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Dockerfile

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+# The Dockerfile is nearly identical to the previous services [cite: 289]
+FROM python:3.9-slim
+WORKDIR /code
+COPY ./requirements.txt /code/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+COPY ./app.py /code/app.py
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+# Adapted from source [cite: 262-285]
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from transformers import pipeline
+from typing import List
+
+app = FastAPI()
+
+class SentenceListPayload(BaseModel):
+    sentences: List[str]
+
+# Load the text classification pipeline on startup
+try:
+    action_item_classifier = pipeline(
+        "text-classification",
+        model="knkarthick/Action_Items",
+        device="cpu",
+    )
+except Exception as e:
+    action_item_classifier = None
+    print(f"Error loading action item model: {e}")
+
+@app.post("/classify-action-items")
+async def classify_sentences(payload: SentenceListPayload):
+    if not action_item_classifier:
+        raise HTTPException(status_code=503, detail="Action item model is not available.")
+    
+    results = action_item_classifier(payload.sentences)
+    
+    # Filter for sentences classified as action items with a confidence threshold
+    action_items = []
+    for i, sentence in enumerate(payload.sentences):
+        if results[i]['label'] == 'LABEL_1' and results[i]['score'] > 0.8:
+            action_items.append({
+                "sentence": sentence,
+                "confidence": results[i]['score']
+            })
+            
+    return {"action_items": action_items}

requirements.txt

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+fastapi
+uvicorn
+torch
+transformers
+pydantic
+typing