feat: Convert all app files to JS
This commit is contained in:
3
packages/backend/src/apps/azure-openai/actions/index.js
Normal file
3
packages/backend/src/apps/azure-openai/actions/index.js
Normal file
@@ -0,0 +1,3 @@
|
||||
import sendPrompt from './send-prompt/index.js';
|
||||
|
||||
export default [sendPrompt];
|
@@ -1,3 +0,0 @@
|
||||
import sendPrompt from './send-prompt';
|
||||
|
||||
export default [sendPrompt];
|
@@ -0,0 +1,97 @@
|
||||
import defineAction from '../../../../helpers/define-action.js';
|
||||
|
||||
const castFloatOrUndefined = (value) => {
|
||||
return value === '' ? undefined : parseFloat(value);
|
||||
};
|
||||
|
||||
export default defineAction({
|
||||
name: 'Send prompt',
|
||||
key: 'sendPrompt',
|
||||
description: 'Creates a completion for the provided prompt and parameters.',
|
||||
arguments: [
|
||||
{
|
||||
label: 'Prompt',
|
||||
key: 'prompt',
|
||||
type: 'string',
|
||||
required: true,
|
||||
variables: true,
|
||||
description: 'The text to analyze.',
|
||||
},
|
||||
{
|
||||
label: 'Temperature',
|
||||
key: 'temperature',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description:
|
||||
'What sampling temperature to use, between 0 and 2. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. We generally recommend altering this or Top P but not both.',
|
||||
},
|
||||
{
|
||||
label: 'Maximum tokens',
|
||||
key: 'maxTokens',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description:
|
||||
'The maximum number of tokens to generate in the completion.',
|
||||
},
|
||||
{
|
||||
label: 'Stop Sequence',
|
||||
key: 'stopSequence',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description:
|
||||
'Single stop sequence where the API will stop generating further tokens. The returned text will not contain the stop sequence.',
|
||||
},
|
||||
{
|
||||
label: 'Top P',
|
||||
key: 'topP',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description:
|
||||
'An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.',
|
||||
},
|
||||
{
|
||||
label: 'Frequency Penalty',
|
||||
key: 'frequencyPenalty',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description: `Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.`,
|
||||
},
|
||||
{
|
||||
label: 'Presence Penalty',
|
||||
key: 'presencePenalty',
|
||||
type: 'string',
|
||||
required: false,
|
||||
variables: true,
|
||||
description: `Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.`,
|
||||
},
|
||||
],
|
||||
|
||||
async run($) {
|
||||
const payload = {
|
||||
model: $.step.parameters.model,
|
||||
prompt: $.step.parameters.prompt,
|
||||
temperature: castFloatOrUndefined($.step.parameters.temperature),
|
||||
max_tokens: castFloatOrUndefined($.step.parameters.maxTokens),
|
||||
stop: $.step.parameters.stopSequence || null,
|
||||
top_p: castFloatOrUndefined($.step.parameters.topP),
|
||||
frequency_penalty: castFloatOrUndefined(
|
||||
$.step.parameters.frequencyPenalty
|
||||
),
|
||||
presence_penalty: castFloatOrUndefined($.step.parameters.presencePenalty),
|
||||
};
|
||||
|
||||
const { data } = await $.http.post(
|
||||
`/deployments/${$.auth.data.deploymentId}/completions`,
|
||||
payload
|
||||
);
|
||||
|
||||
$.setActionItem({
|
||||
raw: data,
|
||||
});
|
||||
},
|
||||
});
|
@@ -1,87 +0,0 @@
|
||||
import defineAction from '../../../../helpers/define-action';
|
||||
|
||||
const castFloatOrUndefined = (value: string | null) => {
|
||||
return value === '' ? undefined : parseFloat(value);
|
||||
}
|
||||
|
||||
export default defineAction({
|
||||
name: 'Send prompt',
|
||||
key: 'sendPrompt',
|
||||
description: 'Creates a completion for the provided prompt and parameters.',
|
||||
arguments: [
|
||||
{
|
||||
label: 'Prompt',
|
||||
key: 'prompt',
|
||||
type: 'string' as const,
|
||||
required: true,
|
||||
variables: true,
|
||||
description: 'The text to analyze.'
