LibreChat/api/server/services/Files/process.js
Danny Avila d6a17784dc
🔗 feat: Agent Chain (Mixture-of-Agents) (#6374)
* wip: first pass, dropdown for selecting sequential agents

* refactor: Improve agent selection logic and enhance performance in SequentialAgents component

* wip: seq. agents working ideas

* wip: sequential agents style change

* refactor: move agent form options/submission outside of AgentConfig

* refactor: prevent repeating code

* refactor: simplify current agent display in SequentialAgents component

* feat: persist  form value handling in AgentSelect component for agent_ids

* feat: first pass, sequential agnets agent update

* feat: enhance message display with agent updates and empty text handling

* chore: update Icon component to use EModelEndpoint for agent endpoints

* feat: update content type checks in BaseClient to use constants for better readability

* feat: adjust max context tokens calculation to use 90% of the model's max tokens

* feat: first pass, agent run message pruning

* chore: increase max listeners for abort controller to prevent memory leaks

* feat: enhance runAgent function to include current index count map for improved token tracking

* chore: update @librechat/agents dependency to version 2.2.5

* feat: update icons and style of SequentialAgents component for improved UI consistency

* feat: add AdvancedButton and AdvancedPanel components for enhanced agent settings navigation, update styling for agent form

* chore: adjust minimum height of AdvancedPanel component for better layout consistency

* chore: update @librechat/agents dependency to version 2.2.6

* feat: enhance message formatting by incorporating tool set into agent message processing, in order to allow better mix/matching of agents (as tool calls for tools not found in set will be stringified)

* refactor: reorder components in AgentConfig for improved readability and maintainability

* refactor: enhance layout of AgentUpdate component for improved visual structure

* feat: add DeepSeek provider to Bedrock settings and schemas

* feat: enhance link styling in mobile.css for better visibility and accessibility

* fix: update banner model import in update banner script; export Banner model

* refactor: `duplicateAgentHandler` to include tool_resources only for OCR context files

* feat: add 'qwen-vl' to visionModels for enhanced model support

* fix: change image format from JPEG to PNG in DALLE3 response

* feat: reorganize Advanced components and add localizations

* refactor: simplify JSX structure in AgentChain component to defer container styling to parent

* feat: add FormInput component for reusable input handling

* feat: make agent recursion limit configurable from builder

* feat: add support for agent capabilities chain in AdvancedPanel and update data-provider version

* feat: add maxRecursionLimit configuration for agents and update related documentation

* fix: update CONFIG_VERSION to 1.2.3 in data provider configuration

* feat: replace recursion limit input with MaxAgentSteps component and enhance input handling

* feat: enhance AgentChain component with hover card for additional information and update related labels

* fix: pass request and response objects to `createActionTool` when using assistant actions to prevent auth error

* feat: update AgentChain component layout to include agent count display

* feat: increase default max listeners and implement capability check function for agent chain

* fix: update link styles in mobile.css for better visibility in dark mode

* chore: temp. remove agents package while bumping shared packages

* chore: update @langchain/google-genai package to version 0.1.11

* chore: update @langchain/google-vertexai package to version 0.2.2

* chore: add @librechat/agents package at version 2.2.8

* feat: add deepseek.r1 model with token rate and context values for bedrock
2025-03-17 16:43:44 -04:00

