Feature/OpenAI Response API (#5014)

* - Added support for built-in OpenAI tools including web search, code interpreter, and image generation.
- Enhanced file handling by extracting artifacts and file annotations from response metadata.
- Implemented download functionality for file annotations in the UI.
- Updated chat history management to include additional kwargs for artifacts, file annotations, and used tools.
- Improved UI components to display used tools and file annotations effectively.

* remove redundant currentContainerId

* update comment
This commit is contained in:
Henry Heng
2025-08-07 17:59:05 +01:00
committed by GitHub
parent 3187377c61
commit b608219642
7 changed files with 860 additions and 14 deletions
@@ -28,6 +28,9 @@ import {
replaceBase64ImagesWithFileReferences,
updateFlowState
} from '../utils'
import { convertMultiOptionsToStringArray, getCredentialData, getCredentialParam } from '../../../src/utils'
import { addSingleFileToStorage } from '../../../src/storageUtils'
import fetch from 'node-fetch'
interface ITool {
agentSelectedTool: string
@@ -78,7 +81,7 @@ class Agent_Agentflow implements INode {
constructor() {
this.label = 'Agent'
this.name = 'agentAgentflow'
this.version = 1.0
this.version = 2.0
this.type = 'Agent'
this.category = 'Agent Flows'
this.description = 'Dynamically choose and utilize tools during runtime, enabling multi-step reasoning'
@@ -132,6 +135,32 @@ class Agent_Agentflow implements INode {
}
]
},
{
label: 'OpenAI Built-in Tools',
name: 'agentToolsBuiltInOpenAI',
type: 'multiOptions',
optional: true,
options: [
{
label: 'Web Search',
name: 'web_search_preview',
description: 'Search the web for the latest information'
},
{
label: 'Code Interpreter',
name: 'code_interpreter',
description: 'Write and run Python code in a sandboxed environment'
},
{
label: 'Image Generation',
name: 'image_generation',
description: 'Generate images based on a text prompt'
}
],
show: {
agentModel: 'chatOpenAI'
}
},
{
label: 'Tools',
name: 'agentTools',
@@ -716,6 +745,26 @@ class Agent_Agentflow implements INode {
const llmWithoutToolsBind = (await newLLMNodeInstance.init(newNodeData, '', options)) as BaseChatModel
let llmNodeInstance = llmWithoutToolsBind
const agentToolsBuiltInOpenAI = convertMultiOptionsToStringArray(nodeData.inputs?.agentToolsBuiltInOpenAI)
if (agentToolsBuiltInOpenAI && agentToolsBuiltInOpenAI.length > 0) {
for (const tool of agentToolsBuiltInOpenAI) {
const builtInTool: ICommonObject = {
type: tool
}
if (tool === 'code_interpreter') {
builtInTool.container = { type: 'auto' }
}
;(toolsInstance as any).push(builtInTool)
;(availableTools as any).push({
name: tool,
toolNode: {
label: tool,
name: tool
}
})
}
}
if (llmNodeInstance && toolsInstance.length > 0) {
if (llmNodeInstance.bindTools === undefined) {
throw new Error(`Agent needs to have a function calling capable models.`)
@@ -814,6 +863,7 @@ class Agent_Agentflow implements INode {
let usedTools: IUsedTool[] = []
let sourceDocuments: Array<any> = []
let artifacts: any[] = []
let fileAnnotations: any[] = []
let additionalTokens = 0
let isWaitingForHumanInput = false
@@ -879,6 +929,9 @@ class Agent_Agentflow implements INode {
}
}
// Address built in tools (after artifacts are processed)
const builtInUsedTools: IUsedTool[] = await this.extractBuiltInUsedTools(response, [])
if (!humanInput && response.tool_calls && response.tool_calls.length > 0) {
const result = await this.handleToolCalls({
response,
@@ -954,6 +1007,46 @@ class Agent_Agentflow implements INode {
} else {
finalResponse = JSON.stringify(response, null, 2)
}
// Address built in tools
const additionalBuiltInUsedTools: IUsedTool[] = await this.extractBuiltInUsedTools(response, builtInUsedTools)
if (additionalBuiltInUsedTools.length > 0) {
usedTools = [...new Set([...usedTools, ...additionalBuiltInUsedTools])]
// Stream used tools if this is the last node
if (isLastNode && sseStreamer) {
sseStreamer.streamUsedToolsEvent(chatId, flatten(usedTools))
}
}
// Extract artifacts from annotations in response metadata
if (response.response_metadata) {
const { artifacts: extractedArtifacts, fileAnnotations: extractedFileAnnotations } =
