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* feat(tools): added calcom * added more triggers, tested * updated regex in script for release to be more lenient * fix(tag-dropdown): performance improvements and scroll bug fixes - Add flatTagIndexMap for O(1) tag lookups (replaces O(n²) findIndex calls) - Memoize caret position calculation to avoid DOM manipulation on every render - Use refs for inputValue/cursorPosition to keep handleTagSelect callback stable - Change itemRefs from index-based to tag-based keys to prevent stale refs - Fix scroll jump in nested folders by removing scroll reset from registerFolder - Add onFolderEnter callback for scroll reset when entering folder via keyboard - Disable keyboard navigation wrap-around at boundaries - Simplify selection reset to single effect on flatTagList.length change Also: - Add safeCompare utility for timing-safe string comparison - Refactor webhook signature validation to use safeCompare Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * updated types * fix(calcom): simplify required field constraints for booking attendee The condition field already restricts these to calcom_create_booking, so simplified to required: true. Per Cal.com API docs, email is optional while name and timeZone are required. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * added tests * updated folder multi select, updated calcom and github tools and docs generator script * updated drag, updated outputs for tools, regen docs with nested docs script * updated setup instructions links, destructure trigger outputs, fix text subblock styling * updated docs gen script * updated docs script * updated docs script * updated script * remove destructuring of stripe webhook * expanded wand textarea, updated calcom tools --------- Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
130 lines
6.0 KiB
Plaintext
130 lines
6.0 KiB
Plaintext
---
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title: Knowledge
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description: Use vector search
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---
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import { BlockInfoCard } from "@/components/ui/block-info-card"
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<BlockInfoCard
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type="knowledge"
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color="#00B0B0"
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/>
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{/* MANUAL-CONTENT-START:intro */}
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Sim's Knowledge Base is a powerful native feature that enables you to create, manage, and query custom knowledge bases directly within the platform. Using advanced AI embeddings and vector search technology, the Knowledge Base block allows you to build intelligent search capabilities into your workflows, making it easy to find and utilize relevant information across your organization.
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The Knowledge Base system provides a comprehensive solution for managing organizational knowledge through its flexible and scalable architecture. With its built-in vector search capabilities, teams can perform semantic searches that understand meaning and context, going beyond traditional keyword matching.
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Key features of the Knowledge Base include:
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- Semantic Search: Advanced AI-powered search that understands meaning and context, not just keywords
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- Vector Embeddings: Automatic conversion of text into high-dimensional vectors for intelligent similarity matching
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- Custom Knowledge Bases: Create and manage multiple knowledge bases for different purposes or departments
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- Flexible Content Types: Support for various document formats and content types
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- Real-time Updates: Immediate indexing of new content for instant searchability
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In Sim, the Knowledge Base block enables your agents to perform intelligent semantic searches across your custom knowledge bases. This creates opportunities for automated information retrieval, content recommendations, and knowledge discovery as part of your AI workflows. The integration allows agents to search and retrieve relevant information programmatically, facilitating automated knowledge management tasks and ensuring that important information is easily accessible. By leveraging the Knowledge Base block, you can build intelligent agents that enhance information discovery while automating routine knowledge management tasks, improving team efficiency and ensuring consistent access to organizational knowledge.
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{/* MANUAL-CONTENT-END */}
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## Usage Instructions
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Integrate Knowledge into the workflow. Can search, upload chunks, and create documents.
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## Tools
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### `knowledge_search`
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Search for similar content in a knowledge base using vector similarity
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `knowledgeBaseId` | string | Yes | ID of the knowledge base to search in |
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| `query` | string | No | Search query text \(optional when using tag filters\) |
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| `topK` | number | No | Number of most similar results to return \(1-100\) |
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| `tagFilters` | array | No | Array of tag filters with tagName and tagValue properties |
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| `items` | object | No | No description |
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| `properties` | string | No | No description |
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| `tagName` | string | No | No description |
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| `tagValue` | string | No | No description |
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| `tagFilters` | string | No | No description |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `results` | array | Array of search results from the knowledge base |
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| ↳ `documentId` | string | Document ID |
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| ↳ `documentName` | string | Document name |
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| ↳ `content` | string | Content of the result |
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| ↳ `chunkIndex` | number | Index of the chunk within the document |
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| ↳ `similarity` | number | Similarity score of the result |
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| ↳ `metadata` | object | Metadata of the result, including tags |
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| `query` | string | The search query that was executed |
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| `totalResults` | number | Total number of results found |
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| `cost` | object | Cost information for the search operation |
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### `knowledge_upload_chunk`
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Upload a new chunk to a document in a knowledge base
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `knowledgeBaseId` | string | Yes | ID of the knowledge base containing the document |
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| `documentId` | string | Yes | ID of the document to upload the chunk to |
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| `content` | string | Yes | Content of the chunk to upload |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `data` | object | Information about the uploaded chunk |
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| ↳ `chunkId` | string | Chunk ID |
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| ↳ `chunkIndex` | number | Index of the chunk within the document |
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| ↳ `content` | string | Content of the chunk |
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| ↳ `contentLength` | number | Length of the content in characters |
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| ↳ `tokenCount` | number | Number of tokens in the chunk |
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| ↳ `enabled` | boolean | Whether the chunk is enabled |
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| ↳ `createdAt` | string | Creation timestamp |
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| ↳ `updatedAt` | string | Last update timestamp |
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| `message` | string | Success or error message describing the operation result |
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| `documentId` | string | ID of the document the chunk was added to |
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| `documentName` | string | Name of the document the chunk was added to |
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| `cost` | object | Cost information for the upload operation |
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### `knowledge_create_document`
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Create a new document in a knowledge base
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `knowledgeBaseId` | string | Yes | ID of the knowledge base containing the document |
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| `name` | string | Yes | Name of the document |
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| `content` | string | Yes | Content of the document |
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| `documentTags` | object | No | Document tags |
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| `documentTags` | string | No | No description |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `data` | object | Information about the created document |
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| ↳ `documentId` | string | Document ID |
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| ↳ `documentName` | string | Document name |
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| ↳ `type` | string | Document type |
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| ↳ `enabled` | boolean | Whether the document is enabled |
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| ↳ `createdAt` | string | Creation timestamp |
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| ↳ `updatedAt` | string | Last update timestamp |
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| `message` | string | Success or error message describing the operation result |
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| `documentId` | string | ID of the created document |
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