Inception builds Mercury, a family of diffusion large language models (dLLMs) that refine all tokens in parallel instead of generating them left-to-right, making them very fast. Inception serves the models through an OpenAI-compatible API, so you drive them through Agno like any other OpenAI-compatible provider. TheDocumentation Index
Fetch the complete documentation index at: https://docs.agno.com/llms.txt
Use this file to discover all available pages before exploring further.
Inception class defaults to mercury-2 and points at https://api.inceptionlabs.ai/v1.
Authentication
- Create an account at the Inception Platform.
- Open the dashboard and go to API Keys.
- Create a key and set your
INCEPTION_API_KEYenvironment variable.
Example
UseInception with your Agent:
View more examples here.
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
id | str | "mercury-2" | The id of the Mercury model to use |
name | str | "Inception" | The name of the model |
provider | str | "InceptionLabs" | The provider of the model |
api_key | Optional[str] | None | The API key for Inception (defaults to INCEPTION_API_KEY env var) |
base_url | str | "https://api.inceptionlabs.ai/v1" | The base URL for the Inception API |
Inception extends the OpenAI-compatible interface and supports most parameters from the OpenAI model.
Note: Inception’s OpenAI-compatible endpoint does not advertise native json_schema structured outputs, so supports_native_structured_outputs is set to False. Use use_json_mode=True for structured output.
To hit a different host (private deployment, regional endpoint), pass base_url:
Available Models
| Model id | Notes |
|---|---|
mercury-2 | Flagship reasoning dLLM. Tunable reasoning depth, 128K context, native tool use, JSON output. |
mercury-coder-small | Coding-focused variant for latency-sensitive code workflows. |
The original
mercury model is only available to accounts created before February 24, 2026. New accounts should use mercury-2 (or the coder variants) instead.