Adapters loading (ml-explore#902)

* Added functionality to load in adapters through post-requests so you do not need to restart the server

* ran pre-commit

* nits

* fix test

---------

Co-authored-by: Awni Hannun <[email protected]>

Author: khushgx

llms/mlx_lm/SERVER.md

@@ -78,3 +78,10 @@ curl localhost:8080/v1/chat/completions \
 - `logprobs`: (Optional) An integer specifying the number of top tokens and
   corresponding log probabilities to return for each output in the generated
   sequence. If set, this can be any value between 1 and 10, inclusive.
+
+- `model`: (Optional) A string path to a local model or Hugging Face repo id.
+  If the path is local is must be relative to the directory the server was
+  started in.
+
+- `adapters`: (Optional) A string path to low-rank adapters. The path must be
+  rlative to the directory the server was started in.

llms/mlx_lm/server.py

@@ -97,8 +97,9 @@ def _validate_model_path(self, model_path: str):
                 "Local models must be relative to the current working dir."
             )
 
-    def load(self, model_path):
-        if self.model_key == model_path:
+    # Added in adapter_path to load dynamically
+    def load(self, model_path, adapter_path=None):
+        if self.model_key == (model_path, adapter_path):
             return self.model, self.tokenizer
 
         # Remove the old model if it exists.
@@ -116,18 +117,22 @@ def load(self, model_path):
         if model_path == "default_model" and self.cli_args.model is not None:
             model, tokenizer = load(
                 self.cli_args.model,
-                adapter_path=self.cli_args.adapter_path,
+                adapter_path=(
+                    adapter_path if adapter_path else self.cli_args.adapter_path
+                ),  # if the user doesn't change the model but adds an adapter path
                 tokenizer_config=tokenizer_config,
             )
         else:
             self._validate_model_path(model_path)
-            model, tokenizer = load(model_path, tokenizer_config=tokenizer_config)
+            model, tokenizer = load(
+                model_path, adapter_path=adapter_path, tokenizer_config=tokenizer_config
+            )
 
         if self.cli_args.use_default_chat_template:
             if tokenizer.chat_template is None:
                 tokenizer.chat_template = tokenizer.default_chat_template
 
-        self.model_key = model_path
+        self.model_key = (model_path, adapter_path)
         self.model = model
         self.tokenizer = tokenizer
 
@@ -193,6 +198,7 @@ def do_POST(self):
         self.stream = self.body.get("stream", False)
         self.stream_options = self.body.get("stream_options", None)
         self.requested_model = self.body.get("model", "default_model")
+        self.adapter = self.body.get("adapters", None)
         self.max_tokens = self.body.get("max_tokens", 100)
         self.temperature = self.body.get("temperature", 1.0)
         self.top_p = self.body.get("top_p", 1.0)
@@ -204,7 +210,9 @@ def do_POST(self):
 
         # Load the model if needed
         try:
-            self.model, self.tokenizer = self.model_provider.load(self.requested_model)
+            self.model, self.tokenizer = self.model_provider.load(
+                self.requested_model, self.adapter
+            )
         except:
             self._set_completion_headers(404)
             self.end_headers()
@@ -278,6 +286,8 @@ def validate_model_parameters(self):
 
         if not isinstance(self.requested_model, str):
             raise ValueError("model must be a string")
+        if self.adapter is not None and not isinstance(self.adapter, str):
+            raise ValueError("adapter must be a string")
 
     def generate_response(
         self,

llms/tests/test_server.py

@@ -12,7 +12,7 @@ def __init__(self):
         HF_MODEL_PATH = "mlx-community/Qwen1.5-0.5B-Chat-4bit"
         self.model, self.tokenizer = load(HF_MODEL_PATH)
 
-    def load(self, model):
+    def load(self, model, adapter=None):
         assert model in ["default_model", "chat_model"]
         return self.model, self.tokenizer