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Resolves #17031: [ACTION] OpenAI Responses API #17052

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39 changes: 39 additions & 0 deletions .github/workflows/retrieve-commits.yml
Original file line number Diff line number Diff line change
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name: Retrieve Commits


on:
workflow_dispatch:

jobs:
fetch-commits:
runs-on: ubuntu-latest
steps:

- name: Checkout repository
uses: actions/checkout@v3


- name: List commits
run: |
gh api \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
/repos/${{ github.repository_owner }}/${{ github.event.repository.name }}/commits?per_page=30 \
> commits.json

- name: Get specific commit
run: |
gh api \
-H "Accept: application/vnd.github+json" \
-H "X-GitHub-Api-Version: 2022-11-28" \
/repos/${{ github.repository_owner }}/${{ github.event.repository.name }}/commits/${{ github.sha }} \
> commit.json


- name: Upload commit data
uses: actions/upload-artifact@v3
with:
name: commit-data
path: |
commits.json
commit.json
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So this is the solution to this issue #17031
Please increase the minor version in its package.json file

Original file line number Diff line number Diff line change
@@ -0,0 +1,196 @@
import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";
import axios from "axios";

export default {
...common,
key: "openai-chat-using-responses-api",
name: "Chat with OpenAI Responses API",
version: "0.0.1",
description:
"Send a chat via the Responses API, mixing built-in tools and MCP servers.",
type: "action",
props: {
openai,
modelId: {
type: "string",
label: "Model",
description: "Model used to generate the response",
default: "gpt-4o",
options: [
"gpt-4o",
"gpt-4o-mini",
],
},
input: {
type: "string",
label: "Chat Input",
description: "Text input to the model used to generate a response",
},
instructions: {
type: "string",
label: "Instructions",
description:
"Inserts a system (or developer) message as the first item in the model's context",
optional: true,
},
previousResponseId: {
type: "string",
label: "Previous Response ID",
description:
"The unique ID of the previous response to the model. Use this to create multi-turn conversations",
optional: true,
},
truncation: {
type: "string",
label: "Truncation",
description:
"Specifies the truncation mode for the response if it exceeds the context window",
default: "auto",
options: [
"auto",
"disabled",
],
optional: true,
},
responseFormat: {
type: "string",
label: "Response Format",
description:
"- **text**: Returns unstructured text output.\n- **json_schema**: Enforces a specific structure using a JSON schema.",
options: [
"text",
"json_schema",
],
default: "text",
optional: true,
reloadProps: true,
},
skipThisStep: {
type: "boolean",
label: "Skip This Step",
description:
"Pass in a boolean custom expression to skip execution at runtime",
default: false,
optional: true,
},
builtInTools: {
type: "string[]",
label: "Built-In Tools",
description:
"Which of OpenAI’s first-party tools to enable (web search, file search, code interpreter).",
options: [
{
label: "Web Search",
value: "web_search_preview",
},
{
label: "File Search",
value: "file_search",
},
{
label: "Code Interpreter",
value: "code_interpreter",
},
],
default: [],
},
mcpServers: {
type: "string[]",
label: "MCP Server URLs",
description:
"Enter your MCP server base URLs. To set one up, visit https://mcp.pipedream.com/ and click “Create new server.",
optional: true,
},
mcpTools: {
type: "string[]",
label: "MCP Tools to Enable",
description:
"Select which tools from your MCP servers to include in the chat.",
optional: true,
async options({ mcpServers }) {
if (!mcpServers?.length) return [];
const all = [];
for (let url of mcpServers) {
url = url.replace(/\/$/, "");
const { data } = await axios.get(`${url}/tools`);
for (const t of data.tools) {
all.push({
label: t.name,
value: t.id,
});
}
}
return all;
},
Comment on lines +106 to +126
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can you please create a propDefinition for this one in openai.app.mjs file and reference here, so you can use the axios lib from @pipedream/plaform instead?

import { axios } from "@pipedream/platform";

},
},
additionalProps() {
const props = {};
if (
this.responseFormat ===
constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value
) {
props.jsonSchema = {
type: "string",
label: "JSON Schema",
description:
"Define the schema that the model's output must adhere to.",
};
}
return props;
},
methods: {
...common.methods,
},
async run({ $ }) {
if (this.skipThisStep) {
$.export("$summary", "Step execution skipped");
return;
}
const tools = [];
for (const id of this.builtInTools) {
tools.push({
type: id,
});
}
for (const id of this.mcpTools || []) {
tools.push({
type: id,
});
}
const data = {
model: this.modelId,
input: this.input,
instructions: this.instructions,
previous_response_id: this.previousResponseId,
truncation: this.truncation,
tools,
};
if (
this.responseFormat ===
constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value
) {
try {
data.text = {
format: {
type: this.responseFormat,
...JSON.parse(this.jsonSchema),
},
};
} catch {
throw new Error("Invalid JSON format in the provided JSON Schema");
}
}
const response = await this.openai.responses({
$,
data,
});
if (response) {
$.export("$summary", `Chat sent (id: ${response.id})`);
$.export("chat_responses", response.output);
}
return response;
},
};
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