AI Agent for LabVIEW Introduction


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Product Overview

Agent for LabVIEW is an intelligent agent development toolkit for measurement, control, and automation scenarios. It brings the understanding, planning, and execution capabilities of large language models (LLM) into LabVIEW, enabling developers to quickly build deployable intelligent applications through natural language + VI toolchains.
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The core objectives of this toolkit are:

  • Enable the model to understand LabVIEW projects and VI logic

  • Enable the model to call VIs to complete actual tasks

  • Enable the model to participate in document processing, code generation, and engineering collaboration

  • Parse VIs to complete LabVIEW-to-other-language conversion

The current version supports both LabVIEW 64-bit and 32-bit environments (LabVIEW 2018 and above), facilitating smooth integration into existing projects and historical systems.

Why Agent for LabVIEW is Needed

In scenarios such as industrial testing, production line control, device commissioning, and scientific research experiments, LabVIEW has stable and reliable graphical development capabilities, but still needs enhancement in the following areas:

  • Rapid understanding and knowledge reuse of complex projects

  • Automatic decomposition and execution of natural language requirements

  • Unified scheduling of multi-tool and multi-module workflows

The design goal of Agent for LabVIEW is to upgrade LabVIEW from a "programmable tool" to a "collaborative intelligent agent platform": Not only can it execute predetermined programs, but it can also complete understanding, planning, calling, and feedback within constraints.

Core Capabilities

VI Parsing and Understanding (VI Understanding)

The model can read VI-related information and provide structured explanations, helping teams quickly take over and maintain projects.

  • Analyze VI inputs/outputs and key nodes

  • Understand block diagram flows and module relationships

  • Generate readable function descriptions and calling suggestions

  • Assist in locating potential logic issues

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Tool Calling and Task Execution (Tool Calling)

The model can call your defined VI tools to complete real task loops under strategic control.

  • Support encapsulating any VI as a callable tool

  • Support integration with cameras, DAQ, instruments, databases, and other systems

  • Support multi-step task orchestration (acquire -> process -> output)

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Document Understanding and Generation (Document Parsing)

Support extracting information from project documents and participating in Q&A, summarization, and process generation.

  • Support common document types (such as PDF, Word, TXT)

  • Targeted at manuals, parameter sheets, process documents, and other scenarios

  • Assist in generating experimental steps and operation suggestions

Support packaging content into complete documents to generate project code documentation.

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Multi-Model Integration and Switching (Multi-LLM Support)

The toolkit uses a unified interface, making it easy to switch between different model service providers based on scenarios.

  • Unified integration protocol, reducing repetitive development

  • Can select model capabilities by task type

  • Easy subsequent expansion and operational management

  • Already supports mainstream models including Qwen, DeepSeek, Wenxin Yiyan, Doubao, Zhipu, Siliconflow, Kimi, and continues to expand

Code Generation and Automation Assistance (Code Assistance)

Under constraints, the model can assist in generating scripts/code and engineering content to improve development efficiency.

  • Generate common scripts or configuration files

  • Assist in building prototype flows and verification logic

  • Work with existing LabVIEW projects

Note: Some capabilities (such as directly generating runnable VIs) are detailed in the VI Generator product.

多模态感知

Give the system "eyes," supporting VLM visual understanding and AIGC generation. From industrial visual quality inspection to automated document generation, AI can both identify defects and draw prototypes.

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Multi-Agent Collaboration and Engineering Extension (Multi-Agent)

For complex tasks, multi-agent task decomposition and collaborative execution can be performed.

  • Support single-agent and multi-agent workflows

  • Support contextual conversation and streaming output

  • Support business-encapsulated enterprise private toolkits

Typical Application Scenarios

  • Automated test process assistant (requirement parsing -> test execution -> result aggregation)

  • Laboratory task automation (document reading -> parameter下发 -> process recording)

  • Device commissioning and troubleshooting (data acquisition -> diagnostic suggestions -> operation guidance)

  • Engineering knowledge accumulation (automated VI documentation, experience Q&A)

  • Intelligent quality inspection and monitoring (visual recognition -> judgment -> linked execution)

  • Robot/execution mechanism control (task understanding -> tool calling -> action execution)

Version and Compatibility Notes

  • LabVIEW Version: LabVIEW 2018 and above

  • System Architecture: Supports 32-bit and 64-bit versions

  • Recommended Component: VIPM installation recommended (for toolkit installation and management)

  • Network Requirement: Network connection required for initial configuration and model calling

Notes:

  • The 32-bit version maintains core capabilities (model integration, tool calling, multi-agent, contextual conversation, etc.)

  • For privatization or local model routes, planning can be done in conjunction with the enterprise environment at the deployment stage

From 0 to 1 Getting Started Path

Step 1: Complete Installation and Activation

  1. Install toolkit and restart LabVIEW

  2. Check authorization status in License Manager

  3. If not activated, apply for trial or import authorization as per process

Step 2: Configure Model Key

  1. Open LLM Keys configuration entry from LabVIEW menu

  2. Select corresponding model service provider and fill in API Key

  3. Use Test to verify connectivity and click OK to save

Step 3: Run Official Examples

  1. Enter VIRobotics/AI Agent directory through Find Examples

  2. First run basic chat example to confirm model calling is normal

  3. Then run complete examples to experience context, streaming output, and tool calling

Step 4: Create Your VI Tools

  1. Write reusable VI logic and organize inputs/outputs

  2. Supplement tool JSON description information (function, parameters, path)

  3. Load tools in Agent and perform conversational calling verification

It is recommended to start from a single small tool (such as getting time, file processing, basic acquisition), then gradually expand to toolchains.

Target Audience

  • LabVIEW development engineers

  • Automation testing and equipment engineers

  • Scientific research experiments and teaching teams

  • Industrial software integration and operations teams

Documentation Reading Recommendations

If you are new to this toolkit, it is recommended to read in the following order:

  1. This chapter: Understand toolkit positioning and capability boundaries

  2. Installation Guide: Complete environment installation, activation, and model key configuration

  3. Developer Guide: Learn modules, examples, tool encapsulation, and calling processes

  4. FAQ: Troubleshoot common issues

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