Merge branch 'model_type' into 'main'

add model type getter

See merge request tps-llm/lazyllm!141

lazyllm/components/auto/autodeploy.py

@@ -15,7 +15,7 @@ def __new__(cls, base_model, source=lazyllm.config['model_source'], trust_remote
                 launcher=launchers.remote(ngpus=1), stream=False, type=None, **kw):
         base_model = ModelDownloader(source).download(base_model)
         model_name = get_model_name(base_model)
-        if type == 'embed' or cls.get_model_type(model_name) == 'embed':
+        if type == 'embed' or ModelDownloader.get_model_type(model_name) == 'embed':
             return EmbeddingDeploy(trust_remote_code, launcher)
         map_name = model_map(model_name)
         candidates = get_configer().query_deploy(lazyllm.config['gpu_type'], launcher.ngpus,
@@ -31,10 +31,3 @@ def __new__(cls, base_model, source=lazyllm.config['model_source'], trust_remote
             return deploy_cls(trust_remote_code=trust_remote_code, launcher=launcher, stream=stream, **kw)
         raise RuntimeError(f'No valid framework found, candidates are {[c.framework.lower() for c in candidates]}')
 
-    @classmethod
-    def get_model_type(cls, model_name):
-        from lazyllm.components.utils.downloader.model_mapping import model_name_mapping
-        if model_name in model_name_mapping:
-            return model_name_mapping[model_name].get('type', 'llm')
-        else:
-            return 'llm'

lazyllm/components/auto/autofinetune.py

@@ -11,7 +11,7 @@ def __new__(cls, base_model, target_path, source=lazyllm.config['model_source'],
                 batch_size=32, lora_r=8, launcher=launchers.remote(ngpus=1), **kw):
         base_model = ModelDownloader(source).download(base_model)
         model_name = get_model_name(base_model)
-        if cls.get_model_type(model_name) == 'embed':
+        if ModelDownloader.get_model_type(model_name) == 'embed':
             raise RuntimeError('Fine-tuning of the embed model is not currently supported.')
         map_name = model_map(model_name)
         base_name = model_name.split('-')[0].split('_')[0].lower()
@@ -31,11 +31,3 @@ def __new__(cls, base_model, target_path, source=lazyllm.config['model_source'],
                 return finetune_cls(base_model, target_path, merge_path, cp_files='tokeniz*',
                                     batch_size=batch_size, lora_r=lora_r, launcher=launcher, **kw)
         raise RuntimeError(f'No valid framework found, candidates are {[c.framework.lower() for c in candidates]}')
-
-    @classmethod
-    def get_model_type(cls, model_name):
-        from lazyllm.components.utils.downloader.model_mapping import model_name_mapping
-        if model_name in model_name_mapping:
-            return model_name_mapping[model_name].get('type', 'llm')
-        else:
-            return 'llm'

lazyllm/components/utils/downloader/model_downloader.py

@@ -19,7 +19,22 @@ def __init__(self, model_source=lazyllm.config['model_source'],
         self.token = token
         self.cache_dir = cache_dir
         self.model_pathes = model_path.split(":") if len(model_path) > 0 else []
-
+
+    @classmethod
+    def get_model_type(cls, model) ->str:
+        assert isinstance(model, str) and len(model) > 0, "model name should be a non-empty string"
+        for name, info in model_name_mapping.items():
+            if 'type' not in info: continue
+
+            model_name_set={name.casefold()}
+            for source in info:
+                if source == 'type': continue
+                model_name_set.add(info[source].split('/')[-1].casefold())
+
+            if model.split(os.sep)[-1].casefold() in model_name_set:
+                return info['type']
+        return 'llm'
+
     def download(self, model=''):
         assert isinstance(model, str), "model name should be a string."
         if len(model) == 0 or model[0] in (os.sep, '.', '~'): return model  # Dummy or local model.

lazyllm/module/module.py

@@ -10,6 +10,7 @@
 import lazyllm
 from lazyllm import FlatList, LazyLlmResponse, LazyLlmRequest, Option, launchers, LOG
 from ..components.prompter import PrompterBase, ChatPrompter, EmptyPrompter
+from ..components.utils import ModelDownloader
 from ..flow import FlowBase, Pipeline, Parallel
 import uuid
 from ..client import get_redis, redis_client
@@ -374,18 +375,19 @@ class TrainableModule(UrlModule):
     __enable_request__ = False
 
     def __init__(self, base_model: Option = '', target_path='', *, stream=False, return_trace=False):
+        self.base_model = base_model
         super().__init__(url=None, stream=stream, meta=TrainableModule, return_trace=return_trace)
         # Fake base_model and target_path for dummy
         self.target_path = target_path
         self._train = None  # lazyllm.train.auto
         self._finetune = lazyllm.finetune.auto
         self._deploy = lazyllm.deploy.auto
-
-        self.base_model = base_model
         self._deploy_flag = lazyllm.once_flag()
 
     # modify default value to ''
     def prompt(self, prompt=''):
+        if prompt == '' and ModelDownloader.get_model_type(self.base_model) != 'llm':
+            prompt = None
         return super(__class__, self).prompt(prompt)
 
     def _get_args(self, arg_cls, disable=[]):