mudler-agentandEttore Di Giacinto
c7ce0c602c
* fix(http): stop listing the models directory on embeddings and bearer requests Every embeddings request read the whole models directory before the body was parsed, even when the body named its model. On a network-backed models directory this cost seconds per request. Embeddings now binds the body first and looks up a default model only when the body has none, like chat. The pre-bind default lookup and the gpt-4o constant default are gone from that route. The first-available default lookup skips the directory when the filter cannot accept an unconfigured file. Every usecase filter rejects files without a config, so the scan never added results for them. Match-all, nil and name filters keep the scan. The bearer token check is now an exact test: a configured name, or one stat of that name in the models directory. The value is a literal, not a regular expression, and a name that is not a local relative path never matches a file. Assisted-by: Claude Code:claude-haiku-5-5 * perf(config): cache GGUF header reads for model defaults Model defaults re-parsed the GGUF header on every SetDefaults call, which runs per request and at startup reload. Put a bounded LRU in front of the parser, keyed by absolute path and validated by size and modification time. The cached value is a snapshot of the fields the defaults use, not the parser output. A changed size or mtime is a miss. Missing files and parse errors are not cached, so the existing fallback is unchanged. LOCALAI_DISABLE_GUESSING, the empty-path guard, the alias early return, the panic recovery and the context-size default are all kept in front of the cache. Assisted-by: Claude:claude-haiku-5-5 * test(http): cover listing-free default lookup on every usecase route Assisted-by: Claude Code:claude-haiku-5-5 * feat(config): persist the GGUF header cache per instance The header cache kept parsed GGUF results only in memory, so every restart parsed each model file again before its defaults were known. Write the cache to a per-instance file in the data path and load it at startup. A restarted frontend with a fixed instance ID starts warm. The file is versioned and records the estimator inputs (gguf-parser version, candidate contexts, auto context size, offload count). A mismatch on any of them makes the file ignored. Each entry keeps path, size and mtime, so a changed model file is a miss on load. Writes run on one background saver, debounced, through a temp file and rename. The entry bound applies to the file as well. Without a data path the cache stays in memory only. Documented as a per-instance exception in the model configuration docs. Assisted-by: Claude:claude-haiku-5-5 * docs(embeddings): document model selection and the no-model error Assisted-by: Claude Code:claude-haiku-5-5 * refactor(config): split the header cache into a generic cache The GGUF header cache mixed two things: the mechanics (bounded LRU keyed by path and identity, per-instance file, debounced atomic save, tolerant load) and the GGUF fields. Move the mechanics into headerCache[S], driven by a headerCacheSpec[S] that names the file prefix, schema, fingerprint, parser and the snapshot encode/decode pair. The GGUF cache becomes one instance of it. File names, the identity check, LRU size, debounce, atomic write and the corruption handling are unchanged. The on-disk JSON keeps the "estimator" key so existing files still load. Assisted-by: Claude Code:claude-haiku-5-5 * feat(config): share one GGUF header cache file between frontends Every frontend used to write its own header cache file, named after its instance ID, so a header read by one frontend was never reused by another. The cache now uses one file, header-cache.json, in the data path, for all frontends and for standalone mode. The instance ID no longer changes the file name. Frontends share the file in three ways. A save first merges the file's entries in, so one frontend's write does not drop another's entries. A miss reloads the file when its modification time has changed, and a hit never reads it. Writes go to a temp file that is renamed into place, so a reader never sees a partial file. Two frontends saving at the same moment can still drop each other's last entries. That costs one re-parse, never a wrong value, because every entry is checked against its model file before use. The shared file is valid only when every frontend mounts the same data volume. The distributed-mode and model-configuration docs state this mode and its volume limit. Assisted-by: Claude:claude-haiku-5-5 * feat(config): give an instance ID its own header cache file Assisted-by: Claude Code:claude-haiku-5-5 * style(config): gofmt the distributed config struct Assisted-by: Claude Code:claude-haiku-5-5 --------- Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
LocalAI website
LocalAI documentation website
Requirement
In this project, the Docsy theme component is pulled in as a Hugo module, together with other module dependencies:
$ hugo mod graph
hugo: collected modules in 566 ms
hugo: collected modules in 578 ms
github.com/google/docsy-example github.com/google/docsy@v0.5.1-0.20221017155306-99eacb09ffb0
github.com/google/docsy-example github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/twbs/bootstrap@v4.6.2+incompatible
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/FortAwesome/Font-Awesome@v0.0.0-20220831210243-d3a7818c253f
If you want to do SCSS edits and want to publish these, you need to install PostCSS
npm install
Running the website locally
Building and running the site locally requires a recent extended version of Hugo.
You can find out more about how to install Hugo for your environment in our
Getting started guide.
From the LocalAI repository root, run:
make docs
The Hugo configuration lives in the docs directory. To invoke Hugo
directly instead, run:
cd docs
hugo server
Running a container locally
You can run docsy-example inside a Docker
container, the container runs with a volume bound to the docsy-example
folder. This approach doesn't require you to install any dependencies other
than Docker Desktop on
Windows and Mac, and Docker Compose
on Linux.
-
Build the docker image
docker-compose build -
Run the built image
docker-compose upNOTE: You can run both commands at once with
docker-compose up --build. -
Verify that the service is working.
Open your web browser and type
http://localhost:1313in your navigation bar, This opens a local instance of the docsy-example homepage. You can now make changes to the docsy example and those changes will immediately show up in your browser after you save.
Cleanup
To stop Docker Compose, on your terminal window, press Ctrl + C.
To remove the produced images run:
docker-compose rm
For more information see the Docker Compose documentation.
Troubleshooting
As you run the website locally, you may run into the following error:
➜ hugo server
INFO 2021/01/21 21:07:55 Using config file:
Building sites … INFO 2021/01/21 21:07:55 syncing static files to /
Built in 288 ms
Error: Error building site: TOCSS: failed to transform "scss/main.scss" (text/x-scss): resource "scss/scss/main.scss_9fadf33d895a46083cdd64396b57ef68" not found in file cache
This error occurs if you have not installed the extended version of Hugo. See this section of the user guide for instructions on how to install Hugo.
Or you may encounter the following error:
➜ hugo server
Error: failed to download modules: binary with name "go" not found
This error occurs if you have not installed the go programming language on your system.
See this section of the user guide for instructions on how to install go.