no action set is found
// throw new Error(`Tool ${currentAction.tool} not found.`);
continue;
}
let builders = ActionBuildersMap[actionSet.metadata.domain];
if (!builders) {
const validationResult = validateAndParseOpenAPISpec(actionSet.metadata.raw_spec);
if (!validationResult.spec) {
throw new Error(
`Invalid spec: user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id}`,
);
}
const { requestBuilders } = openapiToFunction(validationResult.spec);
ActionToolMap[actionSet.metadata.domain] = requestBuilders;
builders = requestBuilders;
}
const functionName = currentAction.tool.replace(`${actionDelimiter}${currentDomain}`, '');
const requestBuilder = builders[functionName];
if (!requestBuilder) {
// throw new Error(`Tool ${currentAction.tool} not found.`);
continue;
}
tool = await createActionTool({ action: actionSet, requestBuilder });
if (!tool) {
logger.warn(
`Invalid action: user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id} | toolName: ${currentAction.tool}`,
);
throw new Error(`{"type":"${ErrorTypes.INVALID_ACTION}"}`);
}
isActionTool = !!tool;
ActionToolMap[currentAction.tool] = tool;
}
if (currentAction.tool === 'calculator') {
currentAction.toolInput = currentAction.toolInput.input;
}
const handleToolError = (error) => {
logger.error(
`tool_call_id: ${currentAction.toolCallId} | Error processing tool ${currentAction.tool}`,
error,
);
return {
tool_call_id: currentAction.toolCallId,
output: `Error processing tool ${currentAction.tool}: ${redactMessage(error.message, 256)}`,
};
};
try {
const promise = tool
._call(currentAction.toolInput)
.then(handleToolOutput)
.catch(handleToolError);
promises.push(promise);
} catch (error) {
const toolOutputError = handleToolError(error);
promises.push(Promise.resolve(toolOutputError));
}
}
return {
tool_outputs: await Promise.all(promises),
};
}
/**
* Processes the runtime tool calls and returns the tool classes.
* @param {Object} params - Run params containing user and request information.
* @param {ServerRequest} params.req - The request object.
* @param {ServerResponse} params.res - The request object.
* @param {Agent} params.agent - The agent to load tools for.
* @param {string | undefined} [params.openAIApiKey] - The OpenAI API key.
* @returns {Promise<{ tools?: StructuredTool[] }>} The agent tools.
*/
async function loadAgentTools({ req, res, agent, tool_resources, openAIApiKey }) {
if (!agent.tools || agent.tools.length === 0) {
return {};
}
const endpointsConfig = await getEndpointsConfig(req);
const capabilities = endpointsConfig?.[EModelEndpoint.agents]?.capabilities ?? [];
const areToolsEnabled = capabilities.includes(AgentCapabilities.tools);
if (!areToolsEnabled) {
logger.debug('Tools are not enabled for this agent.');
return {};
}
const isFileSearchEnabled = capabilities.includes(AgentCapabilities.file_search);
const isCodeEnabled = capabilities.includes(AgentCapabilities.execute_code);
const areActionsEnabled = capabilities.includes(AgentCapabilities.actions);
const _agentTools = agent.tools?.filter((tool) => {
if (tool === Tools.file_search && !isFileSearchEnabled) {
return false;
} else if (tool === Tools.execute_code && !isCodeEnabled) {
return false;
}
return true;
});
if (!_agentTools || _agentTools.length === 0) {
return {};
}
const { loadedTools, toolContextMap } = await loadTools({
agent,
functions: true,
user: req.user.id,
tools: _agentTools,
options: {
req,
openAIApiKey,
tool_resources,
processFileURL,
uploadImageBuffer,
returnMetadata: true,
fileStrategy: req.app.locals.fileStrategy,
},
});
const agentTools = [];
for (let i = 0; i < loadedTools.length; i++) {
const tool = loadedTools[i];
if (tool.name && (tool.name === Tools.execute_code || tool.name === Tools.file_search)) {
agentTools.push(tool);
continue;
}
if (tool.mcp === true) {
agentTools.push(tool);
continue;
}
if (tool instanceof DynamicStructuredTool) {
agentTools.push(tool);
continue;
}
const toolDefinition = {
name: tool.name,
schema: tool.schema,
description: tool.description,
};
if (imageGenTools.has(tool.name)) {
toolDefinition.responseFormat = 'content_and_artifact';
}
const toolInstance = toolFn(async (...args) => {
return tool['_call'](...args);
}, toolDefinition);
agentTools.push(toolInstance);
}
const ToolMap = loadedTools.reduce((map, tool) => {
map[tool.name] = tool;
return map;
}, {});
if (!areActionsEnabled) {
return {
tools: agentTools,
toolContextMap,
};
}
let actionSets = [];
const ActionToolMap = {};
for (const toolName of _agentTools) {
if (ToolMap[toolName]) {
continue;
}
if (!actionSets.length) {
actionSets = (await loadActionSets({ agent_id: agent.id })) ?? [];
}
let actionSet = null;
let currentDomain = '';
for (let action of actionSets) {
const domain = await domainParser(req, action.metadata.domain, true);
if (toolName.includes(domain)) {
currentDomain = domain;
actionSet = action;
break;
}
}
if (!actionSet) {
continue;
}
const validationResult = validateAndParseOpenAPISpec(actionSet.metadata.raw_spec);
if (validationResult.spec) {
const { requestBuilders, functionSignatures, zodSchemas } = openapiToFunction(
validationResult.spec,
true,
);
const functionName = toolName.replace(`${actionDelimiter}${currentDomain}`, '');
const functionSig = functionSignatures.find((sig) => sig.name === functionName);
const requestBuilder = requestBuilders[functionName];
const zodSchema = zodSchemas[functionName];
if (requestBuilder) {
const tool = await createActionTool({
req,
res,
action: actionSet,
requestBuilder,
zodSchema,
name: toolName,
description: functionSig.description,
});
if (!tool) {
logger.warn(
`Invalid action: user: ${req.user.id} | agent_id: ${agent.id} | toolName: ${toolName}`,
);
throw new Error(`{"type":"${ErrorTypes.INVALID_ACTION}"}`);
}
agentTools.push(tool);
ActionToolMap[toolName] = tool;
}
}
}
if (_agentTools.length > 0 && agentTools.length === 0) {
logger.warn(`No tools found for the specified tool calls: ${_agentTools.join(', ')}`);
return {};
}
return {
tools: agentTools,
toolContextMap,
};
}
module.exports = {
loadAgentTools,
loadAndFormatTools,
processRequiredActions,
formatToOpenAIAssistantTool,
};