feat: Added application file

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "src.api:app", "--host", "0.0.0.0", "--port", "7860"]

config/config.ini

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+[data]
+data_dir = C:\Users\kbuzlu\PycharmProjects\SentimentIntentionAnalysis\data\data.json
+possible_labels_dir = C:\Users\kbuzlu\PycharmProjects\SentimentIntentionAnalysis\data\possible_labels.json
+
+[model]
+name = facebook/bart-large-mnli

data/data.json

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+[
+    {"text": "Hello! Thank you for reaching out to our customer service. How can I assist you today?"},
+    {"text": "Hi! I'm interested in purchasing the new iPhone 14."},
+    {"text": "That's fantastic to hear! The iPhone 14 is a great choice. Which specific model are you considering?"},
+    {"text": "I'm looking at the iPhone 14 Pro Max with the highest storage capacity."},
+    {"text": "Excellent choice! Would you like to buy it outright or explore our payment plan options?"},
+    {"text": "I'd like to explore the payment plan options, please."},
+    {"text": "Of course. We offer several flexible payment plans. Could you please provide your information so I can assist you further?"},
+    {"text": "Sure, I'm ready."},
+    {"text": "Firstly, may I have your full name and email address?"},
+    {"text": "My name is John Doe and my email address is johndoe@example.com."},
+    {"text": "Thank you, John. Now, would you prefer a 12-month or 24-month payment plan?"},
+    {"text": "I think a 24-month plan would be more manageable for me."},
+    {"text": "Understood. Do you have any devices you'd like to trade in towards your purchase?"},
+    {"text": "Yes, I have an iPhone 12 Pro that I'd like to trade in."},
+    {"text": "I see. Let me check our current offers and see if we have any promotions that would benefit you."},
+    {"text": "Based on the condition of your iPhone 12 Pro, I'm sorry to say that we can't offer much for a trade-in value."},
+    {"text": "That's disappointing to hear."},
+    {"text": "I understand your frustration. Is there anything else I can assist you with?"},
+    {"text": "No, that's all for now. Thank you!"},
+    {"text": "You're welcome! If you have any further questions, feel free to reach out to us anytime. Have a great day!"}
+]
+

data/possible_labels.json

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+{
+  "sentiment_labels": ["Positive", "Negative", "Neutral"],
+  "intention_labels": ["Inquire", "Inform", "Payment", "Price", "Trade In", "Discount", "Complaint", "Approve", "Selling", "Confusion", "Change Package", "Upgrade", "Purchase", "Help"]
+}

requirements.txt

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+fastapi
+uvicorn
+torch
+configparser
+transformers
+pydantic

src/SentimentAndIntentionAnalysis.py

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+from transformers import pipeline, BartTokenizer, BartForSequenceClassification
+class ZeroShotClassifier:
+
+    def __init__(self, model_name, sentiment_labels, intention_labels):
+        self.model = self.create_model(model_name)
+        self.model_name = model_name
+        self.sentiment_labels = sentiment_labels
+        self.intention_labels = intention_labels
+
+    def create_model(self, model_name):
+        # Create Model
+        tokenizer = BartTokenizer.from_pretrained(model_name)
+        model = BartForSequenceClassification.from_pretrained(model_name)
+        classifier = pipeline("zero-shot-classification", model=model, tokenizer=tokenizer)
+        return classifier
+
+    def analyze_text(self, text):
+        # Sentiment analysis
+        sentiment_result = self.model(text, self.sentiment_labels)
+        sentiment = sentiment_result["labels"][0]
+
+        # Intention analysis
+        intention_result = self.model(text, self.intention_labels)
+        intention = intention_result["labels"][0]
+
+        return {"sentiment": sentiment, "intention": intention}

src/api.py

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+import configparser
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from SentimentAndIntentionAnalysis import ZeroShotClassifier
+from data_loader import *
+
+# Initialize FastAPI app
+app = FastAPI()
+app.add_middleware(CORSMiddleware,
+                   allow_origins=["http://localhost:8501"],
+                   allow_credentials=True,
+                   allow_methods=["*"],
+                   allow_headers=["*"],)
+#Get model_name, data_path and labels_path
+model_name, data_path, labels_path = get_config()
+
+# Load sentiment labels and intention labels
+sentiment_labels, intention_labels = load_labels(labels_path)
+# Create Analzer
+analyzer = ZeroShotClassifier(model_name=model_name, sentiment_labels=sentiment_labels, intention_labels=intention_labels)
+
+class AnalysisResult(BaseModel):
+    sentiment: str
+    intention: str
+
+class Text(BaseModel):
+    text: str
+
+@app.post("/analyze/")
+def analyze_text(data: Text):
+    result = analyzer.analyze_text(data.text)
+    return AnalysisResult(sentiment=result["sentiment"], intention=result["intention"])
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run("api:app", host="0.0.0.0", port=8000, reload=True)
+
+

src/data_loader.py

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+import configparser
+import json
+def get_config():
+    # Read config
+    config = configparser.ConfigParser()
+    config.read(r"C:\Users\kbuzlu\PycharmProjects\SentimentIntentionAnalysis\config\config.ini")
+
+    # Get model_name
+    model_name = config["model"]["name"]
+
+    # Get data path
+    data_path = config["data"]["data_dir"]
+
+    # Get possible labels
+    labels_path = config["data"]["possible_labels_dir"]
+    return model_name, data_path, labels_path
+
+def load_data(data_path):
+    # Load data
+    with open(data_path, "r") as file:
+        data = json.load(file)
+    texts = [entry["text"] for entry in data]
+    return texts
+
+def load_labels(labels_path):
+    # Load labels
+    with open(labels_path, "r") as file:
+        data = json.load(file)
+    sentiment_labels = data["sentiment_labels"]
+    intention_labels = data["intention_labels"]
+    return sentiment_labels, intention_labels