Add Activepieces integration for workflow automation
- Add Activepieces fork with SmoothSchedule custom piece - Create integrations app with Activepieces service layer - Add embed token endpoint for iframe integration - Create Automations page with embedded workflow builder - Add sidebar visibility fix for embed mode - Add list inactive customers endpoint to Public API - Include SmoothSchedule triggers: event created/updated/cancelled - Include SmoothSchedule actions: create/update/cancel events, list resources/services/customers 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
poduck
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import { createAction, Property, StoreScope } from '@activepieces/pieces-framework';
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import { groqAuth } from '../..';
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import { httpClient, HttpMethod, AuthenticationType } from '@activepieces/pieces-common';
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export const askGroq = createAction({
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auth: groqAuth,
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name: 'ask-ai',
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displayName: 'Ask AI',
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description: 'Ask Groq anything using fast language models.',
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props: {
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model: Property.Dropdown({
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auth: groqAuth,
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displayName: 'Model',
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required: true,
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description: 'The model which will generate the completion.',
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refreshers: [],
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defaultValue: 'llama-3.1-70b-versatile',
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options: async ({ auth }) => {
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if (!auth) {
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return {
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disabled: true,
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placeholder: 'Please connect your Groq account first.',
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options: [],
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};
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}
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try {
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const response = await httpClient.sendRequest({
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url: 'https://api.groq.com/openai/v1/models',
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method: HttpMethod.GET,
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text,
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},
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});
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// Filter out audio models
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const models = (response.body.data as Array<{ id: string }>).filter(
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(model) => !model.id.toLowerCase().includes('whisper'),
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);
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return {
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disabled: false,
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options: models.map((model) => {
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return {
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label: model.id,
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value: model.id,
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};
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}),
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};
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} catch (error) {
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return {
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disabled: true,
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options: [],
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placeholder: "Couldn't load models, API key is invalid",
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};
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}
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},
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}),
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prompt: Property.LongText({
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displayName: 'Question',
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required: true,
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}),
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temperature: Property.Number({
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displayName: 'Temperature',
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required: false,
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description:
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'Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.',
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defaultValue: 0.9,
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}),
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maxTokens: Property.Number({
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displayName: 'Maximum Tokens',
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required: true,
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description:
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"The maximum number of tokens to generate. The total length of input tokens and generated tokens is limited by the model's context length.",
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defaultValue: 2048,
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}),
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topP: Property.Number({
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displayName: 'Top P',
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required: false,
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description:
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'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.',
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defaultValue: 1,
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}),
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frequencyPenalty: Property.Number({
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displayName: 'Frequency penalty',
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required: false,
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description:
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"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.",
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defaultValue: 0,
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}),
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presencePenalty: Property.Number({
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displayName: 'Presence penalty',
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required: false,
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description:
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"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.",
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defaultValue: 0.6,
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}),
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memoryKey: Property.ShortText({
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displayName: 'Memory Key',
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description:
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'A memory key that will keep the chat history shared across runs and flows. Keep it empty to leave Groq without memory of previous messages.',
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required: false,
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}),
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roles: Property.Json({
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displayName: 'Roles',
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required: false,
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description: 'Array of roles to specify more accurate response',
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defaultValue: [{ role: 'system', content: 'You are a helpful assistant.' }],
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}),
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},
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async run({ auth, propsValue, store }) {
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const {
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model,
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temperature,
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maxTokens,
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topP,
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frequencyPenalty,
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presencePenalty,
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prompt,
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memoryKey,
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} = propsValue;
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let messageHistory: any[] | null = [];
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// If memory key is set, retrieve messages stored in history
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if (memoryKey) {
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messageHistory = (await store.get(memoryKey, StoreScope.PROJECT)) ?? [];
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}
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// Add user prompt to message history
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messageHistory.push({
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role: 'user',
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content: prompt,
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});
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// Add system instructions if set by user
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const rolesArray = propsValue.roles ? (propsValue.roles as any) : [];
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const roles = rolesArray.map((item: any) => {
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const rolesEnum = ['system', 'user', 'assistant'];
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if (!rolesEnum.includes(item.role)) {
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throw new Error('The only available roles are: [system, user, assistant]');
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}
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return {
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role: item.role,