960 lines
29 KiB
JavaScript

const fs = require('fs');
const path = require('path');
const mime = require('mime');
const { v4 } = require('uuid');
const {
isUUID,
megabyte,
FileContext,
FileSources,
imageExtRegex,
EModelEndpoint,
EToolResources,
mergeFileConfig,
hostImageIdSuffix,
AgentCapabilities,
checkOpenAIStorage,
removeNullishValues,
hostImageNamePrefix,
isAssistantsEndpoint,
} = require('librechat-data-provider');
const { EnvVar } = require('@librechat/agents');
const {
convertImage,
resizeAndConvert,
resizeImageBuffer,
} = require('~/server/services/Files/images');
const { addResourceFileId, deleteResourceFileId } = require('~/server/controllers/assistants/v2');
const { addAgentResourceFile, removeAgentResourceFiles } = require('~/models/Agent');
const { getOpenAIClient } = require('~/server/controllers/assistants/helpers');
const { createFile, updateFileUsage, deleteFiles } = require('~/models/File');
const { loadAuthValues } = require('~/server/services/Tools/credentials');
const { checkCapability } = require('~/server/services/Config');
const { LB_QueueAsyncCall } = require('~/server/utils/queue');
const { getStrategyFunctions } = require('./strategies');
const { determineFileType } = require('~/server/utils');
const { logger } = require('~/config');
/**
*
* @param {Array<MongoFile>} files
* @param {Array<string>} [fileIds]
* @returns
*/
const processFiles = async (files, fileIds) => {
const promises = [];
const seen = new Set();
for (let file of files) {
const { file_id } = file;
if (seen.has(file_id)) {
continue;
}
seen.add(file_id);
promises.push(updateFileUsage({ file_id }));
}
if (!fileIds) {
return await Promise.all(promises);
}
for (let file_id of fileIds) {
if (seen.has(file_id)) {
continue;
}
seen.add(file_id);
promises.push(updateFileUsage({ file_id }));
}
// TODO: calculate token cost when image is first uploaded
return await Promise.all(promises);
};
/**
* Enqueues the delete operation to the leaky bucket queue if necessary, or adds it directly to promises.
*
* @param {object} params - The passed parameters.
* @param {ServerRequest} params.req - The express request object.
* @param {MongoFile} params.file - The file object to delete.
* @param {Function} params.deleteFile - The delete file function.
* @param {Promise[]} params.promises - The array of promises to await.
* @param {string[]} params.resolvedFileIds - The array of promises to await.
* @param {OpenAI | undefined} [params.openai] - If an OpenAI file, the initialized OpenAI client.
*/
function enqueueDeleteOperation({ req, file, deleteFile, promises, resolvedFileIds, openai }) {
if (checkOpenAIStorage(file.source)) {
// Enqueue to leaky bucket
promises.push(
new Promise((resolve, reject) => {
LB_QueueAsyncCall(
() => deleteFile(req, file, openai),
[],
(err, result) => {
if (err) {
logger.error('Error deleting file from OpenAI source', err);
reject(err);
} else {
resolvedFileIds.push(file.file_id);
resolve(result);
}
},
);
}),
);
} else {
// Add directly to promises
promises.push(
deleteFile(req, file)
.then(() => resolvedFileIds.push(file.file_id))
.catch((err) => {
logger.error('Error deleting file', err);
return Promise.reject(err);
}),
);
}
}
// TODO: refactor as currently only image files can be deleted this way
// as other filetypes will not reside in public path
/**
* Deletes a list of files from the server filesystem and the database.
*
* @param {Object} params - The params object.
* @param {MongoFile[]} params.files - The file objects to delete.
* @param {ServerRequest} params.req - The express request object.
* @param {DeleteFilesBody} params.req.body - The request body.
* @param {string} [params.req.body.agent_id] - The agent ID if file uploaded is associated to an agent.
* @param {string} [params.req.body.assistant_id] - The assistant ID if file uploaded is associated to an assistant.
