mirror of
https://github.com/simstudioai/sim.git
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Tool call version
This commit is contained in:
Siddharth Ganesan
@@ -0,0 +1,488 @@
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import { eq, and } from 'drizzle-orm'
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import { type NextRequest, NextResponse } from 'next/server'
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import { z } from 'zod'
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import { createLogger } from '@/lib/logs/console-logger'
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import { getRotatingApiKey } from '@/lib/utils'
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import { getSession } from '@/lib/auth'
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import { db } from '@/db'
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import { copilotChats } from '@/db/schema'
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import { executeProviderRequest } from '@/providers'
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import type { Message } from '@/providers/types'
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import { executeTool } from '@/tools'
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const logger = createLogger('CopilotChat')
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// Configuration for copilot chat
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const COPILOT_CONFIG = {
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defaultProvider: 'anthropic',
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defaultModel: 'claude-3-7-sonnet-latest',
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temperature: 0.1,
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maxTokens: 4000, // Increased for more comprehensive documentation responses
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} as const
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const CopilotChatSchema = z.object({
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message: z.string().min(1, 'Message is required'),
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chatId: z.string().optional(),
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workflowId: z.string().optional(),
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createNewChat: z.boolean().optional().default(false),
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stream: z.boolean().optional().default(false),
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})
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/**
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* Generate a chat title using LLM based on the first user message
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*/
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async function generateChatTitle(userMessage: string): Promise<string> {
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try {
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const apiKey = getRotatingApiKey('anthropic')
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const response = await executeProviderRequest('anthropic', {
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model: 'claude-3-haiku-20240307',
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systemPrompt: 'You are a helpful assistant that generates concise, descriptive titles for chat conversations. Create a title that captures the main topic or question being discussed. Keep it under 50 characters and make it specific and clear.',
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context: `Generate a concise title for a conversation that starts with this user message: "${userMessage}"
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Return only the title text, nothing else.`,
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temperature: 0.3,
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maxTokens: 50,
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apiKey,
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stream: false,
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})
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if (typeof response === 'object' && 'content' in response) {
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return response.content?.trim() || 'New Chat'
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}
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return 'New Chat'
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} catch (error) {
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logger.error('Failed to generate chat title:', error)
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return 'New Chat'
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}
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}
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/**
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* Generate chat response with tool calling support
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*/
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interface StreamingChatResponse {
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stream: ReadableStream
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citations: Array<{
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id: number
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title: string
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url: string
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}>
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}
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/**
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* Extract citations from provider response that contains tool results
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*/
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function extractCitationsFromResponse(response: any): Array<{
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id: number
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title: string
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url: string
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}> {
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if (!response.toolResults || !Array.isArray(response.toolResults)) {
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return []
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}
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const docsSearchResult = response.toolResults.find((result: any) =>
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result.sources && Array.isArray(result.sources)
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)
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if (!docsSearchResult || !docsSearchResult.sources) {
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return []
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}
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return docsSearchResult.sources.map((source: any) => ({
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id: source.id,
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title: source.title,
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url: source.link,
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}))
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}
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async function generateChatResponse(
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message: string,
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conversationHistory: any[] = [],
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stream = false,
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requestId?: string
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): Promise<string | ReadableStream | StreamingChatResponse> {
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const apiKey = getRotatingApiKey('anthropic')
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// Build conversation context
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const messages: Message[] = []
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// Add conversation history
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for (const msg of conversationHistory.slice(-10)) { // Keep last 10 messages
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messages.push({
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role: msg.role as 'user' | 'assistant' | 'system',
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content: msg.content,
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})
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}
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// Add current user message
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messages.push({
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role: 'user',
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content: message,
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})
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const systemPrompt = `You are a helpful AI assistant for Sim Studio, a powerful workflow automation platform. You can help users with questions about:
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- Creating and managing workflows
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- Using different tools and blocks
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- Understanding features and capabilities
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- Troubleshooting issues
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- Best practices
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You have access to the Sim Studio documentation through a search tool, but use it SELECTIVELY.
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WHEN TO SEARCH DOCUMENTATION:
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- User asks "How do I create a workflow?"
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- User asks about specific tools or blocks
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- User needs help with Sim Studio features
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- User has technical questions about the platform
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WHEN NOT TO SEARCH DOCUMENTATION:
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- Simple greetings like "hi", "hello", "hey"
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- General conversation like "how are you?"
