import openai from "../../openai.app.mjs"; import common from "../common/common.mjs"; import constants from "../../common/constants.mjs"; export default { ...common, name: "Chat", version: "0.3.4", annotations: { destructiveHint: false, openWorldHint: true, readOnlyHint: false, }, key: "openai-chat", description: "The Chat API, using the `gpt-3.5-turbo` or `gpt-4` model. [See the documentation](https://platform.openai.com/docs/api-reference/chat)", type: "action", props: { openai, alert: { type: "alert", alertType: "info", content: "Looking to chat with your tools? Check out our individual actions: [Chat using Web Search](https://pipedream.com/apps/openai/actions/chat-using-web-search), [Chat using File Search](https://pipedream.com/apps/openai/actions/chat-using-file-search), and [Chat using Functions](https://pipedream.com/apps/openai/actions/chat-using-functions).", }, modelId: { propDefinition: [ openai, "chatCompletionModelId", ], }, userMessage: { label: "User Message", type: "string", description: "The user messages provide instructions to the assistant. They can be generated by the end users of an application, or set by a developer as an instruction.", }, ...common.props, systemInstructions: { label: "System Instructions", type: "string", description: "The system message helps set the behavior of the assistant. For example: \"You are a helpful assistant.\" [See these docs](https://platform.openai.com/docs/guides/chat/instructing-chat-models) for tips on writing good instructions.", optional: true, }, messages: { label: "Prior Message History", type: "string[]", description: "_Advanced_. Because [the models have no memory of past chat requests](https://platform.openai.com/docs/guides/chat/introduction), all relevant information must be supplied via the conversation. You can provide [an array of messages](https://platform.openai.com/docs/guides/chat/introduction) from prior conversations here. If this param is set, the action ignores the values passed to **System Instructions** and **Assistant Response**, appends the new **User Message** to the end of this array, and sends it to the API.", optional: true, }, images: { label: "Images", type: "string[]", description: "Provide one or more images to [OpenAI's vision model](https://platform.openai.com/docs/guides/vision). Each entry should be either a file URL or a path to a file in the `/tmp` directory (for example, `/tmp/myFile.jpg`), or raw base64-encoded image data. Compatible with the `gpt4-vision-preview` model", optional: true, }, audio: { type: "string", label: "Audio", description: "The audio file to upload. Provide either a file URL or a path to a file in the `/tmp` directory (for example, `/tmp/myFile.mp3`). For use with the `gpt-4o-audio-preview` model. Currently supports `wav` and `mp3` files.", optional: true, }, 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: Object.values(constants.CHAT_RESPONSE_FORMAT), default: constants.CHAT_RESPONSE_FORMAT.TEXT.value, optional: true, reloadProps: true, }, toolTypes: { type: "string[]", label: "Tool Types", description: "The types of tools to enable on the assistant", options: constants.TOOL_TYPES.filter((toolType) => toolType === "function"), optional: true, reloadProps: true, }, }, additionalProps() { const { responseFormat, toolTypes, numberOfFunctions, } = this; const props = {}; 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. [See the documentation here](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas).", }; } if (toolTypes?.includes("function")) { props.numberOfFunctions = { type: "integer", label: "Number of Functions", description: "The number of functions to define", optional: true, reloadProps: true, default: 1, }; for (let i = 0; i < (numberOfFunctions || 1); i++) { props[`functionName_${i}`] = { type: "string", label: `Function Name ${i + 1}`, description: "The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.", }; props[`functionDescription_${i}`] = { type: "string", label: `Function Description ${i + 1}`, description: "A description of what the function does, used by the model to choose when and how to call the function.", optional: true, }; props[`functionParameters_${i}`] = { type: "object", label: `Function Parameters ${i + 1}`, description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/text-generation/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.", optional: true, }; } } return props; }, methods: { ...common.methods, _buildTools() { const tools = this.toolTypes?.filter((toolType) => toolType !== "function")?.map((toolType) => ({ type: toolType, })) || []; if (this.toolTypes?.includes("function")) { const numberOfFunctions = this.numberOfFunctions || 1; for (let i = 0; i < numberOfFunctions; i++) { tools.push({ type: "function", function: { name: this[`functionName_${i}`], description: this[`functionDescription_${i}`], parameters: this[`functionParameters_${i}`], }, }); } } return tools.length ? tools : undefined; }, }, async run({ $ }) { const args = await this._getChatArgs(); const response = await this.openai.createChatCompletion({ $, data: { ...args, tools: this._buildTools(), }, }); if (this.responseFormat === constants.CHAT_RESPONSE_FORMAT.JSON_SCHEMA.value) { for (const choice of response.choices) { try { choice.message.content = JSON.parse(choice.message.content); } catch { console.log(`Unable to parse JSON: ${choice.message.content}`); } } } if (response) { $.export("$summary", `Successfully sent chat with id ${response.id}`); } const { messages } = args; return { original_messages: messages, original_messages_with_assistant_response: messages.concat(response.choices[0]?.message), ...response, }; }, };
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