* @param {string} [params.req.body.tool_resource] - The tool resource if assistant file uploaded is associated to a tool resource.
*
* @returns {Promise<void>}
*/
const processDeleteRequest = async ({ req, files }) => {
const resolvedFileIds = [];
const deletionMethods = {};
const promises = [];
/** @type {Record<string, OpenAI | undefined>} */
const client = { [FileSources.openai]: undefined, [FileSources.azure]: undefined };
const initializeClients = async () => {
const openAIClient = await getOpenAIClient({
req,
overrideEndpoint: EModelEndpoint.assistants,
});
client[FileSources.openai] = openAIClient.openai;
if (!req.app.locals[EModelEndpoint.azureOpenAI]?.assistants) {
return;
}
const azureClient = await getOpenAIClient({
req,
overrideEndpoint: EModelEndpoint.azureAssistants,
});
client[FileSources.azure] = azureClient.openai;
};
if (req.body.assistant_id !== undefined) {
await initializeClients();
}
const agentFiles = [];
for (const file of files) {
const source = file.source ?? FileSources.local;
if (req.body.agent_id && req.body.tool_resource) {
agentFiles.push({
tool_resource: req.body.tool_resource,
file_id: file.file_id,
});
}
if (source === FileSources.text) {
resolvedFileIds.push(file.file_id);
continue;
}
if (checkOpenAIStorage(source) && !client[source]) {
await initializeClients();
}
const openai = client[source];
if (req.body.assistant_id && req.body.tool_resource) {
promises.push(
deleteResourceFileId({
req,
openai,
file_id: file.file_id,
assistant_id: req.body.assistant_id,
tool_resource: req.body.tool_resource,
}),
);
} else if (req.body.assistant_id) {
promises.push(openai.beta.assistants.files.del(req.body.assistant_id, file.file_id));
}
if (deletionMethods[source]) {
enqueueDeleteOperation({
req,
file,
deleteFile: deletionMethods[source],
promises,
resolvedFileIds,
openai,
});
continue;
}
const { deleteFile } = getStrategyFunctions(source);
if (!deleteFile) {
throw new Error(`Delete function not implemented for ${source}`);
}
deletionMethods[source] = deleteFile;
enqueueDeleteOperation({ req, file, deleteFile, promises, resolvedFileIds, openai });
}
if (agentFiles.length > 0) {
promises.push(
removeAgentResourceFiles({
agent_id: req.body.agent_id,
files: agentFiles,
}),
);
}
await Promise.allSettled(promises);
await deleteFiles(resolvedFileIds);
};
/**
* Processes a file URL using a specified file handling strategy. This function accepts a strategy name,
* fetches the corresponding file processing functions (for saving and retrieving file URLs), and then
* executes these functions in sequence. It first saves the file using the provided URL and then retrieves
* the URL of the saved file. If any error occurs during this process, it logs the error and throws an
* exception with an appropriate message.
*
* @param {Object} params - The parameters object.
* @param {FileSources} params.fileStrategy - The file handling strategy to use.
* Must be a value from the `FileSources` enum, which defines different file
* handling strategies (like saving to Firebase, local storage, etc.).
* @param {string} params.userId - The user's unique identifier. Used for creating user-specific paths or
* references in the file handling process.
* @param {string} params.URL - The URL of the file to be processed.
* @param {string} params.fileName - The name that will be used to save the file (including extension)
* @param {string} params.basePath - The base path or directory where the file will be saved or retrieved from.
* @param {FileContext} params.context - The context of the file (e.g., 'avatar', 'image_generation', etc.)
* @returns {Promise<MongoFile>} A promise that resolves to the DB representation (MongoFile)
* of the processed file. It throws an error if the file processing fails at any stage.
*/
const processFileURL = async ({ fileStrategy, userId, URL, fileName, basePath, context }) => {
