Fraime SDK

Python client for the Fraime API — build a request with typed models/enums instead of hand-writing JSON, point it at a running Fraime instance, get a generated video back.

Prerequisites

• Python 3.11+
• A running Fraime API instance to talk to (see api/README.md for how to run one) — you'll need its base URL, and its API key if one is configured (AUTH_API_KEY on the API side).

Install

Option 1 — pip

pip install fraime-sdk

Option 2 — from a local clone

Step by step, from scratch:

# 1. Clone the repo (skip if you already have it)
git clone <this-repo-url>
cd fraime

# 2. (Recommended) create a virtualenv for your own project
python3 -m venv .venv
source .venv/bin/activate

# 3. Install the SDK from the sdk/ folder
pip install ./sdk
#   or, for local development on the SDK itself (editable install):
pip install -e ./sdk

That's it — import fraime is now available in that environment.

Option 3 — straight from git, no local clone needed

pip install "git+ssh://git@santiago/santiagoMeloMedina/fraime.git#subdirectory=sdk"

(Adjust the URL to whatever remote you actually have push/pull access to — this is this repo's own origin in SSH form.)

Usage

from fraime import FraimeClient, VideoType, GenerationParams, CinematicPromptFields

client = FraimeClient(
    base_url="http://127.0.0.1:8000",  # or set FRAIME_BASE_URL instead
    api_key="your-api-key",             # or set FRAIME_API_KEY instead; omit both if the API has none configured
)

response = client.generate(
    video_type=VideoType.PIXAR,
    fields=CinematicPromptFields(
        subject="a small orange fox with oversized ears",
        action="hops between rocks, pauses, and looks up curiously",
        scene="a sunlit forest clearing at golden hour",
        camera="medium shot, slow dolly-in",
        lighting="warm rim lighting from the low sun",
        style="3D animated feature style, stylized proportions, warm rim lighting",
    ),
    params=GenerationParams(duration_s=3, fps=16, resolution="768x512"),
    # model=...              # optional: pin an exact model instead of auto-selecting
    # references=[...]       # optional: Reference(url=...) list, for image-to-video
)

print(response.video_path, response.model)

model is optional on client.generate() — omit it and the API auto-selects by hardware, same as calling it directly.

Picking the right fields class per video type

Every video_type has its own field set — some add fields the base six (subject, action, scene, camera, lighting, style, negative_prompt) don't cover:

Not sure which class a given VideoType needs? Look it up instead of guessing:

from fraime import PROMPT_FIELDS_BY_VIDEO_TYPE, VideoType

fields_class = PROMPT_FIELDS_BY_VIDEO_TYPE[VideoType.SOCIAL_SHORT_FORM_AD]
# -> SocialAdPromptFields

Reference images (image-to-video)

from fraime import Reference

response = client.generate(
    video_type=VideoType.UGC_PRODUCT_REVIEW,
    fields=ugc_fields,
    params=params,
    references=[Reference(url="https://example.com/product-photo.jpg")],
)

Error handling

from fraime import FraimeAuthError, FraimeAPIError, FraimeConnectionError

try:
    response = client.generate(video_type=VideoType.PIXAR, fields=fields, params=params)
except FraimeAuthError:
    ...  # missing/invalid API key
except FraimeAPIError as e:
    ...  # e.status_code, e.detail — the API reached but returned an error
except FraimeConnectionError:
    ...  # couldn't reach the API at all

Configuration reference

timeout defaults high on purpose — real generation runs can take several minutes; see api/README.md for why.