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app.py

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+import gradio as gr
+import torch
+import tempfile
+import os
+from typing import List, Tuple
+from transformers import VoxtralForConditionalGeneration, AutoProcessor
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+repo_id = "mistralai/Voxtral-Mini-3B-2507"
+
+processor = AutoProcessor.from_pretrained(repo_id)
+model = VoxtralForConditionalGeneration.from_pretrained(
+    repo_id,
+    torch_dtype=torch.bfloat16,
+    device_map=device,
+)
+
+def respond(audio_files: List[str], question: str) -> Tuple[str, List[str]]:
+    if not audio_files:
+        return "Please upload at least one audio file.", []
+
+    conversation = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "audio", "path": path} for path in audio_files
+            ] + [{"type": "text", "text": question}],
+        }
+    ]
+
+    inputs = processor.apply_chat_template(conversation)
+    inputs = inputs.to(device, dtype=torch.bfloat16)
+
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_new_tokens=500)
+    decoded = processor.batch_decode(
+        outputs[:, inputs.input_ids.shape[1]:],
+        skip_special_tokens=True,
+    )
+    return decoded[0], audio_files
+
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Audio(type="filepath", label="Audio files", file_count="multiple"),
+        gr.Textbox(lines=2, placeholder="Ask something about the audio(s)...", label="Question"),
+    ],
+    outputs=[
+        gr.Textbox(label="Answer"),
+        gr.Gallery(label="Uploaded audio files"),
+    ],
+    title="Voxtral-Mini-3B-2507 Audio Q&A",
+    description="Upload one or more audio files and ask any question about them.",
+    examples=[
+        [
+            [
+                "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/mary_had_lamb.mp3",
+                "https://huggingface.co/datasets/hf-internal-testing/dummy-audio-samples/resolve/main/winning_call.mp3",
+            ],
+            "What sport and what nursery rhyme are referenced?",
+        ]
+    ],
+    cache_examples=False,
+)
+
+if __name__ == "__main__":
+    demo.launch()