clipia — Python SDK

Official Python SDK for the Clipia public API: queue-based AI image, video, speech and music generation with a submit → status → result flow and signed webhooks. Clipia-native from the ground up: models are addressed by Clipia slugs and billed in credits, not USD.

• Sync (Clipia) and async (AsyncClipia) clients
• High-level subscribe() that submits and polls until the job finishes
• Typed responses (SubmitResponse, StatusResponse, ResultResponse, ...)
• HMAC-SHA256 webhook signature verification
• Single runtime dependency: httpx

Prefer driving Clipia from an AI agent (Claude Code / Cursor) instead of writing code? Clipia ships a hosted MCP server — no SDK required. See Using Clipia via MCP below.

Install

pip install clipia

Requires Python 3.9+.

Authentication

Create an API key in the Clipia Developer Console (clipia.ai/developer, API keys tab). The key is shown once — store it as a server-side secret (never ship it to browsers or mobile apps). It is sent as Authorization: Bearer <key>.

export CLIPIA_KEY="clipia_live_xxxxxxxxxxxxxxxxxxxxxx"

Keys come in two flavours: clipia_live_… (production, charges credits) and clipia_test_… (sandbox — instant mock results, no credits charged). Use a test key to validate your integration before going live.

Quickstart (sync)

import os
from clipia import Clipia

client = Clipia(api_key=os.environ["CLIPIA_KEY"])

# One call: submit + poll until COMPLETED / FAILED.
result = client.subscribe(
    "nano-banana-2",
    input={"prompt": "a sunset over mountains, cinematic"},
    on_queue_update=lambda s: print("status:", s.status, s.progress),
)
print(result.output["images"][0]["url"])

Manual queue control

job = client.submit("nano-banana-2", input={"prompt": "a cat"})
print(job.request_id, job.cost)

status = client.status(job.request_id)   # IN_QUEUE | IN_PROGRESS | COMPLETED | FAILED
result = client.result(job.request_id)   # result.pending == True while still running (HTTP 202)

A generation cannot be canceled: credits are reserved the moment it starts and the underlying compute cannot be interrupted. Submit deliberately — and use a clipia_test_… sandbox key while iterating.

Models, cost estimate & account

client.models.list()             # text + image/video/audio catalog
client.models.get("nano-banana-2")

# Audio models carry `type == "audio"`; text-to-speech ones add `text_limits`
# (min/max characters of `input["prompt"]`) and per-1000-characters pricing.
tts = client.models.get("gemini-3-1-flash-tts")
print(tts["text_limits"], tts["pricing"])

# Deterministic credit cost for an input, before you submit.
est = client.models.estimate("seedance-2-fast-t2v", {"prompt": "neon city", "duration": 8})
print(est.credits)

client.account.get()             # { "balance": { "credits": ... }, "usage_30d": { ... } }

The unified catalog also returns OpenAI-compatible text models such as gpt-5.6-sol; their entries use id, context_length and per-token pricing. Use the standard OpenAI Python SDK with base_url="https://api.clipia.ai/v1" for chat completions.

The client is also a context manager:

with Clipia(api_key=os.environ["CLIPIA_KEY"]) as client:
    client.account.get()

Quickstart (async)

import asyncio, os
from clipia import AsyncClipia

async def main():
    async with AsyncClipia(api_key=os.environ["CLIPIA_KEY"]) as client:
        result = await client.subscribe(
            "seedance-2-fast-i2v",
            input={"image_url": "https://.../in.png", "duration": 4},
        )
        print(result.output["video"]["url"])

asyncio.run(main())

on_queue_update may be a plain function or an async def coroutine.

