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[Doc] Update vlm.rst to include an example on videos #9155

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24 changes: 23 additions & 1 deletion docs/source/models/vlm.rst
Original file line number Diff line number Diff line change
Expand Up @@ -133,7 +133,29 @@ Instead of passing in a single image, you can pass in a list of images.
generated_text = o.outputs[0].text
print(generated_text)

A code example can be found in `examples/offline_inference_vision_language_multi_image.py <https://github.com/vllm-project/vllm/blob/main/examples/offline_inference_vision_language_multi_image.py>`_.
A code example can be found in `examples/offline_inference_vision_language_multi_image.py <https://github.com/vllm-project/vllm/blob/main/examples/offline_inference_vision_language_multi_image.py>`_. Multi-image input can be extended to
perform video captioning. We show this with `Qwen2-VL <https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct>`_ as it supports videos:
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.. code-block:: python
# Specify the maximum number of frames per video to be 4. This can be changed.
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llm = LLM("Qwen/Qwen2-VL-2B-Instruct", limit_mm_per_prompt={"image": 4})

# Create the request payload.
video_frames = ... # load your video making sure it only has the number of frames specified earlier.
messages = [
{"role": "user", "content": [{"type": "text", "text": "Describe this set of frames. Consider the frames to be a part of the same video."}]}
]
for i in range(len(video_frames)):
base64_image = encode_image(video_frames[i]) # base64 encoding.
new_image = {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
messages[0]["content"].append(new_image)

# Perform inference and log output.
outputs = llm.chat(messages)
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Did you forget to input the images here?

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Done.

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for o in outputs:
generated_text = o.outputs[0].text
print(generated_text)

Online Inference
----------------
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