feat(openai): dynamic model_type registration

openllm-python/src/openllm/entrypoints/_openapi.py

@@ -35,7 +35,7 @@
         example:
           object: 'list'
           data:
-            - id: meta-llama--Llama-2-13b-chat-hf
+            - id: __model_id__
               object: model
               created: 1686935002
               owned_by: 'na'
@@ -69,7 +69,7 @@
                 content: You are a helpful assistant.
               - role: user
                 content: Hello, I'm looking for a chatbot that can help me with my work.
-            model: meta-llama--Llama-2-13b-chat-hf
+            model: __model_id__
             max_tokens: 256
             temperature: 0.7
             top_p: 0.43
@@ -83,7 +83,7 @@
                 content: You are a helpful assistant.
               - role: user
                 content: Hello, I'm looking for a chatbot that can help me with my work.
-            model: meta-llama--Llama-2-13b-chat-hf
+            model: __model_id__
             max_tokens: 256
             temperature: 0.7
             top_p: 0.43
@@ -206,7 +206,7 @@
           summary: One-shot input example
           value:
             prompt: This is a test
-            model: meta-llama--Llama-2-13b-chat-hf
+            model: __model_id__
             max_tokens: 256
             temperature: 0.7
             logprobs: 1
@@ -217,7 +217,7 @@
           summary: Streaming input example
           value:
             prompt: This is a test
-            model: meta-llama--Llama-2-13b-chat-hf
+            model: __model_id__
             max_tokens: 256
             temperature: 0.7
             top_p: 0.43
@@ -472,6 +472,12 @@
 _SCHEMAS = {k[:-7].lower(): v for k, v in locals().items() if k.endswith('_SCHEMA')}
 
 
+def apply_schema(func, **attrs):
+  for k, v in attrs.items():
+    func.__doc__ = func.__doc__.replace(k, v)
+  return func
+
+
 def add_schema_definitions(func):
   append_str = _SCHEMAS.get(func.__name__.lower(), '')
   if not append_str:

openllm-python/src/openllm/entrypoints/_openapi.pyi

@@ -15,6 +15,7 @@ class OpenLLMSchemaGenerator:
   def get_schema(self, routes: list[BaseRoute], mount_path: Optional[str] = ...) -> Dict[str, Any]: ...
   def parse_docstring(self, func_or_method: Callable[P, Any]) -> Dict[str, Any]: ...
 
+def apply_schema(func: Callable[P, Any], **attrs: Any) -> Callable[P, Any]: ...
 def add_schema_definitions(func: Callable[P, Any]) -> Callable[P, Any]: ...
 def append_schemas(
   svc: Service, generated_schema: Dict[str, Any], tags_order: Literal['prepend', 'append'] = ..., inject: bool = ...

openllm-python/src/openllm/entrypoints/openai.py

@@ -13,7 +13,7 @@
 from openllm_core._schemas import SampleLogprobs
 from openllm_core.utils import converter, gen_random_uuid
 
-from ._openapi import add_schema_definitions, append_schemas, get_generator
+from ._openapi import add_schema_definitions, append_schemas, apply_schema, get_generator
 from ..protocol.openai import (
   ChatCompletionRequest,
   ChatCompletionResponse,
@@ -100,12 +100,25 @@ def create_logprobs(token_ids, id_logprobs, initial_text_offset=0, *, llm):
 
 
 def mount_to_svc(svc, llm):
+  list_models.__doc__ = list_models.__doc__.replace('__model_id__', llm.llm_type)
+  completions.__doc__ = completions.__doc__.replace('__model_id__', llm.llm_type)
+  chat_completions.__doc__ = chat_completions.__doc__.replace('__model_id__', llm.llm_type)
   app = Starlette(
     debug=True,
     routes=[
-      Route('/models', functools.partial(list_models, llm=llm), methods=['GET']),
-      Route('/completions', functools.partial(completions, llm=llm), methods=['POST']),
-      Route('/chat/completions', functools.partial(chat_completions, llm=llm), methods=['POST']),
+      Route(
+        '/models', functools.partial(apply_schema(list_models, __model_id__=llm.llm_type), llm=llm), methods=['GET']
+      ),
+      Route(
+        '/completions',
+        functools.partial(apply_schema(completions, __model_id__=llm.llm_type), llm=llm),
+        methods=['POST'],
+      ),
+      Route(
+        '/chat/completions',
+        functools.partial(apply_schema(chat_completions, __model_id__=llm.llm_type), llm=llm),
+        methods=['POST'],
+      ),
       Route('/schema', endpoint=lambda req: schemas.OpenAPIResponse(req), include_in_schema=False),
     ],
   )