[Model][Misc] Add e5-mistral-7b-instruct and Embedding API (#3734)

tests/models/test_embedding.py

@@ -0,0 +1,44 @@
+"""Compare the outputs of HF and vLLM for Mistral models using greedy sampling.
+
+Run `pytest tests/models/test_llama_embedding.py`.
+"""
+import pytest
+import torch
+import torch.nn.functional as F
+
+MODELS = [
+    "intfloat/e5-mistral-7b-instruct",
+]
+
+
+def compare_embeddings(embeddings1, embeddings2):
+    similarities = [
+        F.cosine_similarity(torch.tensor(e1), torch.tensor(e2), dim=0)
+        for e1, e2 in zip(embeddings1, embeddings2)
+    ]
+    return similarities
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("dtype", ["half"])
+def test_models(
+    hf_runner,
+    vllm_runner,
+    example_prompts,
+    model: str,
+    dtype: str,
+) -> None:
+    hf_model = hf_runner(model, dtype=dtype)
+    hf_outputs = hf_model.encode(example_prompts)
+    del hf_model
+
+    vllm_model = vllm_runner(model, dtype=dtype)
+    vllm_outputs = vllm_model.encode(example_prompts)
+    del vllm_model
+
+    similarities = compare_embeddings(hf_outputs, vllm_outputs)
+    all_similarities = torch.stack(similarities)
+    tolerance = 1e-2
+    assert torch.all((all_similarities <= 1.0 + tolerance)
+                     & (all_similarities >= 1.0 - tolerance)
+                     ), f"Not all values are within {tolerance} of 1.0"