Upload 5 files

Dockerfile

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+# Use official Python image
+FROM python:3.9-slim
+
+# Set working directory
+WORKDIR /app
+
+# Copy requirement and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy app code
+COPY app ./app
+
+# Expose port (Hugging Face Spaces expects 7860)
+EXPOSE 7860
+
+# Start FastAPI with uvicorn
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

app/emotion_classifier_pipe_lr.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:faad44a2f2f17f9ce68314ec5785352ca76934cedba1fb641e7fa0bf44fdb8d8
+size 2015652

app/main.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+import joblib
+
+app = FastAPI()
+
+# Load your model at startup
+model = joblib.load("app/emotion_classifier_pipe_lr.pkl")
+
+class Request(BaseModel):
+    text: str
+
+@app.post("/predict")
+async def predict_emotion(request: Request):
+    prediction = model.predict([request.text])[0]
+    return {"emotion": prediction}

requirements.txt

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+fastapi
+uvicorn
+scikit-learn
+joblib