Upload 5 files

.gitignore

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+/env
+env
+/__pycache__
+/outputs
+.vercel

.vercelignore

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+/env
+env
+/__pycache__
+/outputs

app.py

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+from fastapi import FastAPI, File, UploadFile
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+import numpy as np
+
+app = FastAPI()
+
+mapper = ["angry", "disgust", "fear", "happy",
+          "neutral", "other", "sad", "surprised", "unknown"]
+
+inference_pipeline = pipeline(
+    task=Tasks.emotion_recognition,
+    model="iic/emotion2vec_base_finetuned", model_revision="v2.0.4")
+
+
+@app.post("/emotion_recognition")
+async def emotion_recognition(audio_file: UploadFile = File(...)):
+    audio_bytes = await audio_file.read()
+    rec_result = inference_pipeline(
+        audio_bytes, output_dir="./outputs", granularity="utterance", extract_embedding=False)
+    max_emotion_score = np.argmax(rec_result[0]["scores"])
+    return {
+        "emotion": mapper[max_emotion_score],
+        "confidence":rec_result[0]["scores"][max_emotion_score]
+    }

requirements.txt

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+funasr
+modelscope
+fastapi 
+nest-asyncio 
+uvicorn
+python-multipart
+torchaudio
+datasets==2.18.0

vercel.json

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+{
+    "builds": [
+        {
+            "src": "app.py",
+            "use": "@vercel/python"
+        }
+    ],
+    "routes": [
+        {
+            "src": "/(.*)",
+            "dest": "app.py"
+        }
+    ]
+}