> ## Documentation Index
> Fetch the complete documentation index at: https://langchat.neurobrains.co/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChatEngine

> Internal engine API reference. Advanced use only.

## Overview

`LangChatEngine` is the internal engine that powers `LangChat`. In most cases you don't interact with it directly — use the `LangChat` SDK class instead.

Access it via `lc.engine` when you need low-level control.

```python theme={null}
from langchat.core.engine import LangChatEngine
```

***

## Constructor

```python theme={null}
LangChatEngine(
    *,
    llm,
    vector_db,
    db,
    reranker=None,
    prompt_template=None,
    standalone_question_prompt=None,
    verbose=False,
    max_chat_history=20,
)
```

Same parameters as `LangChat`. All are keyword-only.

***

## Methods

### `async chat()`

Process a chat query. Returns a raw dict (not a `ChatResponse`).

```python theme={null}
async def chat(
    self,
    query: str,
    user_id: str,
    platform: str = "default",
    standalone_question: str | None = None,
) -> dict
```

<ParamField path="standalone_question" type="str | None" default="None">
  If provided, skips the standalone question generation step and uses this value directly. Useful for pre-processing.
</ParamField>

**Returns:**

```python theme={null}
{
    "response": str,           # AI response text
    "user_id": str,            # echoed user_id
    "timestamp": str,          # ISO 8601 UTC
    "status": "success"|"error",
    "response_time": float,    # seconds
    "error": str | None,       # error message on failure
}
```

***

### `get_session()`

Get or create a `UserSession`.

```python theme={null}
def get_session(
    self,
    user_id: str,
    platform: str = "default",
) -> UserSession
```

Sessions are cached in `self.sessions` dict keyed by `"{user_id}_{platform}"`.

***

## Attributes

| Attribute          | Type                     | Description                  |
| ------------------ | ------------------------ | ---------------------------- |
| `llm`              | Any                      | LLM provider instance        |
| `vector_adapter`   | Any                      | Vector DB provider instance  |
| `history_store`    | Any                      | Database provider instance   |
| `reranker_adapter` | Any                      | Reranker instance            |
| `sessions`         | `dict[str, UserSession]` | In-memory session cache      |
| `id_manager`       | `IDManager`              | Database ID sequence manager |
| `prompt_template`  | `str`                    | System prompt template       |
| `verbose`          | `bool`                   | Verbose logging flag         |
| `max_chat_history` | `int`                    | History window size          |

***

## Advanced: skip standalone question generation

If you're building a pipeline that pre-processes questions, you can skip the standalone question step:

```python theme={null}
# Pre-process the question yourself
standalone = f"Question about Acme Corp: {user_query}"

result = await lc.engine.chat(
    query=user_query,
    user_id="alice",
    standalone_question=standalone,
)
```

***

## API server mode

When running as an API server, the engine suppresses Rich console output (the formatted response panel):

```python theme={null}
from langchat.core.engine import set_api_server_mode
set_api_server_mode(True)   # called automatically by create_app()
```