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Note that some of these functions make use of proprietary software, which could incur additional runtime charges.
inference
Run LLM inference on a string
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charityengine.inference(model, prompt, assets, context, system, template, options)
PARAMETERS
model // Name of the model to use [string] [required]
prompt // Text to pass to the model as input [string] [required]
assets // Images or files [array of string]
context // Additional context for the model [string]
system // System parameters for the model [string]
template // Template to guide response format [string]
options // Additional options for the request [object] |
embeddings
Generate a vector embedding for a string
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charityengine.embeddings(model, prompt)
PARAMETERS
model // Name of the model to use [string] [required]
prompt // Text to pass to the model as input [string] [required] |
wolframengine
Run Wolfram Language Code
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charityengine.wolframengine(commandline, inputfile)
PARAMETERS
commandline // Command to execute within the application [string] [required]
inputfile // Names of local files to use as input [array of string] |
To For example, to generate a chi-squared distribution with with v degrees of freedom using Wolfram Engine:
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charityengine.wolframengine('ChiSquareDistribution[v]')
.then(response => console.log('Response:', response))
.catch(error => console.error('Error:', error)); |
vina
Run a protein-ligand binding simulation
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charityengine.vina(commandline, inputfile)
PARAMETERS
commandline // Command line for the application [string] [required]
inputfile // Names of local files to use as input [array of string] |
blastp
Compare an amino acid sequence (protein sequence) against a protein sequence database
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charityengine.blastp(commandline, inputfile)
PARAMETERS
commandline // Command line for the application [string] [required]
inputfile // Names of local files to use as input [array of string] |
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