Flowise/packages/components/nodes/llms/Replicate/Replicate.ts

137 lines
5.2 KiB
TypeScript

import { BaseCache } from '@langchain/core/caches'
import { BaseLLMParams } from '@langchain/core/language_models/llms'
import { ICommonObject, INode, INodeData, INodeParams } from '../../../src/Interface'
import { getBaseClasses, getCredentialData, getCredentialParam } from '../../../src/utils'
import { Replicate, ReplicateInput } from './core'
class Replicate_LLMs implements INode {
label: string
name: string
version: number
type: string
icon: string
category: string
description: string
baseClasses: string[]
credential: INodeParams
inputs: INodeParams[]
constructor() {
this.label = 'Replicate'
this.name = 'replicate'
this.version = 2.0
this.type = 'Replicate'
this.icon = 'replicate.svg'
this.category = 'LLMs'
this.description = 'Use Replicate to run open source models on cloud'
this.baseClasses = [this.type, 'BaseChatModel', ...getBaseClasses(Replicate)]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['replicateApi']
}
this.inputs = [
{
label: 'Cache',
name: 'cache',
type: 'BaseCache',
optional: true
},
{
label: 'Model',
name: 'model',
type: 'string',
placeholder: 'a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5',
optional: true
},
{
label: 'Temperature',
name: 'temperature',
type: 'number',
step: 0.1,
description:
'Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.',
default: 0.7,
optional: true
},
{
label: 'Max Tokens',
name: 'maxTokens',
type: 'number',
step: 1,
description: 'Maximum number of tokens to generate. A word is generally 2-3 tokens',
optional: true,
additionalParams: true
},
{
label: 'Top Probability',
name: 'topP',
type: 'number',
step: 0.1,
description:
'When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens',
optional: true,
additionalParams: true
},
{
label: 'Repetition Penalty',
name: 'repetitionPenalty',
type: 'number',
step: 0.1,
description:
'Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it. (minimum: 0.01; maximum: 5)',
optional: true,
additionalParams: true
},
{
label: 'Additional Inputs',
name: 'additionalInputs',
type: 'json',
description:
'Each model has different parameters, refer to the specific model accepted inputs. For example: <a target="_blank" href="https://replicate.com/a16z-infra/llama13b-v2-chat/api#inputs">llama13b-v2</a>',
additionalParams: true,
optional: true
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
const modelName = nodeData.inputs?.model as `${string}/${string}` | `${string}/${string}:${string}`
const temperature = nodeData.inputs?.temperature as string
const maxTokens = nodeData.inputs?.maxTokens as string
const topP = nodeData.inputs?.topP as string
const repetitionPenalty = nodeData.inputs?.repetitionPenalty as string
const additionalInputs = nodeData.inputs?.additionalInputs as string
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const apiKey = getCredentialParam('replicateApiKey', credentialData, nodeData)
const cache = nodeData.inputs?.cache as BaseCache
const obj: ReplicateInput & BaseLLMParams = {
model: modelName,
apiKey
}
let inputs: any = {}
if (maxTokens) inputs.max_length = parseInt(maxTokens, 10)
if (temperature) inputs.temperature = parseFloat(temperature)
if (topP) inputs.top_p = parseFloat(topP)
if (repetitionPenalty) inputs.repetition_penalty = parseFloat(repetitionPenalty)
if (additionalInputs) {
const parsedInputs =
typeof additionalInputs === 'object' ? additionalInputs : additionalInputs ? JSON.parse(additionalInputs) : {}
inputs = { ...inputs, ...parsedInputs }
}
if (Object.keys(inputs).length) obj.input = inputs
if (cache) obj.cache = cache
const model = new Replicate(obj)
return model
}
}
module.exports = { nodeClass: Replicate_LLMs }