--- /dev/null
+# llama-server Development Documentation
+
+This document provides an in-depth technical overview of `llama-server`, intended for maintainers and contributors.
+
+If you are an end user consuming `llama-server` as a product, please refer to the main [README](./README.md) instead.
+
+## Backend
+
+### Overview
+
+The server supports two primary operating modes:
+
+- **Inference mode**: The default mode for performing inference with a single loaded GGUF model.
+- **Router mode**: Enables management of multiple inference server instances behind a single API endpoint. Requests are automatically routed to the appropriate backend instance based on the requested model.
+
+The core architecture consists of the following components:
+
+- `server_context`: Holds the primary inference state, including the main `llama_context` and all active slots.
+- `server_slot`: An abstraction over a single “sequence” in llama.cpp, responsible for managing individual parallel inference requests.
+- `server_routes`: Middleware layer between `server_context` and the HTTP interface; handles JSON parsing/formatting and request routing logic.
+- `server_http_context`: Implements the HTTP server using `cpp-httplib`.
+- `server_queue`: Thread-safe queue used by HTTP workers to submit new tasks to `server_context`.
+- `server_response`: Thread-safe queue used by `server_context` to return results to HTTP workers.
+- `server_response_reader`: Higher-level wrapper around the two queues above for cleaner code.
+- `server_task`: Unit of work pushed into `server_queue`.
+- `server_task_result`: Unit of result pushed into `server_response`.
+- `server_tokens`: Unified representation of token sequences (supports both text and multimodal tokens); used by `server_task` and `server_slot`.
+- `server_prompt_checkpoint`: For recurrent (e.g., RWKV) and SWA models, stores snapshots of KV cache state. Enables reuse when subsequent requests share the same prompt prefix, saving redundant computation.
+- `server_models`: Standalone component for managing multiple backend instances (used in router mode). It is completely independent of `server_context`.
+
+```mermaid
+graph TD
+ API_User <--> server_http_context
+ server_http_context <-- router mode --> server_models
+ server_http_context <-- inference mode --> server_routes
+ server_routes -- server_task --> server_queue
+ subgraph server_context
+ server_queue --> server_slot
+ server_slot -- server_task_result --> server_response
+ server_slot[multiple server_slot]
+ end
+ server_response --> server_routes
+```
+
+TODO: mention about how batching is handled by `server_slot`
+
+### Thread Management
+
+`server_context` runs on a dedicated single thread. Because it is single-threaded, heavy post-processing (especially after token generation) should be avoided, as it directly impacts multi-sequence throughput.
+
+Each incoming HTTP request is handled by its own thread managed by the HTTP library. The following operations are performed in HTTP worker threads:
+
+- JSON request parsing
+- Chat template application
+- Tokenization
+- Conversion of `server_task_result` into final JSON response
+- Error formatting into JSON
+- Tracking of partial/incremental responses (e.g., streaming tool calls or reasoning steps)
+
+**Best practices to follow:**
+
+- All JSON formatting and chat template logic must stay in the HTTP layer.
+- Avoid passing raw JSON between the HTTP layer and `server_slot`. Instead, parse everything into native C++ types as early as possible.
+
+### Testing
+
+`llama-server` includes an automated test suite based on `pytest`.
+
+The framework automatically starts a `llama-server` instance, sends requests, and validates responses.
+
+For detailed instructions, see the [test documentation](./tests/README.md).
+
+### Notable Related PRs
+
+- Initial server implementation: https://github.com/ggml-org/llama.cpp/pull/1443
+- Parallel decoding support: https://github.com/ggml-org/llama.cpp/pull/3228
+- Refactor introducing `server_queue` and `server_response`: https://github.com/ggml-org/llama.cpp/pull/5065
+- Reranking endpoint: https://github.com/ggml-org/llama.cpp/pull/9510
+- Multimodal model support (`libmtmd`): https://github.com/ggml-org/llama.cpp/pull/12898
+- Unified KV cache handling: https://github.com/ggml-org/llama.cpp/pull/16736
+- Separation of HTTP logic into dedicated files: https://github.com/ggml-org/llama.cpp/pull/17216
+- Large-scale code base split into smaller files: https://github.com/ggml-org/llama.cpp/pull/17362
+- Introduction of router mode: https://github.com/ggml-org/llama.cpp/pull/17470
+
+
+
+
+## Web UI
+
+The project includes a web-based user interface for interacting with `llama-server`. It supports both single-model (`MODEL` mode) and multi-model (`ROUTER` mode) operation.