await this.extractArtifactsFromResponse(response.response_metadata, newNodeData, options)
if (extractedArtifacts.length > 0) {
artifacts = [...artifacts, ...extractedArtifacts]
// Stream artifacts if this is the last node
if (isLastNode && sseStreamer) {
sseStreamer.streamArtifactsEvent(chatId, extractedArtifacts)
}
}
if (extractedFileAnnotations.length > 0) {
fileAnnotations = [...fileAnnotations, ...extractedFileAnnotations]
// Stream file annotations if this is the last node
if (isLastNode && sseStreamer) {
sseStreamer.streamFileAnnotationsEvent(chatId, fileAnnotations)
}
}
}
// Replace sandbox links with proper download URLs. Example: [Download the script](sandbox:/mnt/data/dummy_bar_graph.py)
if (finalResponse.includes('sandbox:/')) {
finalResponse = await this.processSandboxLinks(finalResponse, options.baseURL, options.chatflowid, chatId)
}
const output = this.prepareOutputObject(
response,
availableTools,
@@ -965,7 +1058,8 @@ class Agent_Agentflow implements INode {
sourceDocuments,
artifacts,
additionalTokens,
isWaitingForHumanInput
isWaitingForHumanInput,
fileAnnotations
)
// End analytics tracking
@@ -978,6 +1072,11 @@ class Agent_Agentflow implements INode {
this.sendStreamingEvents(options, chatId, response)
}
// Stream file annotations if any were extracted
if (fileAnnotations.length > 0 && isLastNode && sseStreamer) {
sseStreamer.streamFileAnnotationsEvent(chatId, fileAnnotations)
}
// Process template variables in state
if (newState && Object.keys(newState).length > 0) {
for (const key in newState) {
@@ -1043,7 +1142,16 @@ class Agent_Agentflow implements INode {
{
role: returnRole,
content: finalResponse,
name: nodeData?.label ? nodeData?.label.toLowerCase().replace(/\s/g, '_').trim() : nodeData?.id
name: nodeData?.label ? nodeData?.label.toLowerCase().replace(/\s/g, '_').trim() : nodeData?.id,
...(((artifacts && artifacts.length > 0) ||
(fileAnnotations && fileAnnotations.length > 0) ||
(usedTools && usedTools.length > 0)) && {
additional_kwargs: {
...(artifacts && artifacts.length > 0 && { artifacts }),
...(fileAnnotations && fileAnnotations.length > 0 && { fileAnnotations }),
...(usedTools && usedTools.length > 0 && { usedTools })
}
})
}
]
}
@@ -1059,6 +1167,105 @@ class Agent_Agentflow implements INode {
}
}
/**
* Extracts built-in used tools from response metadata and processes image generation results
*/
private async extractBuiltInUsedTools(response: AIMessageChunk, builtInUsedTools: IUsedTool[] = []): Promise<IUsedTool[]> {
if (!response.response_metadata) {
return builtInUsedTools
}
const { output, tools } = response.response_metadata
if (!output || !Array.isArray(output) || output.length === 0 || !tools || !Array.isArray(tools) || tools.length === 0) {
return builtInUsedTools
}
for (const outputItem of output) {
if (outputItem.type && outputItem.type.endsWith('_call')) {
let toolInput = outputItem.action ?? outputItem.code
let toolOutput = outputItem.status === 'completed' ? 'Success' : outputItem.status
// Handle image generation calls specially
if (outputItem.type === 'image_generation_call') {
// Create input summary for image generation
toolInput = {
prompt: outputItem.revised_prompt || 'Image generation request',
size: outputItem.size || '1024x1024',
quality: outputItem.quality || 'standard',
output_format: outputItem.output_format || 'png'
}
// Check if image has been processed (base64 replaced with file path)
if (outputItem.result && !outputItem.result.startsWith('data:') && !outputItem.result.includes('base64')) {
toolOutput = `Image generated and saved`
} else {
toolOutput = `Image generated (base64)`
}
}
// Remove "_call" suffix to get the base tool name
const baseToolName = outputItem.type.replace('_call', '')
// Find matching tool that includes the base name in its type
const matchingTool = tools.find((tool) => tool.type && tool.type.includes(baseToolName))
if (matchingTool) {
// Check for duplicates
if (builtInUsedTools.find((tool) => tool.tool === matchingTool.type)) {
continue
}
builtInUsedTools.push({
tool: matchingTool.type,
toolInput,
toolOutput
})
}
}
}
return builtInUsedTools
}
/**
* Saves base64 image data to storage and returns file information
*/