const { saveURL, getFileURL } = getStrategyFunctions(fileStrategy);
try {
const {
bytes = 0,
type = '',
dimensions = {},
} = (await saveURL({ userId, URL, fileName, basePath })) || {};
const filepath = await getFileURL({ fileName: `${userId}/${fileName}`, basePath });
return await createFile(
{
user: userId,
file_id: v4(),
bytes,
filepath,
filename: fileName,
source: fileStrategy,
type,
context,
width: dimensions.width,
height: dimensions.height,
},
true,
);
} catch (error) {
logger.error(`Error while processing the image with ${fileStrategy}:`, error);
throw new Error(`Failed to process the image with ${fileStrategy}. ${error.message}`);
}
};
/**
* Applies the current strategy for image uploads.
* Saves file metadata to the database with an expiry TTL.
*
* @param {Object} params - The parameters object.
* @param {ServerRequest} params.req - The Express request object.
* @param {Express.Response} [params.res] - The Express response object.
* @param {ImageMetadata} params.metadata - Additional metadata for the file.
* @param {boolean} params.returnFile - Whether to return the file metadata or return response as normal.
* @returns {Promise<void>}
*/
const processImageFile = async ({ req, res, metadata, returnFile = false }) => {
const { file } = req;
const source = req.app.locals.fileStrategy;
const { handleImageUpload } = getStrategyFunctions(source);
const { file_id, temp_file_id, endpoint } = metadata;
const { filepath, bytes, width, height } = await handleImageUpload({
req,
file,
file_id,
endpoint,
});
const result = await createFile(
{
user: req.user.id,
file_id,
temp_file_id,
bytes,
filepath,
filename: file.originalname,
context: FileContext.message_attachment,
source,
type: `image/${req.app.locals.imageOutputType}`,
width,
height,
},
true,
);
if (returnFile) {
return result;
}
res.status(200).json({ message: 'File uploaded and processed successfully', ...result });
};
/**
* Applies the current strategy for image uploads and
* returns minimal file metadata, without saving to the database.
*
* @param {Object} params - The parameters object.
* @param {ServerRequest} params.req - The Express request object.
* @param {FileContext} params.context - The context of the file (e.g., 'avatar', 'image_generation', etc.)
* @param {boolean} [params.resize=true] - Whether to resize and convert the image to target format. Default is `true`.
* @param {{ buffer: Buffer, width: number, height: number, bytes: number, filename: string, type: string, file_id: string }} [params.metadata] - Required metadata for the file if resize is false.
* @returns {Promise<{ filepath: string, filename: string, source: string, type: string}>}
*/
const uploadImageBuffer = async ({ req, context, metadata = {}, resize = true }) => {
const source = req.app.locals.fileStrategy;
const { saveBuffer } = getStrategyFunctions(source);
let { buffer, width, height, bytes, filename, file_id, type } = metadata;
if (resize) {
file_id = v4();
type = `image/${req.app.locals.imageOutputType}`;
({ buffer, width, height, bytes } = await resizeAndConvert({
inputBuffer: buffer,
desiredFormat: req.app.locals.imageOutputType,
}));
filename = `${path.basename(req.file.originalname, path.extname(req.file.originalname))}.${
req.app.locals.imageOutputType
}`;
}
const fileName = `${file_id}-${filename}`;
const filepath = await saveBuffer({ userId: req.user.id, fileName, buffer });
return await createFile(
{
user: req.user.id,
file_id,
bytes,
filepath,
filename,
context,
source,
type,
width,
height,
},
true,
);
};
/**
* Applies the current strategy for file uploads.
* Saves file metadata to the database with an expiry TTL.
* Files must be deleted from the server filesystem manually.
*
* @param {Object} params - The parameters object.
* @param {ServerRequest} params.req - The Express request object.
* @param {Express.Response} params.res - The Express response object.