+
+The SvelteKit-based Web UI is introduced in this PR: https://github.com/ggml-org/llama.cpp/pull/14839
+
+### Features
+
+- **Chat interface** with streaming responses
+- **Multi-model support** (ROUTER mode) - switch between models, auto-load on selection
+- **Modality validation** - ensures selected model supports conversation's attachments (images, audio)
+- **Conversation management** - branching, regeneration, editing with history preservation
+- **Attachment support** - images, audio, PDFs (with vision/text fallback)
+- **Configurable parameters** - temperature, top_p, etc. synced with server defaults
+- **Dark/light theme**
+
+### Tech Stack
+
+- **SvelteKit** - frontend framework with Svelte 5 runes for reactive state
+- **TailwindCSS** + **shadcn-svelte** - styling and UI components
+- **Vite** - build tooling
+- **IndexedDB** (Dexie) - local storage for conversations
+- **LocalStorage** - user settings persistence
+
+### Architecture
+
+The WebUI follows a layered architecture:
+
+```
+Routes → Components → Hooks → Stores → Services → Storage/API
+```
+
+- **Stores** - reactive state management (`chatStore`, `conversationsStore`, `modelsStore`, `serverStore`, `settingsStore`)
+- **Services** - stateless API/database communication (`ChatService`, `ModelsService`, `PropsService`, `DatabaseService`)
+- **Hooks** - reusable logic (`useModelChangeValidation`, `useProcessingState`)
+
+For detailed architecture diagrams, see [`tools/server/webui/docs/`](webui/docs/):
+
+- `high-level-architecture.mmd` - full architecture with all modules
+- `high-level-architecture-simplified.mmd` - simplified overview
+- `data-flow-simplified-model-mode.mmd` - data flow for single-model mode
+- `data-flow-simplified-router-mode.mmd` - data flow for multi-model mode
+- `flows/*.mmd` - detailed per-domain flows (chat, conversations, models, etc.)
+
+### Development
+
+```sh
+# make sure you have Node.js installed
+cd tools/server/webui
+npm i
+
+# run dev server (with hot reload)
+npm run dev
+
+# run tests
+npm run test
+
+# build production bundle
+npm run build
+```
+
+After `public/index.html.gz` has been generated, rebuild `llama-server` as described in the [build](#build) section to include the updated UI.
+
+**Note:** The Vite dev server automatically proxies API requests to `http://localhost:8080`. Make sure `llama-server` is running on that port during development.
Fast, lightweight, pure C/C++ HTTP server based on [httplib](https://github.com/yhirose/cpp-httplib), [nlohmann::json](https://github.com/nlohmann/json) and **llama.cpp**.
-Set of LLM REST APIs and a simple web front end to interact with llama.cpp.
+Set of LLM REST APIs and a web UI to interact with llama.cpp.
**Features:**
* LLM inference of F16 and quantized models on GPU and CPU
* Speculative decoding
* Easy-to-use web UI
-The project is under active development, and we are [looking for feedback and contributors](https://github.com/ggml-org/llama.cpp/issues/4216).
+For the ful list of features, please refer to [server's changelog](https://github.com/ggml-org/llama.cpp/issues/9291)
## Usage
cmake --build build --config Release -t llama-server
```
-## Web UI
-
-The project includes a web-based user interface for interacting with `llama-server`. It supports both single-model (`MODEL` mode) and multi-model (`ROUTER` mode) operation.
