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Add
createExtractFunction
for data extraction
Introduce `createExtractFunction` using OpenAI's structured output feature, leveraging a Zod schema for data validation and extraction. This is a better and more modern alternative to the `createAIExtractFunction` utility, which is now deprecated.
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import { zodToJsonSchema } from 'openai-zod-to-json-schema'; | ||
import { type z } from 'zod'; | ||
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import { type Model, type Msg, MsgUtil } from '../model/index.js'; | ||
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/** | ||
* Extract data using OpenAI structured outputs. | ||
* | ||
* Always returns an object satisfying the provided Zod schema. | ||
*/ | ||
export function createExtractFunction<Schema extends z.ZodObject<any>>(args: { | ||
/** The ChatModel used to make API calls. */ | ||
chatModel: Model.Chat.Model; | ||
/** A descriptive name for the object to extract. */ | ||
name: string; | ||
/** The Zod schema for the data to extract. */ | ||
schema: Schema; | ||
/** Add a system message to the beginning of the messages array. */ | ||
systemMessage: string; | ||
}): (input: string | Msg) => Promise<z.infer<Schema>> { | ||
const { chatModel, schema, systemMessage } = args; | ||
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async function runExtract(input: string | Msg): Promise<z.infer<Schema>> { | ||
const inputVal = typeof input === 'string' ? input : (input.content ?? ''); | ||
const messages: Msg[] = [ | ||
MsgUtil.system(systemMessage), | ||
MsgUtil.user(inputVal), | ||
]; | ||
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const { message } = await chatModel.run({ | ||
messages, | ||
response_format: { | ||
type: 'json_schema', | ||
json_schema: { | ||
name: 'TODO', | ||
strict: true, | ||
schema: zodToJsonSchema(schema, { | ||
$refStrategy: 'none', | ||
openaiStrictMode: true, | ||
}), | ||
}, | ||
}, | ||
}); | ||
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MsgUtil.assertAssistant(message); | ||
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const json = JSON.parse(message.content); | ||
return schema.parse(json); | ||
} | ||
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return runExtract; | ||
} |