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- Thank you messages
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- General programming questions unrelated to Sim Studio
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- Small talk or casual conversation
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Guidelines:
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- Be conversational and helpful
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- For greetings and casual conversation, respond directly without searching
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- Only use docs_search_internal when the user specifically needs information about Sim Studio features
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- When you do search, synthesize the information and provide clear, actionable answers
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- Be friendly and natural in your responses
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CITATION INSTRUCTIONS:
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When you search documentation and reference information from the sources, use inline citations strategically and sparingly:
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- Use citation markers like {cite:1}, {cite:2}, etc. to reference specific sources
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- Cite each source only ONCE at the specific header or topic that relates to that source
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- Place citations directly after the header or concept that the source specifically addresses
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- If multiple sources support the same topic, cite them together like {cite:1}{cite:2}{cite:3}
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- Do NOT repeatedly cite the same source throughout your response
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- Only cite sources that you actually reference in your answer
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MAKE SURE YOU FULLY ANSWER THE USER'S QUESTION.
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`
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// Define the documentation search tool for the LLM
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const tools = [
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{
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id: 'docs_search_internal',
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name: 'Search Documentation',
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description: 'Search Sim Studio documentation for information about features, tools, workflows, and functionality',
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params: {},
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parameters: {
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type: 'object',
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properties: {
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query: {
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type: 'string',
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description: 'The search query to find relevant documentation',
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},
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topK: {
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type: 'number',
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description: 'Number of results to return (default: 5, max: 10)',
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default: 5,
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},
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},
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required: ['query'],
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},
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},
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]
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try {
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// For streaming, we always make a non-streaming request first to handle tool calls
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// Then we stream the final response if no tool calls were needed
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const response = await executeProviderRequest('anthropic', {
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model: COPILOT_CONFIG.defaultModel,
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systemPrompt,
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messages,
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tools,
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temperature: COPILOT_CONFIG.temperature,
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maxTokens: COPILOT_CONFIG.maxTokens,
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apiKey,
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stream: false, // Always start with non-streaming to handle tool calls
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})
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// If this is a streaming request and we got a regular response,
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// we need to create a streaming response from the content
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if (stream && typeof response === 'object' && 'content' in response) {
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const content = response.content || 'Sorry, I could not generate a response.'
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// Extract citations from the provider response for later use
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const responseCitations = extractCitationsFromResponse(response)
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// Create a ReadableStream that emits the content in character chunks
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const streamResponse = new ReadableStream({
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start(controller) {
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// Use character-based streaming for more reliable transmission
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const chunkSize = 8 // Stream 8 characters at a time for smooth experience
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let index = 0
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const pushNext = () => {
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if (index < content.length) {
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const chunk = content.slice(index, index + chunkSize)
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controller.enqueue(new TextEncoder().encode(chunk))
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index += chunkSize
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// Add a small delay to simulate streaming
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setTimeout(pushNext, 25)
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} else {
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controller.close()
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}
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}
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pushNext()
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}
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})
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// Store citations for later use in the main streaming handler
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;(streamResponse as any)._citations = responseCitations
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return streamResponse
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}
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// Handle regular response
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if (typeof response === 'object' && 'content' in response) {
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return response.content || 'Sorry, I could not generate a response.'
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}
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return 'Sorry, I could not generate a response.'
