flaxflow 1.0.0

Official Python SDK for the FlaxFlow Engine API — AI document processing.

flaxflow — Python SDK

Official Python SDK for the FlaxFlow Engine API — AI-powered document processing (extraction, classification, webhooks).

pip install flaxflow

Authentication

The SDK authenticates with an API key (sk_...). Create one in the FlaxFlow app under Settings → API keys, then pass it to the client or set FLAXFLOW_API_KEY.

from flaxflow import FlaxFlow

fx = FlaxFlow(api_key="sk_...")  # or FlaxFlow() reading FLAXFLOW_API_KEY

Quickstart

from flaxflow import FlaxFlow

fx = FlaxFlow(api_key="sk_...")

# 1. Create a document class from a sample — the AI infers the fields to extract
doc = fx.documents.create_from_sample("invoice-sample.pdf")

# 2. Process a real document against that class
job = fx.processing.process_document("invoice-001.pdf", document_id=str(doc.document_id))
print(job.result)        # -> {"invoice_number": "123", "total_amount": "99.90", ...}

# 3. Or extract with a free-form prompt, no document class needed
job = fx.processing.process_with_prompt(
    "invoice-001.pdf",
    prompt="Extract invoice number, issue date and total amount",
)
print(job.result)

The file argument accepts a path, raw bytes, or any file-like object. For paths the documentType is inferred from the extension; otherwise pass document_type=.

Resources

Resource	Highlights
fx.documents	create_from_sample, create_manual, update, list, delete
fx.processing	process_document, process_with_prompt, process_many
fx.jobs	list, get, get_batch, analytics, download_document
fx.classifiers	create, list, get, update, set_models, delete
fx.webhooks	create, list, update, delete, delivery_logs
fx.api_keys	create, list, delete

Batch processing

batch = fx.processing.process_many(
    ["a.pdf", "b.pdf", "c.pdf"],
    classifier_id="<classifier_id>",   # let the classifier pick the right class
)
print(batch.batch_id, len(batch.jobs))

Webhooks

hook = fx.webhooks.create("https://example.com/hooks/flaxflow",
                          event_types=["job.completed", "job.failed"])
print(hook.secret)   # HMAC-SHA256 signing secret — shown only once

Error handling

Every failure raises a subclass of FlaxFlowError:

from flaxflow import FlaxFlow, AuthenticationError, NotFoundError, RateLimitError

try:
    fx.jobs.get("does-not-exist")
except NotFoundError:
    ...
except RateLimitError as e:
    print("slow down", e.status_code)
except AuthenticationError:
    print("check your API key")

Configuration

Option	Default	Env var
api_key	– (required)	FLAXFLOW_API_KEY
base_url	https://api.flaxia.com.br	FLAXFLOW_BASE_URL
timeout	60 seconds	–

FlaxFlow is a context manager — use with FlaxFlow(...) as fx: to close the HTTP client automatically.

Types

Response objects are pydantic models generated from the API's OpenAPI spec, so you get full editor autocompletion and validation. Field names are snake_case in Python (the wire format stays camelCase).

Development

python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
bash scripts/generate.sh   # regenerate models from ../openapi.json
pytest

Publishing (maintainers)

Configure o token PyPI no GitHub (uma vez):

bash scripts/configure-pypi.sh   # cole o token pypi-...

Push em main com mudanças nesta pasta publica automaticamente a versão em pyproject.toml. Antes de cada release, aumente version (ex.: 1.0.1).

The generated models live in src/flaxflow/_generated/ and are produced from sdks/openapi.json (exported from the backend via cargo run --bin export_openapi).

Async support (AsyncFlaxFlow) is planned. The sync client is fully featured today.