|
||||
},
|
||||
{
|
||||
label: 'Temperature',
|
||||
key: 'temperature',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: 'What sampling temperature to use, between 0 and 2. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer. We generally recommend altering this or Top P but not both.'
|
||||
},
|
||||
{
|
||||
label: 'Maximum tokens',
|
||||
key: 'maxTokens',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: 'The maximum number of tokens to generate in the completion.'
|
||||
},
|
||||
{
|
||||
label: 'Stop Sequence',
|
||||
key: 'stopSequence',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: 'Single stop sequence where the API will stop generating further tokens. The returned text will not contain the stop sequence.'
|
||||
},
|
||||
{
|
||||
label: 'Top P',
|
||||
key: 'topP',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: 'An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.'
|
||||
},
|
||||
{
|
||||
label: 'Frequency Penalty',
|
||||
key: 'frequencyPenalty',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: `Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.`
|
||||
},
|
||||
{
|
||||
label: 'Presence Penalty',
|
||||
key: 'presencePenalty',
|
||||
type: 'string' as const,
|
||||
required: false,
|
||||
variables: true,
|
||||
description: `Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.`
|
||||
},
|
||||
],
|
||||
|
||||
async run($) {
|
||||
const payload = {
|
||||
model: $.step.parameters.model as string,
|
||||
prompt: $.step.parameters.prompt as string,
|
||||
temperature: castFloatOrUndefined($.step.parameters.temperature as string),
|
||||
max_tokens: castFloatOrUndefined($.step.parameters.maxTokens as string),
|
||||
stop: ($.step.parameters.stopSequence as string || null),
|
||||
top_p: castFloatOrUndefined($.step.parameters.topP as string),
|
||||
frequency_penalty: castFloatOrUndefined($.step.parameters.frequencyPenalty as string),
|
||||
presence_penalty: castFloatOrUndefined($.step.parameters.presencePenalty as string),
|
||||
};
|
||||
const { data } = await $.http.post(`/deployments/${$.auth.data.deploymentId}/completions`, payload);
|
||||
|
||||
$.setActionItem({
|
||||
raw: data,
|
||||
});
|
||||
},
|
||||
});
|
@@ -1,12 +1,12 @@
|
||||
import verifyCredentials from './verify-credentials';
|
||||
import isStillVerified from './is-still-verified';
|
||||
import verifyCredentials from './verify-credentials.js';
|
||||
import isStillVerified from './is-still-verified.js';
|
||||
|
||||
export default {
|
||||
fields: [
|
||||
{
|
||||
key: 'screenName',
|
||||
label: 'Screen Name',
|
||||
type: 'string' as const,
|
||||
type: 'string',
|
||||
required: true,
|
||||
readOnly: false,
|
||||
value: null,
|
||||
@@ -18,7 +18,7 @@ export default {
|
||||
{
|
||||
key: 'yourResourceName',
|
||||
label: 'Your Resource Name',
|
||||
type: 'string' as const,
|
||||
type: 'string',
|
||||
required: true,
|
||||
readOnly: false,
|
||||
value: null,
|
||||
@@ -30,7 +30,7 @@ export default {
|
||||
{
|
||||
key: 'deploymentId',
|
||||
label: 'Deployment ID',
|
||||
type: 'string' as const,
|
||||
type: 'string',
|
||||
required: true,
|
||||
readOnly: false,
|
||||
value: null,
|
||||
@@ -42,7 +42,7 @@ export default {
|
||||
{
|
||||
key: 'apiKey',
|
||||