* @param {FileMetadata} params.metadata - Additional metadata for the file.
* @returns {Promise<void>}
*/
const processFileUpload = async ({ req, res, metadata }) => {
const isAssistantUpload = isAssistantsEndpoint(metadata.endpoint);
const assistantSource =
metadata.endpoint === EModelEndpoint.azureAssistants ? FileSources.azure : FileSources.openai;
const source = isAssistantUpload ? assistantSource : FileSources.vectordb;
const { handleFileUpload } = getStrategyFunctions(source);
const { file_id, temp_file_id } = metadata;
/** @type {OpenAI | undefined} */
let openai;
if (checkOpenAIStorage(source)) {
({ openai } = await getOpenAIClient({ req }));
}
const { file } = req;
const {
id,
bytes,
filename,
filepath: _filepath,
embedded,
height,
width,
} = await handleFileUpload({
req,
file,
file_id,
openai,
});
if (isAssistantUpload && !metadata.message_file && !metadata.tool_resource) {
await openai.beta.assistants.files.create(metadata.assistant_id, {
file_id: id,
});
} else if (isAssistantUpload && !metadata.message_file) {
await addResourceFileId({
req,
openai,
file_id: id,
assistant_id: metadata.assistant_id,
tool_resource: metadata.tool_resource,
});
}
let filepath = isAssistantUpload ? `${openai.baseURL}/files/${id}` : _filepath;
if (isAssistantUpload && file.mimetype.startsWith('image')) {
const result = await processImageFile({
req,
file,
metadata: { file_id: v4() },
returnFile: true,
});
filepath = result.filepath;
}
const result = await createFile(
{
user: req.user.id,
file_id: id ?? file_id,
temp_file_id,
bytes,
filepath,
filename: filename ?? file.originalname,
context: isAssistantUpload ? FileContext.assistants : FileContext.message_attachment,
model: isAssistantUpload ? req.body.model : undefined,
type: file.mimetype,
embedded,
source,
height,
width,
},
true,
);
res.status(200).json({ message: 'File uploaded and processed successfully', ...result });
};
/**
* Applies the current strategy for file uploads.
* Saves file metadata to the database with an expiry TTL.
* Files must be deleted from the server filesystem manually.
*
* @param {Object} params - The parameters object.
* @param {ServerRequest} params.req - The Express request object.
* @param {Express.Response} params.res - The Express response object.
* @param {FileMetadata} params.metadata - Additional metadata for the file.
* @returns {Promise<void>}
*/
const processAgentFileUpload = async ({ req, res, metadata }) => {
const { file } = req;
const { agent_id, tool_resource } = metadata;
if (agent_id && !tool_resource) {
throw new Error('No tool resource provided for agent file upload');
}
if (tool_resource === EToolResources.file_search && file.mimetype.startsWith('image')) {
throw new Error('Image uploads are not supported for file search tool resources');
}
let messageAttachment = !!metadata.message_file;
if (!messageAttachment && !agent_id) {
throw new Error('No agent ID provided for agent file upload');
}
const isImage = file.mimetype.startsWith('image');
if (!isImage && !tool_resource) {
/** Note: this needs to be removed when we can support files to providers */
throw new Error('No tool resource provided for non-image agent file upload');
}
let fileInfoMetadata;
const entity_id = messageAttachment === true ? undefined : agent_id;
if (tool_resource === EToolResources.execute_code) {
const isCodeEnabled = await checkCapability(req, AgentCapabilities.execute_code);
if (!isCodeEnabled) {
throw new Error('Code execution is not enabled for Agents');
}
const { handleFileUpload: uploadCodeEnvFile } = getStrategyFunctions(FileSources.execute_code);
const result = await loadAuthValues({ userId: req.user.id, authFields: [EnvVar.CODE_API_KEY] });
const stream = fs.createReadStream(file.path);
const fileIdentifier = await uploadCodeEnvFile({
req,
stream,
filename: file.originalname,
apiKey: result[EnvVar.CODE_API_KEY],
entity_id,
});
