> For the complete documentation index, see [llms.txt](https://docs.sigrex.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sigrex.io/reaction/llm-reaction.md).

# LLM Reaction

An LLM Reaction allows Sigrex to process incoming data using an AI model.

LLM Reactions are **event-driven** and are triggered automatically when data is received through a **Data Webhook**.

They can be used for:

* Data interpretation and classification
* AI-based decision making
* Event-driven trading logic
* Signal generation without chart analysis

***

### 🛠️ How LLM Reactions Work

1. A **Data Webhook** receives an incoming request
2. The payload is forwarded to all connected **Reactions**
3. The **LLM Reaction** injects the data into its prompt
4. The AI processes the request
5. The result is stored and optionally forwarded as a signal

LLM Reactions run **only when new data arrives** — there is no scheduling.

***

### ⚙️ Configuration

#### Prompt

The prompt defines how the AI should interpret incoming data.

LLM Reactions support the following template variables:

* `{{data}}` → Raw payload from the webhook request
* `{{ip}}` → IP address of the sender
* `{{headers}}` → Request headers in JSON format

These variables are replaced at runtime with the actual values from the incoming request.

***

#### 🧾 Example Prompt

```
You will receive external data below.

IP: {{ip}}
Headers: {{headers}}

Payload:
{{data}}

Analyze the data and decide whether any action is required.
If the data is incomplete or unreliable, take no action.
```

***

### 🧩 Incoming Data & Context

The AI receives structured context from the webhook request:

#### `{{data}}`

* Contains the full request body
* Passed to the AI **as-is**
* No schema enforcement
* Typically JSON (text support coming soon)

***

#### `{{headers}}`

* Contains all HTTP request headers
* Provided as a **JSON object**
* Useful for authentication, source identification, or metadata

***

#### `{{ip}}`

* The IP address of the request sender (if available)
* Can be used for filtering or trust-based logic

***

### 🧪 Example Incoming Payload

```
{
  "event": "trend_signal",
  "symbol": "BTCUSDT",
  "direction": "up",
  "confidence": 0.81
}
```

***

### 🧾 Output & Storage

Each execution produces an output that:

* Is stored in the platform
* Is linked to the triggering webhook event
* Can be reviewed for debugging and auditing
* Can be forwarded to downstream systems

***

### 🧠 System Context (Automatically Injected)

When Trading Decision Mode is enabled, Sigrex automatically injects system-level context.

#### Prepended Context

```
You are a trading decision engine.

The last action was {{last_trigger_action}}.
That action executed at {{last_trigger_at}}.
The current time is {{current_time}}.

IMPORTANT:
- Only one position can be open at a time.
- If the last action was LONG or SHORT, a position is currently open.
- A new position may only be opened after an EXIT.
```

***

### 🧠 Prompt Writing Best Practices

* Clearly define **when to act**
* Explicitly describe **exit conditions**
* Handle conflicting or low-confidence data
* Prefer deterministic language
* Suppress explanations when using decision mode

#### Example Trading Prompt

```
You will receive external trading data below.

{{data}}

Open a position only if confidence is above 0.8.
Exit immediately if the data contradicts the current position.
If conditions are unclear, respond with HOLD.
```

***

### 🚫 Limitations

* No chart or image input
* No price selection
* One action per execution
* No partial positions
* Output must be exact

***

### 🔗 Related Features

* [**Data Webhook**](/reaction/data-webhook.md) – Receive external data
* [**Code Reaction**](/reaction/code-reaction.md) – Deterministic logic processing
* [**LLM Session**](/startegies/llm-session.md) – Scheduled AI analysis
* [**Chart Analysis**](/startegies/llm-session/chart-setup.md) **with** [**Signal Generation**](/startegies/llm-session/signal-generation.md) – Chart-based signals
* [**Signal Bots**](/cex-signal-bot/creating-a-cex-signal-bot.md) – Execute trades

***

### 🧠 Summary

LLM Reactions provide a powerful way to:

* React to live external data
* Apply AI reasoning in real time
* Make structured trading decisions
* Build event-driven trading systems without charts

They are best suited for **clean, rule-guided AI decisions** triggered by external events.


---

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