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content: item.content,
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};
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});
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// Send prompt
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const completion = await httpClient.sendRequest({
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method: HttpMethod.POST,
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url: 'https://api.groq.com/openai/v1/chat/completions',
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text,
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},
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body: {
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model: model,
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messages: [...roles, ...messageHistory],
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temperature: temperature,
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top_p: topP,
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frequency_penalty: frequencyPenalty,
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presence_penalty: presencePenalty,
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max_completion_tokens: maxTokens,
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},
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});
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// Add response to message history
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messageHistory = [...messageHistory, completion.body.choices[0].message];
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// Store history if memory key is set
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if (memoryKey) {
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await store.put(memoryKey, messageHistory, StoreScope.PROJECT);
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}
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// Get the raw content from the response
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const rawContent = completion.body.choices[0].message.content;
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// Check if the response contains thinking (content inside <think> tags)
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const thinkRegex = /<think>([\s\S]*?)<\/think>/;
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const thinkMatch = rawContent.match(thinkRegex);
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// Create the response structure
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const responseStructure = [];
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if (thinkMatch) {
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// Extract the thinking content
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const thinkContent = thinkMatch[1].trim();
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// Extract the final answer (content after the last </think> tag)
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const finalContent = rawContent.split('</think>').pop()?.trim() || '';
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// Add to response structure
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responseStructure.push({
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Think: thinkContent,
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Content: finalContent
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});
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} else {
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// If no thinking tags, just return the content as is
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responseStructure.push({
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Think: null,
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Content: rawContent
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});
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}
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return responseStructure;
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},
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});
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@@ -0,0 +1,126 @@
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import { createAction, Property } from '@activepieces/pieces-framework';
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import { groqAuth } from '../..';
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import { httpClient, HttpMethod, AuthenticationType } from '@activepieces/pieces-common';
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export const transcribeAudio = createAction({
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auth: groqAuth,
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name: 'transcribe-audio',
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displayName: 'Transcribe Audio',
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description: 'Transcribes audio into text in the input language.',
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props: {
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file: Property.File({
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displayName: 'Audio File',
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required: true,
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description:
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'The audio file to transcribe. Supported formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm.',
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}),
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model: Property.Dropdown({
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displayName: 'Model',
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auth: groqAuth,
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required: true,
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description: 'The model to use for transcription.',
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refreshers: [],
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defaultValue: 'whisper-large-v3',
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options: async ({ auth }) => {
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if (!auth) {
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return {
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disabled: true,
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placeholder: 'Please connect your Groq account first.',
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options: [],
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};
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}
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try {
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const response = await httpClient.sendRequest({
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url: 'https://api.groq.com/openai/v1/models',
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method: HttpMethod.GET,
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text,
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},
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});
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// Filter for whisper models only
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const models = (response.body.data as Array<{ id: string }>).filter((model) =>
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model.id.toLowerCase().includes('whisper'),
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);
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return {
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disabled: false,
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options: models.map((model) => {
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return {
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label: model.id,
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value: model.id,
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};
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}),
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};
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} catch (error) {
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return {
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disabled: true,
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options: [],
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placeholder: "Couldn't load models, API key is invalid",
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};
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}
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},
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}),
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language: Property.ShortText({
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displayName: 'Language',
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required: false,
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description:
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'The language of the input audio in ISO-639-1 format (e.g., "en" for English). This will improve accuracy and latency.',
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}),
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prompt: Property.LongText({
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displayName: 'Prompt',
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required: false,
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description:
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"An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.",
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}),
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temperature: Property.Number({
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displayName: 'Temperature',
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required: false,
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description:
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'The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.',
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defaultValue: 0,
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}),
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responseFormat: Property.StaticDropdown({
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displayName: 'Response Format',
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required: false,
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description: 'The format of the transcript output.',
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defaultValue: 'json',
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options: {
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disabled: false,
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options: [
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{ label: 'JSON', value: 'json' },
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{ label: 'Text', value: 'text' },
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{ label: 'Verbose JSON', value: 'verbose_json' },