fileInfoMetadata = { fileIdentifier };
} else if (tool_resource === EToolResources.file_search) {
const isFileSearchEnabled = await checkCapability(req, AgentCapabilities.file_search);
if (!isFileSearchEnabled) {
throw new Error('File search is not enabled for Agents');
}
} else if (tool_resource === EToolResources.ocr) {
const isOCREnabled = await checkCapability(req, AgentCapabilities.ocr);
if (!isOCREnabled) {
throw new Error('OCR capability is not enabled for Agents');
}
const { handleFileUpload } = getStrategyFunctions(
req.app.locals?.ocr?.strategy ?? FileSources.mistral_ocr,
);
const { file_id, temp_file_id } = metadata;
const {
text,
bytes,
// TODO: OCR images support?
images,
filename,
filepath: ocrFileURL,
} = await handleFileUpload({ req, file, file_id, entity_id: agent_id });
const fileInfo = removeNullishValues({
text,
bytes,
file_id,
temp_file_id,
user: req.user.id,
type: file.mimetype,
filepath: ocrFileURL,
source: FileSources.text,
filename: filename ?? file.originalname,
model: messageAttachment ? undefined : req.body.model,
context: messageAttachment ? FileContext.message_attachment : FileContext.agents,
});
if (!messageAttachment && tool_resource) {
await addAgentResourceFile({
req,
file_id,
agent_id,
tool_resource,
});
}
const result = await createFile(fileInfo, true);
return res
.status(200)
.json({ message: 'Agent file uploaded and processed successfully', ...result });
}
const source =
tool_resource === EToolResources.file_search
? FileSources.vectordb
: req.app.locals.fileStrategy;
const { handleFileUpload } = getStrategyFunctions(source);
const { file_id, temp_file_id } = metadata;
const {
bytes,
filename,
filepath: _filepath,
embedded,
height,
width,
} = await handleFileUpload({
req,
file,
file_id,
entity_id,
});
let filepath = _filepath;
if (!messageAttachment && tool_resource) {
await addAgentResourceFile({
req,
file_id,
agent_id,
tool_resource,
});
}
if (isImage) {
const result = await processImageFile({
req,
file,
metadata: { file_id: v4() },
returnFile: true,
});
filepath = result.filepath;
}
const fileInfo = removeNullishValues({
user: req.user.id,
file_id,
temp_file_id,
bytes,
filepath,
filename: filename ?? file.originalname,
context: messageAttachment ? FileContext.message_attachment : FileContext.agents,
model: messageAttachment ? undefined : req.body.model,
metadata: fileInfoMetadata,
type: file.mimetype,
embedded,
source,
height,
width,
});
const result = await createFile(fileInfo, true);
res.status(200).json({ message: 'Agent file uploaded and processed successfully', ...result });
};
/**
* @param {object} params - The params object.
* @param {OpenAI} params.openai - The OpenAI client instance.
* @param {string} params.file_id - The ID of the file to retrieve.
* @param {string} params.userId - The user ID.
* @param {string} [params.filename] - The name of the file. `undefined` for `file_citation` annotations.
* @param {boolean} [params.saveFile=false] - Whether to save the file metadata to the database.
* @param {boolean} [params.updateUsage=false] - Whether to update file usage in database.
*/
const processOpenAIFile = async ({
openai,
file_id,
userId,
filename,
saveFile = false,
updateUsage = false,
}) => {
const _file = await openai.files.retrieve(file_id);
const originalName = filename ?? (_file.filename ? path.basename(_file.filename) : undefined);
const filepath = `${openai.baseURL}/files/${userId}/${file_id}${
originalName ? `/${originalName}` : ''
}`;
const type = mime.getType(originalName ?? file_id);
const source =
openai.req.body.endpoint === EModelEndpoint.azureAssistants
? FileSources.azure
: FileSources.openai;
const file = {
..._file,
type,
file_id,
filepath,
usage: 1,
user: userId,
context: _file.purpose,
source,
model: openai.req.body.model,
filename: originalName ?? file_id,
};
if (saveFile) {
await createFile(file, true);
} else if (updateUsage) {
try {