private async saveBase64Image(
outputItem: any,
options: ICommonObject
): Promise<{ filePath: string; fileName: string; totalSize: number } | null> {
try {
if (!outputItem.result) {
return null
}
// Extract base64 data and create buffer
const base64Data = outputItem.result
const imageBuffer = Buffer.from(base64Data, 'base64')
// Determine file extension and MIME type
const outputFormat = outputItem.output_format || 'png'
const fileName = `generated_image_${outputItem.id || Date.now()}.${outputFormat}`
const mimeType = outputFormat === 'png' ? 'image/png' : 'image/jpeg'
// Save the image using the existing storage utility
const { path, totalSize } = await addSingleFileToStorage(
mimeType,
imageBuffer,
fileName,
options.orgId,
options.chatflowid,
options.chatId
)
return { filePath: path, fileName, totalSize }
} catch (error) {
console.error('Error saving base64 image:', error)
return null
}
}
/**
* Handles memory management based on the specified memory type
*/
@@ -1265,7 +1472,8 @@ class Agent_Agentflow implements INode {
sourceDocuments: Array<any>,
artifacts: any[],
additionalTokens: number = 0,
isWaitingForHumanInput: boolean = false
isWaitingForHumanInput: boolean = false,
fileAnnotations: any[] = []
): any {
const output: any = {
content: finalResponse,
@@ -1296,6 +1504,10 @@ class Agent_Agentflow implements INode {
}
}
if (response.response_metadata) {
output.responseMetadata = response.response_metadata
}
// Add used tools, source documents and artifacts to output
if (usedTools && usedTools.length > 0) {
output.usedTools = flatten(usedTools)
@@ -1317,6 +1529,10 @@ class Agent_Agentflow implements INode {
output.isWaitingForHumanInput = isWaitingForHumanInput
}
if (fileAnnotations && fileAnnotations.length > 0) {
output.fileAnnotations = fileAnnotations
}
return output
}
@@ -1808,6 +2024,10 @@ class Agent_Agentflow implements INode {
// Get LLM response after tool calls
let newResponse: AIMessageChunk
if (llmNodeInstance && (llmNodeInstance as any).builtInTools && (llmNodeInstance as any).builtInTools.length > 0) {
toolsInstance.push(...(llmNodeInstance as any).builtInTools)
}
if (llmNodeInstance && toolsInstance.length > 0) {
if (llmNodeInstance.bindTools === undefined) {
throw new Error(`Agent needs to have a function calling capable models.`)
@@ -1872,6 +2092,224 @@ class Agent_Agentflow implements INode {
return { response: newResponse, usedTools, sourceDocuments, artifacts, totalTokens, isWaitingForHumanInput }
}
/**
* Extracts artifacts from response metadata (both annotations and built-in tools)
*/
private async extractArtifactsFromResponse(
responseMetadata: any,
modelNodeData: INodeData,
options: ICommonObject
): Promise<{ artifacts: any[]; fileAnnotations: any[] }> {
const artifacts: any[] = []
const fileAnnotations: any[] = []
if (!responseMetadata?.output || !Array.isArray(responseMetadata.output)) {
return { artifacts, fileAnnotations }
}
for (const outputItem of responseMetadata.output) {
// Handle container file citations from annotations
if (outputItem.type === 'message' && outputItem.content && Array.isArray(outputItem.content)) {
for (const contentItem of outputItem.content) {
if (contentItem.annotations && Array.isArray(contentItem.annotations)) {
for (const annotation of contentItem.annotations) {
if (annotation.type === 'container_file_citation' && annotation.file_id && annotation.filename) {
try {
// Download and store the file content
const downloadResult = await this.downloadContainerFile(
annotation.container_id,
annotation.file_id,
annotation.filename,
modelNodeData,
options
)
if (downloadResult) {
const fileType = this.getArtifactTypeFromFilename(annotation.filename)
if (fileType === 'png' || fileType === 'jpeg' || fileType === 'jpg') {
const artifact = {
type: fileType,
data: downloadResult.filePath
}
artifacts.push(artifact)
} else {
fileAnnotations.push({
filePath: downloadResult.filePath,
fileName: annotation.filename
})
}
}
} catch (error) {
console.error('Error processing annotation:', error)
}
}
}
}
}
}
// Handle built-in tool artifacts (like image generation)
if (outputItem.type === 'image_generation_call' && outputItem.result) {
try {
