Deploy FastAPI abap model on HF Spaces with custom endpoints

.gitignore

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+venv/
+.env
+__pycache__/
+*.pyc
+.DS_Store

Dockerfile

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+# Use Python as the base image
+FROM python:3.9
+
+# Set the working directory
+WORKDIR /app
+
+# Copy requirements and install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the FastAPI app
+COPY . .
+
+# Run FastAPI server
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import pipeline
+
+# Load your Hugging Face model
+model = pipeline("text-generation", model="devops-bda/Abap")
+
+# Initialize FastAPI app
+app = FastAPI()
+
+# Define input format
+class InputData(BaseModel):
+    input_text: str
+
+# Health check endpoint
+@app.get("/health")
+async def health_check():
+    return {"status": "ok", "message": "Model is ready"}
+    
+# Define prediction endpoint
+@app.post("/predict")
+async def predict(data: InputData):
+    result = model(data.input_text, max_length=500)
+    return {"output": result}

requirements.txt

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+fastapi
+uvicorn
+transformers
+torch