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chatgpt-on-wechat/docs/en/models/deepseek.mdx

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---
title: DeepSeek
description: DeepSeek model configuration
---
Option 1: Native integration (recommended):
```json
{
"model": "deepseek-v4-flash",
"deepseek_api_key": "YOUR_API_KEY"
}
```
| Parameter | Description |
| --- | --- |
| `model` | Supports `deepseek-v4-flash` (default) and `deepseek-v4-pro` |
| `deepseek_api_key` | Create at [DeepSeek Platform](https://platform.deepseek.com/api_keys) |
| `deepseek_api_base` | Optional, defaults to `https://api.deepseek.com/v1`. Can be changed to a third-party proxy |
## Model Selection
| Model | Use Case |
| --- | --- |
| `deepseek-v4-flash` | Default: fast and cost-effective |
| `deepseek-v4-pro` | Stronger on complex tasks |
## Thinking Mode
The V4 series (`deepseek-v4-flash` / `deepseek-v4-pro`) supports an explicit "thinking mode": the model emits a chain-of-thought (`reasoning_content`) before the final answer to improve answer quality.
### Toggle
Controlled by the global `enable_thinking` setting:
```json
{
"enable_thinking": true
}
```
- `true`: thinking is on across all channels. The Web console renders the reasoning trace; IM channels (WeChat / WeCom / DingTalk / Feishu) don't render it but still benefit from higher answer quality.
- `false`: thinking off, faster responses with lower first-token latency.
### Reasoning Effort
Under thinking mode, `reasoning_effort` controls how hard the model thinks:
```json
{
"enable_thinking": true,
"reasoning_effort": "high"
}
```
| Value | Use Case |
| --- | --- |
| `high` (default) | Day-to-day agent tasks; balanced thinking depth and latency |
| `max` | Complex coding, long-horizon planning, strict-constraint tasks. Deeper reasoning at the cost of more output tokens and higher latency |
`reasoning_effort` only takes effect when `enable_thinking` is `true`. It is silently ignored on models that do not support thinking mode.
### Notes
- **Sampling parameters**: under thinking mode, `temperature`, `top_p`, `presence_penalty`, and `frequency_penalty` are silently ignored by the server (no error). CowAgent skips sending them automatically.
- **Multi-turn tool calls**: once the history contains any tool-call turn, DeepSeek requires `reasoning_content` on every assistant message. CowAgent handles the round-trip automatically, including across mid-session toggles of the thinking switch.
<Tip>
Start with `deepseek-v4-flash`; switch to `deepseek-v4-pro` for harder tasks; enable `enable_thinking` when you want deeper reasoning.
</Tip>
Option 2: OpenAI-compatible configuration:
```json
{
"model": "deepseek-v4-flash",
"bot_type": "openai",
"open_ai_api_key": "YOUR_API_KEY",
"open_ai_api_base": "https://api.deepseek.com/v1"
}
```