const savedImageResult = await this.saveBase64Image(outputItem, options)
if (savedImageResult) {
// Replace the base64 result with the file path in the response metadata
outputItem.result = savedImageResult.filePath
// Create artifact in the same format as other image artifacts
const fileType = this.getArtifactTypeFromFilename(savedImageResult.fileName)
artifacts.push({
type: fileType,
data: savedImageResult.filePath
})
}
} catch (error) {
console.error('Error processing image generation artifact:', error)
}
}
}
return { artifacts, fileAnnotations }
}
/**
* Downloads file content from container file citation
*/
private async downloadContainerFile(
containerId: string,
fileId: string,
filename: string,
modelNodeData: INodeData,
options: ICommonObject
): Promise<{ filePath: string; totalSize: number } | null> {
try {
const credentialData = await getCredentialData(modelNodeData.credential ?? '', options)
const openAIApiKey = getCredentialParam('openAIApiKey', credentialData, modelNodeData)
if (!openAIApiKey) {
console.warn('No OpenAI API key available for downloading container file')
return null
}
// Download the file using OpenAI Container API
const response = await fetch(`https://api.openai.com/v1/containers/${containerId}/files/${fileId}/content`, {
method: 'GET',
headers: {
Accept: '*/*',
Authorization: `Bearer ${openAIApiKey}`
}
})
if (!response.ok) {
console.warn(
`Failed to download container file ${fileId} from container ${containerId}: ${response.status} ${response.statusText}`
)
return null
}
// Extract the binary data from the Response object
const data = await response.arrayBuffer()
const dataBuffer = Buffer.from(data)
const mimeType = this.getMimeTypeFromFilename(filename)
// Store the file using the same storage utility as OpenAIAssistant
const { path, totalSize } = await addSingleFileToStorage(
mimeType,
dataBuffer,
filename,
options.orgId,
options.chatflowid,
options.chatId
)
return { filePath: path, totalSize }
} catch (error) {
console.error('Error downloading container file:', error)
return null
}
}
/**
* Gets MIME type from filename extension
*/
private getMimeTypeFromFilename(filename: string): string {
const extension = filename.toLowerCase().split('.').pop()
const mimeTypes: { [key: string]: string } = {
png: 'image/png',
jpg: 'image/jpeg',
jpeg: 'image/jpeg',
gif: 'image/gif',
pdf: 'application/pdf',
txt: 'text/plain',
csv: 'text/csv',
json: 'application/json',
html: 'text/html',
xml: 'application/xml'
}
return mimeTypes[extension || ''] || 'application/octet-stream'
}
/**
* Gets artifact type from filename extension for UI rendering
*/
private getArtifactTypeFromFilename(filename: string): string {
const extension = filename.toLowerCase().split('.').pop()
const artifactTypes: { [key: string]: string } = {
png: 'png',
jpg: 'jpeg',
jpeg: 'jpeg',
html: 'html',
htm: 'html',
md: 'markdown',
markdown: 'markdown',
json: 'json',
js: 'javascript',
javascript: 'javascript',
tex: 'latex',
latex: 'latex',
txt: 'text',
csv: 'text',
pdf: 'text'
}
return artifactTypes[extension || ''] || 'text'
}
/**
* Processes sandbox links in the response text and converts them to file annotations
*/
private async processSandboxLinks(text: string, baseURL: string, chatflowId: string, chatId: string): Promise<string> {
let processedResponse = text
// Regex to match sandbox links: [text](sandbox:/path/to/file)
const sandboxLinkRegex = /\[([^\]]+)\]\(sandbox:\/([^)]+)\)/g
const matches = Array.from(text.matchAll(sandboxLinkRegex))
for (const match of matches) {
const fullMatch = match[0]
const linkText = match[1]
const filePath = match[2]
try {
// Extract filename from the file path
const fileName = filePath.split('/').pop() || filePath
// Replace sandbox link with proper download URL
const downloadUrl = `${baseURL}/api/v1/get-upload-file?chatflowId=${chatflowId}&chatId=${chatId}&fileName=${fileName}&download=true`
const newLink = `[${linkText}](${downloadUrl})`
processedResponse = processedResponse.replace(fullMatch, newLink)
} catch (error) {
console.error('Error processing sandbox link:', error)
// If there's an error, remove the sandbox link as fallback
processedResponse = processedResponse.replace(fullMatch, linkText)
