Link utili¶

Documentazione ufficiale¶

Repository: https://github.com/ggml-org/llama.cpp (README con l'elenco dei backend e dei modelli supportati)
Sito e installer: https://llama.app · guida rapida https://llama.app/docs/quickstart · installazione https://llama.app/docs/installation
llama cli: https://llama.app/docs/cli · llama serve: https://llama.app/docs/serve · API: https://llama.app/docs/api · web UI: https://llama.app/docs/webui
Server (tutti i flag, endpoint, metriche, router mode): https://github.com/ggml-org/llama.cpp/tree/master/tools/server
Build dai sorgenti: https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md · installazione con gestori di pacchetti: https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md
Docker: https://github.com/ggml-org/llama.cpp/blob/master/docs/docker.md · immagini: https://github.com/ggml-org/llama.cpp/pkgs/container/llama.cpp
Release e build notturne: https://github.com/ggml-org/llama.cpp/releases · processo di release: https://github.com/ggml-org/llama.cpp/blob/master/docs/release.md
Multimodale (mtmd): https://github.com/ggml-org/llama.cpp/blob/master/docs/multimodal.md · https://github.com/ggml-org/llama.cpp/tree/master/tools/mtmd
Function calling: https://github.com/ggml-org/llama.cpp/blob/master/docs/function-calling.md
Grammatiche GBNF: https://github.com/ggml-org/llama.cpp/tree/master/grammars
Quantizzazione: https://github.com/ggml-org/llama.cpp/tree/master/tools/quantize · imatrix: https://github.com/ggml-org/llama.cpp/tree/master/tools/imatrix · perplexity/KLD: https://github.com/ggml-org/llama.cpp/tree/master/tools/perplexity
Benchmark: https://github.com/ggml-org/llama.cpp/tree/master/tools/llama-bench · consigli sulle prestazioni: https://github.com/ggml-org/llama.cpp/blob/master/docs/development/token_generation_performance_tips.md
Multi-GPU: https://github.com/ggml-org/llama.cpp/blob/master/docs/multi-gpu.md · RPC: https://github.com/ggml-org/llama.cpp/tree/master/tools/rpc
Android: https://github.com/ggml-org/llama.cpp/blob/master/docs/android.md · iOS/macOS (xcframework): https://github.com/ggml-org/llama.cpp/blob/master/docs/xcframework.md
Backend: SYCL https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/SYCL.md · OpenCL https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/OPENCL.md
API C (llama.h): https://github.com/ggml-org/llama.cpp/blob/master/include/llama.h · esempi: https://github.com/ggml-org/llama.cpp/tree/master/examples
ggml: https://github.com/ggml-org/ggml · formato GGUF: https://github.com/ggml-org/ggml/blob/master/docs/gguf.md
Changelog del server: https://github.com/ggml-org/llama.cpp/issues/9291 · changelog di libllama: https://github.com/ggml-org/llama.cpp/issues/9289

Modelli¶

GGUF ufficiali di ggml-org: https://huggingface.co/ggml-org
Ricerca con filtro llama.cpp: https://huggingface.co/models?apps=llama.cpp&sort=trending
Quantizzatori affidabili: https://huggingface.co/unsloth · https://huggingface.co/bartowski · https://huggingface.co/LiquidAI
Convertire e quantizzare nel browser: GGUF-my-repo https://huggingface.co/spaces/ggml-org/gguf-my-repo · GGUF-my-LoRA https://huggingface.co/spaces/ggml-org/gguf-my-lora · editor di metadati https://huggingface.co/spaces/CISCai/gguf-editor
Modelli consigliati per il corso (repository, file, dimensioni e licenze)

Community e discussioni¶

Discussioni GitHub: https://github.com/ggml-org/llama.cpp/discussions (annunci, "show and tell", domande)
Issue e roadmap: https://github.com/ggml-org/llama.cpp/issues · https://github.com/ggml-org/llama.cpp/discussions/categories/announcements
Blog di ggml.ai: https://ggml.ai · blog Hugging Face su llama.cpp: https://huggingface.co/blog?tag=llama.cpp
Subreddit r/LocalLLaMA: https://www.reddit.com/r/LocalLLaMA/ (confronti di quantizzazioni, hardware, novità)
Discord di ggml (link nel README del repository)

Strumenti compatibili (usano llama.cpp o la sua API)¶

Strumento	Cos'è	Link
Open WebUI	interfaccia web completa (utenti, RAG, documenti) che si collega all'API OpenAI-compatibile di `llama serve`	https://github.com/open-webui/open-webui
LM Studio	app desktop (Windows/macOS/Linux) con motore llama.cpp integrato e catalogo di GGUF	https://lmstudio.ai
Ollama	gestore di modelli con CLI e API, basato su llama.cpp/ggml; modelli GGUF importabili con un `Modelfile`	https://ollama.com
Jan	app desktop open source, motore llama.cpp, API locale	https://jan.ai
KoboldCpp	fork di llama.cpp orientato alla narrativa, con UI integrata	https://github.com/LostRuins/koboldcpp
llama-cpp-python	binding Python di `libllama` con server OpenAI-compatibile	https://github.com/abetlen/llama-cpp-python
node-llama-cpp	binding Node.js	https://github.com/withcatai/node-llama-cpp
llama.vim / llama.vscode	completamento di codice locale (infill) con `llama serve`	https://github.com/ggml-org/llama.vim · https://github.com/ggml-org/llama.vscode
Continue / Cline	assistenti di codice negli IDE, configurabili verso `http://localhost:8080/v1`	https://continue.dev · https://cline.bot
whisper.cpp	trascrizione vocale con lo stesso motore ggml	https://github.com/ggml-org/whisper.cpp
SDK OpenAI (Python/JS)	client ufficiali: basta `base_url="http://localhost:8080/v1"`	https://github.com/openai/openai-python · https://github.com/openai/openai-node

Produzione e monitoraggio (modulo 09)¶

Caddy: https://caddyserver.com/docs/caddyfile/directives/reverse_proxy · basic_auth https://caddyserver.com/docs/caddyfile/directives/basic_auth · rate limit (plugin) https://github.com/mholt/caddy-ratelimit
Nginx: ngx_http_proxy_module https://nginx.org/en/docs/http/ngx_http_proxy_module.html · limit_req https://nginx.org/en/docs/http/ngx_http_limit_req_module.html · certbot https://certbot.eff.org
systemd: systemd.exec (sandboxing) https://www.freedesktop.org/software/systemd/man/latest/systemd.exec.html · systemd.service https://www.freedesktop.org/software/systemd/man/latest/systemd.service.html
Prometheus: https://prometheus.io/docs/prometheus/latest/configuration/configuration/ · Grafana: https://grafana.com/docs/grafana/latest/
Docker Compose (healthcheck, secrets): https://docs.docker.com/compose/compose-file/
OWASP Top 10 per applicazioni LLM (prompt injection e altro): https://owasp.org/www-project-top-10-for-large-language-model-applications/