app.py

import spacy
import re
import random
import json
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from fastapi.responses import HTMLResponse

# Load the model from Hugging Face
nlp = spacy.load("en_pipeline")

# Load FAQs
with open("faq.json") as f:
    faqs = json.load(f)["faqs"]

# Define intents and responses
intents_responses = {
    "get_invoice": "Here is a link to download your invoice: [link_to_invoice].",
    "payment_issue": "If you're facing payment issues, please check your payment method and try again.",
    "check_invoice": "Your invoice details are available here: [link_to_invoice_details].",
    "contact_customer_service": "You can reach our customer service at 1-800-123-456 or email support@company.com.",
    "complain": "We have logged your complaint. Our team will review it and get back to you shortly.",
    "review": "Thank you for your review. We value your feedback and will use it to improve our services.",
    "cancel_order": "Your order has been successfully canceled.",
    "check_cancellation_fee": "There is no cancellation fee if you cancel within 24 hours of placing the order.",
    "check_payment_methods": "We accept Visa, MasterCard, American Express, and PayPal.",
    "set_up_shipping_address": "Your shipping address has been updated successfully.",
    "track_order": "Your order is currently in transit and will be delivered by the estimated date.",
    "place_order": "Your order has been placed successfully. You will receive a confirmation email shortly.",
    "check_refund_policy": "Our refund policy states that refunds can be requested within 30 days of purchase.",
    "get_refund": "Your refund has been processed and will be credited to your account within 5-7 business days.",
    "registration_problems": "If you're having trouble registering, please try clearing your browser cache and cookies.",
    "recover_password": "To recover your password, please click the 'Forgot Password' link on the login page.",
    "track_refund": "Your refund is being processed and should be completed within 5-7 business days.",
    "newsletter_subscription": "You have successfully subscribed to our newsletter.",
    "create_account": "Your account has been created successfully. You can now log in using your credentials.",
    "delivery_options": "We offer standard, express, and next-day delivery options.",
    "delete_account": "Your account has been deleted successfully.",
    "delivery_period": "Standard delivery takes 3-5 business days, while express delivery takes 1-2 business days.",
    "edit_account": "Your account details have been updated successfully.",
    "change_order": "Your order has been updated successfully.",
    "switch_account": "You have successfully switched to your new account.",
    "change_shipping_address": "You can change the shipping address in the orders section.",
    "contact_human_agent": "You are now being connected to a human agent. Please hold on.",
}

# Greeting and farewell patterns
greeting_patterns = re.compile(r'\b(hi|hello|hey|greetings|good morning|good afternoon|good evening|how are you|hiya|howdy|what’s up|sup|yo)\b', re.IGNORECASE)
farewell_patterns = re.compile(r'\b(bye|thank you|thanks|okay|goodbye|see you|farewell|take care|later|peace|cheers|goodnight|cya)\b', re.IGNORECASE)

# Set the confidence threshold
CONFIDENCE_THRESHOLD = 0.7

def get_intent(text):
    doc = nlp(text)
    intent = max(doc.cats, key=doc.cats.get)
    confidence = doc.cats[intent]
    return intent, confidence

def get_response(text):
    if greeting_patterns.search(text):
        return "Hello! How can I assist you today?"
    elif farewell_patterns.search(text):
        return "Thank you for chatting. Have a great day!"
    else:
        intent, confidence = get_intent(text)
        if confidence >= CONFIDENCE_THRESHOLD:
            return intents_responses.get(intent, "I'm not sure how to respond to that. Can you please rephrase your question?")
        else:
            return "I'm not quite sure what you're asking. Could you please provide more details or rephrase your question?"

app = FastAPI(
    title="Intent Classification Chatbot API",
    description="This API provides endpoints for chatting with an intent classification bot, getting intents for messages, and accessing FAQs.",
    version="1.0.0",
)

class ChatInput(BaseModel):
    message: str

@app.post("/chat", summary="Chat with the bot", response_description="Response from the bot")
async def chat(chat_input: ChatInput):
    """
    This endpoint takes a user message as input and returns a response generated by the chatbot.

    - **message**: The user's message.
    
    Example request:
    ```json
    {
      "message": "How do I track my order?"
    }
    
    Example response:
    ```json
    {
      "response": "Your order is currently in transit and will be delivered by the estimated date."
    }
    ```
    """
    response = get_response(chat_input.message)
    return {"response": response}

@app.post("/intent", summary="Get intent of the message", response_description="Detected intent and confidence")
async def intent(chat_input: ChatInput):
    """
    This endpoint takes a user message as input and returns the detected intent and confidence level.

    - **message**: The user's message.

    Example request:
    ```json
    {
      "message": "I need help with my invoice."
    }
    ```
    
    Example response:
    ```json
    {
      "intent": "get_invoice",
      "confidence": 0.85
    }
    ```
    """
    text = chat_input.message
    if greeting_patterns.search(text):
        intent, confidence = "greeting", 1
    elif farewell_patterns.search(text):
        intent, confidence = "farewell", 1
    else:
        intent, confidence = get_intent(text)
    return {"intent": intent, "confidence": confidence}

@app.get("/faqs", summary="Get a list of FAQs", response_description="List of FAQs")
async def get_faqs():
    """
    This endpoint returns a random set of 5 frequently asked questions from the FAQ list.
    
    Example response:
    ```json
    {
      "faqs": [
        "How do I track my order?",
        "What payment methods do you accept?",
        "How do I reset my password?",
        "Can I change my shipping address?",
        "What is your refund policy?"
      ]
    }
    ```
    """
    start_index = random.randint(0, len(faqs) - 5)
    end_index = start_index + 5
    return {"faqs": faqs[start_index:end_index]}

@app.get("/intents", summary="Get all available intent categories", response_description="List of all intent categories")
async def get_intents():
    """
    This endpoint returns a list of all available intent categories supported by the chatbot.
    
    Example response:
    ```json
    {
      "intents": [
        "get_invoice",
        "payment_issue",
        "check_invoice",
        "contact_customer_service",
        ...
      ]
    }
    ```
    """
    return {"intents": list(intents_responses.keys())}

@app.get("/", response_class=HTMLResponse)
async def read_root():
    """
    Root endpoint that returns an HTML page with information about the API.
    """
    with open("index.html", "r") as f:
        html_content = f.read()
    return HTMLResponse(content=html_content, status_code=200)

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)