HappyHorse by Ace Data Cloud for LangChain

Install langchain-happyhorse-acedatacloud to give a LangChain application typed HappyHorse by Ace Data Cloud tools. This is an Ace-provided integration, not an official client of the service brand. It does not install the other four service modules. 中文 · Privacy.

1. Install

Official registry destination: PyPI langchain-happyhorse-acedatacloud. Source is merged on main. Version 0.1.0 is the stable release target; check release status for actual publication before installing. LangChain official directory approval is separate.

python3 -m venv .venv
source .venv/bin/activate
python -m pip install langchain-happyhorse-acedatacloud==0.1.0

For source installation: git clone --branch main https://github.com/AceDataCloud/LangChain.git, cd LangChain, then pip install -e packages/core -e packages/happyhorse.

Get the application API Key

1. Register or sign in → Applications. If no General application exists, choose Initialize General Application.
2. Open the General application. Copy its API Key, or choose Manage Keys → Create to make a separately named LangChain key. Review expiration, usage limitations and Allowed APIs. Allow both the generation and same-ID task query paths used below. Confirm service access, balance and current pricing. No trial allowance is promised.
3. Copy the raw token only, without Bearer , quotation marks or redacted characters. A platform-... account-management token cannot replace this application key.

The credential name Dify tutorial in the historical create-key image is illustrative; name the actual key LangChain HappyHorse. These are real Ace console screenshots reused from SunoDify, retrieved 2026-10-18; later console layouts may differ. They show credential setup, not a LangChain GUI. Real tokens are redacted.

export ACEDATACLOUD_API_TOKEN='your application key'

PowerShell: $env:ACEDATACLOUD_API_TOKEN='your application key'. Keep the token in the environment or secret manager, never in a prompt or workflow export.

2. Put the key in the client, not in model arguments

from langchain_acedatacloud import AceAPIClient
from langchain_happyhorse_acedatacloud import HappyHorseToolkit

# No network requests: instantiate tools and inspect their names/schemas.
kit = HappyHorseToolkit(client=AceAPIClient())
tools = kit.get_tools()  # Query-only by default.
print([tool.name for tool in tools])

There is no service-provider selection GUI in this package. Supply these LangChain BaseTool objects to your application or agent. Screenshots of another host's plugin authorization are not instructions for this Python integration.

3. First use, then query the same ID

After reviewing current service prices and deliberately authorizing one generation:

kit = HappyHorseToolkit(client=AceAPIClient(), include_generation=True)
generate, retrieve = kit.get_tools()
# This line submits one paid generation if you choose to run it:
submitted = generate.invoke({"prompt": "A white horse in warm sunrise light, slow camera push in."})
task_id = submitted["task_id"]
# Query the original ID; never call generate again just to wait:
result = retrieve.invoke({"task_id": task_id})
print(result["status"], result["terminal"], result["media_urls"])

happyhorse_generate_video submits one asynchronous request to /happyhorse/videos. happyhorse_retrieve_task calls /happyhorse/tasks with action=retrieve and the original id. A pending result is normal. Query that ID later until terminal=true; then inspect success/failure and final media URLs. The example shape is illustrative, not an actual paid result. Advanced edit/extend actions are not exposed in this initial toolkit.

Troubleshooting and cost

401: raw Key or token environment; 403: permissions, balance, expiry, Allowed APIs and response details; 429: reduce concurrency. For pending or a timeout, inspect the same task before any new submission. No automatic retries or hidden polling are performed. Usage History owns actual Credits. Avoid printing credentials or sending them to a model.