[gpt-oss] Add gpt-oss bf16 support

vllm/plugins/lora_resolvers/README.md

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+# LoRA Resolver Plugins
+
+This directory contains vLLM general plugins for dynamically discovering and loading LoRA adapters
+via the LoRAResolver plugin framework.
+
+Note that `VLLM_ALLOW_RUNTIME_LORA_UPDATING` must be set to true to allow LoRA resolver plugins
+to work, and `VLLM_PLUGINS` must be set to include the desired resolver plugins.
+
+# lora_filesystem_resolver
+This LoRA Resolver is installed with vLLM by default.
+To use, set `VLLM_PLUGIN_LORA_CACHE_DIR` to a local directory. When vLLM receives a request
+for a LoRA adapter `foobar` it doesn't currently recognize, it will look in that local directory
+for a subdirectory `foobar` containing a LoRA adapter. If such an adapter exists, it will
+load that adapter, and then service the request as normal. That adapter will then be available
+for future requests as normal.

vllm/plugins/lora_resolvers/filesystem_resolver.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+import json
+import os
+from typing import Optional
+
+import vllm.envs as envs
+from vllm.lora.request import LoRARequest
+from vllm.lora.resolver import LoRAResolver, LoRAResolverRegistry
+
+
+class FilesystemResolver(LoRAResolver):
+
+    def __init__(self, lora_cache_dir: str):
+        self.lora_cache_dir = lora_cache_dir
+
+    async def resolve_lora(self, base_model_name: str,
+                           lora_name: str) -> Optional[LoRARequest]:
+        lora_path = os.path.join(self.lora_cache_dir, lora_name)
+        if os.path.exists(lora_path):
+            adapter_config_path = os.path.join(self.lora_cache_dir, lora_name,
+                                               "adapter_config.json")
+            if os.path.exists(adapter_config_path):
+                with open(adapter_config_path) as file:
+                    adapter_config = json.load(file)
+                if adapter_config["peft_type"] == "LORA" and adapter_config[
+                        "base_model_name_or_path"] == base_model_name:
+                    lora_request = LoRARequest(lora_name=lora_name,
+                                               lora_int_id=abs(
+                                                   hash(lora_name)),
+                                               lora_path=lora_path)
+                    return lora_request
+        return None
+
+
+def register_filesystem_resolver():
+    """Register the filesystem LoRA Resolver with vLLM"""
+
+    lora_cache_dir = envs.VLLM_LORA_RESOLVER_CACHE_DIR
+    if lora_cache_dir:
+        if not os.path.exists(lora_cache_dir) or not os.path.isdir(
+                lora_cache_dir):
+            raise ValueError(
+                "VLLM_LORA_RESOLVER_CACHE_DIR must be set to a valid directory \
+                for Filesystem Resolver plugin to function")
+        fs_resolver = FilesystemResolver(lora_cache_dir)
+        LoRAResolverRegistry.register_resolver("Filesystem Resolver",
+                                               fs_resolver)
+
+    return