import app from "../../textcortex.app.mjs";
import constants from "../../common/constants.mjs";
export default {
key: "textcortex-create-social-media-post",
name: "Create Social Media Post",
description: "Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)",
type: "action",
version: "0.0.1",
props: {
app,
context: {
type: "string",
label: "Context",
description: "The context of the social media post.",
},
keywords: {
type: "string[]",
label: "Keywords",
description: "Keywords to be included in the post.",
optional: true,
},
maxTokens: {
propDefinition: [
app,
"maxTokens",
],
},
mode: {
type: "string",
label: "Mode",
description: "The platform, e.g. `twitter` to generate a Tweet. Allowed values: `twitter`, `linkedin`",
options: Object.values(constants.SOCIAL_MEDIA_MODE),
},
model: {
propDefinition: [
app,
"model",
],
},
n: {
propDefinition: [
app,
"n",
],
},
sourceLang: {
propDefinition: [
app,
"sourceLang",
],
},
targetLang: {
propDefinition: [
app,
"targetLang",
],
},
temperature: {
propDefinition: [
app,
"temperature",
],
},
},
methods: {
createSocialMediaPost(args = {}) {
return this.app.post({
path: "/texts/social-media-posts",
...args,
});
},
},
async run({ $: step }) {
const {
createSocialMediaPost,
context,
keywords,
maxTokens,
mode,
model,
n,
sourceLang,
targetLang,
temperature,
} = this;
const response = await createSocialMediaPost({
step,
data: {
context,
keywords,
max_tokens: maxTokens,
mode,
model,
n,
source_lang: sourceLang,
target_lang: targetLang,
temperature,
},
});
step.export("$summary", `Successfully created social media post with status \`${response.status}\``);
return response;
},
};