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} catch (error) {
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logger.error('Failed to generate chat response:', error)
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throw new Error(`Failed to generate response: ${error instanceof Error ? error.message : 'Unknown error'}`)
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}
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}
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/**
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* POST /api/copilot/chat
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* Chat with the copilot using LLM with tool calling
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*/
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export async function POST(req: NextRequest) {
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const requestId = crypto.randomUUID()
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try {
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const body = await req.json()
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const { message, chatId, workflowId, createNewChat, stream } = CopilotChatSchema.parse(body)
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const session = await getSession()
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logger.info(`[${requestId}] Copilot chat message: "${message}"`, {
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chatId,
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workflowId,
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createNewChat,
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stream,
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})
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// Handle chat context
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let currentChat: any = null
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let conversationHistory: any[] = []
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if (chatId && session?.user?.id) {
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// Load existing chat
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const [existingChat] = await db
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.select()
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.from(copilotChats)
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.where(
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and(
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eq(copilotChats.id, chatId),
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eq(copilotChats.userId, session.user.id)
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)
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)
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.limit(1)
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if (existingChat) {
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currentChat = existingChat
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conversationHistory = Array.isArray(existingChat.messages) ? existingChat.messages : []
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}
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} else if (createNewChat && workflowId && session?.user?.id) {
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// Create new chat
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const [newChat] = await db
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.insert(copilotChats)
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.values({
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userId: session.user.id,
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workflowId,
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title: null,
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model: COPILOT_CONFIG.defaultModel,
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messages: [],
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})
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.returning()
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if (newChat) {
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currentChat = newChat
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conversationHistory = []
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}
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}
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// Generate chat response
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const response = await generateChatResponse(message, conversationHistory, stream, requestId)
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// Handle streaming response
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if (response instanceof ReadableStream) {
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logger.info(`[${requestId}] Returning streaming response`)
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const encoder = new TextEncoder()
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// Extract citations from the stream object if available
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const citations = (response as any)._citations || []