await updateFileUsage({ file_id });
} catch (error) {
logger.error('Error updating file usage', error);
}
}
return file;
};
/**
* Process OpenAI image files, convert to target format, save and return file metadata.
* @param {object} params - The params object.
* @param {ServerRequest} params.req - The Express request object.
* @param {Buffer} params.buffer - The image buffer.
* @param {string} params.file_id - The file ID.
* @param {string} params.filename - The filename.
* @param {string} params.fileExt - The file extension.
* @returns {Promise<MongoFile>} The file metadata.
*/
const processOpenAIImageOutput = async ({ req, buffer, file_id, filename, fileExt }) => {
const currentDate = new Date();
const formattedDate = currentDate.toISOString();
const _file = await convertImage(req, buffer, 'high', `${file_id}${fileExt}`);
const file = {
..._file,
usage: 1,
user: req.user.id,
type: `image/${req.app.locals.imageOutputType}`,
createdAt: formattedDate,
updatedAt: formattedDate,
source: req.app.locals.fileStrategy,
context: FileContext.assistants_output,
file_id: `${file_id}${hostImageIdSuffix}`,
filename: `${hostImageNamePrefix}${filename}`,
};
createFile(file, true);
const source =
req.body.endpoint === EModelEndpoint.azureAssistants ? FileSources.azure : FileSources.openai;
createFile(
{
...file,
file_id,
filename,
source,
type: mime.getType(fileExt),
},
true,
);
return file;
};
/**
* Retrieves and processes an OpenAI file based on its type.
*
* @param {Object} params - The params passed to the function.
* @param {OpenAIClient} params.openai - The OpenAI client instance.
* @param {RunClient} params.client - The LibreChat client instance: either refers to `openai` or `streamRunManager`.
* @param {string} params.file_id - The ID of the file to retrieve.
* @param {string} [params.basename] - The basename of the file (if image); e.g., 'image.jpg'. `undefined` for `file_citation` annotations.
* @param {boolean} [params.unknownType] - Whether the file type is unknown.
* @returns {Promise<{file_id: string, filepath: string, source: string, bytes?: number, width?: number, height?: number} | null>}
* - Returns null if `file_id` is not defined; else, the file metadata if successfully retrieved and processed.
*/
async function retrieveAndProcessFile({
openai,
client,
file_id,
basename: _basename,
unknownType,
}) {
if (!file_id) {
return null;
}
let basename = _basename;
const processArgs = { openai, file_id, filename: basename, userId: client.req.user.id };
// If no basename provided, return only the file metadata
if (!basename) {
return await processOpenAIFile({ ...processArgs, saveFile: true });
}
const fileExt = path.extname(basename);
if (client.attachedFileIds?.has(file_id) || client.processedFileIds?.has(file_id)) {
return processOpenAIFile({ ...processArgs, updateUsage: true });
}
/**
* @returns {Promise<Buffer>} The file data buffer.
*/
const getDataBuffer = async () => {
const response = await openai.files.content(file_id);
const arrayBuffer = await response.arrayBuffer();
return Buffer.from(arrayBuffer);
};
let dataBuffer;
if (unknownType || !fileExt || imageExtRegex.test(basename)) {
try {
dataBuffer = await getDataBuffer();
} catch (error) {
logger.error('Error downloading file from OpenAI:', error);
dataBuffer = null;
}
}
if (!dataBuffer) {
return await processOpenAIFile({ ...processArgs, saveFile: true });
}
// If the filetype is unknown, inspect the file
if (dataBuffer && (unknownType || !fileExt)) {
const detectedExt = await determineFileType(dataBuffer);
const isImageOutput = detectedExt && imageExtRegex.test('.' + detectedExt);
if (!isImageOutput) {
return await processOpenAIFile({ ...processArgs, saveFile: true });
}
return await processOpenAIImageOutput({
file_id,
req: client.req,
buffer: dataBuffer,
filename: basename,
fileExt: detectedExt,
});
} else if (dataBuffer && imageExtRegex.test(basename)) {
