[Frontend] enable passing multiple LoRA adapters at once to generate() (#5300)

tests/entrypoints/test_llm_generate_multiple_loras.py

+import weakref
+
+import pytest
+# downloading lora to test lora requests
+from huggingface_hub import snapshot_download
+
+from vllm import LLM
+from vllm.lora.request import LoRARequest
+
+from ..conftest import cleanup
+
+MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+
+PROMPTS = [
+    "Hello, my name is",
+    "The president of the United States is",
+    "The capital of France is",
+    "The future of AI is",
+]
+
+LORA_NAME = "typeof/zephyr-7b-beta-lora"
+
+pytestmark = pytest.mark.llm
+
+
+@pytest.fixture(scope="module")
+def llm():
+    # pytest caches the fixture so we use weakref.proxy to
+    # enable garbage collection
+    llm = LLM(model=MODEL_NAME,
+              tensor_parallel_size=1,
+              max_model_len=8192,
+              enable_lora=True,
+              max_loras=4,
+              max_lora_rank=64,
+              max_num_seqs=128,
+              enforce_eager=True)
+
+    with llm.deprecate_legacy_api():
+        yield weakref.proxy(llm)
+
+        del llm
+
+    cleanup()
+
+
+@pytest.fixture(scope="session")
+def zephyr_lora_files():
+    return snapshot_download(repo_id=LORA_NAME)
+
+
+@pytest.mark.skip_global_cleanup
+def test_multiple_lora_requests(llm: LLM, zephyr_lora_files):
+    lora_request = [
+        LoRARequest(LORA_NAME, idx + 1, zephyr_lora_files)
+        for idx in range(len(PROMPTS))
+    ]
+    # Multiple SamplingParams should be matched with each prompt
+    outputs = llm.generate(PROMPTS, lora_request=lora_request)
+    assert len(PROMPTS) == len(outputs)
+
+    # Exception raised, if the size of params does not match the size of prompts
+    with pytest.raises(ValueError):
+        outputs = llm.generate(PROMPTS, lora_request=lora_request[:1])
+
+    # Single LoRARequest should be applied to every prompt
+    single_lora_request = lora_request[0]
+    outputs = llm.generate(PROMPTS, lora_request=single_lora_request)
+    assert len(PROMPTS) == len(outputs)

vllm/entrypoints/llm.py

@@ -170,7 +170,7 @@ class LLM:
                                         List[SamplingParams]]] = None,
         prompt_token_ids: Optional[List[int]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -182,7 +182,7 @@ class LLM:
                                         List[SamplingParams]]] = None,
         prompt_token_ids: Optional[List[List[int]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -195,7 +195,7 @@ class LLM:
         *,
         prompt_token_ids: List[int],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -208,7 +208,7 @@ class LLM:
         *,
         prompt_token_ids: List[List[int]],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -219,7 +219,7 @@ class LLM:
         sampling_params: None,
         prompt_token_ids: Union[List[int], List[List[int]]],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -232,7 +232,7 @@ class LLM:
         sampling_params: Optional[Union[SamplingParams,
                                         Sequence[SamplingParams]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         ...
 
@@ -249,7 +249,7 @@ class LLM:
                                         Sequence[SamplingParams]]] = None,
         prompt_token_ids: Optional[Union[List[int], List[List[int]]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[RequestOutput]:
         """Generates the completions for the input prompts.
 
@@ -312,7 +312,7 @@ class LLM:
                                        Sequence[PoolingParams]]] = None,
         prompt_token_ids: Optional[List[int]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -324,7 +324,7 @@ class LLM:
                                        Sequence[PoolingParams]]] = None,
         prompt_token_ids: Optional[List[List[int]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -337,7 +337,7 @@ class LLM:
         *,
         prompt_token_ids: List[int],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -350,7 +350,7 @@ class LLM:
         *,
         prompt_token_ids: List[List[int]],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -361,7 +361,7 @@ class LLM:
         pooling_params: None,
         prompt_token_ids: Union[List[int], List[List[int]]],
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -374,7 +374,7 @@ class LLM:
         pooling_params: Optional[Union[PoolingParams,
                                        Sequence[PoolingParams]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         ...
 
@@ -391,7 +391,7 @@ class LLM:
                                        Sequence[PoolingParams]]] = None,
         prompt_token_ids: Optional[Union[List[int], List[List[int]]]] = None,
         use_tqdm: bool = True,
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> List[EmbeddingRequestOutput]:
         """Generates the completions for the input prompts.
 
@@ -498,7 +498,7 @@ class LLM:
         inputs: Union[PromptStrictInputs, Sequence[PromptStrictInputs]],
         params: Union[SamplingParams, Sequence[SamplingParams], PoolingParams,
                       Sequence[PoolingParams]],
-        lora_request: Optional[LoRARequest],
+        lora_request: Optional[Union[Sequence[LoRARequest], LoRARequest]],
     ) -> None:
         if isinstance(inputs, (str, dict)):
             # Convert a single prompt to a list.
@@ -509,20 +509,25 @@ class LLM:
         if isinstance(params, list) and len(params) != num_requests:
             raise ValueError("The lengths of prompts and params "
                              "must be the same.")
+        if isinstance(lora_request,
+                      list) and len(lora_request) != num_requests:
+            raise ValueError("The lengths of prompts and lora_request "
+                             "must be the same.")
 
         # Add requests to the engine.
         for i, request_inputs in enumerate(inputs):
             self._add_request(
                 request_inputs,
                 params[i] if isinstance(params, Sequence) else params,
-                lora_request=lora_request,
+                lora_request=lora_request[i] if isinstance(
+                    lora_request, Sequence) else lora_request,
             )
 
     def _add_request(
         self,
         inputs: PromptInputs,
         params: Union[SamplingParams, PoolingParams],
-        lora_request: Optional[LoRARequest] = None,
+        lora_request: Optional[Union[List[LoRARequest], LoRARequest]] = None,
     ) -> None:
         request_id = str(next(self.request_counter))
         self.llm_engine.add_request(request_id,