Files
LocalAI/core/config/hooks_llamacpp.go
LocalAI [bot] 1154be5eea fix(config): fall back to DefaultContextSize for unparseable GGUFs; pin NVFP4 gallery context_size (#10563)
The GGUF metadata parser (gpustack/gguf-parser-go) cannot read NVFP4-quantized
GGUFs at all: it errors with "read tensor info 0: This quantized type is
currently unsupported" because NVFP4 is a ggml tensor type it does not know.
When ParseGGUFFile errors, the llama-cpp defaults hook skips guessGGUFFromFile
entirely and the deferred fallback sets the context window to the conservative
GGUFFallbackContextSize (1024). The result: a model that trains to 262144
tokens runs with n_ctx=1024, and every prompt over ~1k tokens fails with
"request (N tokens) exceeds the available context size (1024 tokens)".

Two changes:

- Drop GGUFFallbackContextSize (1024) and fall back to DefaultContextSize
  (4096) in both the GGUF run-estimate path (gguf.go) and the deferred hook
  fallback (hooks_llamacpp.go). 1024 is a sensible floor for a tiny CPU GGUF
  but a footgun for a large, long-context model whose header simply cannot be
  parsed. Strengthen the existing "GGUF unreadable" test to assert the value.

- Set context_size explicitly on the four NVFP4 gallery entries
  (qwen3.6-35b-a3b-nvfp4-mtp, qwopus3.6-27b-v2-mtp-nvfp4,
  qwopus3.6-27b-coder-mtp-nvfp4, qwen3.6-27b-nvfp4-mtp) so the parser failure
  is irrelevant for them. 32768 matches sibling Qwen entries and is safe on
  memory; operators can raise it toward the 262144 train length.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 23:34:52 +02:00

61 lines
1.9 KiB
Go

package config
import (
"os"
"path/filepath"
gguf "github.com/gpustack/gguf-parser-go"
"github.com/mudler/xlog"
)
func init() {
// Register for both explicit llama-cpp and empty backend (auto-detect from GGUF file)
RegisterBackendHook("llama-cpp", llamaCppDefaults)
RegisterBackendHook("", llamaCppDefaults)
}
func llamaCppDefaults(cfg *ModelConfig, modelPath string) {
if os.Getenv("LOCALAI_DISABLE_GUESSING") == "true" {
xlog.Debug("llamaCppDefaults: guessing disabled")
return
}
if modelPath == "" {
return
}
guessPath := filepath.Join(modelPath, cfg.ModelFileName())
defer func() {
if r := recover(); r != nil {
xlog.Error("llamaCppDefaults: panic while parsing gguf file")
}
}()
// Default context size if not set, regardless of whether GGUF parsing succeeds
defer func() {
if cfg.ContextSize == nil {
ctx := DefaultContextSize
cfg.ContextSize = &ctx
}
}()
// Startup parses every model's GGUF header to guess defaults. We only need
// scalar metadata (architecture, head/ff counts, chat_template, token IDs,
// MTP head) plus array *lengths* — never the array *contents*. Two options
// keep this cheap, which matters when many models live on slow storage such
// as a Docker volume (see https://github.com/mudler/LocalAI/issues/9790):
//
// - SkipLargeMetadata: seek past large array-valued metadata (the tokenizer
// vocab: tokenizer.ggml.tokens/scores/merges, often >100k entries) instead
// of reading and allocating every element. Lengths stay populated.
// - UseMMap: read the header via a memory map so faulting in a few pages
// replaces hundreds of thousands of tiny read() syscalls (measured ~524k
// -> 8 for a 256k-token vocab), the dominant cost on slow filesystems.
//
// The mapping is released when ParseGGUFFile returns.
f, err := gguf.ParseGGUFFile(guessPath, gguf.UseMMap(), gguf.SkipLargeMetadata())
if err == nil {
guessGGUFFromFile(cfg, f, 0)
}
}