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1 change: 1 addition & 0 deletions en/SUMMARY.md
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* [ChatGoogleGenerativeAI](integrations/langchain/chat-models/google-ai.md)
* [Google VertexAI](integrations/langchain/chat-models/google-vertexai.md)
* [ChatHuggingFace](integrations/langchain/chat-models/chathuggingface.md)
* [ChatInception](integrations/langchain/chat-models/chatinception.md)
* [ChatLocalAI](integrations/langchain/chat-models/chatlocalai.md)
* [ChatMistralAI](integrations/langchain/chat-models/mistral-ai.md)
* [IBM Watsonx](integrations/langchain/chat-models/ibm-watsonx.md)
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1 change: 1 addition & 0 deletions en/integrations/langchain/chat-models/README.md
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* [ChatGooglePaLM](broken-reference)
* [Google VertexAI](google-vertexai.md)
* [ChatHuggingFace](chathuggingface.md)
* [ChatInception](chatinception.md)
* [ChatLocalAI](chatlocalai.md)
* [ChatMistralAI](mistral-ai.md)
* [ChatOllama](chatollama.md)
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28 changes: 28 additions & 0 deletions en/integrations/langchain/chat-models/chatinception.md
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---
description: Wrapper around Inception Mercury diffusion LLMs (OpenAI-compatible API).
---

# ChatInception

## Description
[Inception](https://inceptionlabs.ai/) provides the Mercury family of diffusion LLMs, including **Mercury 2** — a fast reasoning model that supports tool calling and structured outputs. The API is OpenAI-compatible and served from `https://api.inceptionlabs.ai/v1`.

## Prerequisites
1. Create an account on the [Inception Platform](https://platform.inceptionlabs.ai/).
2. Get your API key from the [Inception Platform dashboard](https://platform.inceptionlabs.ai/). New accounts include free tokens to get started.

## Step by Step Guide
1. **Chat Models** > Drag the **ChatInception** node.
2. Create a new credential with your Inception API key.
3. Select a **Model Name** (defaults to `mercury-2`).
4. (Optional) Click **Additional Parameters** to configure **Reasoning Effort** (`instant`, `low`, `medium`, `high`), **Max Tokens**, **Streaming**, **Timeout**, or override the **Base Path**.

## Reasoning Effort
Mercury 2 is a reasoning model. Use the **Reasoning Effort** parameter to trade latency for depth:

| Value | Behavior |
| --- | --- |
| `instant` | Lowest latency, no extended thinking |
| `low` | Minimal reasoning |
| `medium` | Balanced reasoning (default) |
| `high` | Maximum reasoning for complex tasks |