return await processOpenAIImageOutput({
file_id,
req: client.req,
buffer: dataBuffer,
filename: basename,
fileExt,
});
} else {
logger.debug(`[retrieveAndProcessFile] Non-image file type detected: ${basename}`);
return await processOpenAIFile({ ...processArgs, saveFile: true });
}
}
/**
* Converts a base64 string to a buffer.
* @param {string} base64String
* @returns {Buffer<ArrayBufferLike>}
*/
function base64ToBuffer(base64String) {
try {
const typeMatch = base64String.match(/^data:([A-Za-z-+/]+);base64,/);
const type = typeMatch ? typeMatch[1] : '';
const base64Data = base64String.replace(/^data:([A-Za-z-+/]+);base64,/, '');
if (!base64Data) {
throw new Error('Invalid base64 string');
}
return {
buffer: Buffer.from(base64Data, 'base64'),
type,
};
} catch (error) {
throw new Error(`Failed to convert base64 to buffer: ${error.message}`);
}
}
async function saveBase64Image(
url,
{ req, file_id: _file_id, filename: _filename, endpoint, context, resolution = 'high' },
) {
const file_id = _file_id ?? v4();
let filename = `${file_id}-${_filename}`;
const { buffer: inputBuffer, type } = base64ToBuffer(url);
if (!path.extname(_filename)) {
const extension = mime.getExtension(type);
if (extension) {
filename += `.${extension}`;
} else {
throw new Error(`Could not determine file extension from MIME type: ${type}`);
}
}
const image = await resizeImageBuffer(inputBuffer, resolution, endpoint);
const source = req.app.locals.fileStrategy;
const { saveBuffer } = getStrategyFunctions(source);
const filepath = await saveBuffer({
userId: req.user.id,
fileName: filename,
buffer: image.buffer,
});
return await createFile(
{
type,
source,
context,
file_id,
filepath,
filename,
user: req.user.id,
bytes: image.bytes,
width: image.width,
height: image.height,
},
true,
);
}
/**
* Filters a file based on its size and the endpoint origin.
*
* @param {Object} params - The parameters for the function.
* @param {ServerRequest} params.req - The request object from Express.
* @param {string} [params.req.endpoint]
* @param {string} [params.req.file_id]
* @param {number} [params.req.width]
* @param {number} [params.req.height]
* @param {number} [params.req.version]
* @param {boolean} [params.image] - Whether the file expected is an image.
* @param {boolean} [params.isAvatar] - Whether the file expected is a user or entity avatar.
* @returns {void}
*
* @throws {Error} If a file exception is caught (invalid file size or type, lack of metadata).
*/
function filterFile({ req, image, isAvatar }) {
const { file } = req;
const { endpoint, file_id, width, height } = req.body;
if (!file_id && !isAvatar) {
throw new Error('No file_id provided');
}
if (file.size === 0) {
throw new Error('Empty file uploaded');
}
/* parse to validate api call, throws error on fail */
if (!isAvatar) {
isUUID.parse(file_id);
}
if (!endpoint && !isAvatar) {
throw new Error('No endpoint provided');
}
const fileConfig = mergeFileConfig(req.app.locals.fileConfig);
const { fileSizeLimit: sizeLimit, supportedMimeTypes } =
fileConfig.endpoints[endpoint] ?? fileConfig.endpoints.default;
const fileSizeLimit = isAvatar === true ? fileConfig.avatarSizeLimit : sizeLimit;
if (file.size > fileSizeLimit) {
throw new Error(
`File size limit of ${fileSizeLimit / megabyte} MB exceeded for ${
isAvatar ? 'avatar upload' : `${endpoint} endpoint`
}`,
);
}
const isSupportedMimeType = fileConfig.checkType(file.mimetype, supportedMimeTypes);
if (!isSupportedMimeType) {
throw new Error('Unsupported file type');
}
if (!image || isAvatar === true) {
return;
}
if (!width) {
throw new Error('No width provided');
}
if (!height) {
throw new Error('No height provided');
}
}
module.exports = {
filterFile,
processFiles,
processFileURL,
saveBase64Image,
processImageFile,
uploadImageBuffer,
processFileUpload,
processDeleteRequest,
processAgentFileUpload,
retrieveAndProcessFile,
};