> ## Documentation Index
> Fetch the complete documentation index at: https://docs.flexorch.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Process your first document and export a dataset in under 5 minutes.

## Prerequisites

* A FlexOrch account ([sign up free](https://app.flexorch.com/signup))
* An API key — generate one under **Settings → API Keys**

***

## Option 1 — Python SDK

<Steps>
  <Step title="Install the SDK">
    ```bash theme={null}
    pip install flexorch-sdk
    ```
  </Step>

  <Step title="Upload a document">
    ```python theme={null}
    from flexorch_sdk import FlexOrch

    client = FlexOrch(api_key="dfx_your_key_here")

    job = client.jobs.upload("invoice.pdf")
    print(job.id)  # job_abc123
    ```
  </Step>

  <Step title="Wait for processing">
    ```python theme={null}
    result = job.wait_until_done(timeout=120)

    print(result.status)         # "completed"
    print(result.quality_grade)  # "A"
    print(result.pii_count)      # 3
    print(result.detected_language)  # "tr"
    ```
  </Step>

  <Step title="Build a dataset and export">
    ```python theme={null}
    dataset = client.datasets.build(job_ids=[job.id])

    # Export as JSONL for fine-tuning
    client.datasets.export(dataset.id, format="jsonl", path="./output.jsonl")

    # Or export as Parquet for analytics
    client.datasets.export(dataset.id, format="parquet", path="./output.parquet")
    ```
  </Step>
</Steps>

***

## Option 2 — TypeScript SDK

<Steps>
  <Step title="Install the SDK">
    ```bash theme={null}
    npm install flexorch-sdk
    ```
  </Step>

  <Step title="Upload and wait">
    ```typescript theme={null}
    import { FlexOrch } from 'flexorch-sdk';

    const client = new FlexOrch({ apiKey: 'dfx_your_key_here' });

    const job = await client.jobs.upload('invoice.pdf');
    const result = await job.waitUntilDone({ timeout: 120_000 });

    console.log(result.qualityGrade);  // "A"
    console.log(result.piiCount);      // 3
    ```
  </Step>

  <Step title="Export">
    ```typescript theme={null}
    const dataset = await client.datasets.build({ jobIds: [job.id] });
    await client.datasets.export(dataset.id, { format: 'jsonl', path: './output.jsonl' });
    ```
  </Step>
</Steps>

***

## Option 3 — REST API (cURL)

<Steps>
  <Step title="Upload a document">
    ```bash theme={null}
    curl -X POST https://api.flexorch.com/v1/data-process/async \
      -H "X-API-KEY: dfx_your_key_here" \
      -F "files=@invoice.pdf"
    ```

    Response:

    ```json theme={null}
    {
      "data": {
        "job_ids": ["job_abc123"],
        "status": "queued"
      }
    }
    ```
  </Step>

  <Step title="Poll for completion">
    ```bash theme={null}
    curl https://api.flexorch.com/v1/jobs/job_abc123 \
      -H "X-API-KEY: dfx_your_key_here"
    ```

    Completed response includes `quality.grade`, `pii_findings_count`, `detected_language`, and extracted fields.
  </Step>

  <Step title="Build and export a dataset">
    ```bash theme={null}
    # Build
    curl -X POST https://api.flexorch.com/v1/datasets \
      -H "X-API-KEY: dfx_your_key_here" \
      -H "Content-Type: application/json" \
      -d '{"name": "my-dataset", "execution_ids": ["exec_xyz"]}'

    # Export (returns a file download)
    curl https://api.flexorch.com/v1/datasets/{id}/export?format=jsonl \
      -H "X-API-KEY: dfx_your_key_here" \
      -o output.jsonl
    ```
  </Step>
</Steps>

***

## What's next?

<CardGroup cols={2}>
  <Card title="Supported file types" icon="file" href="/guides/upload">
    PDF, DOCX, PPTX, XLSX, HTML, XML e-invoices, EML, images — full list.
  </Card>

  <Card title="PII detection" icon="shield" href="/guides/pii-privacy">
    46 types across TR, EU, and US — TCKN, IBAN, email, phone, passport, and more.
  </Card>

  <Card title="Export formats" icon="download" href="/guides/datasets">
    JSONL, CSV, Parquet, Markdown, XML, XLSX, HuggingFace Arrow.
  </Card>

  <Card title="Automate with connectors" icon="link" href="/connectors/overview">
    Connect an S3 bucket and process documents automatically.
  </Card>
</CardGroup>