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return new Response(
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new ReadableStream({
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async start(controller) {
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const reader = response.getReader()
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let accumulatedResponse = ''
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// Send initial metadata
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const metadata = {
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type: 'metadata',
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chatId: currentChat?.id,
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citations: citations,
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metadata: {
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requestId,
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message,
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},
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}
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controller.enqueue(encoder.encode(`data: ${JSON.stringify(metadata)}\n\n`))
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try {
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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const chunkText = new TextDecoder().decode(value)
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accumulatedResponse += chunkText
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const contentChunk = {
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type: 'content',
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content: chunkText,
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}
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controller.enqueue(encoder.encode(`data: ${JSON.stringify(contentChunk)}\n\n`))
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}
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// Save conversation to database after streaming completes
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if (currentChat && session?.user?.id) {
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const userMessage = {
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id: crypto.randomUUID(),
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role: 'user',
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content: message,
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timestamp: new Date().toISOString(),
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}
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const assistantMessage = {
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id: crypto.randomUUID(),
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role: 'assistant',
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content: accumulatedResponse,
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timestamp: new Date().toISOString(),
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citations: citations.length > 0 ? citations : undefined,
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}
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const updatedMessages = [...conversationHistory, userMessage, assistantMessage]
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// Generate title if this is the first message
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let updatedTitle = currentChat.title
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if (!updatedTitle && conversationHistory.length === 0) {
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updatedTitle = await generateChatTitle(message)
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}
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await db
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.update(copilotChats)
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.set({
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title: updatedTitle,
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||||
messages: updatedMessages,
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updatedAt: new Date(),
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||||
})
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.where(eq(copilotChats.id, currentChat.id))
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||||
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||||
logger.info(`[${requestId}] Updated chat ${currentChat.id} with new messages`)
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||||
}
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||||
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||||
controller.enqueue(encoder.encode(`data: {"type":"done"}\n\n`))
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||||
} catch (error) {
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||||
logger.error(`[${requestId}] Streaming error:`, error)
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||||
const errorChunk = {
|
||||
type: 'error',
|
||||
error: 'Streaming failed',
|
||||
}
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||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify(errorChunk)}\n\n`))
