[Model] Initialize deepseek-vl support

docs/source/models/supported_models.rst

@@ -202,6 +202,10 @@ Vision Language Models
     - Phi-3-Vision
     - :code:`microsoft/Phi-3-vision-128k-instruct`, etc.
     -
+  * - :code:`DeepSeekMultiModalityCausalLM`
+    - deepseek-ai
+    - :code:`deepseek-ai/deepseek-vl-1.3b-chat`, :code:`deepseek-ai/deepseek-vl-7b-chat`, etc.
+    -
 
 If your model uses one of the above model architectures, you can seamlessly run your model with vLLM.
 Otherwise, please refer to :ref:`Adding a New Model <adding_a_new_model>` and :ref:`Enabling Multimodal Inputs <enabling_multimodal_inputs>` 

examples/deepseek_vl_example.py

@@ -0,0 +1,63 @@
+import os
+import subprocess
+
+import torch
+from PIL import Image
+
+# The assets are located at `s3://air-example-data-2/vllm_opensource_llava/`.
+# You can use `.buildkite/download-images.sh` to download them
+from vllm import LLM, SamplingParams
+
+sample_params = SamplingParams(temperature=0, max_tokens=1024)
+model = "deepseek-ai/deepseek-vl-7b-chat"
+model = "deepseek-ai/deepseek-vl-1.3b-chat"
+prompt = "You are a helpful language and vision assistant." \
+    "You are able to understand the visual content that the user provides," \
+    "and assist the user with a variety of tasks using natural language.\n" \
+    "User: <image_placeholder> Describe the content of this image.\nAssistant:"
+
+
+def run_deepseek_vl():
+    llm = LLM(model=model,
+              max_model_len=3072,
+              enforce_eager=True,
+              dtype=torch.bfloat16)
+
+    image = Image.open("images/stop_sign.jpg")
+
+    outputs = llm.generate(
+        {
+            "prompt": prompt,
+            "multi_modal_data": {
+                "image": image
+            },
+        },
+        sampling_params=sample_params)
+
+    for o in outputs:
+        generated_text = o.outputs[0].text
+        print(generated_text)
+
+
+def main():
+    run_deepseek_vl()
+
+
+if __name__ == "__main__":
+    # Download from s3
+    s3_bucket_path = "s3://air-example-data-2/vllm_opensource_llava/"
+    local_directory = "images"
+
+    # Make sure the local directory exists or create it
+    os.makedirs(local_directory, exist_ok=True)
+
+    # Use AWS CLI to sync the directory, assume anonymous access
+    subprocess.check_call([
+        "aws",
+        "s3",
+        "sync",
+        s3_bucket_path,
+        local_directory,
+        "--no-sign-request",
+    ])
+    main()

tests/entrypoints/openai/conftest.py

@@ -66,4 +66,4 @@ def sample_sql_statements():
 table: "table_1" | "table_2"
 condition: column "=" number
 number: "1" | "2"
-""")
+""")