Speech and music

Audio models use the same queue. The result carries output["audio"]["url"] (a file on the Clipia CDN) and, when the extension is known, output["audio"]["format"] (mp3, wav, …):

speech = client.subscribe(
    "gemini-3-1-flash-tts",
    input={"prompt": "Welcome to Clipia.", "voice": "Zephyr"},
)
print(speech.output["audio"]["url"], speech.output["audio"].get("format"))

music = client.subscribe(
    "suno-music",
    input={"prompt": "warm lo-fi beat for a product demo", "instrumental": True},
)
print(music.output["audio"]["url"])

Text-to-speech is billed per 1000 characters of the narration text; the model catalog exposes the bounds in text_limits, and client.models.estimate() returns the exact credit cost before you submit.

Idempotency and retries

Every submit() / subscribe() call fixes one UUID v4 Idempotency-Key and reuses it for the call's own retries. A transient failure (network error, 429, 500/502/503/504) is retried up to max_retries times (default 2, 0 disables) with capped exponential backoff seeded by retry_delay (default 0.5 s); a server-sent Retry-After always wins. The API keeps a key for 24 h, so a retried call resolves to the same request_id and is never charged twice.

Pass your own key to make your retries — a second submit() for the same order after a crash — resolve to the same request:

client = Clipia(api_key=os.environ["CLIPIA_KEY"], max_retries=3, retry_delay=1.0)
client.submit("nano-banana-2", input={"prompt": "x"}, idempotency_key="order-42")

The same key with a different body is rejected with 409 idempotency_key_reuse.

Webhooks

Pass webhook_url to submit()/subscribe() and Clipia will POST the result to your server. Always verify the signature on the raw request body:

from clipia import verify_signature

# In your web handler (Flask/FastAPI/etc.):
ok = verify_signature(
    secret=WEBHOOK_SIGNING_SECRET,   # from your dashboard
    headers=request.headers,         # X-Clipia-Signature: t=...,v1=...
    body=raw_request_body,           # bytes or str, exactly as received
    tolerance_seconds=300,           # freshness window (default 5 min)
)
if not ok:
    return ("invalid signature", 400)

The delivery payload carries status "OK" (success) or "ERROR" (failed). Verification is constant-time and rejects deliveries whose timestamp is outside the tolerance window. Treat webhooks as idempotent by request_id — deliveries can repeat.

Errors

Non-2xx responses raise ClipiaApiError:

from clipia import ClipiaApiError

try:
    client.submit("nano-banana-2", input={"prompt": "x"})
except ClipiaApiError as e:
    print(e.status, e.code, e.message)   # e.g. 402 insufficient_credits "..."

e.type groups the codes (invalid_request_error, authentication_error, permission_error, billing_error, rate_limit_error, api_error) and e.retry_after carries the parsed Retry-After header in seconds.

subscribe() raises ClipiaTimeoutError (a subclass of ClipiaApiError, status=0, code="poll_timeout") if the job does not reach a terminal status within timeout seconds.

Using Clipia via MCP (Claude Code / Cursor)

Clipia hosts a remote Model Context Protocol server, so an AI coding agent can generate images, video, speech and music, poll results, list models, search prompt templates and read your balance directly — no SDK or code required. The server is stateless Streamable HTTP at https://mcp.clipia.ai/mcp and authenticates with the same API key (as a Bearer token).

Tools exposed: generate_image, generate_video, generate_audio, generate_music, wait_generation, get_generation, list_models, get_model, get_balance, search_templates.

Claude Code

claude mcp add --transport http clipia https://mcp.clipia.ai/mcp \
  --header "Authorization: Bearer clipia_live_xxxxxxxx"

Cursor

Add to ~/.cursor/mcp.json (or the project's .cursor/mcp.json):

{
  "mcpServers": {
    "clipia": {
      "url": "https://mcp.clipia.ai/mcp",
      "headers": {
        "Authorization": "Bearer clipia_live_xxxxxxxx"
      }
    }
  }
}

Use a clipia_test_… key first to exercise the integration with instant mock results and no credit charges.

Development

pip install -e ".[dev]"
pytest -q

License

MIT — see LICENSE.