}
}
return processedResponse
}
}
module.exports = { nodeClass: Agent_Agentflow }
+68 -4
View File
@@ -313,6 +313,9 @@ export const getPastChatHistoryImageMessages = async (
if (message.additional_kwargs && message.additional_kwargs.fileUploads) {
// example: [{"type":"stored-file","name":"0_DiXc4ZklSTo3M8J4.jpg","mime":"image/jpeg"}]
const fileUploads = message.additional_kwargs.fileUploads
const artifacts = message.additional_kwargs.artifacts
const fileAnnotations = message.additional_kwargs.fileAnnotations
const usedTools = message.additional_kwargs.usedTools
try {
let messageWithFileUploads = ''
const uploads: IFileUpload[] = typeof fileUploads === 'string' ? JSON.parse(fileUploads) : fileUploads
@@ -358,22 +361,83 @@ export const getPastChatHistoryImageMessages = async (
}
}
const messageContent = messageWithFileUploads ? `${messageWithFileUploads}\n\n${message.content}` : message.content
const hasArtifacts = artifacts && Array.isArray(artifacts) && artifacts.length > 0
const hasFileAnnotations = fileAnnotations && Array.isArray(fileAnnotations) && fileAnnotations.length > 0
const hasUsedTools = usedTools && Array.isArray(usedTools) && usedTools.length > 0
if (imageContents.length > 0) {
chatHistory.push({
const imageMessage: any = {
role: messageRole,
content: imageContents
})
}
if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
imageMessage.additional_kwargs = {}
if (hasArtifacts) imageMessage.additional_kwargs.artifacts = artifacts
if (hasFileAnnotations) imageMessage.additional_kwargs.fileAnnotations = fileAnnotations
if (hasUsedTools) imageMessage.additional_kwargs.usedTools = usedTools
}
chatHistory.push(imageMessage)
transformedPastMessages.push({
role: messageRole,
content: [...JSON.parse((pastChatHistory[i] as any).additional_kwargs.fileUploads)]
})
}
chatHistory.push({
const contentMessage: any = {
role: messageRole,
content: messageContent
})
}
if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
contentMessage.additional_kwargs = {}
if (hasArtifacts) contentMessage.additional_kwargs.artifacts = artifacts
if (hasFileAnnotations) contentMessage.additional_kwargs.fileAnnotations = fileAnnotations
if (hasUsedTools) contentMessage.additional_kwargs.usedTools = usedTools
}
chatHistory.push(contentMessage)
} catch (e) {
// failed to parse fileUploads, continue with text only
const hasArtifacts = artifacts && Array.isArray(artifacts) && artifacts.length > 0
const hasFileAnnotations = fileAnnotations && Array.isArray(fileAnnotations) && fileAnnotations.length > 0
const hasUsedTools = usedTools && Array.isArray(usedTools) && usedTools.length > 0
const errorMessage: any = {
role: messageRole,
content: message.content
}
if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
errorMessage.additional_kwargs = {}
if (hasArtifacts) errorMessage.additional_kwargs.artifacts = artifacts
if (hasFileAnnotations) errorMessage.additional_kwargs.fileAnnotations = fileAnnotations
if (hasUsedTools) errorMessage.additional_kwargs.usedTools = usedTools
}
chatHistory.push(errorMessage)
}
} else if (message.additional_kwargs) {
const hasArtifacts =
message.additional_kwargs.artifacts &&
Array.isArray(message.additional_kwargs.artifacts) &&
message.additional_kwargs.artifacts.length > 0
const hasFileAnnotations =
message.additional_kwargs.fileAnnotations &&
Array.isArray(message.additional_kwargs.fileAnnotations) &&
message.additional_kwargs.fileAnnotations.length > 0
const hasUsedTools =
message.additional_kwargs.usedTools &&
Array.isArray(message.additional_kwargs.usedTools) &&
message.additional_kwargs.usedTools.length > 0
if (hasArtifacts || hasFileAnnotations || hasUsedTools) {
const messageAdditionalKwargs: any = {}
if (hasArtifacts) messageAdditionalKwargs.artifacts = message.additional_kwargs.artifacts
if (hasFileAnnotations) messageAdditionalKwargs.fileAnnotations = message.additional_kwargs.fileAnnotations
if (hasUsedTools) messageAdditionalKwargs.usedTools = message.additional_kwargs.usedTools
chatHistory.push({
role: messageRole,
content: message.content,
additional_kwargs: messageAdditionalKwargs
})
} else {
chatHistory.push({
role: messageRole,
content: message.content