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||||
} finally {
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||||
controller.close()
|
||||
}
|
||||
},
|
||||
}),
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||||
{
|
||||
headers: {
|
||||
'Content-Type': 'text/event-stream',
|
||||
'Cache-Control': 'no-cache',
|
||||
Connection: 'keep-alive',
|
||||
},
|
||||
}
|
||||
)
|
||||
}
|
||||
|
||||
// Save conversation to database for non-streaming response
|
||||
if (currentChat && session?.user?.id) {
|
||||
const userMessage = {
|
||||
id: crypto.randomUUID(),
|
||||
role: 'user',
|
||||
content: message,
|
||||
timestamp: new Date().toISOString(),
|
||||
}
|
||||
|
||||
// Extract citations from response if available
|
||||
const citations = typeof response === 'object' && 'citations' in response ? response.citations :
|
||||
typeof response === 'object' && 'toolResults' in response ? extractCitationsFromResponse(response) : []
|
||||
|
||||
const assistantMessage = {
|
||||
id: crypto.randomUUID(),
|
||||
role: 'assistant',
|
||||
content: typeof response === 'string' ? response :
|
||||
'content' in response ? response.content : '[Error generating response]',
|
||||
timestamp: new Date().toISOString(),
|
||||
citations: citations.length > 0 ? citations : undefined,
|
||||
}
|
||||
|
||||
const updatedMessages = [...conversationHistory, userMessage, assistantMessage]
|
||||
|
||||
// Generate title if this is the first message
|
||||
let updatedTitle = currentChat.title
|
||||
if (!updatedTitle && conversationHistory.length === 0) {
|
||||
updatedTitle = await generateChatTitle(message)
|
||||
}
|
||||
|
||||
await db
|
||||
.update(copilotChats)
|
||||
.set({
|
||||
title: updatedTitle,
|
||||
messages: updatedMessages,
|
||||
updatedAt: new Date(),
|
||||
})
|
||||
.where(eq(copilotChats.id, currentChat.id))
|
||||
|
||||
logger.info(`[${requestId}] Updated chat ${currentChat.id} with new messages`)
|
||||
}
|
||||
|
||||
logger.info(`[${requestId}] Chat response generated successfully`)
|
||||
|
||||
return NextResponse.json({
|
||||
success: true,
|
||||
response: typeof response === 'string' ? response :
|
||||
'content' in response ? response.content : '[Error generating response]',
|
||||
chatId: currentChat?.id,
|
||||
metadata: {
|
||||
requestId,
|
||||
message,
|
||||
},
|
||||
})
|
||||
} catch (error) {
|
||||
if (error instanceof z.ZodError) {
|
||||
return NextResponse.json(
|
||||
{ error: 'Invalid request data', details: error.errors },
|
||||
{ status: 400 }
|
||||
)
|
||||
}
|
||||
|
||||
logger.error(`[${requestId}] Copilot chat error:`, error)
|
||||
return NextResponse.json({ error: 'Internal server error' }, { status: 500 })
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,141 @@
|
||||
import { sql } from 'drizzle-orm'
|
||||
import { type NextRequest, NextResponse } from 'next/server'
|
||||
import { z } from 'zod'
|
||||
import { createLogger } from '@/lib/logs/console-logger'
|
||||
import { generateEmbeddings } from '@/app/api/knowledge/utils'
|
||||
import { db } from '@/db'
|
||||
import { docsEmbeddings } from '@/db/schema'
|
||||
|
||||
const logger = createLogger('DocsSearch')
|
||||
|
||||
const DocsSearchSchema = z.object({
|
||||
query: z.string().min(1, 'Query is required'),
|
||||
topK: z.number().min(1).max(10).default(5),
|
||||
})
|
||||
|
||||
/**
|
||||
* Generate embedding for search query
|
||||
*/
|
||||
async function generateSearchEmbedding(query: string): Promise<number[]> {
|
||||
try {
|
||||
const embeddings = await generateEmbeddings([query])
|
||||
return embeddings[0] || []
|
||||
} catch (error) {
|
||||
logger.error('Failed to generate search embedding:', error)
|
||||
throw new Error('Failed to generate search embedding')
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Search docs embeddings using vector similarity
|
||||
*/
|
||||
async function searchDocs(queryEmbedding: number[], topK: number) {
|
||||
try {
|
||||
const results = await db
|
||||
.select({
|
||||
chunkId: docsEmbeddings.chunkId,
|
||||
chunkText: docsEmbeddings.chunkText,
|
||||
sourceDocument: docsEmbeddings.sourceDocument,
|
||||
sourceLink: docsEmbeddings.sourceLink,
|
||||
headerText: docsEmbeddings.headerText,
|
||||
headerLevel: docsEmbeddings.headerLevel,
|
||||
similarity: sql<number>`1 - (${docsEmbeddings.embedding} <=> ${JSON.stringify(queryEmbedding)}::vector)`,
|
||||
})
|
||||
.from(docsEmbeddings)
|
||||
.orderBy(sql`${docsEmbeddings.embedding} <=> ${JSON.stringify(queryEmbedding)}::vector`)
|
||||
.limit(topK)
|
||||
|
||||
return results
|
||||
} catch (error) {
|
||||
logger.error('Failed to search docs:', error)
|
||||
throw new Error('Failed to search docs')
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* POST /api/docs/search
|
||||
* Search Sim Studio documentation using vector similarity
|
||||
*/
|
||||
export async function POST(req: NextRequest) {
|
||||
const requestId = crypto.randomUUID()
|
||||
|
||||
try {
|
||||
const body = await req.json()
|
||||
const { query, topK } = DocsSearchSchema.parse(body)
|
||||
|
||||
logger.info(`[${requestId}] 🔍 DOCS SEARCH TOOL CALLED - Query: "${query}"`, { topK })
|
||||
|
||||
// Step 1: Generate embedding for the query
|
||||
