| # Server Deployment Guide |
|
|
| Production deployment of llama.cpp server with OpenAI-compatible API. |
|
|
| ## Direct from Hugging Face Hub |
|
|
| Prefer the model repo's local-app page first: |
|
|
| ```text |
| https://huggingface.co/<repo>?local-app=llama.cpp |
| ``` |
|
|
| If the page shows an exact snippet, copy it. If not, use one of these forms: |
|
|
| ```bash |
| # Choose a quant label directly from the Hub repo |
| llama-server -hf bartowski/Llama-3.2-3B-Instruct-GGUF:Q8_0 |
| ``` |
|
|
| ```bash |
| # Pin an exact GGUF file from the repo tree |
| llama-server \ |
| --hf-repo microsoft/Phi-3-mini-4k-instruct-gguf \ |
| --hf-file Phi-3-mini-4k-instruct-q4.gguf \ |
| -c 4096 |
| ``` |
|
|
| Use the file-specific form when the repo has custom naming or when you already extracted the exact filename from the tree API. |
|
|
| ## Server Modes |
|
|
| ### llama-server |
|
|
| ```bash |
| # Basic server |
| ./llama-server \ |
| -m models/llama-2-7b-chat.Q4_K_M.gguf \ |
| --host 0.0.0.0 \ |
| --port 8080 \ |
| -c 4096 # Context size |
| |
| # With GPU acceleration |
| ./llama-server \ |
| -m models/llama-2-70b.Q4_K_M.gguf \ |
| -ngl 40 # Offload 40 layers to GPU |
| ``` |
|
|
| ## OpenAI-Compatible API |
|
|
| ### Chat completions |
| ```bash |
| curl http://localhost:8080/v1/chat/completions \ |
| -H "Content-Type: application/json" \ |
| -d '{ |
| "model": "llama-2", |
| "messages": [ |
| {"role": "system", "content": "You are helpful"}, |
| {"role": "user", "content": "Hello"} |
| ], |
| "temperature": 0.7, |
| "max_tokens": 100 |
| }' |
| ``` |
|
|
| ### Streaming |
| ```bash |
| curl http://localhost:8080/v1/chat/completions \ |
| -H "Content-Type: application/json" \ |
| -d '{ |
| "model": "llama-2", |
| "messages": [{"role": "user", "content": "Count to 10"}], |
| "stream": true |
| }' |
| ``` |
|
|
| ## Docker Deployment |
|
|
| **Dockerfile**: |
| ```dockerfile |
| FROM ubuntu:22.04 |
| RUN apt-get update && apt-get install -y git build-essential |
| RUN git clone https://github.com/ggerganov/llama.cpp |
| WORKDIR /llama.cpp |
| RUN make LLAMA_CUDA=1 |
| COPY models/ /models/ |
| EXPOSE 8080 |
| CMD ["./llama-server", "-m", "/models/model.gguf", "--host", "0.0.0.0", "--port", "8080"] |
| ``` |
|
|
| **Run**: |
| ```bash |
| docker run --gpus all -p 8080:8080 llama-cpp:latest |
| ``` |
|
|
| ## Monitoring |
|
|
| ```bash |
| # Server metrics endpoint |
| curl http://localhost:8080/metrics |
| |
| # Health check |
| curl http://localhost:8080/health |
| ``` |
|
|
| **Metrics**: |
| - requests_total |
| - tokens_generated |
| - prompt_tokens |
| - completion_tokens |
| - kv_cache_tokens |
|
|
| ## Load Balancing |
|
|
| **NGINX**: |
| ```nginx |
| upstream llama_cpp { |
| server llama1:8080; |
| server llama2:8080; |
| } |
| |
| server { |
| location / { |
| proxy_pass http://llama_cpp; |
| proxy_read_timeout 300s; |
| } |
| } |
| ``` |
|
|
| ## Performance Tuning |
|
|
| **Parallel requests**: |
| ```bash |
| ./llama-server \ |
| -m model.gguf \ |
| -np 4 # 4 parallel slots |
| ``` |
|
|
| **Continuous batching**: |
| ```bash |
| ./llama-server \ |
| -m model.gguf \ |
| --cont-batching # Enable continuous batching |
| ``` |
|
|
| **Context caching**: |
| ```bash |
| ./llama-server \ |
| -m model.gguf \ |
| --cache-prompt # Cache processed prompts |
| ``` |
|
|