label: 'API Key',
|
||||
type: 'string' as const,
|
||||
type: 'string',
|
||||
required: true,
|
||||
readOnly: false,
|
||||
value: null,
|
@@ -0,0 +1,6 @@
|
||||
const isStillVerified = async ($) => {
|
||||
await $.http.get('/fine_tuning/jobs');
|
||||
return true;
|
||||
};
|
||||
|
||||
export default isStillVerified;
|
@@ -1,8 +0,0 @@
|
||||
import { IGlobalVariable } from '@automatisch/types';
|
||||
|
||||
const isStillVerified = async ($: IGlobalVariable) => {
|
||||
await $.http.get('/fine_tuning/jobs');
|
||||
return true;
|
||||
};
|
||||
|
||||
export default isStillVerified;
|
@@ -0,0 +1,5 @@
|
||||
const verifyCredentials = async ($) => {
|
||||
await $.http.get('/fine_tuning/jobs');
|
||||
};
|
||||
|
||||
export default verifyCredentials;
|
@@ -1,7 +0,0 @@
|
||||
import { IGlobalVariable } from '@automatisch/types';
|
||||
|
||||
const verifyCredentials = async ($: IGlobalVariable) => {
|
||||
await $.http.get('/fine_tuning/jobs');
|
||||
};
|
||||
|
||||
export default verifyCredentials;
|
@@ -0,0 +1,13 @@
|
||||
const addAuthHeader = ($, requestConfig) => {
|
||||
if ($.auth.data?.apiKey) {
|
||||
requestConfig.headers['api-key'] = $.auth.data.apiKey;
|
||||
}
|
||||
|
||||
requestConfig.params = {
|
||||
'api-version': '2023-10-01-preview',
|
||||
};
|
||||
|
||||
return requestConfig;
|
||||
};
|
||||
|
||||
export default addAuthHeader;
|
@@ -1,15 +0,0 @@
|
||||
import { TBeforeRequest } from '@automatisch/types';
|
||||
|
||||
const addAuthHeader: TBeforeRequest = ($, requestConfig) => {
|
||||
if ($.auth.data?.apiKey) {
|
||||
requestConfig.headers['api-key'] = $.auth.data.apiKey as string;
|
||||
}
|
||||
|
||||
requestConfig.params = {
|
||||
'api-version': '2023-10-01-preview'
|
||||
}
|
||||
|
||||
return requestConfig;
|
||||
};
|
||||
|
||||
export default addAuthHeader;
|
@@ -0,0 +1,11 @@
|
||||
const setBaseUrl = ($, requestConfig) => {
|
||||
const yourResourceName = $.auth.data.yourResourceName;
|
||||
|
||||
if (yourResourceName) {
|
||||
requestConfig.baseURL = `https://${yourResourceName}.openai.azure.com/openai`;
|
||||
}
|
||||
|
||||
return requestConfig;
|
||||
};
|
||||
|
||||
export default setBaseUrl;
|
@@ -1,13 +0,0 @@
|
||||
import { TBeforeRequest } from '@automatisch/types';
|
||||
|
||||
const setBaseUrl: TBeforeRequest = ($, requestConfig) => {
|
||||
const yourResourceName = $.auth.data.yourResourceName as string;
|
||||
|
||||
if (yourResourceName) {
|
||||
requestConfig.baseURL = `https://${yourResourceName}.openai.azure.com/openai`;
|
||||
}
|
||||
|
||||
return requestConfig;
|
||||
};
|
||||
|
||||
export default setBaseUrl;
|
@@ -1,8 +1,8 @@
|
||||
import defineApp from '../../helpers/define-app';
|
||||
import setBaseUrl from './common/set-base-url';
|
||||
import addAuthHeader from './common/add-auth-header';
|
||||
import auth from './auth';
|
||||
import actions from './actions';
|
||||
import defineApp from '../../helpers/define-app.js';
|
||||
import setBaseUrl from './common/set-base-url.js';
|
||||
import addAuthHeader from './common/add-auth-header.js';
|
||||
import auth from './auth/index.js';
|
||||
import actions from './actions/index.js';
|
||||
|
||||
export default defineApp({
|
||||
name: 'Azure OpenAI',
|
Reference in New Issue
Block a user