logger.info(`[${requestId}] Generating query embedding...`)
|
||||
const queryEmbedding = await generateSearchEmbedding(query)
|
||||
|
||||
if (queryEmbedding.length === 0) {
|
||||
return NextResponse.json({ error: 'Failed to generate query embedding' }, { status: 500 })
|
||||
}
|
||||
|
||||
// Step 2: Search for relevant docs chunks
|
||||
logger.info(`[${requestId}] Searching docs for top ${topK} chunks...`)
|
||||
const chunks = await searchDocs(queryEmbedding, topK)
|
||||
|
||||
if (chunks.length === 0) {
|
||||
return NextResponse.json({
|
||||
success: true,
|
||||
response: "I couldn't find any relevant documentation for that query.",
|
||||
sources: [],
|
||||
metadata: {
|
||||
requestId,
|
||||
chunksFound: 0,
|
||||
query,
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
// Step 3: Format the response with context and sources
|
||||
const context = chunks
|
||||
.map((chunk, index) => {
|
||||
const headerText = typeof chunk.headerText === 'string' ? chunk.headerText : String(chunk.headerText || 'Untitled Section')
|
||||
const sourceDocument = typeof chunk.sourceDocument === 'string' ? chunk.sourceDocument : String(chunk.sourceDocument || 'Unknown Document')
|
||||
const sourceLink = typeof chunk.sourceLink === 'string' ? chunk.sourceLink : String(chunk.sourceLink || '#')
|
||||
const chunkText = typeof chunk.chunkText === 'string' ? chunk.chunkText : String(chunk.chunkText || '')
|
||||
|
||||
return `[${index + 1}] ${headerText}
|
||||
Document: ${sourceDocument}
|
||||
URL: ${sourceLink}
|
||||
Content: ${chunkText}`
|
||||
})
|
||||
.join('\n\n')
|
||||
|
||||
// Step 4: Format sources for response
|
||||
const sources = chunks.map((chunk, index) => ({
|
||||
id: index + 1,
|
||||
title: chunk.headerText,
|
||||
document: chunk.sourceDocument,
|
||||
link: chunk.sourceLink,
|
||||
similarity: Math.round(chunk.similarity * 100) / 100,
|
||||
}))
|
||||
|
||||
logger.info(`[${requestId}] Found ${chunks.length} relevant chunks`)
|
||||
|
||||
return NextResponse.json({
|
||||
success: true,
|
||||
response: context,
|
||||
sources,
|
||||
metadata: {
|
||||
requestId,
|
||||
chunksFound: chunks.length,
|
||||
query,
|
||||
topSimilarity: sources[0]?.similarity,
|
||||
},
|
||||
})
|
||||
} catch (error) {
|
||||
if (error instanceof z.ZodError) {
|
||||
return NextResponse.json(
|
||||
{ error: 'Invalid request data', details: error.errors },
|
||||
{ status: 400 }
|
||||
)
|
||||
}
|
||||
|
||||
logger.error(`[${requestId}] Docs search error:`, error)
|
||||
return NextResponse.json({ error: 'Internal server error' }, { status: 500 })
|
||||
}
|
||||
}
|
||||
+14
-20
@@ -197,8 +197,7 @@ export const Copilot = forwardRef<CopilotRef, CopilotProps>(
|
||||
logger.info('Sending docs RAG query:', { query, chatId: currentChat?.id })
|
||||
|
||||
const result = await sendStreamingMessage({
|
||||
query,
|
||||
topK: 5,
|
||||
message: query,
|
||||
chatId: currentChat?.id,
|
||||
workflowId: activeWorkflowId,
|
||||
createNewChat: !currentChat,
|
||||
@@ -208,8 +207,8 @@ export const Copilot = forwardRef<CopilotRef, CopilotProps>(
|
||||
const reader = result.stream.getReader()
|
||||
const decoder = new TextDecoder()
|
||||
let accumulatedContent = ''
|
||||
let sources: any[] = []
|
||||
let newChatId: string | undefined
|
||||
let responseCitations: Array<{id: number, title: string, url: string}> = []
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read()
|
||||
@@ -224,47 +223,43 @@ export const Copilot = forwardRef<CopilotRef, CopilotProps>(
|
||||
const data = JSON.parse(line.slice(6))
|
||||
|
||||
if (data.type === 'metadata') {
|
||||
sources = data.sources || []
|
||||
// Get chatId from metadata (for both new and existing chats)
|
||||
if (data.chatId) {
|
||||
newChatId = data.chatId
|
||||
}
|
||||
// Get citations from metadata
|
||||
if (data.citations) {
|
||||
responseCitations = data.citations
|
||||
}
|
||||
} else if (data.type === 'content') {
|
||||
accumulatedContent += data.content
|
||||
|
||||
// Update the streaming message with accumulated content
|
||||
// Update the streaming message with accumulated content and citations
|
||||
setMessages((prev) =>
|
||||
prev.map((msg) =>
|
||||
msg.id === streamingMessage.id
|
||||
? {
|
||||
...msg,
|
||||
content: accumulatedContent,
|
||||
citations: sources.map((source: any, index: number) => ({
|
||||
id: index + 1,
|
||||
title: source.title,
|
||||
url: source.link,
|
||||
})),
|
||||
citations: responseCitations.length > 0 ? responseCitations : undefined,
|
||||
}
|
||||
: msg
|
||||
)
|
||||
)
|
||||
} else if (data.type === 'done') {
|
||||
// Finish streaming and reload chat if new chat was created
|
||||
// Final update to ensure citations are applied
|
||||
setMessages((prev) =>
|
||||
prev.map((msg) =>
|
||||
msg.id === streamingMessage.id
|
||||
? {
|
||||
...msg,
|
||||
citations: sources.map((source: any, index: number) => ({
|
||||
id: index + 1,
|
||||
title: source.title,
|
||||
url: source.link,
|
||||
})),
|
||||
content: accumulatedContent,
|
||||
citations: responseCitations.length > 0 ? responseCitations : undefined,
|
||||
}
|
||||
: msg
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
// Update current chat state with the chatId from response
|
||||