-
-### Features
-
-- **Chat interface** with streaming responses
-- **Multi-model support** (ROUTER mode) - switch between models, auto-load on selection
-- **Modality validation** - ensures selected model supports conversation's attachments (images, audio)
-- **Conversation management** - branching, regeneration, editing with history preservation
-- **Attachment support** - images, audio, PDFs (with vision/text fallback)
-- **Configurable parameters** - temperature, top_p, etc. synced with server defaults
-- **Dark/light theme**
-
-### Tech Stack
-
-- **SvelteKit** - frontend framework with Svelte 5 runes for reactive state
-- **TailwindCSS** + **shadcn-svelte** - styling and UI components
-- **Vite** - build tooling
-- **IndexedDB** (Dexie) - local storage for conversations
-- **LocalStorage** - user settings persistence
-
-### Architecture
-
-The WebUI follows a layered architecture:
-
-```
-Routes → Components → Hooks → Stores → Services → Storage/API
-```
-
-- **Stores** - reactive state management (`chatStore`, `conversationsStore`, `modelsStore`, `serverStore`, `settingsStore`)
-- **Services** - stateless API/database communication (`ChatService`, `ModelsService`, `PropsService`, `DatabaseService`)
-- **Hooks** - reusable logic (`useModelChangeValidation`, `useProcessingState`)
-
-For detailed architecture diagrams, see [`tools/server/webui/docs/`](webui/docs/):
-
-- `high-level-architecture.mmd` - full architecture with all modules
-- `high-level-architecture-simplified.mmd` - simplified overview
-- `data-flow-simplified-model-mode.mmd` - data flow for single-model mode
-- `data-flow-simplified-router-mode.mmd` - data flow for multi-model mode
-- `flows/*.mmd` - detailed per-domain flows (chat, conversations, models, etc.)
-
-### Development
-
-```sh
-# make sure you have Node.js installed
-cd tools/server/webui
-npm i
-
-# run dev server (with hot reload)
-npm run dev
-
-# run tests
-npm run test
-
-# build production bundle
-npm run build
-```
-
-After `public/index.html.gz` has been generated, rebuild `llama-server` as described in the [build](#build) section to include the updated UI.
-
-**Note:** The Vite dev server automatically proxies API requests to `http://localhost:8080`. Make sure `llama-server` is running on that port during development.
-
## Quick Start
To get started right away, run the following command, making sure to use the correct path for the model you have:
docker run -p 8080:8080 -v /path/to/models:/models --gpus all ghcr.io/ggml-org/llama.cpp:server-cuda -m models/7B/ggml-model.gguf -c 512 --host 0.0.0.0 --port 8080 --n-gpu-layers 99
```
-## Testing with CURL
+## Using with CURL
Using [curl](https://curl.se/). On Windows, `curl.exe` should be available in the base OS.
--data '{"prompt": "Building a website can be done in 10 simple steps:","n_predict": 128}'
```
-## Advanced testing
-
-We implemented a [server test framework](./tests/README.md) using human-readable scenario.
-
-*Before submitting an issue, please try to reproduce it with this format.*
-
-## Node JS Test
-
-You need to have [Node.js](https://nodejs.org/en) installed.
-
-```bash
-mkdir llama-client
-cd llama-client
-```
-
-Create an index.js file and put this inside:
-
-```javascript
-const prompt = "Building a website can be done in 10 simple steps:"
-
-async function test() {
- let response = await fetch("http://127.0.0.1:8080/completion", {
- method: "POST",
- body: JSON.stringify({
- prompt,
- n_predict: 64,
- })
- })
- console.log((await response.json()).content)
-}
-
-test()
-```
-
-And run it:
-
-```bash
-node index.js
-```
-
## API Endpoints
### GET `/health`: Returns health check result
}
```
+## API errors
+
+`llama-server` returns errors in the same format as OAI: https://github.com/openai/openai-openapi
+
+Example of an error:
+
+```json
+{
+ "error": {
+ "code": 401,
+ "message": "Invalid API Key",
+ "type": "authentication_error"
+ }
+}
+```
+
## More examples
### Interactive mode
bash chat.sh
```
-### OAI-like API
-
-The HTTP `llama-server` supports an OAI-like API: https://github.com/openai/openai-openapi
-
-### API errors
-
-`llama-server` returns errors in the same format as OAI: https://github.com/openai/openai-openapi
-
-Example of an error:
-
-```json
-{
- "error": {
- "code": 401,
- "message": "Invalid API Key",
- "type": "authentication_error"
- }
-}
-```
-
Apart from error types supported by OAI, we also have custom types that are specific to functionalities of llama.cpp:
**When /metrics or /slots endpoint is disabled**
overview / pkg / ggml / sources / llama.cpp / commitdiff