LabAgent

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Type two things. Get a measurement. Describe your research direction and sample — LabAgent searches the literature, scans your instruments, picks the measurement, runs it safely, and explains the science (physics, electrochemistry, spectroscopy, whatever fits) with cited references.

See It In Action

Every block above is real: live SSE activity stream, AI-picked measurement type with reasoning, live-drawn measurement curve, extracted quantities, and AI interpretation that cites papers by [N]. The example above shows a cyclic voltammetry scan on a ferrocene probe (via the BioLogic adapter) — swap in a Keithley or a Keysight scope and you'll see an IV sweep or a waveform instead. Sixteen measurement types now run on real instruments (covering electrical, electrochemistry, optoelectronics, and thermoelectric domains — via pymeasure + 3 in-tree VisaDrivers + Zurich Instruments adapter + BioLogic adapter); other measurement types still fall back to a physics simulator, and every CSV/PNG is clearly marked with which backend produced it.

Quick Start

pip install git+https://github.com/Anai-Guo/LabAgent.git
labharness setup    # one-time: pick AI provider, drop API key
labharness web      # opens http://127.0.0.1:8080

Then visit /experiment, type a research direction and material, hit Start.

Prefer terminal?

labharness start    # same flow, CLI-guided

Why It Exists

Most research labs have powerful instruments and terrible automation software. Researchers burn weeks writing one-off LabVIEW scripts for every new measurement, without safety nets or institutional memory. When a student graduates, the code leaves with them.

LabAgent replaces that with a shared, AI-guided framework. Add a new measurement type by writing a 20–30-line YAML template. Swap AI providers with one config line. Every experiment gets a timestamped folder with raw data, analysis figures, AI-cited interpretation, and next-step suggestions — organized the same way for everyone on the team.

Features at a Glance

Feature	Details
46 Measurement Templates	Ready-to-use YAML templates across 9 scientific disciplines
AI at Every Step	8 AI capabilities: classification, optimization, safety advisory, script generation, result interpretation, skill generation, agent chat, experiment memory
Adaptive Web GUI	Real-time dashboard and multi-panel monitor that dynamically generates forms from templates — no hardcoded pages
4 AI Model Providers	Claude, GPT-4o, Ollama, DeepSeek via litellm — switch with one config line; vLLM or any OpenAI-compatible server works through the openai provider with a base_url
Safety-First Design	3-tier boundary validation (block / require confirmation / allow) prevents dangerous configurations
Instrument Drivers	GPIB, USB, and serial instrument scanning with auto-retry and AI-powered classification of unknown devices
Experiment Memory	SQLite + FTS5 full-text search remembers your successful parameters and learns from history
MCP Server	Expose all tools to Claude Code, Cursor, or any MCP-compatible AI IDE

Web GUI

Start the adaptive measurement interface with a single command:

labharness web --port 8080

• Dashboard (/) — Browse all 46 templates grouped by discipline, configure sweep parameters, set safety limits, and generate validated measurement plans
• Monitor (/monitor) — Multi-panel real-time data display with user-selectable X/Y axes and WebSocket streaming

The GUI dynamically generates measurement forms from YAML templates. Adding a new template file automatically makes it available in the web interface — no frontend code changes needed.

Key monitor features:

• 4 chart panels with independently selectable X/Y axes from 16 data channels plus time
• 6 metric cards that auto-configure based on measurement template
• Template selector — switch between AHE, Hall, IV, etc. and the UI reconfigures
• Save/Load presets — save your chart layout for each experiment type, restore with one click
• Real-time sidebar — live channel values, sweep progress, elapsed time

Supported Disciplines

Discipline	Count	Example Measurements
Electrical Characterization	7	IV curve, R-T, delta mode, high resistance, FET transfer/output, breakdown
Electrochemistry	4	Cyclic voltammetry, EIS, chronoamperometry, potentiometry
Semiconductor & Optoelectronics	5	Solar cell IV, DLTS, photocurrent spectroscopy, photoresponse, tunneling
Sensors, Materials & Environmental	7	Gas sensor, humidity, impedance biosensor, cell counting, pH calibration, strain gauge, fatigue
Dielectric & Ferroelectric	4	C-V, P-E loop, pyroelectric current, capacitance-frequency
Thermoelectric	2	Seebeck coefficient, thermal conductivity
Superconductivity	2	Tc transition, critical current density (Jc)
Magnetic Measurements (condensed-matter)	8	Hall effect, magnetoresistance, AHE, SOT loop shift, FMR, hysteresis, magnetostriction, Nernst
Quantum Design PPMS/MPMS	6	PPMS R-T, PPMS MR, PPMS Hall, PPMS heat capacity, MPMS M-H, MPMS M-T ZFC/FC

Plus a universal custom sweep template for user-defined X-Y measurements (46 total).

Supported Instruments

Works out of the box with 68 models from 26 vendors across all the disciplines above:

Category	Representative Vendors / Models
Source meters, DMMs, electrometers, nanovoltmeters	Keithley 2400, 2000, 2182A, 6221, 6517B
Oscilloscopes	Tektronix TDS/MSO, Keysight DSOX/MSOX, Rigol DS/MSO
Function generators	Keysight 33500B/33622A, Tektronix AFG, Rigol DG
DC power supplies	Keysight E36313A, Rigol DP832A
Lock-in amplifiers	SRS SR830/SR860/SR865A, Zurich MFLI/HF2LI
Spectrum analyzers & VNAs	Keysight N9320B/E5071C, R&S FSV/ZNA
LCR & impedance	Keysight E4980A
Optics / photonics	Thorlabs PM100D, LDC205C, MDT693B, Newport 1830-C
UV-Vis spectrometers	Ocean Insight USB2000/QEPro, Thorlabs CCS100
Potentiostats (electrochemistry)	BioLogic SP-200/VSP/VMP3, Gamry Reference 600+/1010B, CH Instruments CHI760E, Metrohm Autolab PGSTAT, Palmsens4
Microplate readers (biology)	BMG CLARIOstar, Molecular Devices SpectraMax
Balances, pH, ISE	Mettler XS/XP (MT-SICS), Ohaus Adventurer, Thermo Orion A221
Gas / flow / pressure	Alicat MC-series MFCs, MKS PR4000
Temperature control	Lakeshore 335/336/340/350, Oxford Mercury iTC
Gaussmeters	Lakeshore 425, 455
DAQ	NI USB-6351/6001
Quantum Design (condensed-matter specialty)	PPMS, MPMS3 via MultiPyVu