if (newChatId && !currentChat) {
|
||||
// For new chats, create a temporary chat object and reload the full chat list
|
||||
@@ -289,9 +284,8 @@ export const Copilot = forwardRef<CopilotRef, CopilotProps>(
|
||||
}
|
||||
}
|
||||
|
||||
logger.info('Received docs RAG response:', {
|
||||
logger.info('Received copilot chat response:', {
|
||||
contentLength: accumulatedContent.length,
|
||||
sourcesCount: sources.length,
|
||||
})
|
||||
} else {
|
||||
throw new Error(result.error || 'Failed to send message')
|
||||
@@ -420,7 +414,7 @@ export const Copilot = forwardRef<CopilotRef, CopilotProps>(
|
||||
{!message.content && (
|
||||
<div className='flex items-center gap-2 text-muted-foreground'>
|
||||
<Loader2 className='h-4 w-4 animate-spin' />
|
||||
<span className='text-sm'>Searching documentation...</span>
|
||||
<span className='text-sm'>Thinking...</span>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
@@ -262,16 +262,21 @@ export async function sendMessage(request: DocsQueryRequest): Promise<{
|
||||
}
|
||||
|
||||
/**
|
||||
* Send a streaming message using the docs RAG API
|
||||
* Send a streaming message using the new copilot chat API
|
||||
*/
|
||||
export async function sendStreamingMessage(request: DocsQueryRequest): Promise<{
|
||||
export async function sendStreamingMessage(request: {
|
||||
message: string
|
||||
chatId?: string
|
||||
workflowId?: string
|
||||
createNewChat?: boolean
|
||||
}): Promise<{
|
||||
success: boolean
|
||||
stream?: ReadableStream
|
||||
chatId?: string
|
||||
error?: string
|
||||
}> {
|
||||
try {
|
||||
const response = await fetch('/api/docs/ask', {
|
||||
const response = await fetch('/api/copilot/chat', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ ...request, stream: true }),
|
||||
|
||||
@@ -0,0 +1,73 @@
|
||||
import type { ToolConfig } from '../types'
|
||||
|
||||
export interface DocsSearchParams {
|
||||
query: string
|
||||
topK?: number
|
||||
}
|
||||
|
||||
export interface DocsSearchResponse {
|
||||
success: boolean
|
||||
output: {
|
||||
response: string
|
||||
sources: Array<{
|
||||
title: string
|
||||
document: string
|
||||
link: string
|
||||
similarity: number
|
||||
}>
|
||||
}
|
||||
error?: string
|
||||
}
|
||||
|
||||
export const docsSearchTool: ToolConfig<DocsSearchParams, DocsSearchResponse> = {
|
||||
id: 'docs_search_internal',
|
||||
name: 'Search Documentation',
|
||||
description: 'Search Sim Studio documentation using vector similarity search',
|
||||
version: '1.0.0',
|
||||
|
||||
params: {
|
||||
query: {
|
||||
type: 'string',
|
||||
required: true,
|
||||
description: 'The search query to find relevant documentation',
|
||||
},
|
||||
topK: {
|
||||
type: 'number',
|
||||
required: false,
|
||||
description: 'Number of results to return (default: 5, max: 10)',
|
||||
},
|
||||
},
|
||||
|
||||
request: {
|
||||
url: '/api/docs/search',
|
||||
method: 'POST',
|
||||
headers: () => ({
|
||||
'Content-Type': 'application/json',
|
||||
}),
|
||||
body: (params) => ({
|
||||
query: params.query,
|
||||
topK: params.topK || 5,
|
||||
}),
|
||||
isInternalRoute: true,
|
||||
},
|
||||
|
||||
transformResponse: async (response: Response) => {
|
||||
const data = await response.json()
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(data.error || 'Failed to search documentation')
|
||||
}
|
||||
|
||||
return {
|
||||
success: true,
|
||||
output: {
|
||||
response: data.response,
|
||||
sources: data.sources || [],
|
||||
},
|
||||
}
|
||||
},
|
||||
|
||||
transformError: (error) => {
|
||||
return error instanceof Error ? error.message : 'An error occurred while searching documentation'
|
||||
},
|
||||
}
|
||||
@@ -3,6 +3,7 @@ import { createLogger } from '@/lib/logs/console-logger'
|
||||
import { useCustomToolsStore } from '@/stores/custom-tools/store'
|
||||
import { useEnvironmentStore } from '@/stores/settings/environment/store'
|
||||
import { tools } from './registry'
|
||||
import { docsSearchTool } from './docs/search'
|
||||
import type { TableRow, ToolConfig, ToolResponse } from './types'
|
||||
|
||||
const logger = createLogger('ToolsUtils')
|
||||
@@ -267,8 +268,17 @@ export function createCustomToolRequestBody(
|
||||
}
|
||||
}
|
||||
|
||||
// Internal-only tools (not exposed to users in workflows)
|
||||
const internalTools: Record<string, ToolConfig> = {
|
||||
docs_search_internal: docsSearchTool,
|
||||
}
|
||||
|
||||
// Get a tool by its ID
|
||||
export function getTool(toolId: string): ToolConfig | undefined {
|
||||
// Check for internal tools first
|
||||
const internalTool = internalTools[toolId]
|
||||
if (internalTool) return internalTool
|
||||
|
||||
// Check for built-in tools
|
||||
const builtInTool = tools[toolId]
|
||||
if (builtInTool) return builtInTool
|
||||
@@ -302,6 +312,10 @@ export async function getToolAsync(
|
||||
toolId: string,
|
||||
workflowId?: string
|
||||
): Promise<ToolConfig | undefined> {
|
||||
// Check for internal tools first
|
||||
const internalTool = internalTools[toolId]
|
||||
if (internalTool) return internalTool
|
||||
|
||||
// Check for built-in tools
|
||||
const builtInTool = tools[toolId]
|
||||
if (builtInTool) return builtInTool
|
||||
|
||||
Reference in New Issue
Block a user