import openai from "../../openai.app.mjs";
import common from "../common/common.mjs";
import constants from "../../common/constants.mjs";
export default {
...common,
name: "Chat using Functions",
version: "0.0.4",
key: "openai-chat-using-functions",
description: "Chat with your models and allow them to invoke functions. Optionally, you can build and invoke workflows as functions. [See the documentation](https://platform.openai.com/docs/guides/function-calling)",
type: "action",
props: {
openai,
alert: {
type: "alert",
alertType: "info",
content: "Provide function names and parameters, and the model will either answer the question directly or decide to invoke one of the functions, returning a function call that adheres to your specified schema. Add a custom code step that includes all available functions which can be invoked based on the model's response - [you can even build an entire workflow as a function](https://pipedream.com/docs/workflows/building-workflows/code/nodejs/#invoke-another-workflow)! Once the appropriate function or workflow is executed, continue the overall execution or pass the result back to the model for further analysis. For more details, [see this guide](https://platform.openai.com/docs/guides/function-calling?api-mode=responses#overview) and this [walkthrough](https://pipedream.com/blog/introducing-enhanced-openai-chat-actions-for-pipedream/#using-pipedream-workflows-as-functions).",
},
modelId: {
propDefinition: [
openai,
"chatCompletionModelId",
],
},
input: {
type: "string",
label: "Chat Input",
description: "Text inputs to the model used to generate a response",
},
functions: {
type: "string",
label: "Functions",
description: "A valid JSON array of functions using OpenAI's function schema definition. [See guide here](https://platform.openai.com/docs/guides/function-calling?api-mode=responses&example=search-knowledge-base#defining-functions).",
default:
`[
{
"type": "function",
"name": "your_function_name",
"description": "Details on when and how to use the function",
"strict": true,
"parameters": {
"type": "object",
"properties": {
"property_name": {
"type": "property_type",
"description": "A description for this property"
},
"another_property_name": {
"type": "property_type",
"description": "A description for this property"
}
},
"required": [
"list",
"of",
"required",
"properties",
"for",
"this",
"object"
],
"additionalProperties": false
}
}
]`,
},
instructions: {
type: "string",
label: "Instructions",
description: "Inserts a system (or developer) message as the first item in the model's context",
optional: true,
},
toolChoice: {
type: "string",
label: "Tool Choice",
description: "- **auto**: The model decides whether and how many functions to call.\n- **required**: The model must call one or more functions.\n- **function_name**: Enter a custom expression to force the model to call this specific function.",
optional: true,
default: "auto",
options: [
"auto",
"required",
],
},
parallelToolCalls: {
type: "boolean",
label: "Parallel Function Calling",
description: "Allow or prevent the model to call multiple functions in a single turn",
optional: true,
default: 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's larger than the context window size",
optional: true,
default: "auto",
options: [
"auto",
"disabled",
],
},
responseFormat: {
type: "string",
label: "Response Format",
description: "- **Text**: Returns unstructured text output.\n- **JSON Schema**: Enables you to define a [specific structure for the model's output using a JSON schema](https://platform.openai.com/docs/guides/structured-outputs?api-mode=responses).",
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 this step's execution at runtime",
optional: true,
default: false,
},
},
additionalProps() {
const {
modelId,
responseFormat,
} = this;
const props = {};
if (this.openai.isReasoningModel(modelId)) {
props.reasoningEffort = {
type: "string",
label: "Reasoning Effort",
description: "Constrains effort on reasoning for reasoning models",
optional: true,
options: [
"low",
"medium",
"high",
],
};
}
if (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. [Generate one here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).",
};
}
return props;
},
methods: {
...common.methods,
},
async run({ $ }) {
if (this.skipThisStep) {
$.export("$summary", "Step execution skipped");
return;
}
const data = {
model: this.modelId,
input: this.input,
instructions: this.instructions,
previous_response_id: this.previousResponseId,
truncation: this.truncation,
parallel_tool_calls: this.parallelToolCalls,
tools: [],
};
let functions = this.functions;
if (typeof functions === "string") {
try {
functions = JSON.parse(functions);
} catch (error) {
throw new Error("Invalid JSON format in the provided Functions Schema");
}
}
if (Array.isArray(functions)) {
data.tools.push(...functions);
} else {
data.tools.push(functions);
}
if (this.toolChoice) {
if (this.toolChoice === "auto" || this.toolChoice === "required") {
data.tool_choice = this.toolChoice;
} else {
data.tool_choice = {
type: "function",
name: this.toolChoice,
};
}
}
if (this.openai.isReasoningModel(this.modelId) && this.reasoningEffort) {
data.reasoning = {
...data.reasoning,
effort: this.reasoningEffort,
};
}
if (this.openai.isReasoningModel(this.modelId) && this.generateSummary) {
data.reasoning = {
...data.reasoning,
generate_summary: this.generateSummary,
};
}
if (this.responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) {
try {
data.text = {
format: {
type: this.responseFormat,
...JSON.parse(this.jsonSchema),
},
};
} catch (error) {
throw new Error("Invalid JSON format in the provided JSON Schema");
}
}
const response = await this.openai.responses({
$,
data,
});
if (response) {
$.export("$summary", `Successfully sent chat with id ${response.id}`);
$.export("chat_responses", response.output);
}
return response;
},
};
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