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],
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},
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}),
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},
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async run({ auth, propsValue }) {
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const { file, model, language, prompt, temperature, responseFormat } = propsValue;
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// Create form data
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const formData = new FormData();
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formData.append('file', new Blob([file.data] as unknown as BlobPart[]), file.filename);
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formData.append('model', model);
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if (language) formData.append('language', language);
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if (prompt) formData.append('prompt', prompt);
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if (temperature !== undefined) formData.append('temperature', temperature.toString());
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if (responseFormat) formData.append('response_format', responseFormat);
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// Send request
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const response = await httpClient.sendRequest({
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method: HttpMethod.POST,
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url: 'https://api.groq.com/openai/v1/audio/transcriptions',
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text,
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},
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headers: {
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'Content-Type': 'multipart/form-data',
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},
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body: formData,
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});
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return response.body;
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},
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});
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@@ -0,0 +1,119 @@
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import { createAction, Property } from '@activepieces/pieces-framework';
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import { groqAuth } from '../..';
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import { httpClient, HttpMethod, AuthenticationType } from '@activepieces/pieces-common';
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export const translateAudio = createAction({
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auth: groqAuth,
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name: 'translate-audio',
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displayName: 'Translate Audio',
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description: 'Translates audio into English text.',
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props: {
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file: Property.File({
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displayName: 'Audio File',
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required: true,
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description:
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'The audio file to translate. Supported formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, webm.',
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}),
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model: Property.Dropdown({
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displayName: 'Model',
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required: true,
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description: 'The model to use for translation.',
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refreshers: [],
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defaultValue: 'whisper-large-v3',
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auth: groqAuth,
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options: async ({ auth }) => {
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if (!auth) {
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return {
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disabled: true,
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placeholder: 'Please connect your Groq account first.',
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options: [],
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};
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}
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try {
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const response = await httpClient.sendRequest({
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url: 'https://api.groq.com/openai/v1/models',
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method: HttpMethod.GET,
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text
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},
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});
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// Filter for whisper models only
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const models = (response.body.data as Array<{ id: string }>).filter((model) =>
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model.id.toLowerCase().includes('whisper'),
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);
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return {
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disabled: false,
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options: models.map((model) => {
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return {
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label: model.id,
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value: model.id,
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};
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}),
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};
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} catch (error) {
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return {
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disabled: true,
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options: [],
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placeholder: "Couldn't load models, API key is invalid",
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};
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}
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},
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}),
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prompt: Property.LongText({
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displayName: 'Prompt',
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required: false,
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description:
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"An optional text in English to guide the model's style or continue a previous audio segment.",
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}),
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temperature: Property.Number({
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displayName: 'Temperature',
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required: false,
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description:
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'The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.',
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defaultValue: 0,
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}),
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responseFormat: Property.StaticDropdown({
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displayName: 'Response Format',
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required: false,
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description: 'The format of the translation output.',
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defaultValue: 'json',
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options: {
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disabled: false,
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options: [
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{ label: 'JSON', value: 'json' },
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{ label: 'Text', value: 'text' },
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{ label: 'Verbose JSON', value: 'verbose_json' },
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],
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},
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}),
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},
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async run({ auth, propsValue }) {
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const { file, model, prompt, temperature, responseFormat } = propsValue;
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// Create form data
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const formData = new FormData();
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formData.append('file', new Blob([file.data] as unknown as BlobPart[]), file.filename);
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formData.append('model', model);
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if (prompt) formData.append('prompt', prompt);
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if (temperature !== undefined) formData.append('temperature', temperature.toString());
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if (responseFormat) formData.append('response_format', responseFormat);
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// Send request
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const response = await httpClient.sendRequest({
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method: HttpMethod.POST,
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url: 'https://api.groq.com/openai/v1/audio/translations',
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authentication: {
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type: AuthenticationType.BEARER_TOKEN,
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token: auth.secret_text
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},
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headers: {
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'Content-Type': 'multipart/form-data',
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},
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body: formData,
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});
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return response.body;
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},
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});
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