Custom logger & error retries (#177)

.changeset/modern-papayas-sneeze.md

@@ -0,0 +1,6 @@
+---
+"@instructor-ai/instructor": minor
+---
+
+add new option for providing custom logger
+add new option for retrying on any error

src/instructor.ts

@@ -31,16 +31,26 @@ class Instructor<C extends GenericClient | OpenAI> {
   readonly mode: Mode
   readonly provider: Provider
   readonly debug: boolean = false
+  readonly retryAllErrors: boolean = false
+  readonly logger?: <T extends unknown[]>(level: LogLevel, ...args: T) => void
 
   /**
    * Creates an instance of the `Instructor` class.
    * @param {OpenAILikeClient} client - An OpenAI-like client.
    * @param {string} mode - The mode of operation.
    */
-  constructor({ client, mode, debug = false }: InstructorConfig<C>) {
+  constructor({
+    client,
+    mode,
+    debug = false,
+    logger = undefined,
+    retryAllErrors = false
+  }: InstructorConfig<C>) {
     this.client = client
     this.mode = mode
     this.debug = debug
+    this.retryAllErrors = retryAllErrors
+    this.logger = logger ?? undefined
 
     const provider =
       typeof this.client?.baseURL === "string" ?
@@ -83,6 +93,10 @@ class Instructor<C extends GenericClient | OpenAI> {
   }
 
   private log<T extends unknown[]>(level: LogLevel, ...args: T) {
+    if (this.logger) {
+      this.logger(level, ...args)
+    }
+
     if (!this.debug && level === "debug") {
       return
     }
@@ -224,7 +238,7 @@ class Instructor<C extends GenericClient | OpenAI> {
 
         return { ...validation.data, _meta: data?._meta ?? {} }
       } catch (error) {
-        if (!(error instanceof ZodError)) {
+        if (!this.retryAllErrors && !(error instanceof ZodError)) {
           throw error
         }
 
@@ -428,11 +442,9 @@ export type InstructorClient<C extends GenericClient | OpenAI> = Instructor<C> &
  * @param args
  * @returns
  */
-export default function createInstructor<C extends GenericClient | OpenAI>(args: {
-  client: OpenAILikeClient<C>
-  mode: Mode
-  debug?: boolean
-}): InstructorClient<C> {
+export default function createInstructor<C extends GenericClient | OpenAI>(
+  args: InstructorConfig<C>
+): InstructorClient<C> {
   const instructor = new Instructor<C>(args)
   const instructorWithProxy = new Proxy(instructor, {
     get: (target, prop, receiver) => {

src/types/index.ts

@@ -71,6 +71,8 @@ export interface InstructorConfig<C> {
   client: OpenAILikeClient<C>
   mode: Mode
   debug?: boolean
+  logger?: <T extends unknown[]>(level: LogLevel, ...args: T) => void
+  retryAllErrors?: boolean
 }
 
 export type InstructorChatCompletionParams<T extends z.AnyZodObject> = {

tests/logger.test.ts

@@ -0,0 +1,68 @@
+import Instructor from "@/instructor"
+import { describe, expect, spyOn, test } from "bun:test"
+import OpenAI from "openai"
+import { z } from "zod"
+
+const textBlock = `
+In our recent online meeting, participants from various backgrounds joined to discuss the upcoming tech conference. The names and contact details of the participants were as follows:
+
+- Name: John Doe, Email: johndoe@email.com, Twitter: @TechGuru44
+- Name: Jane Smith, Email: janesmith@email.com, Twitter: @DigitalDiva88
+- Name: Alex Johnson, Email: alexj@email.com, Twitter: @CodeMaster2023
+
+During the meeting, we agreed on several key points. The conference will be held on March 15th, 2024, at the Grand Tech Arena located at 4521 Innovation Drive. Dr. Emily Johnson, a renowned AI researcher, will be our keynote speaker.
+
+The budget for the event is set at $50,000, covering venue costs, speaker fees, and promotional activities. Each participant is expected to contribute an article to the conference blog by February 20th.
+
+A follow-up meeting is scheduled for January 25th at 3 PM GMT to finalize the agenda and confirm the list of speakers.
+`
+
+async function extractUser() {
+  const ExtractionValuesSchema = z.object({
+    users: z
+      .array(
+        z.object({
+          name: z.string(),
+          handle: z.string(),
+          twitter: z.string()
+        })
+      )
+      .min(3),
+    location: z.string(),
+    budget: z.number()
+  })
+
+  const oai = new OpenAI({
+    apiKey: process.env.OPENAI_API_KEY ?? undefined,
+    organization: process.env.OPENAI_ORG_ID ?? undefined
+  })
+
+  const client = Instructor({
+    client: oai,
+    mode: "TOOLS",
+    logger: (level, ...args) => console.log(`[CUSTOM LOGGER | ${level}]`, ...args)
+  })
+
+  const extraction = await client.chat.completions.create({
+    messages: [{ role: "user", content: textBlock }],
+    model: "gpt-4o",
+    response_model: { schema: ExtractionValuesSchema, name: "Extr" },
+    max_retries: 1,
+    seed: 1
+  })
+
+  return extraction
+}
+
+describe("Custom Logger", () => {
+  test("Should log using custom logger", async () => {
+    const consoleSpy = spyOn(console, "log")
+    await extractUser()
+
+    expect(consoleSpy.mock.calls.flatMap(args => args.join(" ")).toString()).toContain(
+      "[CUSTOM LOGGER"
+    )
+
+    consoleSpy.mockRestore()
+  })
+})