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omp-docs/tools/llama-cpp/index.md

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+# llama.cpp Server — Overview
+
+[llama.cpp](https://github.com/ggml-org/llama.cpp) is a pure C/C++ LLM inference library. The `llama-server` binary is a lightweight, OpenAI-compatible HTTP server for serving GGUF models via REST API.
+
+See [Setup Guide](setup.md) for build instructions (CPU/CUDA/Metal/Vulkan), Docker, and systemd deployment.
+
+---
+
+## Key Features
+
+- OpenAI API-compatible chat completions, completions, and embeddings
+- Anthropic Messages API-compatible chat completions
+- Parallel decoding with multi-user support and continuous batching
+- Multimodal (vision/audio) support
+- Speculative decoding with draft models
+- Schema-constrained JSON output and function calling
+- Built-in Web UI
+- Prometheus metrics
+- Router mode for multi-model deployment
+
+---
+
+## GGUF Model Format
+
+**GGUF** (GGML Universal File) is the binary model file format used by llama.cpp.
+
+### Quantization Methods
+
+| Method | Bits/weight | 8B model size | Quality |
+|--------|------------|---------------|---------|
+| Q4_K_M | 4.9 | 4.58 GB | **Good (recommended default)** |
+| Q5_K_M | 5.7 | 5.33 GB | High |
+| Q6_K | 6.6 | 6.14 GB | Very High |
+| Q8_0 | 8.5 | 7.95 GB | Near-lossless |
+| F16 | 16.0 | 14.96 GB | Full precision |
+
+**Q4_K_M is the recommended default** — best balance of quality and size.
+
+---
+
+## Quick Start
+
+```bash
+# Serve a local model on default port 8080
+llama-server -m /path/to/model.gguf
+
+# From Hugging Face (auto-downloads)
+llama-server -hf ggml-org/gemma-3-1b-it-GGUF
+```
+
+**Defaults**: Listens on `127.0.0.1:8080`. Single slot (one concurrent request).
+
+> **System note:** On this network the Pi inference hosts do not use the default port. Pi serves `frank-default-small` (dankserver) and `frank-default-large` (dankclaw), each on port `7770`. The local Ornith host runs on port `8080`. See [Pi Models Configuration](../../pi/models.md).
+
+---
+
+## Health Check
+
+```bash
+curl http://localhost:8080/health
+# 200: {"status": "ok"}
+# 503: {"error": {"code": 503, "message": "Loading model"}}
+```
+
+---
+
+## API Endpoints
+
+### Chat Completions (OpenAI-compatible)
+
+```bash
+curl http://localhost:8080/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer no-key" \
+  -d '{
+    "model": "gpt-3.5-turbo",
+    "messages": [
+      {"role": "system", "content": "You are a helpful assistant."},
+      {"role": "user", "content": "Write a limerick about Python"}
+    ],
+    "max_tokens": 256,
+    "stream": true
+  }'
+```
+
+### Other Endpoints
+
+```bash
+# Completions
+curl http://localhost:8080/v1/completions
+
+# Embeddings
+curl http://localhost:8080/v1/embeddings
+
+# Native completion
+curl -X POST http://localhost:8080/completion -d '{"prompt": "Hello", "n_predict": 64}'
+
+# Anthropic-compatible
+curl http://localhost:8080/v1/messages
+
+# Monitoring
+curl http://localhost:8080/props
+curl http://localhost:8080/slots
+curl http://localhost:8080/metrics
+```
+
+---
+
+## Python Client
+
+```python
+import openai
+client = openai.OpenAI(
+    base_url="http://localhost:8080/v1",
+    api_key="sk-no-key-required"
+)
+completion = client.chat.completions.create(
+    model="gpt-3.5-turbo",
+    messages=[{"role": "user", "content": "What is the meaning of life?"}],
+    max_tokens=256
+)
+print(completion.choices[0].message.content)
+```
+
+---
+
+## Docker
+
+```bash
+docker run -p 8080:8080 -v /models:/models \
+  ghcr.io/ggml-org/llama.cpp:server \
+  -m /models/model.gguf --host 0.0.0.0 --port 8080
+
+# CUDA variant
+docker run -p 8080:8080 --gpus all \
+  ghcr.io/ggml-org/llama.cpp:server-cuda \
+  -m /models/model.gguf --n-gpu-layers 99
+```
+
+---
+
+## Environment Variables
+
+All CLI options can be set via `LLAMA_ARG_` prefix:
+
+```bash
+LLAMA_ARG_MODEL=/models/model.gguf LLAMA_ARG_CTX_SIZE=8192 llama-server
+```
+
+---
+
+## Cross-References
+
+- See [Setup Guide](setup.md) for build instructions, GPU offloading, and deployment.
+- See [Ornith Setup](../ornith-llama-cpp-setup/index.md) for running Ornith models.