some minor renames and refactorings within BackendConfigLoader - make things more consistent, remove underused code, rename things for clarity
Signed-off-by: Dave Lee <dave@gray101.com>
* models(gallery): add mistral-0.3 and command-r, update functions
Add also disable_parallel_new_lines to disable newlines in the JSON
output when forcing parallel tools. Some models (like mistral) might be
very sensible to that when being used for function calling.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* models(gallery): add aya-23-8b
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(functions): relax mixedgrammars
Extend even more the functionalities and when mixed mode is enabled,
tolerate also both strings and JSON in the result - in this case we make
sure that the JSON can be correctly parsed.
This also updates the examples and the gallery model to configure the
grammar.
The changeset also breaks current function/grammar configuration as it
reserves now a stanza in the YAML config.
For example:
```yaml
function:
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
# prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
```
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* refactor, add a way to disable mixed json and freestring
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* Fix linting issues
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(llama.cpp): Enable decentralized, distributed inference
As https://github.com/mudler/LocalAI/pull/2324 introduced distributed inferencing thanks to
@rgerganov implementation in https://github.com/ggerganov/llama.cpp/pull/6829 in upstream llama.cpp, now
it is possible to distribute the workload to remote llama.cpp gRPC server.
This changeset now uses mudler/edgevpn to establish a secure, distributed network between the nodes using a shared token.
The token is generated automatically when starting the server with the `--p2p` flag, and can be used by starting the workers
with `local-ai worker p2p-llama-cpp-rpc` by passing the token via environment variable (TOKEN) or with args (--token).
As per how mudler/edgevpn works, a network is established between the server and the workers with dht and mdns discovery protocols,
the llama.cpp rpc server is automatically started and exposed to the underlying p2p network so the API server can connect on.
When the HTTP server is started, it will discover the workers in the network and automatically create the port-forwards to the service locally.
Then llama.cpp is configured to use the services.
This feature is behind the "p2p" GO_FLAGS
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* go mod tidy
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* ci: add p2p tag
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* better message
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(functions): allow to use JSONRegexMatch unconditionally
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(functions): make json_regex_match a list
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Correct llama3-8b-instruct model file
This must be a mistake because the config tries to use a model file that is different from the one actually being downloaded.
I assumed the downloaded file is what should be used so I corrected the specified model file to that
Signed-off-by: Aleksandr Oleinikov <10602045+tannisroot@users.noreply.github.com>