Don't see your instrument? The AI calls the manual_lookup tool to fetch the manufacturer's programming manual, then classifies from the *IDN? response — so truly unknown devices are handled gracefully.

AI at Every Step

Capability	How AI Helps
Instrument Classification	LLM identifies unknown instruments from *IDN? responses and maps them to measurement roles
Parameter Optimization	Suggests optimal sweep ranges based on your sample type and literature references
Safety Advisory	Explains why a limit exists and suggests safer alternatives when boundaries are hit
Script Generation	Creates custom analysis scripts with publication-ready plots (PNG 300 dpi + PDF)
Result Interpretation	Extracts physical quantities and explains them with context
Skill Generation	Creates new measurement protocol skills from existing examples
Agent Chat	Multi-turn conversation with tool calling for guided measurement workflows
Experiment Memory	Learns from your history to improve parameter suggestions for future measurements

Choose Your AI Model

One config line switches between cloud and local models:

# Best quality (cloud)
model:
  provider: "anthropic"
  model: "claude-sonnet-4-20250514"

# Free & private (local)
model:
  provider: "ollama"
  model: "qwen3:32b"
  base_url: "http://localhost:11434"

Supported providers: Claude | GPT-4o | Ollama | DeepSeek (via litellm). vLLM or any other OpenAI-compatible server: use provider: "openai" with a base_url — see configs/models.yaml.

CLI Commands

Command	Description
labharness scan	Scan for connected instruments via GPIB/USB/serial
labharness classify <type>	Classify instruments into measurement roles
labharness propose <type>	Generate a measurement plan with safety validation
labharness literature <type>	Search literature for measurement protocols
labharness generate-skill <type>	Generate a new measurement protocol skill with AI
labharness analyze <file>	Analyze measurement data with AI interpretation
labharness chat	Interactive AI chat for guided measurement workflows
labharness procedures	List PICA reference instrument procedures
labharness web	Start the adaptive Web GUI (dashboard + monitor)
labharness serve	Start MCP server for AI IDE integration

MCP Server Tools

Run as an MCP server for integration with Claude Code, Cursor, or any MCP client:

labharness serve

Tool	Description
scan_instruments	Discover all connected lab instruments
classify_lab_instruments	Map instruments to measurement roles
propose_measurement	Generate a validated measurement plan
validate_plan	Check a plan against safety boundaries
search_literature	Find published measurement protocols
analyze_data	Run analysis with AI interpretation
generate_skill	Create new measurement protocol skills
manual_lookup	Fetch the manufacturer's programming manual and known Python drivers for an unfamiliar instrument
healthcheck	Verify system status and available templates

Compared to Alternatives

	LabAgent	LabVIEW	PyMeasure	PICA	Custom Scripts
AI-guided	Yes (4 providers)	No	No	No	No
Setup time	Minutes	Weeks	Hours	Hours	Days
Safety checks	3-tier auto	Manual	None	Manual	Manual
Templates	46 across 9 disciplines	Rebuild each	Code each	~10	Code each
Literature search	Built-in	No	No	No	No
Web GUI	Adaptive dashboard	Desktop only	No	No	No
MCP integration	Native	No	No	No	No
Cost	Free & open source	$$$$ license	Free	Free	Free
Learning curve	Natural language	Steep	Moderate	Moderate	Steep

Architecture

Roadmap

• 46 measurement templates across 9 disciplines
• AI-powered instrument classification, parameter optimization, safety advisory
• Agent loop with tool calling and experiment memory
• MCP server for Claude Code / Cursor integration
• Adaptive Web GUI with real-time monitoring
• Quantum Design PPMS/MPMS integration (MultiPyVu)
• Real-time measurement execution — 16 measurement types (IV, RT, DELTA, HIGH_R, BREAKDOWN, SEEBECK, TUNNELING, PHOTO_IV, CV, TRANSFER, OUTPUT, CYCLIC_VOLTAMMETRY, EIS, CHRONOAMPEROMETRY, PHOTORESPONSE, POTENTIOMETRY) run on real hardware via four backends: pymeasure adapter (16 models), 3 in-tree VisaDrivers (Keithley 2400/6221, Lakeshore 335), Zurich Instruments adapter (MFLI/HF2LI/SHFQA), and BioLogic adapter (SP-200/SP-300/VSP/VMP3). Remaining types fall back to the simulator.
• Real execution for remaining types (HALL, MR, AHE, FMR, PHOTOCURRENT, …)
• Gamry / CH Instruments potentiostat wrappers (electrochemistry)
• Community template marketplace
• PyPI package release

Contributing

We are building the future of AI-powered laboratory automation. Whether you work in physics, chemistry, biology, or materials science, your measurement templates and instrument drivers make this project better for everyone.

See CONTRIBUTING.md for development setup and CATALOG.md for the full template catalog with 46 templates and 33 instrument reference procedures.

Acknowledgments

• Measurement procedures adapted from PICA (MIT License)
• Agent architecture inspired by Hermes Agent patterns

License

MIT