Resume parsing

{
  "name": "Resume parsing",
  "description": "Extract candidate details from resumes",
  "nodes": [
    { "id": "parse_1", "type": "parse" },
    {
      "id": "extract_1",
      "type": "extract",
      "extraction_schema": {
        "fields": [
          { "name": "candidate_name",      "description": "Full name of the candidate", "data_type": "string" },
          { "name": "email",               "description": "Email address", "data_type": "string" },
          { "name": "phone",               "description": "Phone number including country code if present", "data_type": "string" },
          { "name": "years_of_experience", "description": "Total years of professional work experience", "data_type": "integer" },
          {
            "name": "skills",
            "description": "Technical skills, programming languages and tools, one row per skill",
            "data_type": "object",
            "nested_fields": [
              { "name": "skill", "description": "One skill, language or tool", "data_type": "string" }
            ]
          },
          {
            "name": "education",
            "description": "Educational qualifications and degrees, one row per degree",
            "data_type": "object",
            "nested_fields": [
              { "name": "institution",     "description": "University or school name", "data_type": "string" },
              { "name": "degree",          "description": "Degree obtained (e.g. BSc CS, MBA)", "data_type": "string" },
              { "name": "graduation_date", "description": "Date of graduation", "data_type": "date" }
            ]
          },
          {
            "name": "work_history",
            "description": "Previous jobs and roles, most recent first, one row per job",
            "data_type": "object",
            "nested_fields": [
              { "name": "company",    "description": "Company name", "data_type": "string" },
              { "name": "title",      "description": "Job title", "data_type": "string" },
              { "name": "start_date", "description": "Start date of employment", "data_type": "date" },
              { "name": "end_date",   "description": "End date of employment, or empty if this is the current role", "data_type": "date" }
            ]
          }
        ]
      }
    }
  ],
  "edges": [{ "source": "parse_1", "target": "extract_1" }]
}

import os
from anyformat.sdk import Client
from anyformat.workflow import Schema

client = Client(api_key=os.environ["ANYFORMAT_API_KEY"])

workflow = (
    client.workflow("Resume parsing", "Extract candidate details from resumes")
    .parse()
    .extract([
        Schema.string("candidate_name",       "Full name of the candidate"),
        Schema.string("email",                "Email address"),
        Schema.string("phone",                "Phone number including country code if present"),
        Schema.integer("years_of_experience", "Total years of professional work experience"),
        Schema.object("skills", "Technical skills, programming languages and tools, one row per skill", fields=[
            Schema.string("skill", "One skill, language or tool"),
        ]),
        Schema.object("education", "Educational qualifications and degrees, one row per degree", fields=[
            Schema.string("institution",   "University or school name"),
            Schema.string("degree",        "Degree obtained (e.g. BSc CS, MBA)"),
            Schema.date("graduation_date", "Date of graduation"),
        ]),
        Schema.object("work_history", "Previous jobs and roles, most recent first, one row per job", fields=[
            Schema.string("company",  "Company name"),
            Schema.string("title",    "Job title"),
            Schema.date("start_date", "Start date of employment"),
            Schema.date("end_date",   "End date of employment, or empty if this is the current role"),
        ]),
    ])
    .create()
)

import { Anyformat, Schema } from "@anyformat/sdk";

const af = new Anyformat({ apiKey: process.env.ANYFORMAT_API_KEY! });

const workflow = await af
  .workflow("Resume parsing", "Extract candidate details from resumes")
  .parse()
  .extract([
    Schema.string("candidate_name",       "Full name of the candidate"),
    Schema.string("email",                "Email address"),
    Schema.string("phone",                "Phone number including country code if present"),
    Schema.integer("years_of_experience", "Total years of professional work experience"),
    Schema.object("skills", "Technical skills, programming languages and tools, one row per skill", [
      Schema.string("skill", "One skill, language or tool"),
    ]),
    Schema.object("education", "Educational qualifications and degrees, one row per degree", [
      Schema.string("institution",   "University or school name"),
      Schema.string("degree",        "Degree obtained (e.g. BSc CS, MBA)"),
      Schema.date("graduation_date", "Date of graduation"),
    ]),
    Schema.object("work_history", "Previous jobs and roles, most recent first, one row per job", [
      Schema.string("company",  "Company name"),
      Schema.string("title",    "Job title"),
      Schema.date("start_date", "Start date of employment"),
      Schema.date("end_date",   "End date of employment, or empty if this is the current role"),
    ]),
  ])
  .create();

# 1. Create the workflow with the JSON above
curl -X POST 'https://api.anyformat.ai/v3/workflows/' \
  -H "Authorization: Bearer $ANYFORMAT_API_KEY" \
  -H 'Content-Type: application/json' \
  -d @resume-workflow.json
# → 201 { "id": "<workflow_id>", ... }

# 2. Upload the resume and start a run
curl -X POST "https://api.anyformat.ai/v3/workflows/$WORKFLOW_ID/upload/run/" \
  -H "Authorization: Bearer $ANYFORMAT_API_KEY" \
  -F 'files=@resume.docx'
# → 202 { "run_id": "<run_id>", "document_packet_id": "...", "status": "queued" }

# 3. Poll until "status" is "processed"
curl "https://api.anyformat.ai/v3/runs/$RUN_ID/" \
  -H "Authorization: Bearer $ANYFORMAT_API_KEY"

result = workflow.run("resume.docx").wait()

print(result.fields["candidate_name"].value)
print(result.fields["years_of_experience"].value)

skills = [row["skill"].value for row in result.fields["skills"]]
for job in result.fields["work_history"]:
    print(job["company"].value, job["title"].value, job["start_date"].value, job["end_date"].value)

import { readFileSync } from "node:fs";
import type { ExtractedField, ExtractedRows } from "@anyformat/sdk";

const file = new File([readFileSync("resume.docx")], "resume.docx");
const result = await (await workflow.run(file)).wait();

console.log((result.field("candidate_name") as ExtractedField<string> | undefined)?.value);
console.log((result.field("years_of_experience") as ExtractedField<string> | undefined)?.value);

const skills = (result.field("skills") as ExtractedRows).map((row) => row.skill?.value);
for (const job of result.field("work_history") as ExtractedRows) {
  console.log(job.company?.value, job.title?.value, job.start_date?.value, job.end_date?.value);
}