Agent integrations
Every agent framework already speaks our language.
OpenCode, Cline, Kilo Code, Hermes Agent, OpenClaw — each of them takes an OpenAI-compatible endpoint. Aim one here and your agent runs on the same API, serverless or on your own dedicated deployment.
from openai import OpenAI
client = OpenAI(
base_url="https://api.vidman.ai/v1",
api_key="sk-vidman-...",
)
resp = client.chat.completions.create(
model="deepseek-v4-flash", # any served model id
messages=[{"role": "user", "content": "Summarize my inbox"}],
)Three values — base URL, API key, model id. Every framework below takes the same three, just in its own config.
The setup
Three values — and the integration is done
Agent frameworks differ in memory, tools, and channels — but they all speak the same wire protocol. Swap the endpoint, keep everything else.
The OpenAI-compatible endpoint, path-shaped like api.openai.com — no framework can tell the difference.
Your Vidman AI key from the console — one key covers every served model.
Pick from the model library — or the id of your own fine-tuned checkpoint on a dedicated endpoint.
Frameworks
Where those three values land
Each framework keeps its own config format — the values never change. Exact file paths vary between versions; the pattern below is the one every version accepts.
Coding agents
OpenCode
An open-source terminal coding agent — reads your codebase, plans and executes changes, runs tests, and iterates from natural language.
Provider config (opencode.json) — add your API key and base URL, pick any served model id.
Cline
The coding agent that lives in your IDE and plans, edits, and runs your code.
API provider settings in the extension — base URL, key, model id.
Kilo Code
An open-source coding agent for VS Code, JetBrains, and the CLI — bring your own keys, pick from hundreds of models.
Provider settings — add your API key and base URL, then pick any served model id.
Pi
A minimal terminal coding harness you extend with TypeScript packages — read, write, edit, and bash tools out of the box.
Provider config — authenticate with your API key, select the model with /model.
Aider
A terminal pair-programmer that edits git repos with you.
Environment variables — OPENAI_API_BASE and OPENAI_API_KEY.
Continue
An open-source IDE assistant with custom models and context.
config.json — apiBase and apiKey on the model entry.
Personal & messaging agents
Hermes Agent
A self-improving agent with persistent memory, skills, and messaging gateways — Telegram, Discord, Slack, WhatsApp.
Provider config — accepts any OpenAI-compatible endpoint; switch models with `hermes model`.
OpenClaw
A self-hosted gateway that connects WhatsApp, Telegram, Signal, iMessage and more to your AI agent.
Model provider config in the gateway — hosted and local providers both supported.
MIRA
A self-hosted personal agent that reaches you on Signal, Telegram, Discord, WhatsApp, Slack, and email.
Provider config — OpenAI-compatible servers supported; point it at the Vidman AI endpoint.
LibreChat
A self-hosted chat UI that speaks to any OpenAI-compatible API.
Endpoint and key in the UI — no code changes.
Not listed? If it accepts an OpenAI-compatible endpoint, the same three values apply. Per-framework walkthroughs are being verified and will be linked here as they pass.
Run every model through LiteLLM
One OpenAI-compatible proxy in front of the catalog — per-developer virtual keys and spend tracking on the server.
LiteLLM setupBuild with agent frameworks
LangChain, LlamaIndex, CrewAI, PydanticAI, Strands Agents — the orchestration frameworks, on the same three values.
Agent frameworksDedicated deployment
Your weights, your endpoint, the same three lines.
Fine-tune a model on dedicated GPUs, then serve it on a dedicated endpoint behind the same OpenAI-compatible API. The agent config does not change — only the model id does, and the weights behind it are yours.
- The checkpoint is a file you own and can export
- Dedicated hardware, billed per second of GPU time
- The same base_url and api_key as serverless
Illustrative — the agent config is identical to serverless.
Why Vidman AI
Agents are the toughest workload there is — run them on a platform built for it
Agents burn tokens. Pay by the token.
An always-on agent is a high-volume workload, and serverless inference meteres per million tokens at the catalog rates — no seat licences, no minimums, and the calculator shows the monthly figure before you commit.
Your agent reads your email. Zero retention matters.
Agents touch the private material — inboxes, files, messages. Vidman AI handles prompts and responses in memory and keeps nothing, so the agent can work on sensitive input without it becoming anyone’s training data.
Your weights, your endpoint, the same three lines.
Train a model on dedicated GPUs and serve it on a dedicated endpoint behind the same OpenAI-compatible API. Nothing in the agent config changes — only the model id does.
What teams ask before switching
Which agent frameworks run on Vidman AI?+
Anything that takes an OpenAI-compatible endpoint: Hermes Agent, OpenClaw, Cline, Aider, Continue, LibreChat, plus the OpenAI SDKs themselves. The integration surface is three values — base URL, API key, model id — so whatever can point at OpenAI can point here.
Does my agent’s code have to change?+
No. You change where the framework looks, never what it does: set the base URL to the Vidman AI endpoint, drop in your key, pick a served model id. The framework keeps its own loop, tools and memory.
Can the agent use a model I fine-tuned here?+
Yes. A finished checkpoint can sit on a dedicated endpoint behind the same OpenAI-compatible API. The agent config is identical — only the model id moves, and the weights behind it are yours.
How does agent traffic get billed?+
By the million tokens, at the same input and output rates the catalog publishes. No per-seat or per-agent fees exist, and cached input is cheaper wherever the model offers it.
What happens to the data my agent sends?+
Prompts and responses are handled in memory and nothing is kept. Vidman AI retains none of your data and trains on none of it — the same guarantee on serverless inference and on your dedicated deployment.
Aim your agent at Vidman AI tonight.
Get 50% extra on your first wallet top-up.
Per-million-token billing · Zero data retention · Your weights stay yours